Datasets:

liuxinge
/

Stargazer

Error code:   DatasetGenerationError
Exception:    ArrowInvalid
Message:      Column 0: In chunk 0: Invalid: Struct child array #6 invalid: Invalid: List child array invalid: Invalid: Struct child array #6 has length smaller than expected for struct array (120 < 230)
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1893, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 765, in write_table
                  self._write_table(pa_table, writer_batch_size=writer_batch_size)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 775, in _write_table
                  pa_table = embed_table_storage(pa_table)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2263, in embed_table_storage
                  return pa.Table.from_arrays(arrays, schema=features.arrow_schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/table.pxi", line 4912, in pyarrow.lib.Table.from_arrays
                File "pyarrow/table.pxi", line 4256, in pyarrow.lib.Table.validate
                File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Column 0: In chunk 0: Invalid: Struct child array #6 invalid: Invalid: List child array invalid: Invalid: Struct child array #6 has length smaller than expected for struct array (120 < 230)
              
              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 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 1739, 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 1925, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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config dict	difficulty_details unknown	engine string	has_gp_noise bool	hf_split string	instrument_labels list	median_sigma_ms float64	meta unknown	num_instruments int64	num_observations int64	num_planets int64	observation_span_days float64	observations dict	rv_range_ms float64	source_file string	star_mass_solar float64	subset string	task_family string	task_id string	task_summary string	truth_difficulty int64
{ "engine": "keplerian", "instruments": [ { "gamma_ms": -33252, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 7 }, { "gamma_ms": -33166.4198075, "label": "inst_B", "sigma_jitter_ms": 0, "sigma_white_ms": 0.23 }, { "gamma_ms": 11....	{ "n_obs": 639, "real_data": true }	keplerian	false	train	[ "inst_A", "inst_B", "inst_C", "inst_D", "inst_E", "inst_F" ]	2.52	{ "gamma_subtracted_per_instrument_ms": { "inst_A": -33252, "inst_B": -33166.4198075, "inst_C": 11.63455714, "inst_D": 19.675, "inst_E": -4.98, "inst_F": 1.79 }, "rv_semantics": "rv_only" }	6	639	1	7,237.393404	{ "instruments": [ "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "...	193.145	real_001.json	1.11	real	radial-velocity-planet-detection	real_001	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	1
{ "engine": "keplerian", "instruments": [ { "gamma_ms": 0, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 7 } ], "integrator_preference": "whfast", "los_axis": "x", "metadata": {}, "noise": { "gp": { "Q0": 1, "dQ": 0.1, "f": 0.5, "per...	{ "n_obs": 48, "real_data": true }	keplerian	false	train	[ "inst_A" ]	7	{ "rv_semantics": "rv_only" }	1	48	2	2,571.0101	{ "instruments": [ "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "...	215	real_002.json	0.95	real	radial-velocity-planet-detection	real_002	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	9
{ "engine": "keplerian", "instruments": [ { "gamma_ms": 0, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 1.1 } ], "integrator_preference": "whfast", "los_axis": "x", "metadata": {}, "noise": { "gp": { "Q0": 1, "dQ": 0.1, "f": 0.5, "p...	{ "n_obs": 119, "real_data": true }	keplerian	false	train	[ "inst_A" ]	1.1	{ "rv_semantics": "rv_only" }	1	119	4	1,569.759477	{ "instruments": [ "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "...	39.96	real_003.json	0.31	real	radial-velocity-planet-detection	real_003	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	10
{ "engine": "keplerian", "instruments": [ { "gamma_ms": 0, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 1.97 } ], "integrator_preference": "whfast", "los_axis": "x", "metadata": {}, "noise": { "gp": { "Q0": 1, "dQ": 0.1, "f": 0.5, "...	{ "n_obs": 162, "real_data": true }	keplerian	false	train	[ "inst_A" ]	1.97	{ "rv_semantics": "rv_only" }	1	162	4	4,600.64464	{ "instruments": [ "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "...	599.53	real_004.json	0.334	real	radial-velocity-planet-detection	real_004	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	8
