{
  "timestamp_local": "2026-09-18 18:05:33 PDT",
  "timestamp_utc": "2026-09-19T01:05:33.258029+00:00",
  "meta": {
    "config": {
      "d_model": 64,
      "n_modes": 64,
      "n_atoms_max": 512,
      "max_payload_bytes": 32,
      "atomizer_version": "atomizer-v1-byte-span",
      "field_max_rms": 3.0,
      "energy_decay_bounds": [
        0.3,
        0.95
      ],
      "enable_merge": true,
      "merge_coherence_threshold": 0.45,
      "merge_energy_floor": 0.08,
      "slow_every": 1,
      "field_loss_weight": 0.05,
      "field_contrast_weight": 0.1,
      "field_contrast_margin": 0.55,
      "field_ignorance_weight": 0.0,
      "field_ignorance_margin": 0.85,
      "field_ignorance_ablate_shared": false,
      "field_ignorance_prompt_bank": false,
      "field_obligatory_readout": true,
      "field_obligatory_hard": true,
      "printable_aux_weight": 0.0,
      "field_next_packet_weight": 0.05,
      "merge_count_total": 72771
    },
    "training_meta": {
      "step": 3498000,
      "run_steps": 15000,
      "seed": 20260913,
      "episode_reset": false,
      "atom_flush_every": 0,
      "dynamics_on_load": {
        "coupling_scale": 2.0,
        "energy_decay": 0.30000001192092896,
        "phase_sync": 0.4993484914302826,
        "energy_decay_before": 0.30000001192092896,
        "energy_decay_repaired": false,
        "energy_decay_bounds": [
          0.3,
          0.95
        ]
      }
    },
    "checkpoint": "/workspace/exports/atom-ai/checkpoints/atom_native_chat/atom_native.pt",
    "checkpoint_bytes": 54533549
  },
  "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": 2,
      "packet_payloads": [
        "Utilisateur: Bonjour\n",
        "Assistant:"
      ],
      "stats_after_prompt": {
        "field_rms": 0.0025552583392709494,
        "field_norm": 0.16353651881217957,
        "field_mean_abs": 0.0018971064127981663,
        "field_max_abs": 0.01749471388757229,
        "alpha_numel": 4096,
        "persistence_norm": 0.0,
        "persistence_mean_abs": 0.0,
        "persistence_strength": 0.0,
        "n_atoms": 1,
        "consolidation_count": 0,
        "abstraction_count": 0,
        "t": 0.019999999552965164
      },
      "stats_after_gen": {
        "field_rms": 0.0212762001901865,
        "field_norm": 1.3616769313812256,
        "field_mean_abs": 0.015579604543745518,
        "field_max_abs": 0.16742654144763947,
        "alpha_numel": 4096,
        "persistence_norm": 0.00023045156558509916,
        "persistence_mean_abs": 2.8806445698137395e-05,
        "persistence_strength": 0.07243102788925171,
        "n_atoms": 1,
        "consolidation_count": 960,
        "abstraction_count": 0,
        "t": 0.21000002324581146
      },
      "generated_preview": "\n\n\nauiseatiu :  rernui e  ie\n\n\n\nauiseatiu : erernuiee  ie\n\nauiseatiu : e\ufffdernutee  te\n\n\nauiseatiur: e\ufffdernutee  te\n\nau seatiu : e\ufffdernut e  \n\nau  eateu : e\ufffdernut e",
      "generated_bytes": 212,
      "surface_byte_logits_norm": 1408.1553955078125
    },
    {
      "prompt": "Qui es-tu ?",
      "primed_text": "Utilisateur: Qui es-tu ?\nAssistant:",
      "n_prompt_packets": 3,
      "packet_payloads": [
        "Utilisateur: Qui es-tu ?",
        "\n",
        "Assistant:"
      ],
      "stats_after_prompt": {
        "field_rms": 0.004478651098906994,
        "field_norm": 0.2866336703300476,
        "field_mean_abs": 0.003169607138261199,
        "field_max_abs": 0.03362397477030754,
        "alpha_numel": 4096,
        "persistence_norm": 0.0,
        "persistence_mean_abs": 0.0,
        "persistence_strength": 0.0,
        "n_atoms": 1,
        "consolidation_count": 0,
        "abstraction_count": 0,
        "t": 0.029999999329447746
      },
      "stats_after_gen": {
        "field_rms": 0.02201659232378006,
        "field_norm": 1.4090620279312134,
        "field_mean_abs": 0.015995297580957413,
        "field_max_abs": 0.16990996897220612,
        "alpha_numel": 4096,
        "persistence_norm": 0.00026916919159702957,
        "persistence_mean_abs": 3.36461525876075e-05,
