Datasets:

ClarusC64
/

quantum-t2-collapse-horizon-forecasting-intervention-routing-v0.1

Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 1 new columns ({'__index_level_0__'})

This happened while the csv dataset builder was generating data using

hf://datasets/ClarusC64/quantum-t2-collapse-horizon-forecasting-intervention-routing-v0.1/data/test.csv (at revision e66c81e717a42f038c9a0d03e0eff2dd8ae1df5d), [/tmp/hf-datasets-cache/medium/datasets/58700772870580-config-parquet-and-info-ClarusC64-quantum-t2-coll-4e2210eb/hub/datasets--ClarusC64--quantum-t2-collapse-horizon-forecasting-intervention-routing-v0.1/snapshots/e66c81e717a42f038c9a0d03e0eff2dd8ae1df5d/data/test.csv (origin=hf://datasets/ClarusC64/quantum-t2-collapse-horizon-forecasting-intervention-routing-v0.1@e66c81e717a42f038c9a0d03e0eff2dd8ae1df5d/data/test.csv)]

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 675, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              id: string
              hardware_class: int64
              current_t2_us: string
              drift_profile: double
              rolling_corr_x_logical: double
              rolling_corr_z_logical: double
              logical_error_rate: double
              calibration_delta: double
              noise_index: double
              environment_stress_index: int64
              maintenance_lag_days: string
              mitigation_state: double
              coherence_reserve_estimate: double
              predicted_collapse_window_days: double
              time_to_critical_threshold_days: double
              recommended_intervention_set: double
              expected_recovery_gain: double
              forecast_confidence: double
              notes: string
              constraints: string
              gold_checklist: string
              __index_level_0__: string
              -- schema metadata --
              pandas: '{"index_columns": ["__index_level_0__"], "column_indexes": [{"na' + 3195
              to
              {'id': Value('string'), 'hardware_class': Value('string'), 'current_t2_us': Value('int64'), 'drift_profile': Value('string'), 'rolling_corr_x_logical': Value('float64'), 'rolling_corr_z_logical': Value('float64'), 'logical_error_rate': Value('float64'), 'calibration_delta': Value('float64'), 'noise_index': Value('float64'), 'environment_stress_index': Value('float64'), 'maintenance_lag_days': Value('int64'), 'mitigation_state': Value('string'), 'coherence_reserve_estimate': Value('float64'), 'predicted_collapse_window_days': Value('int64'), 'time_to_critical_threshold_days': Value('int64'), 'recommended_intervention_set': Value('string'), 'expected_recovery_gain': Value('float64'), 'forecast_confidence': Value('float64'), 'notes': Value('string'), 'constraints': Value('string'), 'gold_checklist': Value('string')}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1889, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 1 new columns ({'__index_level_0__'})
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/ClarusC64/quantum-t2-collapse-horizon-forecasting-intervention-routing-v0.1/data/test.csv (at revision e66c81e717a42f038c9a0d03e0eff2dd8ae1df5d), [/tmp/hf-datasets-cache/medium/datasets/58700772870580-config-parquet-and-info-ClarusC64-quantum-t2-coll-4e2210eb/hub/datasets--ClarusC64--quantum-t2-collapse-horizon-forecasting-intervention-routing-v0.1/snapshots/e66c81e717a42f038c9a0d03e0eff2dd8ae1df5d/data/test.csv (origin=hf://datasets/ClarusC64/quantum-t2-collapse-horizon-forecasting-intervention-routing-v0.1@e66c81e717a42f038c9a0d03e0eff2dd8ae1df5d/data/test.csv)]
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

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id string	hardware_class string	current_t2_us int64	drift_profile string	rolling_corr_x_logical float64	rolling_corr_z_logical float64	logical_error_rate float64	calibration_delta float64	noise_index float64	environment_stress_index float64	maintenance_lag_days int64	mitigation_state string	coherence_reserve_estimate float64	predicted_collapse_window_days int64	time_to_critical_threshold_days int64	recommended_intervention_set string	expected_recovery_gain float64	forecast_confidence float64	notes string	constraints string	gold_checklist string
QFH-001	superconducting	68	slow-x-drift	0.74	0.72	0.0049	0.04	0.27	0.26	12	baseline	0.41	75	28	recalibrate;x-bias-tune	0.22	0.84	moderate drift	<=300 words	window+threshold+intervention+gain+confidence
QFH-002	superconducting	55	dual-drift	0.68	0.65	0.0063	0.05	0.31	0.29	18	partial-mitigation	0.33	48	18	full-recal;thermal-cycle	0.35	0.82	escalating drift	<=300 words	window+threshold+intervention+gain+confidence
QFH-003	ion_trap	135	stable	0.87	0.85	0.0017	0.02	0.14	0.12	7	baseline	0.72	120	60	none;monitor	0.05	0.9	healthy band	<=300 words	window+threshold+intervention+gain+confidence
QFH-004	neutral_atom	92	z-led-drift	0.77	0.7	0.0031	0.03	0.21	0.2	10	baseline	0.48	66	24	z-calibration;laser-tune	0.26	0.85	z correlation weakening	<=300 words	window+threshold+intervention+gain+confidence
QFH-005	photonic	38	rapid-decouple	0.62	0.59	0.0094	0.07	0.43	0.37	25	mitigation-off	0.21	22	9	halt-workload;full-reset	0.44	0.79	near horizon	<=300 words	window+threshold+intervention+gain+confidence
QFH-006	superconducting	71	gradual-drift	0.76	0.73	0.0042	0.04	0.25	0.23	14	baseline	0.46	82	31	recalibrate;noise-filter	0.2	0.86	watch list	<=300 words	window+threshold+intervention+gain+confidence

What this dataset tests

Whether a system can forecast the failure horizon
of a quantum processor after coherence drift begins
and route minimal interventions to prevent collapse.

Required outputs

predicted_collapse_window_days
time_to_critical_threshold_days
recommended_intervention_set
expected_recovery_gain
forecast_confidence

Use case

Layer 3 of the Quantum T2 Collapse Prediction Trinity.

This dataset supports:

preventive calibration scheduling
workload throttling decisions
maintenance prioritization

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