ATOM (atom-ai): code snapshot (100fae0 + batched-train), README with measured numbers, curated checkpoints (part 3)

docs/artifacts/hard_v2_deeper/chunk_150k/probe.txt

@@ -0,0 +1,19 @@
+[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_obligatory_hard/atom_native.pt (read-only, eval, no optimizer)
+[probe] d_model=64 n_modes=64 step=3275000
+[probe] prompt='Bonjour'
+        RMS 0.004311 -> 0.029649 (norm 0.2759 -> 1.8976) atoms 3 -> 22
+        gen_preview=" 'ns 'ns '�s '�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�sfr!p�"
+[probe] prompt='Qui es-tu ?'
+        RMS 0.006657 -> 0.031680 (norm 0.4261 -> 2.0275) atoms 7 -> 26
+        gen_preview="\n'�a\n'�s\n'�s\n'�s\n'�s\ne�s\n'�s\n'�s\ne�s\n'�s\n'�s\neys\n'ys\n'ysfr�p�.\n'ys\n'ys\n'esgr�p�.\n'ys\n'es\n'esgr�p�."
+[probe] prompt='Il était une fois'
+        RMS 0.006141 -> 0.030857 (norm 0.3930 -> 1.9749) atoms 6 -> 25
+        gen_preview=" a�s a�a a�a '�a '�a '�a '�a 8�a '�a '�a 8�a '�a U�a U�a U�a U�aaU�aaU�aaU�aaU�a"
+[probe] prompt='Utilisateur: Bonjour\nAssistant:'
+        RMS 0.004311 -> 0.029649 (norm 0.2759 -> 1.8976) atoms 3 -> 22
+        gen_preview=" 'ns 'ns '�s '�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�sfr!p�"
+[probe] mean off-diag cosine logits=0.914219 alpha=0.839724
+[probe] reconstruction_succeeds=True field_differs=True
+[probe] wrote /workspace/exports/atom-ai/logs/field_probe_report.json
+[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged
+[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)

docs/artifacts/hard_v2_deeper/chunk_150k/run_metrics.json

@@ -0,0 +1,144 @@
+{
+  "stream": true,
+  "data_path": null,
+  "data_glob": "data/dialogue_shards/part_*",
+  "shard_paths": [
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_000",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_001",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_002",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_003",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_004",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_005",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_006",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_007",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_008",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_train.txt"
+  ],
+  "data_bytes": 7066157,
+  "data_characters": null,
+  "atomizer_version": "atomizer-v1-byte-span",
+  "feature_dim": 320,
+  "packet_count": null,
+  "train_packet_count": null,
+  "validation_packet_count": 2048,
+  "mean_packet_bytes": null,
+  "max_packet_bytes": null,
+  "min_packet_bytes": null,
+  "bytes_seen": 524288,
+  "config": {
+    "d_model": 64,
+    "n_modes": 64,
+    "n_atoms_max": 512,
+    "max_span_bytes": 16,
+    "episode_length": 512,
+    "episode_reset": false,
+    "atom_flush_every": 256,
+    "learning_rate": 0.0001,
+    "surface_learning_rate": 0.0003,
+    "steps": 50000,
+    "start_step": 3225000,
+    "seed": 20260918,
+    "surface_alphabet": 256,
+    "field_max_rms": 3.0,
+    "energy_decay_bounds": [
+      0.3,
+      0.95
+    ],
+    "stream": true,
+    "chunk_bytes": 1048576,
+    "loop_shards": true,
+    "stream_buffer": 2048,
+    "stream_prefetch": true,
+    "enable_merge": true,
+    "field_loss_weight": 0.05,
+    "field_contrast_weight": 0.1,
+    "field_ignorance_weight": 0.0,
+    "field_ignorance_ablate_shared": false,
+    "field_ignorance_prompt_bank": false,
+    "field_obligatory_readout": true,
+    "field_obligatory_hard": true,
+    "slow_every": 1
+  },
+  "packets_seen": 97538,
+  "stream_epoch": 0,
+  "train": {
+    "steps": 50000,
+    "start_step": 3225000,
+    "total_steps": 3275000,
+    "episode_length": 512,
+    "episode_reset": false,
+    "atom_flush_every": 256,
+    "elapsed_seconds": 1381.466633162001,
+    "transitions_per_second": 36.19341850157928,
+    "first_loss": 11.078485488891602,
+    "final_loss": 6.2086687088012695,
+    "final_total_perplexity": 497.0391068427024,
+    "finite_losses": true,
+    "finite_parameters": true,
+    "nan_or_inf": false,
+    "field_rms_before_max": 3.0059940814971924,
+    "field_rms_after_max": 2.999999523162842,
+    "field_scale_min": 0.9980056285858154,
+    "field_norm_max": 191.99998474121094,
+    "field_limited_steps": 48452,
+    "field_limited_fraction": 0.96904,
+    "final_dynamics": {
+      "coupling_scale": 2.0,
+      "energy_decay": 0.30000001192092896,
+      "phase_sync": 0.3081580400466919,
+      "energy_decay_before": 0.29993849992752075,
+      "energy_decay_repaired": true,
+      "energy_decay_bounds": [
+        0.3,
+        0.95
+      ]
+    },
+    "final_atoms_before_validation": 8,
+    "stream": true,
+    "bytes_seen": 524288
+  },
+  "validation": {
+    "transitions": 256,
+    "loss": 7.102966853417456,
+    "total_perplexity": 1215.5681424282864,
+    "byte_loss": 4.10431616846472,
+    "byte_perplexity": 60.60128930231591,
+    "source": "stream_ring"
+  },
+  "checkpoint": "checkpoints/atom_native_obligatory_hard/atom_native.pt",
+  "reload": {
+    "n_atoms": 80,
+    "field_norm": 191.99984741210938,
+    "time": 500.1767883300781,
+    "finite": true
+  },
+  "generation": {
+    "The future of AI is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "21723f2721726c2d3f210a276561216521",
+      "text": "!r?'!rl-?!\n'ea!e!",
+      "reload_text": "!r?'!rl-?!\n'ea!e!",
+      "reload_match": true
+    },
+    "Bonjour, je m'appelle": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "c271706d7975c371202d672c2d4a7971700a20a9",
+      "text": "\ufffdqpmyu\ufffdq -g,-Jyqp\n \ufffd",
+      "reload_text": "\ufffdqpmyu\ufffdq -g,-Jyqp\n \ufffd",
+      "reload_match": true
+    },
+    "Valkyria Chronicles III is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "4165616d217520a869a92155c361216565612175",
+      "text": "Aeam!u \ufffdi\ufffd!U\ufffda!eea!u",
+      "reload_text": "Aeam!u \ufffdi\ufffd!U\ufffda!eea!u",
+      "reload_match": true
+    }
+  }
+}

docs/artifacts/hard_v2_deeper/chunk_150k/train_excerpt.txt

@@ -0,0 +1,29 @@
+train lock skipped (--allow-parallel-train)
+resumed weights from checkpoints/atom_native_obligatory_hard/atom_native.pt (recorded step=3225000, legacy_surface_migrated=False)
+dynamics on load: energy_decay=0.30000001192092896 -> 0.30000001192092896 (repaired=False, bounds=(0.3, 0.95))
+field_obligatory_hard=ON hard-v2+ (mix_floor=1.0, freeze bypass, logits=frozen+cap*scale*alpha_MLP)
+field_obligatory_readout=ON (migrated=False)
+optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (11 tensors); energy_decay_bounds=(0.3, 0.95); field_max_rms=3.0
+stream mode: 10 shard(s), chunk_bytes=1048576, loop_shards=True, stream_buffer=2048, stream_prefetch=True
+optimizer restore skipped: surface LR param groups differ from checkpoint
+step=3225001 (run 1/50000) loss=11.07849 byte_ppl=1135.752 atoms=1 merges=0 field=0.1176 rms=0.0021 scale=1.0000 fcos=0.678 ign=0.0000 mph=0.000 bytes=524288 pkts=97538 shard=0
+step=3225025 (run 25/50000) loss=7.47295 byte_ppl=57.852 atoms=25 merges=0 field=1.1280 rms=0.0177 scale=1.0000 fcos=0.647 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3225050 (run 50/50000) loss=5.37463 byte_ppl=124.084 atoms=50 merges=0 field=2.1560 rms=0.0337 scale=1.0000 fcos=0.624 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3225075 (run 75/50000) loss=6.48096 byte_ppl=32.551 atoms=75 merges=0 field=3.1031 rms=0.0485 scale=1.0000 fcos=0.618 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3225100 (run 100/50000) loss=6.93733 byte_ppl=84.216 atoms=100 merges=0 field=4.0551 rms=0.0634 scale=1.0000 fcos=0.613 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3225125 (run 125/50000) loss=9.17130 byte_ppl=80.493 atoms=125 merges=0 field=4.8758 rms=0.0762 scale=1.0000 fcos=0.607 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3225150 (run 150/50000) loss=5.43816 byte_ppl=39.604 atoms=150 merges=0 field=5.8057 rms=0.0907 scale=1.0000 fcos=0.604 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3225175 (run 175/50000) loss=5.48505 byte_ppl=60.693 atoms=175 merges=0 field=6.6279 rms=0.1036 scale=1.0000 fcos=0.599 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3225200 (run 200/50000) loss=10.14227 byte_ppl=222.128 atoms=200 merges=0 field=7.5621 rms=0.1182 scale=1.0000 fcos=0.594 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3225225 (run 225/50000) loss=4.57154 byte_ppl=19.913 atoms=225 merges=0 field=8.3569 rms=0.1306 scale=1.0000 fcos=0.587 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3225250 (run 250/50000) loss=7.15508 byte_ppl=48.066 atoms=250 merges=0 field=9.3910 rms=0.1467 scale=1.0000 fcos=0.584 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3225275 (run 275/50000) loss=5.39268 byte_ppl=55.482 atoms=19 merges=0 field=10.2292 rms=0.1598 scale=1.0000 fcos=0.578 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+...
+step=3235000 (run 10000/50000) loss=7.28107 byte_ppl=188.979 atoms=16 merges=0 field=191.9999 rms=3.0000 scale=0.9981 fcos=0.550 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3250000 (run 25000/50000) loss=8.16118 byte_ppl=117.372 atoms=168 merges=0 field=191.9999 rms=3.0000 scale=0.9982 fcos=0.550 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3275000 (run 50000/50000) loss=6.20867 byte_ppl=70.255 atoms=80 merges=0 field=191.9998 rms=3.0000 scale=0.9981 fcos=0.550 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+      "reload_text": "Aeam!u \ufffdi\ufffd!U\ufffda!eea!u",
+      "reload_match": true
+    }
+  }
+}

docs/artifacts/hard_v2_deeper/chunk_50k/chat.txt

@@ -0,0 +1,59 @@
+### Bonjour
+Prompt: Bonjour
+Response: uaasu.�
+
+ߧ'
+'�rg'�"�e
+j�s�.y
+C�s s-a
+xts�'�ps�
+ 
+'�s
+'��or�0�.
+O'�yxysgryp 'vs�.�"�.A'v -r�p O�s '� 
+'y aqmp
+ets
+sys��dd�]p'��p�vM
+shMg�Wp
+
+### Qui es-tu ?
+Prompt: Qui es-tu ?
+Response: e a
+8'ag�
+e��
+syao.� 
+sva
+ �a C' �?'v 
+
+s� 
+
+sfa���'s. eya
+j� 
+efa
+'ea
+'va�CyM
+?xha���0s.��
+s s
+
+### Il était une fois
+Prompt: Il était une fois
+Response: !el !'�m!feM '� 
+e�a�nea
+ߔa�'�aj'ts ee �'e
+
+8e
+
+8Qs
+'Qa
+jea
+'�e��es
+'�
+
+s�eiuQd�e
+O'�ir�p?'�e�iL. sye
+xee
+
+
+### Bonjour det
+Prompt: Bonjour
+Response: u�asu'asu'lsu'lsuuliunli6nli6sli6sliustiuOtiuOtiuOtiuO�ijO�ijO�i6O�s6O�s6O�s6O�s6O�s6O�s6O�s6u�s

docs/artifacts/hard_v2_deeper/chunk_50k/probe.txt

@@ -0,0 +1,21 @@
+[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_obligatory_hard/atom_native.pt (read-only, eval, no optimizer)
+[probe] d_model=64 n_modes=64 step=3175000
+[probe] prompt='Bonjour'
+        RMS 0.004304 -> 0.028417 (norm 0.2755 -> 1.8187) atoms 3 -> 22
+        gen_preview=" 'ns 'ns '�s '�s '�s '�s '�s\n'ps\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s"
+[probe] prompt='Qui es-tu ?'
+        RMS 0.006704 -> 0.032128 (norm 0.4291 -> 2.0562) atoms 7 -> 26
+        gen_preview='\nߔa\nߔs\nߔs\ne�s\ne�s\ne�s\ne�s\ne�s\nC�s\nC�s\ne�s\nC�s\nC�sv.mps.\nC�s\nC�s\ne�s\nC�sv.mps.\nC�s\nC�s\nC�s'
+[probe] prompt='Il était une fois'
+        RMS 0.006004 -> 0.028465 (norm 0.3842 -> 1.8217) atoms 6 -> 25
+        gen_preview=" a�a a�a a�a '�a '�a '�a '�a '�aaU�aaU�aaU�aa'�aaU�aaU�aaU�aa'�aaU�a6U�a6U�a6U�a"
+[probe] prompt='Utilisateur: Bonjour\nAssistant:'
+        RMS 0.004304 -> 0.028417 (norm 0.2755 -> 1.8187) atoms 3 -> 22
+        gen_preview=" 'ns 'ns '�s '�s '�s '�s '�s\n'ps\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s\n'�s"
+[probe] mean off-diag cosine logits=0.915435 alpha=0.845265
+[probe] reconstruction_succeeds=True field_differs=True
+[probe] wrote /workspace/exports/atom-ai/logs/field_probe_report.json
+[probe] wrote /workspace/exports/atom-ai/docs/FIELD_PROBE.md
+[probe] wrote /workspace/exports/atom-ai/docs/PERSISTENCE_TEST.md
+[probe] updated /workspace/exports/atom-ai/docs/SCALE.md
+[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)

docs/artifacts/hard_v2_deeper/chunk_50k/run_metrics.json

@@ -0,0 +1,144 @@
+{
+  "stream": true,
+  "data_path": null,
+  "data_glob": "data/dialogue_shards/part_*",
+  "shard_paths": [
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_000",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_001",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_002",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_003",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_004",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_005",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_006",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_007",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_008",
+    "/workspace/repos/toroidal-fractal-intelligence/data/dialogue_shards/part_train.txt"
+  ],
+  "data_bytes": 7066157,
+  "data_characters": null,
+  "atomizer_version": "atomizer-v1-byte-span",
+  "feature_dim": 320,
+  "packet_count": null,
+  "train_packet_count": null,
+  "validation_packet_count": 2048,
+  "mean_packet_bytes": null,
+  "max_packet_bytes": null,
+  "min_packet_bytes": null,
+  "bytes_seen": 524288,
+  "config": {
+    "d_model": 64,
+    "n_modes": 64,
+    "n_atoms_max": 512,
+    "max_span_bytes": 16,
+    "episode_length": 512,
+    "episode_reset": false,
+    "atom_flush_every": 256,
+    "learning_rate": 0.0001,
+    "surface_learning_rate": 0.0003,
+    "steps": 50000,
+    "start_step": 3125000,
+    "seed": 20260918,
+    "surface_alphabet": 256,
+    "field_max_rms": 3.0,
+    "energy_decay_bounds": [
+      0.3,
+      0.95
+    ],
+    "stream": true,
+    "chunk_bytes": 1048576,
+    "loop_shards": true,
+    "stream_buffer": 2048,
+    "stream_prefetch": true,
+    "enable_merge": true,
+    "field_loss_weight": 0.05,
+    "field_contrast_weight": 0.1,
+    "field_ignorance_weight": 0.0,
+    "field_ignorance_ablate_shared": false,
+    "field_ignorance_prompt_bank": false,
+    "field_obligatory_readout": true,
+    "field_obligatory_hard": true,
+    "slow_every": 1
+  },
+  "packets_seen": 97538,
+  "stream_epoch": 0,
+  "train": {
+    "steps": 50000,
+    "start_step": 3125000,
+    "total_steps": 3175000,
+    "episode_length": 512,
+    "episode_reset": false,
+    "atom_flush_every": 256,
+    "elapsed_seconds": 1460.8717423260005,
+    "transitions_per_second": 34.22613946956766,
+    "first_loss": 20.27935218811035,
+    "final_loss": 6.268411636352539,
+    "final_total_perplexity": 527.6386299168859,
+    "finite_losses": true,
+    "finite_parameters": true,
+    "nan_or_inf": false,
+    "field_rms_before_max": 3.0064809322357178,
+    "field_rms_after_max": 2.999999523162842,
+    "field_scale_min": 0.9978440403938293,
+    "field_norm_max": 191.99996948242188,
+    "field_limited_steps": 48500,
+    "field_limited_fraction": 0.97,
+    "final_dynamics": {
+      "coupling_scale": 2.0,
+      "energy_decay": 0.30000001192092896,
+      "phase_sync": 0.28007209300994873,
+      "energy_decay_before": 0.2999384105205536,
+      "energy_decay_repaired": true,
+      "energy_decay_bounds": [
+        0.3,
+        0.95
+      ]
+    },
+    "final_atoms_before_validation": 7,
+    "stream": true,
+    "bytes_seen": 524288
+  },
+  "validation": {
+    "transitions": 256,
+    "loss": 7.183161847293377,
+    "total_perplexity": 1317.0660433453525,
+    "byte_loss": 4.123776443302631,
+    "byte_perplexity": 61.79215676999581,
+    "source": "stream_ring"
+  },
+  "checkpoint": "checkpoints/atom_native_obligatory_hard/atom_native.pt",
+  "reload": {
+    "n_atoms": 80,
+    "field_norm": 191.99986267089844,
+    "time": 500.1767883300781,
+    "finite": true
+  },
+  "generation": {
+    "The future of AI is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "617261616c61726c782d6fa82c61726c61617270",
+      "text": "araalarlx-o\ufffd,arlaarp",
+      "reload_text": "araalarlx-o\ufffd,arlaarp",
+      "reload_match": true
+    },
+    "Bonjour, je m'appelle": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "c2636d61797570612075722c2175706d6175c373",
+      "text": "\ufffdcmayupa ur,!upmau\ufffds",
+      "reload_text": "\ufffdcmayupa ur,!upmau\ufffds",
+      "reload_match": true
+    },
+    "Valkyria Chronicles III is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "2075200a216594a86565212cc3f12075202d2138",
+      "text": " u \n!e\ufffd\ufffdee!,\ufffd\ufffd u -!8",
+      "reload_text": " u \n!e\ufffd\ufffdee!,\ufffd\ufffd u -!8",
+      "reload_match": true
+    }
+  }
+}