        "persistence_strength": 0.07706887274980545,
        "n_atoms": 1,
        "consolidation_count": 1024,
        "abstraction_count": 0,
        "t": 0.2200000286102295
      },
      "generated_preview": "\n\n\n\n\nauiieatiu : ereinunee ote\n\n\nauiieatiu : ereinunee  te\n\nauiieateu : e\ufffdeinunee  te\n\nau ieateur: e\ufffdernunee  \n\nau  eateu : e\ufffdernun e  \n\nau  eateur: e\ufffdernun e  ",
      "generated_bytes": 210,
      "surface_byte_logits_norm": 1435.13037109375
    },
    {
      "prompt": "Il \u00e9tait une fois",
      "primed_text": "Utilisateur: Il \u00e9tait une fois\nAssistant:",
      "n_prompt_packets": 3,
      "packet_payloads": [
        "Utilisateur: Il \u00e9tait une ",
        "fois\n",
        "Assistant:"
      ],
      "stats_after_prompt": {
        "field_rms": 0.003504096530377865,
        "field_norm": 0.22426217794418335,
        "field_mean_abs": 0.002597557380795479,
        "field_max_abs": 0.02230105735361576,
        "alpha_numel": 4096,
        "persistence_norm": 0.0,
        "persistence_mean_abs": 0.0,
        "persistence_strength": 0.0,
        "n_atoms": 1,
        "consolidation_count": 0,
        "abstraction_count": 0,
        "t": 0.029999999329447746
      },
      "stats_after_gen": {
        "field_rms": 0.021159183233976364,
        "field_norm": 1.3541878461837769,
        "field_mean_abs": 0.015545116737484932,
        "field_max_abs": 0.1669299453496933,
        "alpha_numel": 4096,
        "persistence_norm": 0.00022163291578181088,
        "persistence_mean_abs": 2.7704112653736956e-05,
        "persistence_strength": 0.07706887274980545,
        "n_atoms": 1,
        "consolidation_count": 1024,
        "abstraction_count": 0,
        "t": 0.2200000286102295
      },
      "generated_preview": "\n\n\nauiosatiu :  \ufffdernue e  ie\n\n\n\nauiieatiu : e\ufffdernui e  ie\n\n\nauiieatiu : e\ufffdernui e  te\n\nauiseateur: e\ufffdernut e  te\n\n\nauiseateu : e\ufffdernut e  \n\nau  eateu :ee\ufffdernun ",
      "generated_bytes": 212,
      "surface_byte_logits_norm": 1586.9410400390625
    },
    {
      "prompt": "Utilisateur: Bonjour\nAssistant:",
      "primed_text": "Utilisateur: Bonjour\nAssistant:",
      "n_prompt_packets": 2,
      "packet_payloads": [
        "Utilisateur: Bonjour\n",
        "Assistant:"
      ],
      "stats_after_prompt": {
        "field_rms": 0.0025552583392709494,
        "field_norm": 0.16353651881217957,
        "field_mean_abs": 0.0018971064127981663,
        "field_max_abs": 0.01749471388757229,
        "alpha_numel": 4096,
        "persistence_norm": 0.0,
        "persistence_mean_abs": 0.0,
        "persistence_strength": 0.0,
        "n_atoms": 1,
        "consolidation_count": 0,
        "abstraction_count": 0,
        "t": 0.019999999552965164
      },
      "stats_after_gen": {
        "field_rms": 0.0212762001901865,
        "field_norm": 1.3616769313812256,
        "field_mean_abs": 0.015579604543745518,
        "field_max_abs": 0.16742654144763947,
        "alpha_numel": 4096,
        "persistence_norm": 0.00023045156558509916,
        "persistence_mean_abs": 2.8806445698137395e-05,
        "persistence_strength": 0.07243102788925171,
        "n_atoms": 1,
        "consolidation_count": 960,
        "abstraction_count": 0,
        "t": 0.21000002324581146
      },
      "generated_preview": "\n\n\nauiseatiu :  rernui e  ie\n\n\n\nauiseatiu : erernuiee  ie\n\nauiseatiu : e\ufffdernutee  te\n\n\nauiseatiur: e\ufffdernutee  te\n\nau seatiu : e\ufffdernut e  \n\nau  eateu : e\ufffdernut e",
      "generated_bytes": 212,
      "surface_byte_logits_norm": 1408.1553955078125
    }
  ],
  "prompt_sensitivity": {
    "prompts": [
      "Bonjour",
      "Qui es-tu ?",
      "Il \u00e9tait une fois",
      "Utilisateur: Bonjour\nAssistant:"
    ],
    "cosine_alpha": [
      [
        1.0000001198848563,
        0.5723997626100198,
        0.4782710344315834,
        1.0000001198848563
      ],
      [
        0.5723997626100198,
        1.0000000313732404,
        0.5935560518159031,
        0.5723997626100198
