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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
status: string
score: double
m: int64
n: int64
degree: int64
r: int64
verified_shots: int64
value_errors: int64
phase_errors: int64
empirical_error_rate: double
effective_error_rate: double
log2_delta: double
repetition_factor: double
mean_error_weight: double
toffoli_count: double
max_toffoli_count: int64
reaction_depth: int64
num_ops: int64
shot_operation_counts: struct<NEG: int64, BIT_INVERT: int64, BIT_STORE0: int64, BIT_STORE1: int64, X: int64, Z: int64, R: i (... 140 chars omitted)
child 0, NEG: int64
child 1, BIT_INVERT: int64
child 2, BIT_STORE0: int64
child 3, BIT_STORE1: int64
child 4, X: int64
child 5, Z: int64
child 6, R: int64
child 7, HMR: int64
child 8, CX: int64
child 9, CZ: int64
child 10, SWAP: int64
child 11, CSWAP: int64
child 12, CCX: int64
child 13, INFO_TAG: int64
child 14, POP_CONDITION: int64
child 15, PUSH_CONDITION: int64
num_qubits: int64
num_bits: int64
circuit_sha256: string
to
{'brot': Value('int64'), 'error_1_mHa': Value('float64'), 'error_2_mHa': Value('float64'), 'Lambda': Value('float64'), 'E_gap': Value('float64'), 'lambda_eff': Value('float64'), 'heuristic_toffoli': Value('int64'), 'givens_toffoli': Value('int64'), 'T_total_angles_fixed': Value('float64'), 'Q_total_angles_temp_fixed': Value('int64'), 'score_angles_fixed': Value('float64'), 'pass_20mHa': Value('bool')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1876, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 830, in finalize
self.write_rows_on_file()
~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 690, in write_rows_on_file
self._write_table(table)
~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 822, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
status: string
score: double
m: int64
n: int64
degree: int64
r: int64
verified_shots: int64
value_errors: int64
phase_errors: int64
empirical_error_rate: double
effective_error_rate: double
log2_delta: double
repetition_factor: double
mean_error_weight: double
toffoli_count: double
max_toffoli_count: int64
reaction_depth: int64
num_ops: int64
shot_operation_counts: struct<NEG: int64, BIT_INVERT: int64, BIT_STORE0: int64, BIT_STORE1: int64, X: int64, Z: int64, R: i (... 140 chars omitted)
child 0, NEG: int64
child 1, BIT_INVERT: int64
child 2, BIT_STORE0: int64
child 3, BIT_STORE1: int64
child 4, X: int64
child 5, Z: int64
child 6, R: int64
child 7, HMR: int64
child 8, CX: int64
child 9, CZ: int64
child 10, SWAP: int64
child 11, CSWAP: int64
child 12, CCX: int64
child 13, INFO_TAG: int64
child 14, POP_CONDITION: int64
child 15, PUSH_CONDITION: int64
num_qubits: int64
num_bits: int64
circuit_sha256: string
to
{'brot': Value('int64'), 'error_1_mHa': Value('float64'), 'error_2_mHa': Value('float64'), 'Lambda': Value('float64'), 'E_gap': Value('float64'), 'lambda_eff': Value('float64'), 'heuristic_toffoli': Value('int64'), 'givens_toffoli': Value('int64'), 'T_total_angles_fixed': Value('float64'), 'Q_total_angles_temp_fixed': Value('int64'), 'score_angles_fixed': Value('float64'), 'pass_20mHa': Value('bool')}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1379, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 956, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
brot int64 | error_1_mHa float64 | error_2_mHa float64 | Lambda float64 | E_gap float64 | lambda_eff float64 | heuristic_toffoli int64 | givens_toffoli int64 | T_total_angles_fixed float64 | Q_total_angles_temp_fixed int64 | score_angles_fixed float64 | pass_20mHa bool |
|---|---|---|---|---|---|---|---|---|---|---|---|
12 | 3.185195 | 18.639571 | 308.45594 | 3.965477 | 49.301369 | 13,757 | 3,450 | 93,237 | 730 | 3,355,599,588.315538 | true |
11 | 76.95125 | 29.799536 | 308.470935 | 3.980473 | 49.395102 | 13,457 | 3,150 | 92,937 | 722 | 3,314,436,758.651289 | false |
10 | 134.853917 | 44.888833 | 308.507914 | 4.017451 | 49.62551 | 13,157 | 2,850 | 92,637 | 714 | 3,282,371,059.919981 | false |
9 | 273.48203 | 83.765161 | 308.726838 | 4.236376 | 50.968803 | 12,857 | 2,550 | 92,337 | 706 | 3,322,652,300.059647 | false |
8 | 590.53802 | 172.442448 | 309.498919 | 5.008456 | 55.453936 | 12,557 | 2,250 | 92,037 | 698 | 3,562,462,099.821097 | false |
7 | 1,328.669727 | 349.001979 | 311.573171 | 7.082708 | 66.056029 | 19,785 | 1,950 | 99,265 | 690 | 4,524,365,684.301176 | false |
6 | 3,078.969865 | 729.035998 | 318.447458 | 13.956995 | 93.243454 | 19,485 | 1,650 | 98,965 | 682 | 6,293,385,795.2242 | false |
null | null | null | null | null | null | null | null | null | null | null | null |
Verifiable Quantum Circuit Compilation — Baselines and Optimization
Optimization work by Igor Holt on the Google Quantum AI Kaggle competition "Verifiable Quantum Circuit Compilation" ($150,000 pool; final submission Jan 20, 2027). Score is the geometric mean of baseline/submitted cost across three kickmix circuit tasks; the reference scores 1.0.
What is in this dataset
Our own artifacts only. The competition dataset itself is NOT included — it belongs to the Kaggle competition and must be downloaded from Kaggle.
optimization-decision.md— the inference-based optimization decision (dfthcsos first, invsqrt second, DQI third), with cost models, levers, survey results, and the measured field bar (~24.9x leaderboard).gitbook-quantum-circuit-compilation.md— the record as published to GCE Docs (GitBook change request #6, draft): account, dataset, all three verified baselines, decision, brot sweep, field bar.dqi_full_result.json— full DQI verification result from a Kaggle CPU notebook (102,400 shots, 4 workers, 201.5 s): PASS, score 24439463583672.93, 0 value errors, 0 phase errors.dfthcsos_brot_sweep.json/dfthcsos_brot_sweep.py— the first optimization measurement: re-quantizing the reference dfthcsos angle words from 12 bits down to 6 and re-evaluating with the stock verifier. Finding: naive bit reduction is rejected at 11 bits (error_1 76.95 mHa over the 20 mHa bound); the baseline error_2 (18.64 mHa) leaves only 1.36 mHa of headroom, so the lever is factorization re-optimization.
Verified baselines (2026-11-07)
| Task | Result | Score |
|---|---|---|
| dfthcsos | PASS, local full run | 3,355,599,588.32 (exact README baseline) |
| invsqrt | PASS, sampled x=1..1024 | 2,068,518.26 |
| DQI | PASS, full 102,400 shots (Kaggle) | 24,439,463,583,672.93 |
Nothing here has been submitted to the competition.
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