docs/artifacts/hard_v2_deeper/chunk_50k/train_excerpt.txt

@@ -0,0 +1,29 @@
+train lock skipped (--allow-parallel-train)
+resumed weights from checkpoints/atom_native_obligatory_hard/atom_native.pt (recorded step=3125000, legacy_surface_migrated=True)
+dynamics on load: energy_decay=0.30000001192092896 -> 0.30000001192092896 (repaired=False, bounds=(0.3, 0.95))
+field_obligatory_hard=ON hard-v2+ (mix_floor=1.0, freeze bypass, logits=frozen+cap*scale*alpha_MLP)
+field_obligatory_readout=ON (migrated=False)
+optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (11 tensors); energy_decay_bounds=(0.3, 0.95); field_max_rms=3.0
+stream mode: 10 shard(s), chunk_bytes=1048576, loop_shards=True, stream_buffer=2048, stream_prefetch=True
+optimizer restore skipped: surface LayerNorm migration changed bias scale
+step=3125001 (run 1/50000) loss=20.27935 byte_ppl=1781.479 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.000 ign=0.0000 mph=0.000 bytes=524288 pkts=97538 shard=0
+step=3125025 (run 25/50000) loss=11.63221 byte_ppl=115.688 atoms=25 merges=0 field=1.1821 rms=0.0185 scale=1.0000 fcos=0.143 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3125050 (run 50/50000) loss=7.01860 byte_ppl=180.592 atoms=50 merges=0 field=2.2246 rms=0.0348 scale=1.0000 fcos=0.408 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3125075 (run 75/50000) loss=5.78146 byte_ppl=28.657 atoms=75 merges=0 field=3.2307 rms=0.0505 scale=1.0000 fcos=0.373 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3125100 (run 100/50000) loss=6.38058 byte_ppl=75.765 atoms=100 merges=0 field=4.2239 rms=0.0660 scale=1.0000 fcos=0.527 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3125125 (run 125/50000) loss=8.49685 byte_ppl=76.502 atoms=125 merges=0 field=5.0844 rms=0.0794 scale=1.0000 fcos=0.532 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3125150 (run 150/50000) loss=5.92573 byte_ppl=67.643 atoms=150 merges=0 field=6.0760 rms=0.0949 scale=1.0000 fcos=0.536 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3125175 (run 175/50000) loss=5.78230 byte_ppl=72.286 atoms=175 merges=0 field=6.9639 rms=0.1088 scale=1.0000 fcos=0.542 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3125200 (run 200/50000) loss=10.76589 byte_ppl=409.006 atoms=200 merges=0 field=7.9200 rms=0.1238 scale=1.0000 fcos=0.539 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3125225 (run 225/50000) loss=4.54946 byte_ppl=17.638 atoms=225 merges=0 field=8.7302 rms=0.1364 scale=1.0000 fcos=0.550 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3125250 (run 250/50000) loss=7.75172 byte_ppl=52.010 atoms=250 merges=0 field=9.7824 rms=0.1529 scale=1.0000 fcos=0.546 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3125275 (run 275/50000) loss=5.36541 byte_ppl=55.040 atoms=19 merges=0 field=10.6460 rms=0.1663 scale=1.0000 fcos=0.549 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+...
+step=3135000 (run 10000/50000) loss=7.39594 byte_ppl=198.787 atoms=16 merges=0 field=191.9999 rms=3.0000 scale=0.9979 fcos=0.550 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3150000 (run 25000/50000) loss=8.09320 byte_ppl=118.844 atoms=168 merges=0 field=191.9999 rms=3.0000 scale=0.9980 fcos=0.550 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+step=3175000 (run 50000/50000) loss=6.26841 byte_ppl=73.648 atoms=80 merges=0 field=191.9999 rms=3.0000 scale=0.9980 fcos=0.550 ign=0.0000 mph=0.500 bytes=524288 pkts=97538 shard=0
+      "reload_text": " u \n!e\ufffd\ufffdee!,\ufffd\ufffd u -!8",
+      "reload_match": true
+    }
+  }
+}

docs/artifacts/hard_v2_deeper/pytest.txt

@@ -0,0 +1,2 @@
+.............................s...............                            [100%]
+44 passed, 1 skipped in 3.75s

docs/artifacts/last_atom_dropout/chat_seeds_ladrop_4876000.json

@@ -0,0 +1,167 @@
+{
+  "checkpoint": "checkpoints/byte_tick_ladrop/atom_native_step_4876000_d32_ms1M_lrd_b4828_ladrop.pt",
+  "rows": [
+    {
+      "temp": 0.8,
+      "seed": 1,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Je                      \nsoirends              \nAsssistant:::::::::::::::::::O   \nuurrraais     "
+    },
+    {
+      "temp": 0.8,
+      "seed": 1,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je                      \n    \nAsssistant:::::::::::::::::::::::::::O  toirriraaarte.tee         "
+    },
+    {
+      "temp": 0.8,
+      "seed": 1,
+      "prompt": "Il était une fois",
+      "resp": "Je                      \nsoirends              \nAsssistant:::::::::::::::::::O   \nuurrraais     "
+    },
+    {
+      "temp": 0.8,
+      "seed": 2,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Je       \n'uttilisateur::::::::::::::::::::::::::::::::::::::::::::::::::::tuurrriilisateur:::::"
+    },
+    {
+      "temp": 0.8,
+      "seed": 2,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je       \n'uttilisateur::::::::::::::::::::::::::::::::::::::::::::::::::::tuurrriilisateur:::::"
+    },
+    {
+      "temp": 0.8,
+      "seed": 2,
+      "prompt": "Il était une fois",
+      "resp": "Je                      \nAsssistant::::::::::::::::::::::::::::::::::::::::tuurrriilisateur:::::"
+    },
+    {
+      "temp": 0.8,
+      "seed": 3,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Je                      \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrre             "
+    },
+    {
+      "temp": 0.8,
+      "seed": 3,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je                      \nAAsssistant::::::::::::::::::::::::::::::toirrriisaateur:::::::::::::::"
+    },
+    {
+      "temp": 0.8,
+      "seed": 3,
+      "prompt": "Il était une fois",
+      "resp": "Je                      \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrre             "
+    },
+    {
+      "temp": 0.6,
+      "seed": 1,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Je                      \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrrrierraine     "
+    },
+    {
+      "temp": 0.6,
+      "seed": 1,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je                      \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrrrierraine     "
+    },
+    {
+      "temp": 0.6,
+      "seed": 1,
+      "prompt": "Il était une fois",
+      "resp": "Je                      \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrrrierraine     "
+    },
+    {
+      "temp": 0.6,
+      "seed": 2,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Je                      \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrriraaite       "
+    },
+    {
+      "temp": 0.6,
+      "seed": 2,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je                      \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrriraaite       "
+    },
+    {
+      "temp": 0.6,
+      "seed": 2,
+      "prompt": "Il était une fois",
+      "resp": "Je                      \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrriraaite       "
+    },
+    {
+      "temp": 0.6,
+      "seed": 3,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Je                      \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrrriraiisateur::"
+    },
+    {
+      "temp": 0.6,
+      "seed": 3,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je                      \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrrriraiisateur::"
+    },
+    {
+      "temp": 0.6,
+      "seed": 3,
+      "prompt": "Il était une fois",
+      "resp": "Je                      \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrrriraiisateur::"
+    },
+    {
+      "temp": 1.0,
+      "seed": 1,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Je    \n'ut--ourra.toi                  un      \nAsssistant::::::::::::::::::ttiisiisateur:::::::"
+    },
+    {
+      "temp": 1.0,
+      "seed": 1,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je    \n'ut--ourra.toi                  un      \nAsssistant::::::::::::::::::ttiisiisateur:::::::"
+    },
+    {
+      "temp": 1.0,
+      "seed": 1,
+      "prompt": "Il était une fois",
+      "resp": "Je    \n'ut--ourra                      un      \nAsssistant::::::::::::::::::Juurrrriraiisateur::"
+    },
+    {
+      "temp": 1.0,
+      "seed": 2,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Je      uuirra..\nUtilisateur:::::::::::::::::::::::::::::::::::riisiilisateur:::::::::::::::::::"
+    },
+    {
+      "temp": 1.0,
+      "seed": 2,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je      uuirra..\nUtilisateur:::::::::::::::::::::::::::::::::::riisiilisateur:::::::::::::::::::"
+    },
+    {
+      "temp": 1.0,
+      "seed": 2,
+      "prompt": "Il était une fois",
+      "resp": "Je      uuirra..\nUtilisateur:::::::::::::::::::::::::::::::::::riisiilisateur:::::::::::::::::::"
+    },
+    {
+      "temp": 1.0,
+      "seed": 3,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Je                      \nAAsssistant::::::::::::::::::::::::aiiliirs              reuttilisateur"
+    },
+    {
+      "temp": 1.0,
+      "seed": 3,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je                      \nAAsssistant:::::::::::::::::::::O  un  \n\n"
+    },
+    {
+      "temp": 1.0,
+      "seed": 3,
+      "prompt": "Il était une fois",
+      "resp": "Je                      \nAAsssistant::::::::::::::::::::::::aiiliirs              reuuiss       "
+    }
+  ]
+}

docs/artifacts/last_atom_dropout/chat_seeds_ladrop_4876000.txt

@@ -0,0 +1,27 @@
+[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Je                      \nsoirends              \nAsssistant:::::::::::::::::::O   \nuurrraais     '
+[T=0.8 seed=1] 'Qui es-tu ?' -> 'Je                      \n    \nAsssistant:::::::::::::::::::::::::::O  toirriraaarte.tee         '
+[T=0.8 seed=1] 'Il était une fois' -> 'Je                      \nsoirends              \nAsssistant:::::::::::::::::::O   \nuurrraais     '
+[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> "Je       \n'uttilisateur::::::::::::::::::::::::::::::::::::::::::::::::::::tuurrriilisateur:::::"
+[T=0.8 seed=2] 'Qui es-tu ?' -> "Je       \n'uttilisateur::::::::::::::::::::::::::::::::::::::::::::::::::::tuurrriilisateur:::::"
+[T=0.8 seed=2] 'Il était une fois' -> 'Je                      \nAsssistant::::::::::::::::::::::::::::::::::::::::tuurrriilisateur:::::'
+[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> 'Je                      \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrre             '
+[T=0.8 seed=3] 'Qui es-tu ?' -> 'Je                      \nAAsssistant::::::::::::::::::::::::::::::toirrriisaateur:::::::::::::::'
+[T=0.8 seed=3] 'Il était une fois' -> 'Je                      \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrre             '
+[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Je                      \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrrrierraine     '
+[T=0.6 seed=1] 'Qui es-tu ?' -> 'Je                      \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrrrierraine     '
+[T=0.6 seed=1] 'Il était une fois' -> 'Je                      \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrrrierraine     '
+[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> 'Je                      \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrriraaite       '
+[T=0.6 seed=2] 'Qui es-tu ?' -> 'Je                      \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrriraaite       '
+[T=0.6 seed=2] 'Il était une fois' -> 'Je                      \nAsssistant:::::::::::::::::::::::::::::::::::::::::trrrrriraaite       '
+[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> 'Je                      \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrrriraiisateur::'
+[T=0.6 seed=3] 'Qui es-tu ?' -> 'Je                      \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrrriraiisateur::'
+[T=0.6 seed=3] 'Il était une fois' -> 'Je                      \nAAsssistant::::::::::::::::::::::::::::::::::::::::toirrrriraiisateur::'
+[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> "Je    \n'ut--ourra.toi                  un      \nAsssistant::::::::::::::::::ttiisiisateur:::::::"
+[T=1.0 seed=1] 'Qui es-tu ?' -> "Je    \n'ut--ourra.toi                  un      \nAsssistant::::::::::::::::::ttiisiisateur:::::::"
+[T=1.0 seed=1] 'Il était une fois' -> "Je    \n'ut--ourra                      un      \nAsssistant::::::::::::::::::Juurrrriraiisateur::"
+[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> 'Je      uuirra..\nUtilisateur:::::::::::::::::::::::::::::::::::riisiilisateur:::::::::::::::::::'
+[T=1.0 seed=2] 'Qui es-tu ?' -> 'Je      uuirra..\nUtilisateur:::::::::::::::::::::::::::::::::::riisiilisateur:::::::::::::::::::'
+[T=1.0 seed=2] 'Il était une fois' -> 'Je      uuirra..\nUtilisateur:::::::::::::::::::::::::::::::::::riisiilisateur:::::::::::::::::::'
+[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Je                      \nAAsssistant::::::::::::::::::::::::aiiliirs              reuttilisateur'
+[T=1.0 seed=3] 'Qui es-tu ?' -> 'Je                      \nAAsssistant:::::::::::::::::::::O  un  \n\n'
+[T=1.0 seed=3] 'Il était une fois' -> 'Je                      \nAAsssistant::::::::::::::::::::::::aiiliirs              reuuiss       '

docs/artifacts/last_atom_dropout/chat_seeds_live_4876000.json

@@ -0,0 +1,167 @@
+{
+  "checkpoint": "checkpoints/byte_tick/atom_native_step_4876000_d32_ms1M_lrd_b4828.pt",
+  "rows": [
+    {
+      "temp": 0.8,
+      "seed": 1,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peut--..\nUtilisateur:::::::::::::::aaiilisateurr::::::::::::::riiliisateure             \nsoireco"
+    },
+    {
+      "temp": 0.8,
+      "seed": 1,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je    \n'ut-- on                    \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa"
+    },
+    {
+      "temp": 0.8,
+      "seed": 1,
+      "prompt": "Il était une fois",
+      "resp": "Je    \n'ut-- on                    \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa"
+    },
+    {
+      "temp": 0.8,
+      "seed": 2,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peuu'''''                      un         \nAsssistant:::::::::::::::Onnnnnnnnnnnnner,  parle    "
+    },
+    {
+      "temp": 0.8,
+      "seed": 2,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je       \n'ut-- on                 \n'uttilisateur::::::::::::::::D'aiilisateur::::::::::::::::::"
+    },
+    {
+      "temp": 0.8,
+      "seed": 2,
+      "prompt": "Il était une fois",
+      "resp": "Je       \n'ut-- on                 \n'uttilisateur::::::::::::::::D'aiilisateur::::::::::::::::::"
+    },
+    {
+      "temp": 0.8,
+      "seed": 3,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peut--                  \nAAsssistant:::::::::::::::::aissssistant::::::::::::, toirrierrrqu'''''"
+    },
+    {
+      "temp": 0.8,
+      "seed": 3,
+      "prompt": "Qui es-tu ?",
+      "resp": "Oui,,                              \nsoirra.\nUtilisateur:::::::::::::::::J'aiilisateur:::::::::::"
+    },
+    {
+      "temp": 0.8,
+      "seed": 3,
+      "prompt": "Il était une fois",
+      "resp": "Je                      \nAAssistant::::::::::::::::::aaiilisateur:::::::::::aiililisateur:::::::"
+    },
+    {
+      "temp": 0.6,
+      "seed": 1,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peut--..\nUtilisateur:::::::::::::::aaiilisateur:::::::::::::::riiliisateur::::::::::::::aiiliisa"
+    },
+    {
+      "temp": 0.6,
+      "seed": 1,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je                      \nAsssistant:::::::::::::::::::tuurrrirraaimee                   \nerrra.."
+    },
+    {
+      "temp": 0.6,
+      "seed": 1,
+      "prompt": "Il était une fois",
+      "resp": "Je                      \nAsssistant:::::::::::::::::::D'aiilisateur:::::::::::::::::risiilisateu"
+    },
+    {
+      "temp": 0.6,
+      "seed": 2,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peuu''''''''''''                   \n'uuttilisateur:::::::::::::::aaiilisateur:::::::::::::::::::"
+    },
+    {
+      "temp": 0.6,
+      "seed": 2,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je       \n'ut-- on                 \n'uttilisateur::::::::::::::::J  prrrra..\nUtilisateur::::::::"
+    },
+    {
+      "temp": 0.6,
+      "seed": 2,
+      "prompt": "Il était une fois",
+      "resp": "Je       \n'ut-- on                 \nAsssistant::::::::::::::::D'aiilisateur:::::::::::::::::J  q"
+    },
+    {
+      "temp": 0.6,
+      "seed": 3,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peut--                  \nAsssistant:::::::::::::::::::::O   \nuurrrra..\nUtilisateur::::::::::::::"
+    },
+    {
+      "temp": 0.6,
+      "seed": 3,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je                      \nAAssistant:::::::::::::::::::::O   \nuurrrra..\nUtilisateur::::::::::::::"
+    },
+    {
+      "temp": 0.6,
+      "seed": 3,
+      "prompt": "Il était une fois",
+      "resp": "Je                      \nAAssistant:::::::::::::::::::::O   \nuurrrra..\nUtilisateur::::::::::::::"
+    },
+    {
+      "temp": 1.0,
+      "seed": 1,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peut--..\nUtilisateur:::::::::::::::aaiilisateurr::::::::::::::riiliisateure             \nsoireco"
+    },
+    {
+      "temp": 1.0,
+      "seed": 1,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je    \n'ut-- on                    \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa"
+    },
+    {
+      "temp": 1.0,
+      "seed": 1,
+      "prompt": "Il était une fois",
+      "resp": "Je    \n'ut-- on                    \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa"
+    },
+    {
+      "temp": 1.0,
+      "seed": 2,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peuu'''''                     \n  D''ut--                \n'uttilisateur::::::::::::aiilisatteurr:"
+    },
+    {
+      "temp": 1.0,
+      "seed": 2,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je      ,\nAsssistant:::::::::::::Tiisaaccord                     \nAsssistant::::::::::::::aaiili"
+    },
+    {
+      "temp": 1.0,
+      "seed": 2,
+      "prompt": "Il était une fois",
+      "resp": "Je      ,nds                  \n  rd       \nsoirra..\nUtilisateur::::::::::::aiilisaateur:::::::::"
+    },
+    {
+      "temp": 1.0,
+      "seed": 3,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peut--                  \nAAsssistant:::::::::::::::::aiiliisateur:::::::::::aiilisatt           "
+    },
+    {
+      "temp": 1.0,
+      "seed": 3,
+      "prompt": "Qui es-tu ?",
+      "resp": "Oui,,                          T'ut--                    Teuut-- ourra.\n\n"
+    },
+    {
+      "temp": 1.0,
+      "seed": 3,
+      "prompt": "Il était une fois",
+      "resp": "Je                      \n'uttilisateur:::::::::::::::::Pourrllisaarte..\n\n"
+    }
+  ]
+}

docs/artifacts/last_atom_dropout/chat_seeds_live_4876000.txt

@@ -0,0 +1,27 @@
+[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Peut--..\nUtilisateur:::::::::::::::aaiilisateurr::::::::::::::riiliisateure             \nsoireco'
+[T=0.8 seed=1] 'Qui es-tu ?' -> "Je    \n'ut-- on                    \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa"
+[T=0.8 seed=1] 'Il était une fois' -> "Je    \n'ut-- on                    \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa"
+[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> "Peuu'''''                      un         \nAsssistant:::::::::::::::Onnnnnnnnnnnnner,  parle    "
+[T=0.8 seed=2] 'Qui es-tu ?' -> "Je       \n'ut-- on                 \n'uttilisateur::::::::::::::::D'aiilisateur::::::::::::::::::"
+[T=0.8 seed=2] 'Il était une fois' -> "Je       \n'ut-- on                 \n'uttilisateur::::::::::::::::D'aiilisateur::::::::::::::::::"
+[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> "Peut--                  \nAAsssistant:::::::::::::::::aissssistant::::::::::::, toirrierrrqu'''''"
+[T=0.8 seed=3] 'Qui es-tu ?' -> "Oui,,                              \nsoirra.\nUtilisateur:::::::::::::::::J'aiilisateur:::::::::::"
+[T=0.8 seed=3] 'Il était une fois' -> 'Je                      \nAAssistant::::::::::::::::::aaiilisateur:::::::::::aiililisateur:::::::'
+[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Peut--..\nUtilisateur:::::::::::::::aaiilisateur:::::::::::::::riiliisateur::::::::::::::aiiliisa'
+[T=0.6 seed=1] 'Qui es-tu ?' -> 'Je                      \nAsssistant:::::::::::::::::::tuurrrirraaimee                   \nerrra..'
+[T=0.6 seed=1] 'Il était une fois' -> "Je                      \nAsssistant:::::::::::::::::::D'aiilisateur:::::::::::::::::risiilisateu"
+[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> "Peuu''''''''''''                   \n'uuttilisateur:::::::::::::::aaiilisateur:::::::::::::::::::"
+[T=0.6 seed=2] 'Qui es-tu ?' -> "Je       \n'ut-- on                 \n'uttilisateur::::::::::::::::J  prrrra..\nUtilisateur::::::::"
+[T=0.6 seed=2] 'Il était une fois' -> "Je       \n'ut-- on                 \nAsssistant::::::::::::::::D'aiilisateur:::::::::::::::::J  q"
+[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> 'Peut--                  \nAsssistant:::::::::::::::::::::O   \nuurrrra..\nUtilisateur::::::::::::::'
+[T=0.6 seed=3] 'Qui es-tu ?' -> 'Je                      \nAAssistant:::::::::::::::::::::O   \nuurrrra..\nUtilisateur::::::::::::::'
+[T=0.6 seed=3] 'Il était une fois' -> 'Je                      \nAAssistant:::::::::::::::::::::O   \nuurrrra..\nUtilisateur::::::::::::::'
+[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> 'Peut--..\nUtilisateur:::::::::::::::aaiilisateurr::::::::::::::riiliisateure             \nsoireco'
+[T=1.0 seed=1] 'Qui es-tu ?' -> "Je    \n'ut-- on                    \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa"
+[T=1.0 seed=1] 'Il était une fois' -> "Je    \n'ut-- on                    \nAssaaistant:::::::::::::::D'aiilisateur:::::::::::::aiiliisa"
+[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> "Peuu'''''                     \n  D''ut--                \n'uttilisateur::::::::::::aiilisatteurr:"
+[T=1.0 seed=2] 'Qui es-tu ?' -> 'Je      ,\nAsssistant:::::::::::::Tiisaaccord                     \nAsssistant::::::::::::::aaiili'
+[T=1.0 seed=2] 'Il était une fois' -> 'Je      ,nds                  \n  rd       \nsoirra..\nUtilisateur::::::::::::aiilisaateur:::::::::'
+[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Peut--                  \nAAsssistant:::::::::::::::::aiiliisateur:::::::::::aiilisatt           '
+[T=1.0 seed=3] 'Qui es-tu ?' -> "Oui,,                          T'ut--                    Teuut-- ourra.\n\n"
+[T=1.0 seed=3] 'Il était une fois' -> "Je                      \n'uttilisateur:::::::::::::::::Pourrllisaarte..\n\n"