      ],
      [
        0.4782710344315834,
        0.5935560518159031,
        0.999999913243217,
        0.4782710344315834
      ],
      [
        1.0000001198848563,
        0.5723997626100198,
        0.4782710344315834,
        1.0000001198848563
      ]
    ],
    "cosine_output_state": [
      [
        0.9999999200269104,
        0.7557485577811226,
        0.8741069440643682,
        0.9999999200269104
      ],
      [
        0.7557485577811226,
        0.9999999644194125,
        0.812574246981293,
        0.7557485577811226
      ],
      [
        0.8741069440643682,
        0.812574246981293,
        0.9999999936767365,
        0.8741069440643682
      ],
      [
        0.9999999200269104,
        0.7557485577811226,
        0.8741069440643682,
        0.9999999200269104
      ]
    ],
    "cosine_surface_logits": [
      [
        0.9999999275888765,
        0.9983408628178381,
        0.9984243081442599,
        0.9999999275888765
      ],
      [
        0.9983408628178381,
        0.9999998733360834,
        0.9985799400534325,
        0.9983408628178381
      ],
      [
        0.9984243081442599,
        0.9985799400534325,
        0.9999999216576336,
        0.9984243081442599
      ],
      [
        0.9999999275888765,
        0.9983408628178381,
        0.9984243081442599,
        0.9999999275888765
      ]
    ],
    "cosine_persistence": [
      [
        null,
        null,
        null,
        null
      ],
      [
        null,
        null,
        null,
        null
      ],
      [
        null,
        null,
        null,
        null
      ],
      [
        null,
        null,
        null,
        null
      ]
    ],
    "l2_alpha": [
      [
        0.0,
        0.23503296077251434,
        0.20483282208442688,
        0.0
      ],
      [
        0.23503296077251434,
        0.0,
        0.236946240067482,
        0.23503296077251434
      ],
      [
        0.20483282208442688,
        0.236946240067482,
        0.0,
        0.20483282208442688
      ],
      [
        0.0,
        0.23503296077251434,
        0.20483282208442688,
        0.0
      ]
    ],
    "mean_offdiag_cosine_alpha": 0.6158162942973276,
    "mean_offdiag_cosine_output_state": 0.8453808617831976,
    "mean_offdiag_cosine_surface_logits": 0.9986850349277508,
    "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": [
      0.23503296077251434,
      0.20483282208442688,
      0.0,
      0.236946240067482,
      0.23503296077251434,
      0.20483282208442688
    ],
    "pairwise_persistence_l2": [
      0.0,
      0.0,
      0.0,
      0.0,
      0.0,
      0.0
    ],
    "mean_pairwise_alpha_l2": 0.18611296763022742,
    "linear_probe": {
      "status": "ok",
      "method": "dual_ridge_least_squares",
      "lambda": 0.01,
      "n_prompts": 4,
      "field_dim": 4224,
      "feature_dim": 320,
      "train_mse": 3.6532430385705084e-05,
      "baseline_mean_mse": 0.000621866318397224,
      "mse_improvement_vs_mean": 0.0005853338880115189,
      "pred_target_cosine_per_prompt": [
        0.9996123994309712,
        0.9977090132625108,
        0.9978436500913965,
        0.9996123994309712
      ],
      "mean_pred_target_cosine": 0.9986943655539624,
      "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": 0.7915157649440582,
      "per_prompt": [
        0.7680577955314842,
        0.8786917924880981,
        0.7512556762251661,
        0.7680577955314842
      ],
      "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 differs across prompts but surface logits nearly identical \u2014 field not reliably read by surface (Transformer-regime risk / surface-only byte-LM behavior at decode)",
    "mean_offdiag_cosine_surface_logits": 0.9986850349277508,
    "mean_offdiag_cosine_alpha": 0.6158162942973276,
    "mean_field_rms_after_prompt": 0.0032733160769566894,
    "mean_field_rms_after_20_gen": 0.021432043984532356,
    "reconstruction_succeeds": true,
    "regime_note": "CE down + gen still noise without field reconstruction = still Transformer regime without the farm."
  }
}