docs/artifacts/last_atom_dropout/chat_seeds_start_4868000.json

@@ -0,0 +1,167 @@
+{
+  "checkpoint": "checkpoints/byte_tick/atom_native_step_4868000_d32_ms1M_lrd_b4828.pt",
+  "rows": [
+    {
+      "temp": 0.8,
+      "seed": 1,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peuut--                            \nAAssistant::::::::::::::::toirre        \n\n"
+    },
+    {
+      "temp": 0.8,
+      "seed": 1,
+      "prompt": "Qui es-tu ?",
+      "resp": "Oui,,                              \nAAssistant::::::::::::::::toirre        \n\n"
+    },
+    {
+      "temp": 0.8,
+      "seed": 1,
+      "prompt": "Il était une fois",
+      "resp": "Je                      \nourrra.iis            \nAsssistant::::::::::::::::::Jarliilisateur::::::"
+    },
+    {
+      "temp": 0.8,
+      "seed": 2,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peut--                         un         \nAAssistant::::::::::::::::toirrrilisateur::::::::::::"
+    },
+    {
+      "temp": 0.8,
+      "seed": 2,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je       \n'uurrecommence                  \nAAssistant:::::::::::::::On nnnnnnnnnnne       \naitti"
+    },
+    {
+      "temp": 0.8,
+      "seed": 2,
+      "prompt": "Il était une fois",
+      "resp": "Je       \n'uurrecommence                  \nAAssistant:::::::::::::::On nnnnnnnnnnne       \naitti"
+    },
+    {
+      "temp": 0.8,
+      "seed": 3,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peuues                             \neuuttilisateur::::::::::::::::J'aiilisateur:::::::::::::::::"
+    },
+    {
+      "temp": 0.8,
+      "seed": 3,
+      "prompt": "Qui es-tu ?",
+      "resp": "Oui,,                              \neuuttilisateur::::::::::::::::aaiilisateur::::::::::::::::::"
+    },
+    {
+      "temp": 0.8,
+      "seed": 3,
+      "prompt": "Il était une fois",
+      "resp": "Oui,,                              \neuuttilisateur::::::::::::::::aaiilisateur::::::::::::::::::"
+    },
+    {
+      "temp": 0.6,
+      "seed": 1,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peuut--                            \nAAssistant::::::::::::::::toirrirrraaartout                 "
+    },
+    {
+      "temp": 0.6,
+      "seed": 1,
+      "prompt": "Qui es-tu ?",
+      "resp": "Oui,,                              \nAAssistant::::::::::::::::toirrrraiisateur::::::::::::::::::"
+    },
+    {
+      "temp": 0.6,
+      "seed": 1,
+      "prompt": "Il était une fois",
+      "resp": "Je                      \n'uut--                \nAAssistant::::::::::::::::::J    \naiilisateur:::"
+    },
+    {
+      "temp": 0.6,
+      "seed": 2,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peut--                             \naittilisateur:::::::::::::::::::aaiilisateur::::::::::::::::"
+    },
+    {
+      "temp": 0.6,
+      "seed": 2,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je                      \nAAssistant::::::::::::::::::::::On nnnnnnnnnnnne  \nerra..              "
+    },
+    {
+      "temp": 0.6,
+      "seed": 2,
+      "prompt": "Il était une fois",
+      "resp": "Je                      \nAAssistant::::::::::::::::::::::On nnnnnnnnnnnne  \nerra..              "
+    },
+    {
+      "temp": 0.6,
+      "seed": 3,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peuu''''''''''''                   \neuuirra..\nUtilisateur:::::::::::::::::::J   toirraaime      "
+    },
+    {
+      "temp": 0.6,
+      "seed": 3,
+      "prompt": "Qui es-tu ?",
+      "resp": "Oui,,                              \nAsssistant::::::::::::::::toirrirrrraaarte..\n\n"
+    },
+    {
+      "temp": 0.6,
+      "seed": 3,
+      "prompt": "Il était une fois",
+      "resp": "Oui,,                              \nAsssistant::::::::::::::::toirrirrrraaarte..\n\n"
+    },
+    {
+      "temp": 1.0,
+      "seed": 1,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peuut--                            \nAssaaistant:::::::::::::::toirre        \n\n"
+    },
+    {
+      "temp": 1.0,
+      "seed": 1,
+      "prompt": "Qui es-tu ?",
+      "resp": "Oui,,                              \nAssaaistant:::::::::::::::toirre        \n\n"
+    },
+    {
+      "temp": 1.0,
+      "seed": 1,
+      "prompt": "Il était une fois",
+      "resp": "Je    \n'ut-- recommence                ??itilis--ilisateur::::::::::::::::Jriisaait      �uee   "
+    },
+    {
+      "temp": 1.0,
+      "seed": 2,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Peut--être                    un         \nAAssistant:::::::::::::::On rirrilisateur::::::::::::"
+    },
+    {
+      "temp": 1.0,
+      "seed": 2,
+      "prompt": "Qui es-tu ?",
+      "resp": "Je      ,ndre                  un         \nAAssistant:::::::::::::::Onnnnnne    \narle           "
+    },
+    {
+      "temp": 1.0,
+      "seed": 2,
+      "prompt": "Il était une fois",
+      "resp": "Je      ,ndi,,,                           \nsourrais                        \n       \nAAssistant::"
+    },
+    {
+      "temp": 1.0,
+      "seed": 3,
+      "prompt": "Bonjour, comment ça va ?",
+      "resp": "Oui,,                          rd                        rdirra..                 un          \na"
+    },
+    {
+      "temp": 1.0,
+      "seed": 3,
+      "prompt": "Qui es-tu ?",
+      "resp": "Oui,,                          T'ut--ourra..\n\n"
+    },
+    {
+      "temp": 1.0,
+      "seed": 3,
+      "prompt": "Il était une fois",
+      "resp": "Oui,                           rirrases                  T'ut--             \nourrapposes        "
+    }
+  ]
+}

docs/artifacts/last_atom_dropout/chat_seeds_start_4868000.txt

@@ -0,0 +1,27 @@
+[T=0.8 seed=1] 'Bonjour, comment ça va ?' -> 'Peuut--                            \nAAssistant::::::::::::::::toirre        \n\n'
+[T=0.8 seed=1] 'Qui es-tu ?' -> 'Oui,,                              \nAAssistant::::::::::::::::toirre        \n\n'
+[T=0.8 seed=1] 'Il était une fois' -> 'Je                      \nourrra.iis            \nAsssistant::::::::::::::::::Jarliilisateur::::::'
+[T=0.8 seed=2] 'Bonjour, comment ça va ?' -> 'Peut--                         un         \nAAssistant::::::::::::::::toirrrilisateur::::::::::::'
+[T=0.8 seed=2] 'Qui es-tu ?' -> "Je       \n'uurrecommence                  \nAAssistant:::::::::::::::On nnnnnnnnnnne       \naitti"
+[T=0.8 seed=2] 'Il était une fois' -> "Je       \n'uurrecommence                  \nAAssistant:::::::::::::::On nnnnnnnnnnne       \naitti"
+[T=0.8 seed=3] 'Bonjour, comment ça va ?' -> "Peuues                             \neuuttilisateur::::::::::::::::J'aiilisateur:::::::::::::::::"
+[T=0.8 seed=3] 'Qui es-tu ?' -> 'Oui,,                              \neuuttilisateur::::::::::::::::aaiilisateur::::::::::::::::::'
+[T=0.8 seed=3] 'Il était une fois' -> 'Oui,,                              \neuuttilisateur::::::::::::::::aaiilisateur::::::::::::::::::'
+[T=0.6 seed=1] 'Bonjour, comment ça va ?' -> 'Peuut--                            \nAAssistant::::::::::::::::toirrirrraaartout                 '
+[T=0.6 seed=1] 'Qui es-tu ?' -> 'Oui,,                              \nAAssistant::::::::::::::::toirrrraiisateur::::::::::::::::::'
+[T=0.6 seed=1] 'Il était une fois' -> "Je                      \n'uut--                \nAAssistant::::::::::::::::::J    \naiilisateur:::"
+[T=0.6 seed=2] 'Bonjour, comment ça va ?' -> 'Peut--                             \naittilisateur:::::::::::::::::::aaiilisateur::::::::::::::::'
+[T=0.6 seed=2] 'Qui es-tu ?' -> 'Je                      \nAAssistant::::::::::::::::::::::On nnnnnnnnnnnne  \nerra..              '
+[T=0.6 seed=2] 'Il était une fois' -> 'Je                      \nAAssistant::::::::::::::::::::::On nnnnnnnnnnnne  \nerra..              '
+[T=0.6 seed=3] 'Bonjour, comment ça va ?' -> "Peuu''''''''''''                   \neuuirra..\nUtilisateur:::::::::::::::::::J   toirraaime      "
+[T=0.6 seed=3] 'Qui es-tu ?' -> 'Oui,,                              \nAsssistant::::::::::::::::toirrirrrraaarte..\n\n'
+[T=0.6 seed=3] 'Il était une fois' -> 'Oui,,                              \nAsssistant::::::::::::::::toirrirrrraaarte..\n\n'
+[T=1.0 seed=1] 'Bonjour, comment ça va ?' -> 'Peuut--                            \nAssaaistant:::::::::::::::toirre        \n\n'
+[T=1.0 seed=1] 'Qui es-tu ?' -> 'Oui,,                              \nAssaaistant:::::::::::::::toirre        \n\n'
+[T=1.0 seed=1] 'Il était une fois' -> "Je    \n'ut-- recommence                ??itilis--ilisateur::::::::::::::::Jriisaait      �uee   "
+[T=1.0 seed=2] 'Bonjour, comment ça va ?' -> 'Peut--être                    un         \nAAssistant:::::::::::::::On rirrilisateur::::::::::::'
+[T=1.0 seed=2] 'Qui es-tu ?' -> 'Je      ,ndre                  un         \nAAssistant:::::::::::::::Onnnnnne    \narle           '
+[T=1.0 seed=2] 'Il était une fois' -> 'Je      ,ndi,,,                           \nsourrais                        \n       \nAAssistant::'
+[T=1.0 seed=3] 'Bonjour, comment ça va ?' -> 'Oui,,                          rd                        rdirra..                 un          \na'
+[T=1.0 seed=3] 'Qui es-tu ?' -> "Oui,,                          T'ut--ourra..\n\n"
+[T=1.0 seed=3] 'Il était une fois' -> "Oui,                           rirrases                  T'ut--             \nourrapposes        "

docs/artifacts/last_atom_dropout/gen_coherent_4868000_b4828.txt

@@ -0,0 +1,6 @@
+PROMPT: Bonjour, comment ça va ?
+RESP: Oui,,                              
+PROMPT: Qui es-tu ?
+RESP: Oui,,                              
+PROMPT: Il était une fois
+RESP: Oui,,                              

docs/artifacts/last_atom_dropout/gen_coherent_4876000_b4828.txt

@@ -0,0 +1,6 @@
+PROMPT: Bonjour, comment ça va ?
+RESP: Bonne                   
+PROMPT: Qui es-tu ?
+RESP: Oui,,                              
+PROMPT: Il était une fois
+RESP: Oui,,                              

docs/artifacts/last_atom_dropout/gen_coherent_4876000_ladrop.txt

@@ -0,0 +1,6 @@
+PROMPT: Bonjour, comment ça va ?
+RESP: Bonne                              
+PROMPT: Qui es-tu ?
+RESP: Bonne                              
+PROMPT: Il était une fois
+RESP: Bonne                              

docs/artifacts/last_atom_dropout/measure.sh

@@ -0,0 +1,26 @@
+#!/usr/bin/env bash
+set -u
+cd /workspace/exports/atom-ai
+export PYTHONPATH=. OMP_NUM_THREADS=1 MKL_NUM_THREADS=1
+PY=.venv/bin/python
+A=docs/artifacts/last_atom_dropout
+LA=checkpoints/byte_tick_ladrop/atom_native_step_4876000_d32_ms1M_lrd_b4828_ladrop.pt
+LIVE=checkpoints/byte_tick/atom_native_step_4876000_d32_ms1M_lrd_b4828.pt
+START=checkpoints/byte_tick/atom_native_step_4868000_d32_ms1M_lrd_b4828.pt
+# 1) exact coherence-probe CLI (unseeded, as in train_until_coherent.sh)
+G=$A/gen_coherent_4876000_ladrop.txt; : > $G
+for p in "Bonjour, comment ça va ?" "Qui es-tu ?" "Il était une fois"; do
+  RESP=$($PY tools/chat_atom_native.py --checkpoint "$LA" --prompt "$p" --no-role-prime \
+    --max-packets 96 --max-length 100 --temperature 0.8 --top-k 12 2>/dev/null | sed -n 's/^Response: //p' | head -1)
+  echo "PROMPT: $p" >> $G; echo "RESP: $RESP" >> $G
+done
+# 2) seeded chats, 3 ckpts x 3 seeds x 3 temps
+for tag in ladrop_4876000:$LA live_4876000:$LIVE start_4868000:$START; do
+  name=${tag%%:*}; ck=${tag#*:}
+  $PY tools/chat_seeds_probe.py --checkpoint "$ck" --seeds 1 2 3 --temps 0.8 0.6 1.0 \
+    --out $A/chat_seeds_${name}.json > $A/chat_seeds_${name}.txt 2>&1
+done
+# 3) val normal vs last_atom-zeroed on both rings
+$PY -u tools/eval_last_atom_ablation.py --end-steps 4868000 4876000 \
+  --checkpoints "$START" "$LIVE" "$LA" --out $A/val_ablation.json > $A/val_ablation.txt 2>&1
+echo DONE > $A/.measure_done

docs/artifacts/last_atom_dropout/probe_start_time.txt

@@ -0,0 +1 @@
+2026-09-28T10:45:12-07:00

docs/artifacts/last_atom_dropout/pytest_full.txt

@@ -0,0 +1,87 @@
+..................F.......................................s............. [ 68%]
+....................F.F..........                                        [100%]
+=================================== FAILURES ===================================
+_ ChatMergeOffIngestTests.test_payload_copy_sees_distinct_atoms_when_merge_off _
+
+self = <test_chat_merge_off.ChatMergeOffIngestTests testMethod=test_payload_copy_sees_distinct_atoms_when_merge_off>
+
+    def test_payload_copy_sees_distinct_atoms_when_merge_off(self) -> None:
+        """Distinct living payloads under merge-off boost target byte mass vs MERGE collapse."""
+        torch.manual_seed(5)
+        model = self._tiny()
+        model.eval()
+        prompt = "AAA BBB CCC DDD EEE FFF "
+        packets = model.atomizer.encode(prompt, reset=True)
+        self.assertGreaterEqual(len(packets), 2)
+    
+        model.reset_state(reset_atomizer=True)
+        last_off = None
+        for p in packets:
+            last_off = model.forward_packet(p, merge_enabled=False)
+        assert last_off is not None
+        n_off = len(model.core.atoms)
+        logits_off = last_off["surface"]["byte_logits"]
+        # Bytes present in prompt payloads.
+        target = sorted({b for p in packets for b in (p.payload or b"")})
+        mass_off = float(logits_off.softmax(dim=-1)[:, target].sum().item())
+    
+        model.reset_state(reset_atomizer=True)
+        packets2 = model.atomizer.encode(prompt, reset=True)
+        last_on = None
+        for p in packets2:
+            last_on = model.forward_packet(p)
+        assert last_on is not None
+        n_on = len(model.core.atoms)
+        logits_on = last_on["surface"]["byte_logits"]
+        mass_on = float(logits_on.softmax(dim=-1)[:, target].sum().item())
+    
+        self.assertGreaterEqual(n_off, 2)
+        self.assertEqual(n_on, 1)
+        # Soft check: merge-off should not be worse on prompt-byte mass.
+>       self.assertGreaterEqual(
+            mass_off + 1e-6,
+            mass_on * 0.9,
+            msg=f"mass_off={mass_off:.4f} mass_on={mass_on:.4f} n_off={n_off} n_on={n_on}",
+        )
+E       AssertionError: 3.050107763839722 not greater than or equal to 3.1522358894348144 : mass_off=3.0501 mass_on=3.5025 n_off=3 n_on=1
+
+test/test_chat_merge_off.py:123: AssertionError
+____________________ SpeechLockUnitTests.test_dialogue_wrap ____________________
+
+self = <test_speech_lock.SpeechLockUnitTests testMethod=test_dialogue_wrap>
+
+    def test_dialogue_wrap(self) -> None:
+>       self.assertEqual(
+            format_dialogue_prompt("Bonjour"),
+            "Utilisateur: Bonjour\nAssistant:",
+        )
+E       AssertionError: 'Utilisateur: Bonjour\nAssistant: ' != 'Utilisateur: Bonjour\nAssistant:'
+E         Utilisateur: Bonjour
+E       - Assistant: 
+E       ?           -
+E       + Assistant:
+
+test/test_speech_lock.py:17: AssertionError
+__________ SpeechLockUnitTests.test_speech_ok_rejects_attractor_soup ___________
+
+self = <test_speech_lock.SpeechLockUnitTests testMethod=test_speech_ok_rejects_attractor_soup>
+
+    def test_speech_ok_rejects_attractor_soup(self) -> None:
+        self.assertFalse(speech_ok(b""))
+>       self.assertFalse(speech_ok(b"auiseateu : aernun e"))
+E       AssertionError: True is not false
+
+test/test_speech_lock.py:25: AssertionError
+=============================== warnings summary ===============================
+test/test_field_hard_couple.py::FieldHardCoupleTests::test_load_keeps_tip_field_feat_norm
+  /workspace/exports/atom-ai/test/test_field_hard_couple.py:125: UserWarning: Converting a tensor with requires_grad=True to a scalar may lead to unexpected behavior.
+  Consider using tensor.detach() first. (Triggered internally at /__w/pytorch/pytorch/torch/csrc/autograd/generated/python_variable_methods.cpp:820.)
+    float(model2.surface.field_hard_couple_byte.weight.abs().mean()), 0.0
+
+-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html
+=========================== short test summary info ============================
+FAILED test/test_chat_merge_off.py::ChatMergeOffIngestTests::test_payload_copy_sees_distinct_atoms_when_merge_off
+FAILED test/test_speech_lock.py::SpeechLockUnitTests::test_dialogue_wrap - As...
+FAILED test/test_speech_lock.py::SpeechLockUnitTests::test_speech_ok_rejects_attractor_soup
+3 failed, 101 passed, 1 skipped, 1 warning in 77.00s (0:01:16)
+HEAD 6bc06a9 (pre-change, git archive): same 3 failures (test_chat_merge_off::test_payload_copy_sees_distinct_atoms_when_merge_off, test_speech_lock::test_dialogue_wrap, test_speech_lock::test_speech_ok_rejects_attractor_soup) -> pre-existing

docs/artifacts/last_atom_dropout/run_metrics_4868000_d32_ms1M_lrd_b4828.json

@@ -0,0 +1,163 @@
+{
+  "stream": true,
+  "data_path": null,
+  "data_glob": "data/corpus_fr_medium*.txt",
+  "shard_paths": [
+    "/workspace/exports/atom-ai/data/corpus_fr_medium.txt",
+    "/workspace/exports/atom-ai/data/corpus_fr_medium_s21.txt"
+  ],
+  "data_bytes": 1000453,
+  "data_characters": null,
+  "atomizer_version": "atomizer-v1-byte-span",
+  "feature_dim": 320,
+  "packet_count": null,
+  "train_packet_count": null,
+  "validation_packet_count": 2048,
+  "mean_packet_bytes": null,
+  "max_packet_bytes": null,
+  "min_packet_bytes": null,
+  "bytes_seen": 4395028,
+  "config": {
+    "d_model": 32,
+    "n_modes": 32,
+    "n_atoms_max": 64,
+    "max_span_bytes": 1,
+    "episode_length": 8000,
+    "episode_reset": true,
+    "atom_flush_every": 64,
+    "learning_rate": 1.5e-05,
+    "surface_learning_rate": 3.6e-05,
+    "steps": 8000,
+    "start_step": 4860000,
+    "seed": 20260913,
+    "surface_alphabet": 256,
+    "field_max_rms": 3.0,
+    "energy_decay_bounds": [
+      0.3,
+      0.95
+    ],
+    "stream": true,
+    "chunk_bytes": 65536,
+    "loop_shards": true,
+    "stream_buffer": 2048,
+    "stream_prefetch": true,
+    "stream_skip_packets": 4364000,
+    "last_atom_readout": true,
+    "last_atom_scale": 1.0,
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docs/artifacts/last_atom_dropout/run_metrics_4876000_d32_ms1M_lrd_b4828.json

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docs/artifacts/last_atom_dropout/run_metrics_4876000_ladrop.json

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docs/artifacts/last_atom_dropout/train_ladrop.log

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+{
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+  "data_path": null,
+  "data_glob": "data/corpus_fr_medium*.txt",
+  "shard_paths": [
+    "/workspace/exports/atom-ai/data/corpus_fr_medium.txt",
+    "/workspace/exports/atom-ai/data/corpus_fr_medium_s21.txt"
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+  "mean_packet_bytes": null,
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+      "energy_decay_repaired": false,
+      "energy_decay_bounds": [
+        0.3,
+        0.95
+      ]
+    },
+    "final_atoms_before_validation": 63,
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+    "bytes_seen": 4395028
+  },
+  "validation": {
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+    "loss": 0.5363390516140498,
+    "total_perplexity": 1.709736135040312,
+    "byte_loss": 0.5309394766522244,
+    "byte_perplexity": 1.7005291658437964,
+    "source": "stream_ring"
+  },
+  "checkpoint": "checkpoints/byte_tick_ladrop/atom_native_step_4876000_d32_ms1M_lrd_b4828_ladrop.pt",
+  "reload": {
+    "n_atoms": 0,
+    "field_norm": 95.99996185302734,
+    "time": 88.0003890991211,
+    "finite": true
+  },
+  "generation": {
+    "The future of AI is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "4a65202020202020",
+      "text": "Je      ",
+      "reload_text": "Je      ",
+      "reload_match": true
+    },
+    "Bonjour, je m'appelle": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "4a65202020202020",
+      "text": "Je      ",
+      "reload_text": "Je      ",
+      "reload_match": true
+    },
+    "Valkyria Chronicles III is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3a3a3a3a3a3a3a3a",
+      "text": "::::::::",
+      "reload_text": "::::::::",
+      "reload_match": true
+    }
+  }
+}

docs/artifacts/last_atom_dropout/train_live_4868000_4876000.log

@@ -0,0 +1,504 @@
+train lock skipped (--allow-parallel-train)
+stream skip: advancing 4372000 packet transitions...
+stream skip done: packets_seen=4395028
+resumed weights from checkpoints/byte_tick/atom_native_step_4868000_d32_ms1M_lrd_b4828.pt (recorded step=4868000, legacy_surface_migrated=False, span_head_migrated=False)
+atomizer pack_mode=linguistic max_span_bytes=1
+dynamics on load: energy_decay=0.3000006675720215 -> 0.3000006675720215 (repaired=False, bounds=(0.3, 0.95))
+MERGE gates: enable=False coherence_thr=0.450 energy_floor=0.080
+field_obligatory_hard=ON hard-v2+ (mix_floor=1.0, freeze bypass, logits=frozen+cap*(α_MLP+payload_prod))
+payload_copy=False (train-time copy-bias branch)
+last_atom_readout=True (byte-tick 2-gram + dentate)
+last_atom_dropout=0.0 (train-only per-position zeroing of la_byte; 0=off/current)
+field_hard_couple_scale=0 (OFF — hard path unchanged)
+last_atom_scale=1.0 (1.0=off/current; hard-path la_byte *= S)
+efference_every=10 (0=off)
+free_run_aux_every=0 horizon=4 weight=1.0 (0=off)
+optimizer groups: field/other lr=1.5e-05 (13 tensors), surface lr=3.6e-05 (27 tensors); energy_decay_bounds=(0.3, 0.95); field_max_rms=3.0
+stream mode: 2 shard(s), chunk_bytes=65536, loop_shards=True, stream_buffer=2048, stream_prefetch=True
+optimizer restore skipped: surface LR param groups differ from checkpoint
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+    "The future of AI is": {
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+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "4a65202020202020",
+      "text": "Je      ",
+      "reload_text": "Je      ",
+      "reload_match": true
+    },
+    "Bonjour, je m'appelle": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "4f75692c2c2c2020",
+      "text": "Oui,,,  ",
+      "reload_text": "Oui,,,  ",
+      "reload_match": true
+    },
+    "Valkyria Chronicles III is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "4f75692c2c202020",
+      "text": "Oui,,   ",
+      "reload_text": "Oui,,   ",
+      "reload_match": true
+    }
+  }
+}

docs/artifacts/last_atom_dropout/val_ablation.json

@@ -0,0 +1,87 @@
+{
+  "val_source": "stream_ring_last256 (same as run_atom_native stream val)",
+  "rings": {
+    "4868000": {
+      "n_pairs": 256,
+      "checkpoints": {
+        "checkpoints/byte_tick/atom_native_step_4868000_d32_ms1M_lrd_b4828.pt": {
+          "normal": {
+            "loss": 0.4010402589169644,
+            "byte_loss": 0.3989881433232547,
+            "n": 256
+          },
+          "la_zeroed": {
+            "loss": 6.121935051400214,
+            "byte_loss": 6.119882937986404,
+            "n": 256
+          }
+        },
+        "checkpoints/byte_tick/atom_native_step_4876000_d32_ms1M_lrd_b4828.pt": {
+          "normal": {
+            "loss": 0.40236979978362797,
+            "byte_loss": 0.4002634185616909,
+            "n": 256
+          },
+          "la_zeroed": {
+            "loss": 6.197015048470348,
+            "byte_loss": 6.194908656645566,
+            "n": 256
+          }
+        },
+        "checkpoints/byte_tick_ladrop/atom_native_step_4876000_d32_ms1M_lrd_b4828_ladrop.pt": {
+          "normal": {
+            "loss": 0.5363390516140498,
+            "byte_loss": 0.5309394766522244,
+            "n": 256
+          },
+          "la_zeroed": {
+            "loss": 3.404181201942265,
+            "byte_loss": 3.3987816316075623,
+            "n": 256
+          }
+        }
+      }
+    },
+    "4876000": {
+      "n_pairs": 256,
+      "checkpoints": {
+        "checkpoints/byte_tick/atom_native_step_4868000_d32_ms1M_lrd_b4828.pt": {
+          "normal": {
+            "loss": 0.4010402589169644,
+            "byte_loss": 0.3989881433232547,
+            "n": 256
+          },
+          "la_zeroed": {
+            "loss": 6.121935051400214,
+            "byte_loss": 6.119882937986404,
+            "n": 256
+          }
+        },
+        "checkpoints/byte_tick/atom_native_step_4876000_d32_ms1M_lrd_b4828.pt": {
+          "normal": {
+            "loss": 0.40236979978362797,
+            "byte_loss": 0.4002634185616909,
+            "n": 256
+          },
+          "la_zeroed": {
+            "loss": 6.197015048470348,
+            "byte_loss": 6.194908656645566,
+            "n": 256
+          }
+        },
+        "checkpoints/byte_tick_ladrop/atom_native_step_4876000_d32_ms1M_lrd_b4828_ladrop.pt": {
+          "normal": {
+            "loss": 0.5363390516140498,
+            "byte_loss": 0.5309394766522244,
+            "n": 256
+          },
+          "la_zeroed": {
+            "loss": 3.404181201942265,
+            "byte_loss": 3.3987816316075623,
+            "n": 256
+          }
+        }
+      }
+    }
+  }
+}

docs/artifacts/last_atom_dropout/val_ablation.txt

@@ -0,0 +1,19 @@
+val rings built for [4868000, 4876000] in 473.1s
+[ring@4868000] checkpoints/byte_tick/atom_native_step_4868000_d32_ms1M_lrd_b4828.pt
+  normal   loss=0.4010 byte_ce=0.3990
+  la_zero  loss=6.1219 byte_ce=6.1199
+[ring@4868000] checkpoints/byte_tick/atom_native_step_4876000_d32_ms1M_lrd_b4828.pt
+  normal   loss=0.4024 byte_ce=0.4003
+  la_zero  loss=6.1970 byte_ce=6.1949
+[ring@4868000] checkpoints/byte_tick_ladrop/atom_native_step_4876000_d32_ms1M_lrd_b4828_ladrop.pt
+  normal   loss=0.5363 byte_ce=0.5309
+  la_zero  loss=3.4042 byte_ce=3.3988
+[ring@4876000] checkpoints/byte_tick/atom_native_step_4868000_d32_ms1M_lrd_b4828.pt
+  normal   loss=0.4010 byte_ce=0.3990
+  la_zero  loss=6.1219 byte_ce=6.1199
+[ring@4876000] checkpoints/byte_tick/atom_native_step_4876000_d32_ms1M_lrd_b4828.pt
+  normal   loss=0.4024 byte_ce=0.4003
+  la_zero  loss=6.1970 byte_ce=6.1949
+[ring@4876000] checkpoints/byte_tick_ladrop/atom_native_step_4876000_d32_ms1M_lrd_b4828_ladrop.pt
+  normal   loss=0.5363 byte_ce=0.5309
+  la_zero  loss=3.4042 byte_ce=3.3988

docs/artifacts/last_atom_dropout/val_window_baselines.json

@@ -0,0 +1,7 @@
+{
+  "val_window_text": ": Je vais bien, merci. Et toi ?\nUtilisateur: Dis-m'en plus.\nAssistant: Oui, tout à fait.\nUtilisateur: Dis-m'en plus.\nAssistant: Bonne question, je vais réfléchir.\n\nUtilisateur: Merci bien\nAssistant: Avec grand plaisir.\nUtilisateur: Dis-m'en plus.\nAssista",
+  "n_targets": 256,
+  "unigram_ce_corpus": 3.2359449769619477,
+  "bigram_ce_corpus_add0.01": 1.7686215704800623,
+  "uniform_ce": 5.545177444479562
+}

docs/artifacts/last_atom_dropout/yield_to_live.py

@@ -0,0 +1,72 @@
+"""Pause (SIGSTOP) MY probe PIDs while the live b4828 loop is in a multi-threaded phase.
+
+Live torch uses 8 spinning OMP threads; any other busy process on a core cuts live
+throughput ~38x (measured 77 -> 2 steps/s). The live stream-skip phase is
+single-threaded, so my single-threaded probe runs only then. Only signals the PIDs
+listed in the pid file (my own processes). Never touches the live loop.
+"""
+import glob, os, signal, sys, time, subprocess
+PIDFILE = sys.argv[1]
+LOG = "/workspace/exports/atom-ai/logs/ladrop_yield.log"
+ROOT = "/workspace/exports/atom-ai/logs"
+
+def my_pids():
+    try:
+        return [int(x) for x in open(PIDFILE).read().split() if x.strip()]
+    except FileNotFoundError:
+        return []
+
+def alive(pg):
+    # pg is a process-group id (setsid leader); alive if any member exists
+    try:
+        os.killpg(pg, 0)
+        return True
+    except Exception:
+        return False
+
+def live_busy():
+    mine = set(my_pids())
+    out = subprocess.run(["ps", "-eo", "pid,args"], capture_output=True, text=True).stdout
+    for line in out.splitlines()[1:]:
+        pid_s, _, args = line.strip().partition(" ")
+        pid = int(pid_s)
+        try:
+            if os.getpgid(pid) in mine:
+                continue
+        except Exception:
+            continue
+        if "ladrop" in args:
+            continue
+        if "chat_atom_native.py" in args and "lrd_b4828.pt" in args:
+            return True
+        if "run_atom_native.py" in args and "lrd_b4828.pt" in args:
+            logs = [l for l in glob.glob(f"{ROOT}/train_d32_*_ms1M_lrd_b4828.log")]
+            if not logs:
+                return True
+            cur = max(logs, key=os.path.getmtime)
+            txt = open(cur, errors="replace").read()
+            if "stream skip done" in txt:
+                return True  # training / val / generation phase
+            return False  # still skipping (single-threaded)
+    return False
+
+state = None
+while True:
+    pids = [p for p in my_pids() if alive(p)]
+    if not pids:
+        break
+    busy = live_busy()
+    want = "STOP" if busy else "CONT"
+    for p in pids:
+        try:
+            os.killpg(p, signal.SIGSTOP if busy else signal.SIGCONT)
+        except ProcessLookupError:
+            pass
+    if want != state:
+        with open(LOG, "a") as f:
+            f.write(f"{time.strftime('%H:%M:%S')} {want} pids={pids}\n")
+        state = want
+    time.sleep(0.5)
+for p in my_pids():
+    try: os.killpg(p, signal.SIGCONT)
+    except Exception: pass

docs/artifacts/lign_ablate_2k5/lign_probe_after.txt

@@ -0,0 +1,19 @@
+[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_ablate/atom_native.pt (read-only, eval, no optimizer)
+[probe] d_model=64 n_modes=64 step=2105000
+[probe] prompt='Bonjour'
+        RMS 0.003866 -> 0.032616 (norm 0.2474 -> 2.0874) atoms 3 -> 22
+        gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Qui es-tu ?'
+        RMS 0.006797 -> 0.034313 (norm 0.4350 -> 2.1960) atoms 7 -> 26
+        gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Il était une fois'
+        RMS 0.006037 -> 0.033744 (norm 0.3864 -> 2.1596) atoms 6 -> 25
+        gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Utilisateur: Bonjour\nAssistant:'
+        RMS 0.003866 -> 0.032616 (norm 0.2474 -> 2.0874) atoms 3 -> 22
+        gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] mean off-diag cosine logits=0.991780 alpha=0.698509
+[probe] reconstruction_succeeds=True field_differs=True
+[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_ablate_2k5/probe_after_report.json
+[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged
+[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)

docs/artifacts/lign_ablate_2k5/lign_probe_before.txt

@@ -0,0 +1,19 @@
+[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native_src.pt (read-only, eval, no optimizer)
+[probe] d_model=64 n_modes=64 step=2102500
+[probe] prompt='Bonjour'
+        RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22
+        gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f<N�f'
+[probe] prompt='Qui es-tu ?'
+        RMS 0.006684 -> 0.024246 (norm 0.4278 -> 1.5518) atoms 7 -> 26
+        gen_preview='un!> sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.�> Uu>rN�frN�frN�f<Nqf-Nqk'
+[probe] prompt='Il était une fois'
+        RMS 0.006216 -> 0.024691 (norm 0.3978 -> 1.5803) atoms 6 -> 25
+        gen_preview='us!> su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk<NqkrNqk<NqkrNqk<Nqk'
+[probe] prompt='Utilisateur: Bonjour\nAssistant:'
+        RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22
+        gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f<N�f'
+[probe] mean off-diag cosine logits=0.992294 alpha=0.720524
+[probe] reconstruction_succeeds=True field_differs=True
+[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_ablate_2k5/probe_before_report.json
+[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged
+[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)

docs/artifacts/lign_ablate_2k5/probe_after.txt

@@ -0,0 +1,19 @@
+[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_ablate/atom_native.pt (read-only, eval, no optimizer)
+[probe] d_model=64 n_modes=64 step=2105000
+[probe] prompt='Bonjour'
+        RMS 0.003866 -> 0.032616 (norm 0.2474 -> 2.0874) atoms 3 -> 22
+        gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Qui es-tu ?'
+        RMS 0.006797 -> 0.034313 (norm 0.4350 -> 2.1960) atoms 7 -> 26
+        gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Il était une fois'
+        RMS 0.006037 -> 0.033744 (norm 0.3864 -> 2.1596) atoms 6 -> 25
+        gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Utilisateur: Bonjour\nAssistant:'
+        RMS 0.003866 -> 0.032616 (norm 0.2474 -> 2.0874) atoms 3 -> 22
+        gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] mean off-diag cosine logits=0.991780 alpha=0.698509
+[probe] reconstruction_succeeds=True field_differs=True
+[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_ablate_2k5/probe_after_report.json
+[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged
+[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)

docs/artifacts/lign_ablate_2k5/probe_after_report.json

@@ -0,0 +1,447 @@
+{
+  "timestamp_local": "2026-09-17 19:11:52 PDT",
+  "timestamp_utc": "2026-09-18T02:11:52.830435+00:00",
+  "meta": {
+    "config": {
+      "d_model": 64,
+      "n_modes": 64,
+      "n_atoms_max": 512,
+      "max_payload_bytes": 16,
+      "atomizer_version": "atomizer-v1-byte-span",
+      "field_max_rms": 3.0,
+      "energy_decay_bounds": [
+        0.45,
+        0.95
+      ],
+      "enable_merge": true,
+      "slow_every": 4,
+      "field_loss_weight": 0.08,
+      "field_contrast_weight": 0.45,
+      "field_contrast_margin": 0.45,
+      "field_ignorance_weight": 0.08,
+      "field_ignorance_margin": 0.85,
+      "field_ignorance_ablate_shared": true,
+      "field_ignorance_prompt_bank": false,
+      "merge_count_total": 0
+    },
+    "training_meta": {
+      "step": 2105000,
+      "run_steps": 2500,
+      "seed": 20260917,
+      "episode_reset": false,
+      "atom_flush_every": 256,
+      "dynamics_on_load": {
+        "coupling_scale": 1.9906045198440552,
+        "energy_decay": 0.44999998807907104,
+        "phase_sync": 0.9987071752548218,
+        "energy_decay_before": 0.44999998807907104,
+        "energy_decay_repaired": false,
+        "energy_decay_bounds": [
+          0.45,
+          0.95
+        ]
+      }
+    },
+    "checkpoint": "/workspace/exports/atom-ai/checkpoints/atom_native_lign_ablate/atom_native.pt",
+    "checkpoint_bytes": 20532464
+  },
+  "n_gen": 20,
+  "prompts": [
+    "Bonjour",
+    "Qui es-tu ?",
+    "Il \u00e9tait une fois",
+    "Utilisateur: Bonjour\nAssistant:"
+  ],
+  "per_prompt": [
+    {
+      "prompt": "Bonjour",
+      "primed_text": "Utilisateur: Bonjour\nAssistant:",
+      "n_prompt_packets": 3,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Bonjour\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.0038661202415823936,
+        "field_norm": 0.247431680560112,
+        "field_mean_abs": 0.0029331459663808346,
+        "field_max_abs": 0.024348242208361626,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 3,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.029999999329447746
+      },
+      "stats_after_gen": {
+        "field_rms": 0.032615795731544495,
+        "field_norm": 2.0874109268188477,
+        "field_mean_abs": 0.0234804917126894,
+        "field_max_abs": 0.14776422083377838,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 22,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2200000286102295
+      },
+      "generated_preview": "unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 264.658935546875
+    },
+    {
+      "prompt": "Qui es-tu ?",
+      "primed_text": "Utilisateur: Qui es-tu ?\nAssistant:",
+      "n_prompt_packets": 7,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Qui ",
+        "es-",
+        "tu ",
+        "?",
+        "\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.006796767003834248,
+        "field_norm": 0.43499308824539185,
+        "field_mean_abs": 0.005092245060950518,
+        "field_max_abs": 0.0342055968940258,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 7,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.06999999284744263
+      },
+      "stats_after_gen": {
+        "field_rms": 0.03431277722120285,
+        "field_norm": 2.1960175037384033,
+        "field_mean_abs": 0.025360628962516785,
+        "field_max_abs": 0.15245617926120758,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 26,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2600000202655792
+      },
+      "generated_preview": "unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 217.61972045898438
+    },
+    {
+      "prompt": "Il \u00e9tait une fois",
+      "primed_text": "Utilisateur: Il \u00e9tait une fois\nAssistant:",
+      "n_prompt_packets": 6,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Il ",
+        "\u00e9tait ",
+        "une ",
+        "fois\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.006037322338670492,
+        "field_norm": 0.3863886296749115,
+        "field_mean_abs": 0.004503290634602308,
+        "field_max_abs": 0.03781157359480858,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 6,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.059999994933605194
+      },
+      "stats_after_gen": {
+        "field_rms": 0.033743564039468765,
+        "field_norm": 2.159588098526001,
+        "field_mean_abs": 0.024512071162462234,
+        "field_max_abs": 0.15108709037303925,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 25,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2500000298023224
+      },
+      "generated_preview": "unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 235.82313537597656
+    },
+    {
+      "prompt": "Utilisateur: Bonjour\nAssistant:",
+      "primed_text": "Utilisateur: Bonjour\nAssistant:",
+      "n_prompt_packets": 3,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Bonjour\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.0038661202415823936,
+        "field_norm": 0.247431680560112,
+        "field_mean_abs": 0.0029331459663808346,
+        "field_max_abs": 0.024348242208361626,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 3,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.029999999329447746
+      },
+      "stats_after_gen": {
+        "field_rms": 0.032615795731544495,
+        "field_norm": 2.0874109268188477,
+        "field_mean_abs": 0.0234804917126894,
+        "field_max_abs": 0.14776422083377838,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 22,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2200000286102295
+      },
+      "generated_preview": "unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 264.658935546875
+    }
+  ],
+  "prompt_sensitivity": {
+    "prompts": [
+      "Bonjour",
+      "Qui es-tu ?",
+      "Il \u00e9tait une fois",
+      "Utilisateur: Bonjour\nAssistant:"
+    ],
+    "cosine_alpha": [
+      [
+        0.9999999591503186,
+        0.4765916552705683,
+        0.8353639415455211,
+        0.9999999591503186
+      ],
+      [
+        0.4765916552705683,
+        1.0000001375930643,
+        0.5671435013560066,
+        0.4765916552705683
+      ],
+      [
+        0.8353639415455211,
+        0.5671435013560066,
+        1.0000001418181077,
+        0.8353639415455211
+      ],
+      [
+        0.9999999591503186,
+        0.4765916552705683,
+        0.8353639415455211,
+        0.9999999591503186
+      ]
+    ],
+    "cosine_output_state": [
+      [
+        0.9999999505621286,
+        0.9704693246384373,
+        0.9899996836884695,
+        0.9999999505621286
+      ],
+      [
+        0.9704693246384373,
+        0.9999999381350225,
+        0.9767315391244513,
+        0.9704693246384373
+      ],
+      [
+        0.9899996836884695,
+        0.9767315391244513,
+        1.000000080813615,
+        0.9899996836884695
+      ],
+      [
+        0.9999999505621286,
+        0.9704693246384373,
+        0.9899996836884695,
+        0.9999999505621286
+      ]
+    ],
+    "cosine_surface_logits": [
+      [
+        1.000000089773527,
+        0.9856087639128152,
+        0.9952362798386291,
+        1.000000089773527
+      ],
+      [
+        0.9856087639128152,
+        1.0000001131637146,
+        0.98899230137612,
+        0.9856087639128152
+      ],
+      [
+        0.9952362798386291,
+        0.98899230137612,
+        0.9999999569902737,
+        0.9952362798386291
+      ],
+      [
+        1.000000089773527,
+        0.9856087639128152,
+        0.9952362798386291,
+        1.000000089773527
+      ]
+    ],
+    "cosine_persistence": [
+      [
+        null,
+        null,
+        null,
+        null
+      ],
+      [
+        null,
+        null,
+        null,
+        null
+      ],
+      [
+        null,
+        null,
+        null,
+        null
+      ],
+      [
+        null,
+        null,
+        null,
+        null
+      ]
+    ],
+    "l2_alpha": [
+      [
+        0.0,
+        0.384511798620224,
+        0.22536420822143555,
+        0.0
+      ],
+      [
+        0.384511798620224,
+        0.0,
+        0.3845365643501282,
+        0.384511798620224
+      ],
+      [
+        0.22536420822143555,
+        0.3845365643501282,
+        0.0,
+        0.22536420822143555
+      ],
+      [
+        0.0,
+        0.384511798620224,
+        0.22536420822143555,
+        0.0
+      ]
+    ],
+    "mean_offdiag_cosine_alpha": 0.6985091090230839,
+    "mean_offdiag_cosine_output_state": 0.9829449177233989,
+    "mean_offdiag_cosine_surface_logits": 0.991780413108756,
+    "mean_offdiag_cosine_persistence": null,
+    "interpretation": "If inter-prompt cosine of surface logits / output_state \u2248 1.0, the surface largely ignores prompt-conditioned field differences. Meaningfully < 1 suggests prompt-sensitive state."
+  },
+  "reconstruction": {
+    "last_k": 4,
+    "notes": [
+      "No MERGE/SPLIT in this architecture yet.",
+      "No dedicated field\u2192past-packet decoder exists.",
+      "Consolidation is a single EMA persistence vector, not a packet stack.",
+      "Linear probe below is few-shot diagnostic on the probe prompts only."
+    ],
+    "not_possible_yet": [
+      "MERGE of packets into durable field structures",
+      "SPLIT / dual-clock span control",
+      "Dedicated field \u2192 past-packet decoder",
+      "Retrieving arbitrary past payloads from alpha alone as text"
+    ],
+    "field_differs_across_prompts": true,
+    "persistence_differs_across_prompts": false,
+    "pairwise_alpha_l2": [
+      0.384511798620224,
+      0.22536420822143555,
+      0.0,
+      0.3845365643501282,
+      0.384511798620224,
+      0.22536420822143555
+    ],
+    "pairwise_persistence_l2": [
+      0.0,
+      0.0,
+      0.0,
+      0.0,
+      0.0,
+      0.0
+    ],
+    "mean_pairwise_alpha_l2": 0.2673814296722412,
+    "linear_probe": {
+      "status": "ok",
+      "method": "dual_ridge_least_squares",
+      "lambda": 0.01,
+      "n_prompts": 4,
+      "field_dim": 4224,
+      "feature_dim": 320,
+      "train_mse": 7.184626671374872e-09,
+      "baseline_mean_mse": 0.0012413040967658162,
+      "mse_improvement_vs_mean": 0.0012412969121391448,
+      "pred_target_cosine_per_prompt": [
+        1.0000000605084391,
+        0.9999992448845294,
+        0.9999996897767539,
+        1.0000000605084391
+      ],
+      "mean_pred_target_cosine": 0.9999997639195404,
+      "note": "In-sample fit only (P prompts). Success means field features linearly span last-k packet features on this set \u2014 not a general decoder."
+    },
+    "alpha_reprime_1nn_accuracy": 0.75,
+    "atom_collection_probe": {
+      "status": "ok",
+      "mean_last_k_compiled_vs_stored_r_cosine": 1.0000000186264528,
+      "per_prompt": [
+        0.9999999999999988,
+        1.000000074505813,
+        1.0000000000000009,
+        0.9999999999999988
+      ],
+      "note": "Atom collection stores detached compiled atoms from this episode; high cosine is expected (same episode write). This is NOT recovery from field alone \u2014 it shows structural memory buffer retention."
+    },
+    "reconstruction_succeeds": true,
+    "reconstruction_summary": "partial/diagnostic linear map from field features to last-k packet features works in-sample"
+  },
+  "verdict": {
+    "label": "field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)",
+    "mean_offdiag_cosine_surface_logits": 0.991780413108756,
+    "mean_offdiag_cosine_alpha": 0.6985091090230839,
+    "mean_field_rms_after_prompt": 0.005141582456417382,
+    "mean_field_rms_after_20_gen": 0.03332198318094015,
+    "reconstruction_succeeds": true,
+    "regime_note": "CE down + gen still noise without field reconstruction = still Transformer regime without the farm."
+  }
+}

docs/artifacts/lign_ablate_2k5/probe_before.txt

@@ -0,0 +1,19 @@
+[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native_src.pt (read-only, eval, no optimizer)
+[probe] d_model=64 n_modes=64 step=2102500
+[probe] prompt='Bonjour'
+        RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22
+        gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f<N�f'
+[probe] prompt='Qui es-tu ?'
+        RMS 0.006684 -> 0.024246 (norm 0.4278 -> 1.5518) atoms 7 -> 26
+        gen_preview='un!> sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.�> Uu>rN�frN�frN�f<Nqf-Nqk'
+[probe] prompt='Il était une fois'
+        RMS 0.006216 -> 0.024691 (norm 0.3978 -> 1.5803) atoms 6 -> 25
+        gen_preview='us!> su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk<NqkrNqk<NqkrNqk<Nqk'
+[probe] prompt='Utilisateur: Bonjour\nAssistant:'
+        RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22
+        gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f<N�f'
+[probe] mean off-diag cosine logits=0.992294 alpha=0.720524
+[probe] reconstruction_succeeds=True field_differs=True
+[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_ablate_2k5/probe_before_report.json
+[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged
+[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)

docs/artifacts/lign_ablate_2k5/probe_before_report.json

@@ -0,0 +1,443 @@
+{
+  "timestamp_local": "2026-09-17 19:10:49 PDT",
+  "timestamp_utc": "2026-09-18T02:10:49.897119+00:00",
+  "meta": {
+    "config": {
+      "d_model": 64,
+      "n_modes": 64,
+      "n_atoms_max": 512,
+      "max_payload_bytes": 16,
+      "atomizer_version": "atomizer-v1-byte-span",
+      "field_max_rms": 3.0,
+      "energy_decay_bounds": [
+        0.45,
+        0.95
+      ],
+      "enable_merge": true,
+      "slow_every": 4,
+      "field_loss_weight": 0.08,
+      "field_contrast_weight": 0.45,
+      "field_contrast_margin": 0.45,
+      "merge_count_total": 0
+    },
+    "training_meta": {
+      "step": 2102500,
+      "run_steps": 2500,
+      "seed": 20260917,
+      "episode_reset": false,
+      "atom_flush_every": 256,
+      "dynamics_on_load": {
+        "coupling_scale": 2.0,
+        "energy_decay": 0.44999998807907104,
+        "phase_sync": 1.0,
+        "energy_decay_before": 0.44999998807907104,
+        "energy_decay_repaired": false,
+        "energy_decay_bounds": [
+          0.45,
+          0.95
+        ]
+      }
+    },
+    "checkpoint": "/workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native_src.pt",
+    "checkpoint_bytes": 20531696
+  },
+  "n_gen": 20,
+  "prompts": [
+    "Bonjour",
+    "Qui es-tu ?",
+    "Il \u00e9tait une fois",
+    "Utilisateur: Bonjour\nAssistant:"
+  ],
+  "per_prompt": [
+    {
+      "prompt": "Bonjour",
+      "primed_text": "Utilisateur: Bonjour\nAssistant:",
+      "n_prompt_packets": 3,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Bonjour\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.003676084103062749,
+        "field_norm": 0.23526939749717712,
+        "field_mean_abs": 0.0028248238377273083,
+        "field_max_abs": 0.023399701341986656,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 3,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.029999999329447746
+      },
+      "stats_after_gen": {
+        "field_rms": 0.024275178089737892,
+        "field_norm": 1.5536115169525146,
+        "field_mean_abs": 0.01747151091694832,
+        "field_max_abs": 0.15346266329288483,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 22,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2200000286102295
+      },
+      "generated_preview": "us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdf<N\ufffdf",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 258.1448059082031
+    },
+    {
+      "prompt": "Qui es-tu ?",
+      "primed_text": "Utilisateur: Qui es-tu ?\nAssistant:",
+      "n_prompt_packets": 7,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Qui ",
+        "es-",
+        "tu ",
+        "?",
+        "\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.006684120744466782,
+        "field_norm": 0.427783727645874,
+        "field_mean_abs": 0.004947622772306204,
+        "field_max_abs": 0.03267180919647217,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 7,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.06999999284744263
+      },
+      "stats_after_gen": {
+        "field_rms": 0.024246206507086754,
+        "field_norm": 1.5517570972442627,
+        "field_mean_abs": 0.017805296927690506,
+        "field_max_abs": 0.15625834465026855,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 26,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2600000202655792
+      },
+      "generated_preview": "un!> sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdfrN\ufffdf<Nqf-Nqk",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 256.7497253417969
+    },
+    {
+      "prompt": "Il \u00e9tait une fois",
+      "primed_text": "Utilisateur: Il \u00e9tait une fois\nAssistant:",
+      "n_prompt_packets": 6,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Il ",
+        "\u00e9tait ",
+        "une ",
+        "fois\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.006216110195964575,
+        "field_norm": 0.39783111214637756,
+        "field_mean_abs": 0.00469403387978673,
+        "field_max_abs": 0.03926796838641167,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 6,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.059999994933605194
+      },
+      "stats_after_gen": {
+        "field_rms": 0.024691486731171608,
+        "field_norm": 1.5802550315856934,
+        "field_mean_abs": 0.01791311614215374,
+        "field_max_abs": 0.17595124244689941,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 25,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2500000298023224
+      },
+      "generated_preview": "us!> su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk<NqkrNqk<NqkrNqk<Nqk",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 231.27496337890625
+    },
+    {
+      "prompt": "Utilisateur: Bonjour\nAssistant:",
+      "primed_text": "Utilisateur: Bonjour\nAssistant:",
+      "n_prompt_packets": 3,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Bonjour\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.003676084103062749,
+        "field_norm": 0.23526939749717712,
+        "field_mean_abs": 0.0028248238377273083,
+        "field_max_abs": 0.023399701341986656,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 3,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.029999999329447746
+      },
+      "stats_after_gen": {
+        "field_rms": 0.024275178089737892,
+        "field_norm": 1.5536115169525146,
+        "field_mean_abs": 0.01747151091694832,
+        "field_max_abs": 0.15346266329288483,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 22,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2200000286102295
+      },
+      "generated_preview": "us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdf<N\ufffdf",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 258.1448059082031
+    }
+  ],
+  "prompt_sensitivity": {
+    "prompts": [
+      "Bonjour",
+      "Qui es-tu ?",
+      "Il \u00e9tait une fois",
+      "Utilisateur: Bonjour\nAssistant:"
+    ],
+    "cosine_alpha": [
+      [
+        1.0000000010696808,
+        0.5777154791055652,
+        0.7729251253508227,
+        1.0000000010696808
+      ],
+      [
+        0.5777154791055652,
+        1.000000042671644,
+        0.6218612447610297,
+        0.5777154791055652
+      ],
+      [
+        0.7729251253508227,
+        0.6218612447610297,
+        0.9999999392637661,
+        0.7729251253508227
+      ],
+      [
+        1.0000000010696808,
+        0.5777154791055652,
+        0.7729251253508227,
+        1.0000000010696808
+      ]
+    ],
+    "cosine_output_state": [
+      [
+        0.9999999891192305,
+        0.9161426365659249,
+        0.9742751370113187,
+        0.9999999891192305
+      ],
+      [
+        0.9161426365659249,
+        0.9999998381068331,
+        0.9461548317893612,
+        0.9161426365659249
+      ],
+      [
+        0.9742751370113187,
+        0.9461548317893612,
+        1.0000000097048674,
+        0.9742751370113187
+      ],
+      [
+        0.9999999891192305,
+        0.9161426365659249,
+        0.9742751370113187,
+        0.9999999891192305
+      ]
+    ],
+    "cosine_surface_logits": [
+      [
+        0.9999998618914014,
+        0.9879877343692317,
+        0.9963434716757233,
+        0.9999998618914014
+      ],
+      [
+        0.9879877343692317,
+        1.0000001023017826,
+        0.9851037468519606,
+        0.9879877343692317
+      ],
+      [
+        0.9963434716757233,
+        0.9851037468519606,
+        0.9999998670446335,
+        0.9963434716757233
+      ],
+      [
+        0.9999998618914014,
+        0.9879877343692317,
+        0.9963434716757233,
+        0.9999998618914014
+      ]
+    ],
+    "cosine_persistence": [
+      [
+        null,
+        null,
+        null,
+        null
+      ],
+      [
+        null,
+        null,
+        null,
+        null
+      ],
+      [
+        null,
+        null,
+        null,
+        null
+      ],
+      [
+        null,
+        null,
+        null,
+        null
+      ]
+    ],
+    "l2_alpha": [
+      [
+        0.0,
+        0.34937506914138794,
+        0.2625519931316376,
+        0.0
+      ],
+      [
+        0.34937506914138794,
+        0.0,
+        0.3600066006183624,
+        0.34937506914138794
+      ],
+      [
+        0.2625519931316376,
+        0.3600066006183624,
+        0.0,
+        0.2625519931316376
+      ],
+      [
+        0.0,
+        0.34937506914138794,
+        0.2625519931316376,
+        0.0
+      ]
+    ],
+    "mean_offdiag_cosine_alpha": 0.7205237424572477,
+    "mean_offdiag_cosine_output_state": 0.9544983946771799,
+    "mean_offdiag_cosine_surface_logits": 0.9922943368055454,
+    "mean_offdiag_cosine_persistence": null,
+    "interpretation": "If inter-prompt cosine of surface logits / output_state \u2248 1.0, the surface largely ignores prompt-conditioned field differences. Meaningfully < 1 suggests prompt-sensitive state."
+  },
+  "reconstruction": {
+    "last_k": 4,
+    "notes": [
+      "No MERGE/SPLIT in this architecture yet.",
+      "No dedicated field\u2192past-packet decoder exists.",
+      "Consolidation is a single EMA persistence vector, not a packet stack.",
+      "Linear probe below is few-shot diagnostic on the probe prompts only."
+    ],
+    "not_possible_yet": [
+      "MERGE of packets into durable field structures",
+      "SPLIT / dual-clock span control",
+      "Dedicated field \u2192 past-packet decoder",
+      "Retrieving arbitrary past payloads from alpha alone as text"
+    ],
+    "field_differs_across_prompts": true,
+    "persistence_differs_across_prompts": false,
+    "pairwise_alpha_l2": [
+      0.34937506914138794,
+      0.2625519931316376,
+      0.0,
+      0.3600066006183624,
+      0.34937506914138794,
+      0.2625519931316376
+    ],
+    "pairwise_persistence_l2": [
+      0.0,
+      0.0,
+      0.0,
+      0.0,
+      0.0,
+      0.0
+    ],
+    "mean_pairwise_alpha_l2": 0.2639767875274022,
+    "linear_probe": {
+      "status": "ok",
+      "method": "dual_ridge_least_squares",
+      "lambda": 0.01,
+      "n_prompts": 4,
+      "field_dim": 4224,
+      "feature_dim": 320,
+      "train_mse": 8.09912759081044e-09,
+      "baseline_mean_mse": 0.0012413040967658162,
+      "mse_improvement_vs_mean": 0.0012412959976382254,
+      "pred_target_cosine_per_prompt": [
+        0.9999999407911363,
+        0.9999993095673745,
+        0.9999995249463862,
+        0.9999999407911363
+      ],
+      "mean_pred_target_cosine": 0.9999996790240083,
+      "note": "In-sample fit only (P prompts). Success means field features linearly span last-k packet features on this set \u2014 not a general decoder."
+    },
+    "alpha_reprime_1nn_accuracy": 0.75,
+    "atom_collection_probe": {
+      "status": "ok",
+      "mean_last_k_compiled_vs_stored_r_cosine": 1.0000000161429243,
+      "per_prompt": [
+        1.00000003973643,
+        0.9999999999999991,
+        0.9999999850988388,
+        1.00000003973643
+      ],
+      "note": "Atom collection stores detached compiled atoms from this episode; high cosine is expected (same episode write). This is NOT recovery from field alone \u2014 it shows structural memory buffer retention."
+    },
+    "reconstruction_succeeds": true,
+    "reconstruction_summary": "partial/diagnostic linear map from field features to last-k packet features works in-sample"
+  },
+  "verdict": {
+    "label": "field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)",
+    "mean_offdiag_cosine_surface_logits": 0.9922943368055454,
+    "mean_offdiag_cosine_alpha": 0.7205237424572477,
+    "mean_field_rms_after_prompt": 0.0050630997866392136,
+    "mean_field_rms_after_20_gen": 0.024372012354433537,
+    "reconstruction_succeeds": true,
+    "regime_note": "CE down + gen still noise without field reconstruction = still Transformer regime without the farm."
+  }
+}

docs/artifacts/lign_ablate_2k5/run_metrics.json

@@ -0,0 +1,126 @@
+{
+  "stream": false,
+  "data_path": "data/corpus_train_chat.txt",
+  "data_glob": null,
+  "shard_paths": [
+    "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt"
+  ],
+  "data_bytes": 777806,
+  "data_characters": 766865,
+  "atomizer_version": "atomizer-v1-byte-span",
+  "feature_dim": 320,
+  "packet_count": 154661,
+  "train_packet_count": 154597,
+  "validation_packet_count": 64,
+  "mean_packet_bytes": 5.029102359353684,
+  "max_packet_bytes": 17,
+  "min_packet_bytes": 1,
+  "config": {
+    "d_model": 64,
+    "n_modes": 64,
+    "n_atoms_max": 512,
+    "max_span_bytes": 16,
+    "episode_length": 512,
+    "episode_reset": false,
+    "atom_flush_every": 256,
+    "learning_rate": 0.0001,
+    "surface_learning_rate": 0.0003,
+    "steps": 2500,
+    "start_step": 2102500,
+    "seed": 20260917,
+    "surface_alphabet": 256,
+    "field_max_rms": 3.0,
+    "energy_decay_bounds": [
+      0.45,
+      0.95
+    ],
+    "stream": false,
+    "enable_merge": true,
+    "field_loss_weight": 0.08,
+    "field_contrast_weight": 0.45,
+    "field_ignorance_weight": 0.08,
+    "field_ignorance_ablate_shared": true,
+    "field_ignorance_prompt_bank": false,
+    "slow_every": 4
+  },
+  "train": {
+    "steps": 2500,
+    "start_step": 2102500,
+    "total_steps": 2105000,
+    "episode_length": 512,
+    "episode_reset": false,
+    "atom_flush_every": 256,
+    "elapsed_seconds": 44.848359566996805,
+    "transitions_per_second": 55.74339895900474,
+    "first_loss": 6.400629043579102,
+    "final_loss": 6.3305253982543945,
+    "final_total_perplexity": 561.4515020131753,
+    "finite_losses": true,
+    "finite_parameters": true,
+    "nan_or_inf": false,
+    "field_rms_before_max": 3.0074563026428223,
+    "field_rms_after_max": 2.999999523162842,
+    "field_scale_min": 0.997520387172699,
+    "field_norm_max": 191.9999542236328,
+    "field_limited_steps": 1262,
+    "field_limited_fraction": 0.5048,
+    "final_dynamics": {
+      "coupling_scale": 1.9906045198440552,
+      "energy_decay": 0.44999998807907104,
+      "phase_sync": 0.9987071752548218,
+      "energy_decay_before": 0.4499995708465576,
+      "energy_decay_repaired": true,
+      "energy_decay_bounds": [
+        0.45,
+        0.95
+      ]
+    },
+    "final_atoms_before_validation": 7,
+    "stream": false,
+    "bytes_seen": 777806
+  },
+  "validation": {
+    "transitions": 63,
+    "loss": 17.185137315401956,
+    "total_perplexity": 29067675.73906257,
+    "byte_loss": 6.6650525984309965,
+    "byte_perplexity": 784.5047276135747,
+    "source": "held_out_tail"
+  },
+  "checkpoint": "checkpoints/atom_native_lign_ablate/atom_native.pt",
+  "reload": {
+    "n_atoms": 196,
+    "field_norm": 191.9998779296875,
+    "time": 25.000476837158203,
+    "finite": true
+  },
+  "generation": {
+    "The future of AI is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c69692c652c7121742d5671696e4eaa6a3c6576",
+      "text": "<ii,e,q!t-VqinN\ufffdj<ev",
+      "reload_text": "<ii,e,q!t-VqinN\ufffdj<ev",
+      "reload_match": true
+    },
+    "Bonjour, je m'appelle": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c687166662c2c21659174d8d720646b3e203d6b",
+      "text": "<hqff,,!e\ufffdt\ufffd\ufffd dk> =k",
+      "reload_text": "<hqff,,!e\ufffdt\ufffd\ufffd dk> =k",
+      "reload_match": true
+    },
+    "Valkyria Chronicles III is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c69692c6f2c71216520706b3e203d6b3e203d6b",
+      "text": "<ii,o,q!e pk> =k> =k",
+      "reload_text": "<ii,o,q!e pk> =k> =k",
+      "reload_match": true
+    }
+  }
+}

docs/artifacts/lign_ablate_2k5/series_row.json

@@ -0,0 +1,12 @@
+{
+  "name": "ablate",
+  "before_logits_cos": 0.992294,
+  "after_logits_cos": 0.991780,
+  "before_alpha_cos": 0.720524,
+  "after_alpha_cos": 0.698509,
+  "final_ign": 0.1500,
+  "final_mph": 0.500,
+  "merges_nonzero_log_lines": 0,
+  "checkpoint": "checkpoints/atom_native_lign_ablate/atom_native.pt",
+  "flags": ["--field-ignorance-ablate-shared", "--no-field-ignorance-prompt-bank"]
+}

docs/artifacts/lign_ablate_2k5/train_log.txt

@@ -0,0 +1,146 @@
+===== TRAIN ablate =====
+train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3147288)
+resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False)
+dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95))
+optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (14 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0
+optimizer restore skipped: surface LR param groups differ from checkpoint
+step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000
+step=2102700 (run 200/2500) loss=12.30129 byte_ppl=40.252 atoms=200 merges=0 field=9.9244 rms=0.1551 scale=1.0000 fcos=0.293 ign=0.1468 mph=0.500
+step=2102900 (run 400/2500) loss=2.37023 byte_ppl=2.444 atoms=144 merges=0 field=21.5615 rms=0.3369 scale=1.0000 fcos=0.076 ign=0.1462 mph=0.500
+step=2103100 (run 600/2500) loss=0.84953 byte_ppl=1.217 atoms=88 merges=0 field=38.1373 rms=0.5959 scale=1.0000 fcos=0.215 ign=0.1497 mph=0.500
+step=2103300 (run 800/2500) loss=4.14532 byte_ppl=5.120 atoms=32 merges=0 field=64.3113 rms=1.0049 scale=1.0000 fcos=0.234 ign=0.1498 mph=0.500
+step=2103500 (run 1000/2500) loss=10.31853 byte_ppl=92.074 atoms=232 merges=0 field=106.9234 rms=1.6707 scale=1.0000 fcos=0.254 ign=0.1499 mph=0.500
+step=2103700 (run 1200/2500) loss=6.81425 byte_ppl=76.736 atoms=176 merges=0 field=174.8289 rms=2.7317 scale=1.0000 fcos=0.151 ign=0.1499 mph=0.500
+step=2103900 (run 1400/2500) loss=4.61975 byte_ppl=18.999 atoms=120 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.183 ign=0.1499 mph=0.500
+step=2104100 (run 1600/2500) loss=6.30454 byte_ppl=51.807 atoms=64 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.187 ign=0.1500 mph=0.500
+step=2104300 (run 1800/2500) loss=5.01119 byte_ppl=18.008 atoms=8 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.290 ign=0.1500 mph=0.500
+step=2104500 (run 2000/2500) loss=6.39907 byte_ppl=19.718 atoms=208 merges=0 field=191.9999 rms=3.0000 scale=0.9975 fcos=0.277 ign=0.1500 mph=0.500
+step=2104700 (run 2200/2500) loss=6.85184 byte_ppl=13.419 atoms=152 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.235 ign=0.1500 mph=0.500
+step=2104900 (run 2400/2500) loss=8.30257 byte_ppl=124.561 atoms=96 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.275 ign=0.1500 mph=0.500
+step=2105000 (run 2500/2500) loss=6.33053 byte_ppl=20.570 atoms=196 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.300 ign=0.1500 mph=0.500
+{
+  "stream": false,
+  "data_path": "data/corpus_train_chat.txt",
+  "data_glob": null,
+  "shard_paths": [
+    "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt"
+  ],
+  "data_bytes": 777806,
+  "data_characters": 766865,
+  "atomizer_version": "atomizer-v1-byte-span",
+  "feature_dim": 320,
+  "packet_count": 154661,
+  "train_packet_count": 154597,
+  "validation_packet_count": 64,
+  "mean_packet_bytes": 5.029102359353684,
+  "max_packet_bytes": 17,
+  "min_packet_bytes": 1,
+  "config": {
+    "d_model": 64,
+    "n_modes": 64,
+    "n_atoms_max": 512,
+    "max_span_bytes": 16,
+    "episode_length": 512,
+    "episode_reset": false,
+    "atom_flush_every": 256,
+    "learning_rate": 0.0001,
+    "surface_learning_rate": 0.0003,
+    "steps": 2500,
+    "start_step": 2102500,
+    "seed": 20260917,
+    "surface_alphabet": 256,
+    "field_max_rms": 3.0,
+    "energy_decay_bounds": [
+      0.45,
+      0.95
+    ],
+    "stream": false,
+    "enable_merge": true,
+    "field_loss_weight": 0.08,
+    "field_contrast_weight": 0.45,
+    "field_ignorance_weight": 0.08,
+    "field_ignorance_ablate_shared": true,
+    "field_ignorance_prompt_bank": false,
+    "slow_every": 4
+  },
+  "train": {
+    "steps": 2500,
+    "start_step": 2102500,
+    "total_steps": 2105000,
+    "episode_length": 512,
+    "episode_reset": false,
+    "atom_flush_every": 256,
+    "elapsed_seconds": 44.848359566996805,
+    "transitions_per_second": 55.74339895900474,
+    "first_loss": 6.400629043579102,
+    "final_loss": 6.3305253982543945,
+    "final_total_perplexity": 561.4515020131753,
+    "finite_losses": true,
+    "finite_parameters": true,
+    "nan_or_inf": false,
+    "field_rms_before_max": 3.0074563026428223,
+    "field_rms_after_max": 2.999999523162842,
+    "field_scale_min": 0.997520387172699,
+    "field_norm_max": 191.9999542236328,
+    "field_limited_steps": 1262,
+    "field_limited_fraction": 0.5048,
+    "final_dynamics": {
+      "coupling_scale": 1.9906045198440552,
+      "energy_decay": 0.44999998807907104,
+      "phase_sync": 0.9987071752548218,
+      "energy_decay_before": 0.4499995708465576,
+      "energy_decay_repaired": true,
+      "energy_decay_bounds": [
+        0.45,
+        0.95
+      ]
+    },
+    "final_atoms_before_validation": 7,
+    "stream": false,
+    "bytes_seen": 777806
+  },
+  "validation": {
+    "transitions": 63,
+    "loss": 17.185137315401956,
+    "total_perplexity": 29067675.73906257,
+    "byte_loss": 6.6650525984309965,
+    "byte_perplexity": 784.5047276135747,
+    "source": "held_out_tail"
+  },
+  "checkpoint": "checkpoints/atom_native_lign_ablate/atom_native.pt",
+  "reload": {
+    "n_atoms": 196,
+    "field_norm": 191.9998779296875,
+    "time": 25.000476837158203,
+    "finite": true
+  },
+  "generation": {
+    "The future of AI is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c69692c652c7121742d5671696e4eaa6a3c6576",
+      "text": "<ii,e,q!t-VqinN\ufffdj<ev",
+      "reload_text": "<ii,e,q!t-VqinN\ufffdj<ev",
+      "reload_match": true
+    },
+    "Bonjour, je m'appelle": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c687166662c2c21659174d8d720646b3e203d6b",
+      "text": "<hqff,,!e\ufffdt\ufffd\ufffd dk> =k",
+      "reload_text": "<hqff,,!e\ufffdt\ufffd\ufffd dk> =k",
+      "reload_match": true
+    },
+    "Valkyria Chronicles III is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c69692c6f2c71216520706b3e203d6b3e203d6b",
+      "text": "<ii,o,q!e pk> =k> =k",
+      "reload_text": "<ii,o,q!e pk> =k> =k",
+      "reload_match": true
+    }
+  }
+}

docs/artifacts/lign_ablate_2k5/train_log_excerpt.txt

@@ -0,0 +1,57 @@
+# train log excerpt — ablate
+
+===== TRAIN ablate =====
+train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3147288)
+resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False)
+dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95))
+optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (14 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0
+optimizer restore skipped: surface LR param groups differ from checkpoint
+step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000
+step=2102700 (run 200/2500) loss=12.30129 byte_ppl=40.252 atoms=200 merges=0 field=9.9244 rms=0.1551 scale=1.0000 fcos=0.293 ign=0.1468 mph=0.500
+...
+3:resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False)
+7:step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000
+8:step=2102700 (run 200/2500) loss=12.30129 byte_ppl=40.252 atoms=200 merges=0 field=9.9244 rms=0.1551 scale=1.0000 fcos=0.293 ign=0.1468 mph=0.500
+9:step=2102900 (run 400/2500) loss=2.37023 byte_ppl=2.444 atoms=144 merges=0 field=21.5615 rms=0.3369 scale=1.0000 fcos=0.076 ign=0.1462 mph=0.500
+10:step=2103100 (run 600/2500) loss=0.84953 byte_ppl=1.217 atoms=88 merges=0 field=38.1373 rms=0.5959 scale=1.0000 fcos=0.215 ign=0.1497 mph=0.500
+11:step=2103300 (run 800/2500) loss=4.14532 byte_ppl=5.120 atoms=32 merges=0 field=64.3113 rms=1.0049 scale=1.0000 fcos=0.234 ign=0.1498 mph=0.500
+12:step=2103500 (run 1000/2500) loss=10.31853 byte_ppl=92.074 atoms=232 merges=0 field=106.9234 rms=1.6707 scale=1.0000 fcos=0.254 ign=0.1499 mph=0.500
+13:step=2103700 (run 1200/2500) loss=6.81425 byte_ppl=76.736 atoms=176 merges=0 field=174.8289 rms=2.7317 scale=1.0000 fcos=0.151 ign=0.1499 mph=0.500
+14:step=2103900 (run 1400/2500) loss=4.61975 byte_ppl=18.999 atoms=120 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.183 ign=0.1499 mph=0.500
+15:step=2104100 (run 1600/2500) loss=6.30454 byte_ppl=51.807 atoms=64 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.187 ign=0.1500 mph=0.500
+16:step=2104300 (run 1800/2500) loss=5.01119 byte_ppl=18.008 atoms=8 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.290 ign=0.1500 mph=0.500
+17:step=2104500 (run 2000/2500) loss=6.39907 byte_ppl=19.718 atoms=208 merges=0 field=191.9999 rms=3.0000 scale=0.9975 fcos=0.277 ign=0.1500 mph=0.500
+18:step=2104700 (run 2200/2500) loss=6.85184 byte_ppl=13.419 atoms=152 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.235 ign=0.1500 mph=0.500
+19:step=2104900 (run 2400/2500) loss=8.30257 byte_ppl=124.561 atoms=96 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.275 ign=0.1500 mph=0.500
+20:step=2105000 (run 2500/2500) loss=6.33053 byte_ppl=20.570 atoms=196 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.300 ign=0.1500 mph=0.500
+...
+  "generation": {
+    "The future of AI is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c69692c652c7121742d5671696e4eaa6a3c6576",
+      "text": "<ii,e,q!t-VqinN\ufffdj<ev",
+      "reload_text": "<ii,e,q!t-VqinN\ufffdj<ev",
+      "reload_match": true
+    },
+    "Bonjour, je m'appelle": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c687166662c2c21659174d8d720646b3e203d6b",
+      "text": "<hqff,,!e\ufffdt\ufffd\ufffd dk> =k",
+      "reload_text": "<hqff,,!e\ufffdt\ufffd\ufffd dk> =k",
+      "reload_match": true
+    },
+    "Valkyria Chronicles III is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c69692c6f2c71216520706b3e203d6b3e203d6b",
+      "text": "<ii,o,q!e pk> =k> =k",
+      "reload_text": "<ii,o,q!e pk> =k> =k",
+      "reload_match": true
+    }
+  }
+}

docs/artifacts/lign_both_2k5/lign_probe_after.txt

@@ -0,0 +1,19 @@
+[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_both/atom_native.pt (read-only, eval, no optimizer)
+[probe] d_model=64 n_modes=64 step=2105000
+[probe] prompt='Bonjour'
+        RMS 0.003867 -> 0.032399 (norm 0.2475 -> 2.0735) atoms 3 -> 22
+        gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> ,k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Qui es-tu ?'
+        RMS 0.006798 -> 0.034249 (norm 0.4351 -> 2.1919) atoms 7 -> 26
+        gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Il était une fois'
+        RMS 0.006038 -> 0.033752 (norm 0.3864 -> 2.1602) atoms 6 -> 25
+        gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Utilisateur: Bonjour\nAssistant:'
+        RMS 0.003867 -> 0.032399 (norm 0.2475 -> 2.0735) atoms 3 -> 22
+        gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> ,k> =k> =k> =k> =k> =k> =k>'
+[probe] mean off-diag cosine logits=0.992358 alpha=0.698481
+[probe] reconstruction_succeeds=True field_differs=True
+[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_both_2k5/probe_after_report.json
+[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged
+[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)

docs/artifacts/lign_both_2k5/lign_probe_before.txt

@@ -0,0 +1,19 @@
+[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native_src.pt (read-only, eval, no optimizer)
+[probe] d_model=64 n_modes=64 step=2102500
+[probe] prompt='Bonjour'
+        RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22
+        gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f<N�f'
+[probe] prompt='Qui es-tu ?'
+        RMS 0.006684 -> 0.024246 (norm 0.4278 -> 1.5518) atoms 7 -> 26
+        gen_preview='un!> sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.�> Uu>rN�frN�frN�f<Nqf-Nqk'
+[probe] prompt='Il était une fois'
+        RMS 0.006216 -> 0.024691 (norm 0.3978 -> 1.5803) atoms 6 -> 25
+        gen_preview='us!> su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk<NqkrNqk<NqkrNqk<Nqk'
+[probe] prompt='Utilisateur: Bonjour\nAssistant:'
+        RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22
+        gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f<N�f'
+[probe] mean off-diag cosine logits=0.992294 alpha=0.720524
+[probe] reconstruction_succeeds=True field_differs=True
+[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_both_2k5/probe_before_report.json
+[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged
+[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)

docs/artifacts/lign_both_2k5/probe_after.txt

@@ -0,0 +1,19 @@
+[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_both/atom_native.pt (read-only, eval, no optimizer)
+[probe] d_model=64 n_modes=64 step=2105000
+[probe] prompt='Bonjour'
+        RMS 0.003867 -> 0.032399 (norm 0.2475 -> 2.0735) atoms 3 -> 22
+        gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> ,k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Qui es-tu ?'
+        RMS 0.006798 -> 0.034249 (norm 0.4351 -> 2.1919) atoms 7 -> 26
+        gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Il était une fois'
+        RMS 0.006038 -> 0.033752 (norm 0.3864 -> 2.1602) atoms 6 -> 25
+        gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Utilisateur: Bonjour\nAssistant:'
+        RMS 0.003867 -> 0.032399 (norm 0.2475 -> 2.0735) atoms 3 -> 22
+        gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> ,k> =k> =k> =k> =k> =k> =k>'
+[probe] mean off-diag cosine logits=0.992358 alpha=0.698481
+[probe] reconstruction_succeeds=True field_differs=True
+[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_both_2k5/probe_after_report.json
+[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged
+[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)

docs/artifacts/lign_both_2k5/probe_after_report.json

@@ -0,0 +1,447 @@
+{
+  "timestamp_local": "2026-09-17 19:13:57 PDT",
+  "timestamp_utc": "2026-09-18T02:13:57.778386+00:00",
+  "meta": {
+    "config": {
+      "d_model": 64,
+      "n_modes": 64,
+      "n_atoms_max": 512,
+      "max_payload_bytes": 16,
+      "atomizer_version": "atomizer-v1-byte-span",
+      "field_max_rms": 3.0,
+      "energy_decay_bounds": [
+        0.45,
+        0.95
+      ],
+      "enable_merge": true,
+      "slow_every": 4,
+      "field_loss_weight": 0.08,
+      "field_contrast_weight": 0.45,
+      "field_contrast_margin": 0.45,
+      "field_ignorance_weight": 0.08,
+      "field_ignorance_margin": 0.85,
+      "field_ignorance_ablate_shared": true,
+      "field_ignorance_prompt_bank": true,
+      "merge_count_total": 0
+    },
+    "training_meta": {
+      "step": 2105000,
+      "run_steps": 2500,
+      "seed": 20260917,
+      "episode_reset": false,
+      "atom_flush_every": 256,
+      "dynamics_on_load": {
+        "coupling_scale": 1.9910084009170532,
+        "energy_decay": 0.44999998807907104,
+        "phase_sync": 0.9985595941543579,
+        "energy_decay_before": 0.44999998807907104,
+        "energy_decay_repaired": false,
+        "energy_decay_bounds": [
+          0.45,
+          0.95
+        ]
+      }
+    },
+    "checkpoint": "/workspace/exports/atom-ai/checkpoints/atom_native_lign_both/atom_native.pt",
+    "checkpoint_bytes": 20532464
+  },
+  "n_gen": 20,
+  "prompts": [
+    "Bonjour",
+    "Qui es-tu ?",
+    "Il \u00e9tait une fois",
+    "Utilisateur: Bonjour\nAssistant:"
+  ],
+  "per_prompt": [
+    {
+      "prompt": "Bonjour",
+      "primed_text": "Utilisateur: Bonjour\nAssistant:",
+      "n_prompt_packets": 3,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Bonjour\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.0038667896296828985,
+        "field_norm": 0.2474745512008667,
+        "field_mean_abs": 0.002933506853878498,
+        "field_max_abs": 0.02435270883142948,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 3,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.029999999329447746
+      },
+      "stats_after_gen": {
+        "field_rms": 0.032398514449596405,
+        "field_norm": 2.07350492477417,
+        "field_mean_abs": 0.023319242522120476,
+        "field_max_abs": 0.14671093225479126,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 22,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2200000286102295
+      },
+      "generated_preview": "unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> ,k> =k> =k> =k> =k> =k> =k>",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 277.39556884765625
+    },
+    {
+      "prompt": "Qui es-tu ?",
+      "primed_text": "Utilisateur: Qui es-tu ?\nAssistant:",
+      "n_prompt_packets": 7,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Qui ",
+        "es-",
+        "tu ",
+        "?",
+        "\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.006798470858484507,
+        "field_norm": 0.43510210514068604,
+        "field_mean_abs": 0.005093753337860107,
+        "field_max_abs": 0.03420306369662285,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 7,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.06999999284744263
+      },
+      "stats_after_gen": {
+        "field_rms": 0.03424892947077751,
+        "field_norm": 2.1919312477111816,
+        "field_mean_abs": 0.02527393214404583,
+        "field_max_abs": 0.1521221101284027,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 26,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2600000202655792
+      },
+      "generated_preview": "unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 224.024658203125
+    },
+    {
+      "prompt": "Il \u00e9tait une fois",
+      "primed_text": "Utilisateur: Il \u00e9tait une fois\nAssistant:",
+      "n_prompt_packets": 6,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Il ",
+        "\u00e9tait ",
+        "une ",
+        "fois\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.006037530023604631,
+        "field_norm": 0.3864019513130188,
+        "field_mean_abs": 0.004503221251070499,
+        "field_max_abs": 0.03779352456331253,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 6,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.059999994933605194
+      },
+      "stats_after_gen": {
+        "field_rms": 0.033752478659152985,
+        "field_norm": 2.160158634185791,
+        "field_mean_abs": 0.024521082639694214,
+        "field_max_abs": 0.15114596486091614,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 25,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2500000298023224
+      },
+      "generated_preview": "unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 247.80909729003906
+    },
+    {
+      "prompt": "Utilisateur: Bonjour\nAssistant:",
+      "primed_text": "Utilisateur: Bonjour\nAssistant:",
+      "n_prompt_packets": 3,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Bonjour\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.0038667896296828985,
+        "field_norm": 0.2474745512008667,
+        "field_mean_abs": 0.002933506853878498,
+        "field_max_abs": 0.02435270883142948,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 3,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.029999999329447746
+      },
+      "stats_after_gen": {
+        "field_rms": 0.032398514449596405,
+        "field_norm": 2.07350492477417,
+        "field_mean_abs": 0.023319242522120476,
+        "field_max_abs": 0.14671093225479126,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 22,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2200000286102295
+      },
+      "generated_preview": "unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> ,k> =k> =k> =k> =k> =k> =k>",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 277.39556884765625
+    }
+  ],
+  "prompt_sensitivity": {
+    "prompts": [
+      "Bonjour",
+      "Qui es-tu ?",
+      "Il \u00e9tait une fois",
+      "Utilisateur: Bonjour\nAssistant:"
+    ],
+    "cosine_alpha": [
+      [
+        0.9999999968217755,
+        0.4764792049119334,
+        0.8354733430631697,
+        0.9999999968217755
+      ],
+      [
+        0.4764792049119334,
+        1.000000167715084,
+        0.5669796813780352,
+        0.4764792049119334
+      ],
+      [
+        0.8354733430631697,
+        0.5669796813780352,
+        0.9999997550955949,
+        0.8354733430631697
+      ],
+      [
+        0.9999999968217755,
+        0.4764792049119334,
+        0.8354733430631697,
+        0.9999999968217755
+      ]
+    ],
+    "cosine_output_state": [
+      [
+        1.0000001201656668,
+        0.970649331773234,
+        0.9900165471385234,
+        1.0000001201656668
+      ],
+      [
+        0.970649331773234,
+        0.999999947744685,
+        0.9767877563333452,
+        0.970649331773234
+      ],
+      [
+        0.9900165471385234,
+        0.9767877563333452,
+        0.9999999134828831,
+        0.9900165471385234
+      ],
+      [
+        1.0000001201656668,
+        0.970649331773234,
+        0.9900165471385234,
+        1.0000001201656668
+      ]
+    ],
+    "cosine_surface_logits": [
+      [
+        1.0000002645084607,
+        0.9868905506754033,
+        0.9955139524229406,
+        1.0000002645084607
+      ],
+      [
+        0.9868905506754033,
+        1.0000000457084584,
+        0.9893375376062745,
+        0.9868905506754033
+      ],
+      [
+        0.9955139524229406,
+        0.9893375376062745,
+        0.9999999218617306,
+        0.9955139524229406
+      ],
+      [
+        1.0000002645084607,
+        0.9868905506754033,
+        0.9955139524229406,
+        1.0000002645084607
+      ]
+    ],
+    "cosine_persistence": [
+      [
+        null,
+        null,
+        null,
+        null
+      ],
+      [
+        null,
+        null,
+        null,
+        null
+      ],
+      [
+        null,
+        null,
+        null,
+        null
+      ],
+      [
+        null,
+        null,
+        null,
+        null
+      ]
+    ],
+    "l2_alpha": [
+      [
+        0.0,
+        0.38463765382766724,
+        0.22531399130821228,
+        0.0
+      ],
+      [
+        0.38463765382766724,
+        0.0,
+        0.38467419147491455,
+        0.38463765382766724
+      ],
+      [
+        0.22531399130821228,
+        0.38467419147491455,
+        0.0,
+        0.22531399130821228
+      ],
+      [
+        0.0,
+        0.38463765382766724,
+        0.22531399130821228,
+        0.0
+      ]
+    ],
+    "mean_offdiag_cosine_alpha": 0.6984807956916694,
+    "mean_offdiag_cosine_output_state": 0.9830199390537544,
+    "mean_offdiag_cosine_surface_logits": 0.9923578013852371,
+    "mean_offdiag_cosine_persistence": null,
+    "interpretation": "If inter-prompt cosine of surface logits / output_state \u2248 1.0, the surface largely ignores prompt-conditioned field differences. Meaningfully < 1 suggests prompt-sensitive state."
+  },
+  "reconstruction": {
+    "last_k": 4,
+    "notes": [
+      "No MERGE/SPLIT in this architecture yet.",
+      "No dedicated field\u2192past-packet decoder exists.",
+      "Consolidation is a single EMA persistence vector, not a packet stack.",
+      "Linear probe below is few-shot diagnostic on the probe prompts only."
+    ],
+    "not_possible_yet": [
+      "MERGE of packets into durable field structures",
+      "SPLIT / dual-clock span control",
+      "Dedicated field \u2192 past-packet decoder",
+      "Retrieving arbitrary past payloads from alpha alone as text"
+    ],
+    "field_differs_across_prompts": true,
+    "persistence_differs_across_prompts": false,
+    "pairwise_alpha_l2": [
+      0.38463765382766724,
+      0.22531399130821228,
+      0.0,
+      0.38467419147491455,
+      0.38463765382766724,
+      0.22531399130821228
+    ],
+    "pairwise_persistence_l2": [
+      0.0,
+      0.0,
+      0.0,
+      0.0,
+      0.0,
+      0.0
+    ],
+    "mean_pairwise_alpha_l2": 0.26742958029111225,
+    "linear_probe": {
+      "status": "ok",
+      "method": "dual_ridge_least_squares",
+      "lambda": 0.01,
+      "n_prompts": 4,
+      "field_dim": 4224,
+      "feature_dim": 320,
+      "train_mse": 7.22156645593941e-09,
+      "baseline_mean_mse": 0.0012413040967658162,
+      "mse_improvement_vs_mean": 0.0012412968751993603,
+      "pred_target_cosine_per_prompt": [
+        0.999999935346222,
+        0.9999992268162038,
+        0.9999996283491076,
+        0.999999935346222
+      ],
+      "mean_pred_target_cosine": 0.9999996814644388,
+      "note": "In-sample fit only (P prompts). Success means field features linearly span last-k packet features on this set \u2014 not a general decoder."
+    },
+    "alpha_reprime_1nn_accuracy": 0.75,
+    "atom_collection_probe": {
+      "status": "ok",
+      "mean_last_k_compiled_vs_stored_r_cosine": 0.9999999838570781,
+      "per_prompt": [
+        0.9999999602635737,
+        0.9999999701976776,
+        1.0000000447034871,
+        0.9999999602635737
+      ],
+      "note": "Atom collection stores detached compiled atoms from this episode; high cosine is expected (same episode write). This is NOT recovery from field alone \u2014 it shows structural memory buffer retention."
+    },
+    "reconstruction_succeeds": true,
+    "reconstruction_summary": "partial/diagnostic linear map from field features to last-k packet features works in-sample"
+  },
+  "verdict": {
+    "label": "field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)",
+    "mean_offdiag_cosine_surface_logits": 0.9923578013852371,
+    "mean_offdiag_cosine_alpha": 0.6984807956916694,
+    "mean_field_rms_after_prompt": 0.005142395035363734,
+    "mean_field_rms_after_20_gen": 0.03319960925728083,
+    "reconstruction_succeeds": true,
+    "regime_note": "CE down + gen still noise without field reconstruction = still Transformer regime without the farm."
+  }
+}

docs/artifacts/lign_both_2k5/probe_before.txt

@@ -0,0 +1,19 @@
+[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native_src.pt (read-only, eval, no optimizer)
+[probe] d_model=64 n_modes=64 step=2102500
+[probe] prompt='Bonjour'
+        RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22
+        gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f<N�f'
+[probe] prompt='Qui es-tu ?'
+        RMS 0.006684 -> 0.024246 (norm 0.4278 -> 1.5518) atoms 7 -> 26
+        gen_preview='un!> sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.�> Uu>rN�frN�frN�f<Nqf-Nqk'
+[probe] prompt='Il était une fois'
+        RMS 0.006216 -> 0.024691 (norm 0.3978 -> 1.5803) atoms 6 -> 25
+        gen_preview='us!> su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk<NqkrNqk<NqkrNqk<Nqk'
+[probe] prompt='Utilisateur: Bonjour\nAssistant:'
+        RMS 0.003676 -> 0.024275 (norm 0.2353 -> 1.5536) atoms 3 -> 22
+        gen_preview='us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.�> Uu>rN�frN�f<N�f'
+[probe] mean off-diag cosine logits=0.992294 alpha=0.720524
+[probe] reconstruction_succeeds=True field_differs=True
+[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_both_2k5/probe_before_report.json
+[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged
+[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)

docs/artifacts/lign_both_2k5/probe_before_report.json

@@ -0,0 +1,443 @@
+{
+  "timestamp_local": "2026-09-17 19:12:57 PDT",
+  "timestamp_utc": "2026-09-18T02:12:57.935306+00:00",
+  "meta": {
+    "config": {
+      "d_model": 64,
+      "n_modes": 64,
+      "n_atoms_max": 512,
+      "max_payload_bytes": 16,
+      "atomizer_version": "atomizer-v1-byte-span",
+      "field_max_rms": 3.0,
+      "energy_decay_bounds": [
+        0.45,
+        0.95
+      ],
+      "enable_merge": true,
+      "slow_every": 4,
+      "field_loss_weight": 0.08,
+      "field_contrast_weight": 0.45,
+      "field_contrast_margin": 0.45,
+      "merge_count_total": 0
+    },
+    "training_meta": {
+      "step": 2102500,
+      "run_steps": 2500,
+      "seed": 20260917,
+      "episode_reset": false,
+      "atom_flush_every": 256,
+      "dynamics_on_load": {
+        "coupling_scale": 2.0,
+        "energy_decay": 0.44999998807907104,
+        "phase_sync": 1.0,
+        "energy_decay_before": 0.44999998807907104,
+        "energy_decay_repaired": false,
+        "energy_decay_bounds": [
+          0.45,
+          0.95
+        ]
+      }
+    },
+    "checkpoint": "/workspace/exports/atom-ai/checkpoints/atom_native_lign_smoke/atom_native_src.pt",
+    "checkpoint_bytes": 20531696
+  },
+  "n_gen": 20,
+  "prompts": [
+    "Bonjour",
+    "Qui es-tu ?",
+    "Il \u00e9tait une fois",
+    "Utilisateur: Bonjour\nAssistant:"
+  ],
+  "per_prompt": [
+    {
+      "prompt": "Bonjour",
+      "primed_text": "Utilisateur: Bonjour\nAssistant:",
+      "n_prompt_packets": 3,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Bonjour\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.003676084103062749,
+        "field_norm": 0.23526939749717712,
+        "field_mean_abs": 0.0028248238377273083,
+        "field_max_abs": 0.023399701341986656,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 3,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.029999999329447746
+      },
+      "stats_after_gen": {
+        "field_rms": 0.024275178089737892,
+        "field_norm": 1.5536115169525146,
+        "field_mean_abs": 0.01747151091694832,
+        "field_max_abs": 0.15346266329288483,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 22,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2200000286102295
+      },
+      "generated_preview": "us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdf<N\ufffdf",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 258.1448059082031
+    },
+    {
+      "prompt": "Qui es-tu ?",
+      "primed_text": "Utilisateur: Qui es-tu ?\nAssistant:",
+      "n_prompt_packets": 7,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Qui ",
+        "es-",
+        "tu ",
+        "?",
+        "\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.006684120744466782,
+        "field_norm": 0.427783727645874,
+        "field_mean_abs": 0.004947622772306204,
+        "field_max_abs": 0.03267180919647217,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 7,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.06999999284744263
+      },
+      "stats_after_gen": {
+        "field_rms": 0.024246206507086754,
+        "field_norm": 1.5517570972442627,
+        "field_mean_abs": 0.017805296927690506,
+        "field_max_abs": 0.15625834465026855,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 26,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2600000202655792
+      },
+      "generated_preview": "un!> sn>use>ub!> su>us!> su>us!> bu>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdfrN\ufffdf<Nqf-Nqk",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 256.7497253417969
+    },
+    {
+      "prompt": "Il \u00e9tait une fois",
+      "primed_text": "Utilisateur: Il \u00e9tait une fois\nAssistant:",
+      "n_prompt_packets": 6,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Il ",
+        "\u00e9tait ",
+        "une ",
+        "fois\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.006216110195964575,
+        "field_norm": 0.39783111214637756,
+        "field_mean_abs": 0.00469403387978673,
+        "field_max_abs": 0.03926796838641167,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 6,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.059999994933605194
+      },
+      "stats_after_gen": {
+        "field_rms": 0.024691486731171608,
+        "field_norm": 1.5802550315856934,
+        "field_mean_abs": 0.01791311614215374,
+        "field_max_abs": 0.17595124244689941,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 25,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2500000298023224
+      },
+      "generated_preview": "us!> su>us!> bu>ub!> su>ub!> pu> su>uN!>u.q> Uu>rNqfdNqkdNdk<NqkrNqk<NqkrNqk<Nqk",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 231.27496337890625
+    },
+    {
+      "prompt": "Utilisateur: Bonjour\nAssistant:",
+      "primed_text": "Utilisateur: Bonjour\nAssistant:",
+      "n_prompt_packets": 3,
+      "packet_payloads": [
+        "Utilisateur:",
+        " Bonjour\n",
+        "Assistant:"
+      ],
+      "stats_after_prompt": {
+        "field_rms": 0.003676084103062749,
+        "field_norm": 0.23526939749717712,
+        "field_mean_abs": 0.0028248238377273083,
+        "field_max_abs": 0.023399701341986656,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 3,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.029999999329447746
+      },
+      "stats_after_gen": {
+        "field_rms": 0.024275178089737892,
+        "field_norm": 1.5536115169525146,
+        "field_mean_abs": 0.01747151091694832,
+        "field_max_abs": 0.15346266329288483,
+        "alpha_numel": 4096,
+        "persistence_norm": 0.0,
+        "persistence_mean_abs": 0.0,
+        "persistence_strength": 0.0,
+        "n_atoms": 22,
+        "consolidation_count": 0,
+        "abstraction_count": 0,
+        "t": 0.2200000286102295
+      },
+      "generated_preview": "us!> su>us!> su>us!> bu>us!> bu>ub!> pu> su>ub!> pu> su>uN!>u.\ufffd> Uu>rN\ufffdfrN\ufffdf<N\ufffdf",
+      "generated_bytes": 80,
+      "surface_byte_logits_norm": 258.1448059082031
+    }
+  ],
+  "prompt_sensitivity": {
+    "prompts": [
+      "Bonjour",
+      "Qui es-tu ?",
+      "Il \u00e9tait une fois",
+      "Utilisateur: Bonjour\nAssistant:"
+    ],
+    "cosine_alpha": [
+      [
+        1.0000000010696808,
+        0.5777154791055652,
+        0.7729251253508227,
+        1.0000000010696808
+      ],
+      [
+        0.5777154791055652,
+        1.000000042671644,
+        0.6218612447610297,
+        0.5777154791055652
+      ],
+      [
+        0.7729251253508227,
+        0.6218612447610297,
+        0.9999999392637661,
+        0.7729251253508227
+      ],
+      [
+        1.0000000010696808,
+        0.5777154791055652,
+        0.7729251253508227,
+        1.0000000010696808
+      ]
+    ],
+    "cosine_output_state": [
+      [
+        0.9999999891192305,
+        0.9161426365659249,
+        0.9742751370113187,
+        0.9999999891192305
+      ],
+      [
+        0.9161426365659249,
+        0.9999998381068331,
+        0.9461548317893612,
+        0.9161426365659249
+      ],
+      [
+        0.9742751370113187,
+        0.9461548317893612,
+        1.0000000097048674,
+        0.9742751370113187
+      ],
+      [
+        0.9999999891192305,
+        0.9161426365659249,
+        0.9742751370113187,
+        0.9999999891192305
+      ]
+    ],
+    "cosine_surface_logits": [
+      [
+        0.9999998618914014,
+        0.9879877343692317,
+        0.9963434716757233,
+        0.9999998618914014
+      ],
+      [
+        0.9879877343692317,
+        1.0000001023017826,
+        0.9851037468519606,
+        0.9879877343692317
+      ],
+      [
+        0.9963434716757233,
+        0.9851037468519606,
+        0.9999998670446335,
+        0.9963434716757233
+      ],
+      [
+        0.9999998618914014,
+        0.9879877343692317,
+        0.9963434716757233,
+        0.9999998618914014
+      ]
+    ],
+    "cosine_persistence": [
+      [
+        null,
+        null,
+        null,
+        null
+      ],
+      [
+        null,
+        null,
+        null,
+        null
+      ],
+      [
+        null,
+        null,
+        null,
+        null
+      ],
+      [
+        null,
+        null,
+        null,
+        null
+      ]
+    ],
+    "l2_alpha": [
+      [
+        0.0,
+        0.34937506914138794,
+        0.2625519931316376,
+        0.0
+      ],
+      [
+        0.34937506914138794,
+        0.0,
+        0.3600066006183624,
+        0.34937506914138794
+      ],
+      [
+        0.2625519931316376,
+        0.3600066006183624,
+        0.0,
+        0.2625519931316376
+      ],
+      [
+        0.0,
+        0.34937506914138794,
+        0.2625519931316376,
+        0.0
+      ]
+    ],
+    "mean_offdiag_cosine_alpha": 0.7205237424572477,
+    "mean_offdiag_cosine_output_state": 0.9544983946771799,
+    "mean_offdiag_cosine_surface_logits": 0.9922943368055454,
+    "mean_offdiag_cosine_persistence": null,
+    "interpretation": "If inter-prompt cosine of surface logits / output_state \u2248 1.0, the surface largely ignores prompt-conditioned field differences. Meaningfully < 1 suggests prompt-sensitive state."
+  },
+  "reconstruction": {
+    "last_k": 4,
+    "notes": [
+      "No MERGE/SPLIT in this architecture yet.",
+      "No dedicated field\u2192past-packet decoder exists.",
+      "Consolidation is a single EMA persistence vector, not a packet stack.",
+      "Linear probe below is few-shot diagnostic on the probe prompts only."
+    ],
+    "not_possible_yet": [
+      "MERGE of packets into durable field structures",
+      "SPLIT / dual-clock span control",
+      "Dedicated field \u2192 past-packet decoder",
+      "Retrieving arbitrary past payloads from alpha alone as text"
+    ],
+    "field_differs_across_prompts": true,
+    "persistence_differs_across_prompts": false,
+    "pairwise_alpha_l2": [
+      0.34937506914138794,
+      0.2625519931316376,
+      0.0,
+      0.3600066006183624,
+      0.34937506914138794,
+      0.2625519931316376
+    ],
+    "pairwise_persistence_l2": [
+      0.0,
+      0.0,
+      0.0,
+      0.0,
+      0.0,
+      0.0
+    ],
+    "mean_pairwise_alpha_l2": 0.2639767875274022,
+    "linear_probe": {
+      "status": "ok",
+      "method": "dual_ridge_least_squares",
+      "lambda": 0.01,
+      "n_prompts": 4,
+      "field_dim": 4224,
+      "feature_dim": 320,
+      "train_mse": 8.09912759081044e-09,
+      "baseline_mean_mse": 0.0012413040967658162,
+      "mse_improvement_vs_mean": 0.0012412959976382254,
+      "pred_target_cosine_per_prompt": [
+        0.9999999407911363,
+        0.9999993095673745,
+        0.9999995249463862,
+        0.9999999407911363
+      ],
+      "mean_pred_target_cosine": 0.9999996790240083,
+      "note": "In-sample fit only (P prompts). Success means field features linearly span last-k packet features on this set \u2014 not a general decoder."
+    },
+    "alpha_reprime_1nn_accuracy": 0.75,
+    "atom_collection_probe": {
+      "status": "ok",
+      "mean_last_k_compiled_vs_stored_r_cosine": 1.0000000161429243,
+      "per_prompt": [
+        1.00000003973643,
+        0.9999999999999991,
+        0.9999999850988388,
+        1.00000003973643
+      ],
+      "note": "Atom collection stores detached compiled atoms from this episode; high cosine is expected (same episode write). This is NOT recovery from field alone \u2014 it shows structural memory buffer retention."
+    },
+    "reconstruction_succeeds": true,
+    "reconstruction_summary": "partial/diagnostic linear map from field features to last-k packet features works in-sample"
+  },
+  "verdict": {
+    "label": "field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)",
+    "mean_offdiag_cosine_surface_logits": 0.9922943368055454,
+    "mean_offdiag_cosine_alpha": 0.7205237424572477,
+    "mean_field_rms_after_prompt": 0.0050630997866392136,
+    "mean_field_rms_after_20_gen": 0.024372012354433537,
+    "reconstruction_succeeds": true,
+    "regime_note": "CE down + gen still noise without field reconstruction = still Transformer regime without the farm."
+  }
+}

docs/artifacts/lign_both_2k5/run_metrics.json

@@ -0,0 +1,126 @@
+{
+  "stream": false,
+  "data_path": "data/corpus_train_chat.txt",
+  "data_glob": null,
+  "shard_paths": [
+    "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt"
+  ],
+  "data_bytes": 777806,
+  "data_characters": 766865,
+  "atomizer_version": "atomizer-v1-byte-span",
+  "feature_dim": 320,
+  "packet_count": 154661,
+  "train_packet_count": 154597,
+  "validation_packet_count": 64,
+  "mean_packet_bytes": 5.029102359353684,
+  "max_packet_bytes": 17,
+  "min_packet_bytes": 1,
+  "config": {
+    "d_model": 64,
+    "n_modes": 64,
+    "n_atoms_max": 512,
+    "max_span_bytes": 16,
+    "episode_length": 512,
+    "episode_reset": false,
+    "atom_flush_every": 256,
+    "learning_rate": 0.0001,
+    "surface_learning_rate": 0.0003,
+    "steps": 2500,
+    "start_step": 2102500,
+    "seed": 20260917,
+    "surface_alphabet": 256,
+    "field_max_rms": 3.0,
+    "energy_decay_bounds": [
+      0.45,
+      0.95
+    ],
+    "stream": false,
+    "enable_merge": true,
+    "field_loss_weight": 0.08,
+    "field_contrast_weight": 0.45,
+    "field_ignorance_weight": 0.08,
+    "field_ignorance_ablate_shared": true,
+    "field_ignorance_prompt_bank": true,
+    "slow_every": 4
+  },
+  "train": {
+    "steps": 2500,
+    "start_step": 2102500,
+    "total_steps": 2105000,
+    "episode_length": 512,
+    "episode_reset": false,
+    "atom_flush_every": 256,
+    "elapsed_seconds": 44.728401276050135,
+    "transitions_per_second": 55.89289866567682,
+    "first_loss": 6.400629043579102,
+    "final_loss": 6.317938327789307,
+    "final_total_perplexity": 554.4287629702109,
+    "finite_losses": true,
+    "finite_parameters": true,
+    "nan_or_inf": false,
+    "field_rms_before_max": 3.0074567794799805,
+    "field_rms_after_max": 2.999999761581421,
+    "field_scale_min": 0.9975202679634094,
+    "field_norm_max": 191.9999542236328,
+    "field_limited_steps": 1262,
+    "field_limited_fraction": 0.5048,
+    "final_dynamics": {
+      "coupling_scale": 1.9910084009170532,
+      "energy_decay": 0.44999998807907104,
+      "phase_sync": 0.9985595941543579,
+      "energy_decay_before": 0.4499995708465576,
+      "energy_decay_repaired": true,
+      "energy_decay_bounds": [
+        0.45,
+        0.95
+      ]
+    },
+    "final_atoms_before_validation": 7,
+    "stream": false,
+    "bytes_seen": 777806
+  },
+  "validation": {
+    "transitions": 63,
+    "loss": 17.255518042852007,
+    "total_perplexity": 31187191.600063678,
+    "byte_loss": 6.73190822203954,
+    "byte_perplexity": 838.7462539442383,
+    "source": "held_out_tail"
+  },
+  "checkpoint": "checkpoints/atom_native_lign_both/atom_native.pt",
+  "reload": {
+    "n_atoms": 196,
+    "field_norm": 191.99989318847656,
+    "time": 25.000476837158203,
+    "finite": true
+  },
+  "generation": {
+    "The future of AI is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c69762c662c7121742d5671696e4e6966726969",
+      "text": "<iv,f,q!t-VqinNifrii",
+      "reload_text": "<iv,f,q!t-VqinNifrii",
+      "reload_match": true
+    },
+    "Bonjour, je m'appelle": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c687166662c2c21659174d8d720646b3e203d6b",
+      "text": "<hqff,,!e\ufffdt\ufffd\ufffd dk> =k",
+      "reload_text": "<hqff,,!e\ufffdt\ufffd\ufffd dk> =k",
+      "reload_match": true
+    },
+    "Valkyria Chronicles III is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c69692c6f2c71216520706b3e203d6b3e203d6b",
+      "text": "<ii,o,q!e pk> =k> =k",
+      "reload_text": "<ii,o,q!e pk> =k> =k",
+      "reload_match": true
+    }
+  }
+}

docs/artifacts/lign_both_2k5/series_row.json

@@ -0,0 +1,12 @@
+{
+  "name": "both",
+  "before_logits_cos": 0.992294,
+  "after_logits_cos": 0.992358,
+  "before_alpha_cos": 0.720524,
+  "after_alpha_cos": 0.698481,
+  "final_ign": 0.0000,
+  "final_mph": 0.500,
+  "merges_nonzero_log_lines": 0,
+  "checkpoint": "checkpoints/atom_native_lign_both/atom_native.pt",
+  "flags": ["--field-ignorance-ablate-shared", "--field-ignorance-prompt-bank"]
+}

docs/artifacts/lign_both_2k5/train_log.txt

@@ -0,0 +1,146 @@
+===== TRAIN both =====
+train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3168090)
+resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False)
+dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95))
+optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (14 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0
+optimizer restore skipped: surface LR param groups differ from checkpoint
+step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000
+step=2102700 (run 200/2500) loss=12.29504 byte_ppl=40.226 atoms=200 merges=0 field=9.9246 rms=0.1551 scale=1.0000 fcos=0.303 ign=0.1457 mph=0.500
+step=2102900 (run 400/2500) loss=2.36884 byte_ppl=2.444 atoms=144 merges=0 field=21.5616 rms=0.3369 scale=1.0000 fcos=0.119 ign=0.1265 mph=0.500
+step=2103100 (run 600/2500) loss=0.84731 byte_ppl=1.223 atoms=88 merges=0 field=38.1377 rms=0.5959 scale=1.0000 fcos=0.325 ign=0.0591 mph=0.500
+step=2103300 (run 800/2500) loss=4.13253 byte_ppl=5.113 atoms=32 merges=0 field=64.3126 rms=1.0049 scale=1.0000 fcos=0.368 ign=0.0000 mph=0.500
+step=2103500 (run 1000/2500) loss=10.28781 byte_ppl=90.063 atoms=232 merges=0 field=106.9277 rms=1.6707 scale=1.0000 fcos=0.390 ign=0.0000 mph=0.500
+step=2103700 (run 1200/2500) loss=6.81054 byte_ppl=77.353 atoms=176 merges=0 field=174.8396 rms=2.7319 scale=1.0000 fcos=0.295 ign=0.0000 mph=0.500
+step=2103900 (run 1400/2500) loss=4.60311 byte_ppl=18.904 atoms=120 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.334 ign=0.0000 mph=0.500
+step=2104100 (run 1600/2500) loss=6.28093 byte_ppl=51.199 atoms=64 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.305 ign=0.0000 mph=0.500
+step=2104300 (run 1800/2500) loss=5.00042 byte_ppl=18.019 atoms=8 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.268 ign=0.0022 mph=0.500
+step=2104500 (run 2000/2500) loss=6.38675 byte_ppl=19.710 atoms=208 merges=0 field=191.9999 rms=3.0000 scale=0.9975 fcos=0.267 ign=0.0000 mph=0.500
+step=2104700 (run 2200/2500) loss=6.83892 byte_ppl=13.414 atoms=152 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.297 ign=0.0000 mph=0.500
+step=2104900 (run 2400/2500) loss=8.30884 byte_ppl=126.876 atoms=96 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.319 ign=0.0000 mph=0.500
+step=2105000 (run 2500/2500) loss=6.31794 byte_ppl=20.556 atoms=196 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.243 ign=0.0000 mph=0.500
+{
+  "stream": false,
+  "data_path": "data/corpus_train_chat.txt",
+  "data_glob": null,
+  "shard_paths": [
+    "/workspace/repos/toroidal-fractal-intelligence/data/corpus_train_chat.txt"
+  ],
+  "data_bytes": 777806,
+  "data_characters": 766865,
+  "atomizer_version": "atomizer-v1-byte-span",
+  "feature_dim": 320,
+  "packet_count": 154661,
+  "train_packet_count": 154597,
+  "validation_packet_count": 64,
+  "mean_packet_bytes": 5.029102359353684,
+  "max_packet_bytes": 17,
+  "min_packet_bytes": 1,
+  "config": {
+    "d_model": 64,
+    "n_modes": 64,
+    "n_atoms_max": 512,
+    "max_span_bytes": 16,
+    "episode_length": 512,
+    "episode_reset": false,
+    "atom_flush_every": 256,
+    "learning_rate": 0.0001,
+    "surface_learning_rate": 0.0003,
+    "steps": 2500,
+    "start_step": 2102500,
+    "seed": 20260917,
+    "surface_alphabet": 256,
+    "field_max_rms": 3.0,
+    "energy_decay_bounds": [
+      0.45,
+      0.95
+    ],
+    "stream": false,
+    "enable_merge": true,
+    "field_loss_weight": 0.08,
+    "field_contrast_weight": 0.45,
+    "field_ignorance_weight": 0.08,
+    "field_ignorance_ablate_shared": true,
+    "field_ignorance_prompt_bank": true,
+    "slow_every": 4
+  },
+  "train": {
+    "steps": 2500,
+    "start_step": 2102500,
+    "total_steps": 2105000,
+    "episode_length": 512,
+    "episode_reset": false,
+    "atom_flush_every": 256,
+    "elapsed_seconds": 44.728401276050135,
+    "transitions_per_second": 55.89289866567682,
+    "first_loss": 6.400629043579102,
+    "final_loss": 6.317938327789307,
+    "final_total_perplexity": 554.4287629702109,
+    "finite_losses": true,
+    "finite_parameters": true,
+    "nan_or_inf": false,
+    "field_rms_before_max": 3.0074567794799805,
+    "field_rms_after_max": 2.999999761581421,
+    "field_scale_min": 0.9975202679634094,
+    "field_norm_max": 191.9999542236328,
+    "field_limited_steps": 1262,
+    "field_limited_fraction": 0.5048,
+    "final_dynamics": {
+      "coupling_scale": 1.9910084009170532,
+      "energy_decay": 0.44999998807907104,
+      "phase_sync": 0.9985595941543579,
+      "energy_decay_before": 0.4499995708465576,
+      "energy_decay_repaired": true,
+      "energy_decay_bounds": [
+        0.45,
+        0.95
+      ]
+    },
+    "final_atoms_before_validation": 7,
+    "stream": false,
+    "bytes_seen": 777806
+  },
+  "validation": {
+    "transitions": 63,
+    "loss": 17.255518042852007,
+    "total_perplexity": 31187191.600063678,
+    "byte_loss": 6.73190822203954,
+    "byte_perplexity": 838.7462539442383,
+    "source": "held_out_tail"
+  },
+  "checkpoint": "checkpoints/atom_native_lign_both/atom_native.pt",
+  "reload": {
+    "n_atoms": 196,
+    "field_norm": 191.99989318847656,
+    "time": 25.000476837158203,
+    "finite": true
+  },
+  "generation": {
+    "The future of AI is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c69762c662c7121742d5671696e4e6966726969",
+      "text": "<iv,f,q!t-VqinNifrii",
+      "reload_text": "<iv,f,q!t-VqinNifrii",
+      "reload_match": true
+    },
+    "Bonjour, je m'appelle": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c687166662c2c21659174d8d720646b3e203d6b",
+      "text": "<hqff,,!e\ufffdt\ufffd\ufffd dk> =k",
+      "reload_text": "<hqff,,!e\ufffdt\ufffd\ufffd dk> =k",
+      "reload_match": true
+    },
+    "Valkyria Chronicles III is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c69692c6f2c71216520706b3e203d6b3e203d6b",
+      "text": "<ii,o,q!e pk> =k> =k",
+      "reload_text": "<ii,o,q!e pk> =k> =k",
+      "reload_match": true
+    }
+  }
+}

docs/artifacts/lign_both_2k5/train_log_excerpt.txt

@@ -0,0 +1,57 @@
+# train log excerpt — both
+
+===== TRAIN both =====
+train lock acquired: /workspace/exports/atom-ai/checkpoints/atom-ai-train.lock (pid=3168090)
+resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False)
+dynamics on load: energy_decay=0.44999998807907104 -> 0.44999998807907104 (repaired=False, bounds=(0.45, 0.95))
+optimizer groups: field/other lr=0.0001 (11 tensors), surface lr=0.0003 (14 tensors); energy_decay_bounds=(0.45, 0.95); field_max_rms=3.0
+optimizer restore skipped: surface LR param groups differ from checkpoint
+step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000
+step=2102700 (run 200/2500) loss=12.29504 byte_ppl=40.226 atoms=200 merges=0 field=9.9246 rms=0.1551 scale=1.0000 fcos=0.303 ign=0.1457 mph=0.500
+...
+3:resumed weights from checkpoints/atom_native_lign_smoke/atom_native_src.pt (recorded step=2102500, legacy_surface_migrated=False)
+7:step=2102501 (run 1/2500) loss=6.40063 byte_ppl=32.202 atoms=1 merges=0 field=0.1173 rms=0.0021 scale=1.0000 fcos=0.999 ign=0.0000 mph=0.000
+8:step=2102700 (run 200/2500) loss=12.29504 byte_ppl=40.226 atoms=200 merges=0 field=9.9246 rms=0.1551 scale=1.0000 fcos=0.303 ign=0.1457 mph=0.500
+9:step=2102900 (run 400/2500) loss=2.36884 byte_ppl=2.444 atoms=144 merges=0 field=21.5616 rms=0.3369 scale=1.0000 fcos=0.119 ign=0.1265 mph=0.500
+10:step=2103100 (run 600/2500) loss=0.84731 byte_ppl=1.223 atoms=88 merges=0 field=38.1377 rms=0.5959 scale=1.0000 fcos=0.325 ign=0.0591 mph=0.500
+11:step=2103300 (run 800/2500) loss=4.13253 byte_ppl=5.113 atoms=32 merges=0 field=64.3126 rms=1.0049 scale=1.0000 fcos=0.368 ign=0.0000 mph=0.500
+12:step=2103500 (run 1000/2500) loss=10.28781 byte_ppl=90.063 atoms=232 merges=0 field=106.9277 rms=1.6707 scale=1.0000 fcos=0.390 ign=0.0000 mph=0.500
+13:step=2103700 (run 1200/2500) loss=6.81054 byte_ppl=77.353 atoms=176 merges=0 field=174.8396 rms=2.7319 scale=1.0000 fcos=0.295 ign=0.0000 mph=0.500
+14:step=2103900 (run 1400/2500) loss=4.60311 byte_ppl=18.904 atoms=120 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.334 ign=0.0000 mph=0.500
+15:step=2104100 (run 1600/2500) loss=6.28093 byte_ppl=51.199 atoms=64 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.305 ign=0.0000 mph=0.500
+16:step=2104300 (run 1800/2500) loss=5.00042 byte_ppl=18.019 atoms=8 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.268 ign=0.0022 mph=0.500
+17:step=2104500 (run 2000/2500) loss=6.38675 byte_ppl=19.710 atoms=208 merges=0 field=191.9999 rms=3.0000 scale=0.9975 fcos=0.267 ign=0.0000 mph=0.500
+18:step=2104700 (run 2200/2500) loss=6.83892 byte_ppl=13.414 atoms=152 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.297 ign=0.0000 mph=0.500
+19:step=2104900 (run 2400/2500) loss=8.30884 byte_ppl=126.876 atoms=96 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.319 ign=0.0000 mph=0.500
+20:step=2105000 (run 2500/2500) loss=6.31794 byte_ppl=20.556 atoms=196 merges=0 field=191.9999 rms=3.0000 scale=0.9976 fcos=0.243 ign=0.0000 mph=0.500
+...
+  "generation": {
+    "The future of AI is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c69762c662c7121742d5671696e4e6966726969",
+      "text": "<iv,f,q!t-VqinNifrii",
+      "reload_text": "<iv,f,q!t-VqinNifrii",
+      "reload_match": true
+    },
+    "Bonjour, je m'appelle": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c687166662c2c21659174d8d720646b3e203d6b",
+      "text": "<hqff,,!e\ufffdt\ufffd\ufffd dk> =k",
+      "reload_text": "<hqff,,!e\ufffdt\ufffd\ufffd dk> =k",
+      "reload_match": true
+    },
+    "Valkyria Chronicles III is": {
+      "temperature": 0.8,
+      "top_k": 5,
+      "max_length": 20,
+      "bytes_hex": "3c69692c6f2c71216520706b3e203d6b3e203d6b",
+      "text": "<ii,o,q!e pk> =k> =k",
+      "reload_text": "<ii,o,q!e pk> =k> =k",
+      "reload_match": true
+    }
+  }
+}

docs/artifacts/lign_prompt_bank_2k5/lign_probe_after.txt

@@ -0,0 +1,19 @@
+[probe] loading /workspace/exports/atom-ai/checkpoints/atom_native_lign_prompt_bank/atom_native.pt (read-only, eval, no optimizer)
+[probe] d_model=64 n_modes=64 step=2105000
+[probe] prompt='Bonjour'
+        RMS 0.003866 -> 0.032612 (norm 0.2474 -> 2.0872) atoms 3 -> 22
+        gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Qui es-tu ?'
+        RMS 0.006797 -> 0.034235 (norm 0.4350 -> 2.1911) atoms 7 -> 26
+        gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Il était une fois'
+        RMS 0.006036 -> 0.033740 (norm 0.3863 -> 2.1594) atoms 6 -> 25
+        gen_preview='unk> ,k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] prompt='Utilisateur: Bonjour\nAssistant:'
+        RMS 0.003866 -> 0.032612 (norm 0.2474 -> 2.0872) atoms 3 -> 22
+        gen_preview='unk> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k> =k>'
+[probe] mean off-diag cosine logits=0.991156 alpha=0.698703
+[probe] reconstruction_succeeds=True field_differs=True
+[probe] wrote /workspace/exports/atom-ai/docs/artifacts/lign_prompt_bank_2k5/probe_after_report.json
+[probe] skip-docs: left FIELD_PROBE/PERSISTENCE_TEST/SCALE unchanged
+[probe] VERDICT: field is carrying structure (prompt-sensitive; diagnostic reconstruction partial)