{ "engine": "keplerian", "instruments": [ { "gamma_ms": 0, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 0.525 } ], "integrator_preference": "whfast", "los_axis": "x", "metadata": {}, "noise": { "gp": { "Q0": 1, "dQ": 0.1, "f": 0.5, ...	{ "n_obs": 190, "real_data": true }	keplerian	false	train	[ "inst_A" ]	0.525	{ "rv_semantics": "rv_only" }	1	190	5	2,428.194514	{ "instruments": [ "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "...	33.53	real_005.json	1.06	real	radial-velocity-planet-detection	real_005	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	6
{ "engine": "keplerian", "instruments": [ { "gamma_ms": 0, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 0.525 } ], "integrator_preference": "whfast", "los_axis": "x", "metadata": {}, "noise": { "gp": { "Q0": 1, "dQ": 0.1, "f": 0.5, ...	{ "n_obs": 190, "real_data": true }	keplerian	false	train	[ "inst_A" ]	0.525	{ "rv_semantics": "rv_only" }	1	190	7	2,428.194514	{ "instruments": [ "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "...	33.53	real_006.json	1.06	real	radial-velocity-planet-detection	real_006	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	10
{ "engine": "keplerian", "instruments": [ { "gamma_ms": 9.55, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 1.4 }, { "gamma_ms": -8.2, "label": "inst_B", "sigma_jitter_ms": 0, "sigma_white_ms": 5.4 } ], "integrator_preference": "whfast...	{ "n_obs": 106, "real_data": true }	keplerian	false	train	[ "inst_A", "inst_B" ]	1.5	{ "rv_semantics": "rv_only" }	2	106	2	3,571.31555	{ "instruments": [ "inst_B", "inst_A", "inst_A", "inst_A", "inst_A", "inst_B", "inst_A", "inst_A", "inst_A", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "...	185.5	real_007.json	1.07	real	radial-velocity-planet-detection	real_007	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	4
{ "engine": "keplerian", "instruments": [ { "gamma_ms": 22.15, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 3 }, { "gamma_ms": -9343.3, "label": "inst_B", "sigma_jitter_ms": 0, "sigma_white_ms": 1.2 }, { "gamma_ms": 23.7, ...	{ "n_obs": 380, "real_data": true }	keplerian	false	train	[ "inst_A", "inst_B", "inst_C" ]	2.65	{ "rv_semantics": "rv_only" }	3	380	4	6,317.5886	{ "instruments": [ "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "...	9,480.4	real_008.json	1.08	real	radial-velocity-planet-detection	real_008	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	9
{ "engine": "keplerian", "instruments": [ { "gamma_ms": 10.3, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 4.7 }, { "gamma_ms": -5.2, "label": "inst_B", "sigma_jitter_ms": 0, "sigma_white_ms": 5.3 } ], "integrator_preference": "whfast...	{ "n_obs": 88, "real_data": true }	keplerian	false	train	[ "inst_A", "inst_B" ]	5	{ "rv_semantics": "rv_only" }	2	88	1	2,668.840892	{ "instruments": [ "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_A", "inst_A", "inst_A", "...	250.5	real_009.json	1.24	real	radial-velocity-planet-detection	real_009	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	2
{ "engine": "keplerian", "instruments": [ { "gamma_ms": -2232, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 3.4 } ], "integrator_preference": "whfast", "los_axis": "x", "metadata": {}, "noise": { "gp": { "Q0": 1, "dQ": 0.1, "f": 0.5, ...	{ "n_obs": 33, "real_data": true }	keplerian	false	train	[ "inst_A" ]	3.4	{ "rv_semantics": "rv_only" }	1	33	1	41.9567	{ "instruments": [ "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "...	408.4	real_010.json	0.823	real	radial-velocity-planet-detection	real_010	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	2
{ "engine": "keplerian", "instruments": [ { "gamma_ms": 0, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 0.23 } ], "integrator_preference": "whfast", "los_axis": "x", "metadata": {}, "noise": { "gp": { "Q0": 1, "dQ": 0.1, "f": 0.5, "...	{ "n_obs": 187, "real_data": true }	keplerian	false	train	[ "inst_A" ]	0.23	{ "rv_semantics": "rv_only" }	1	187	3	2,609.9315	{ "instruments": [ "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "...	7.74	real_011.json	0.7	real	radial-velocity-planet-detection	real_011	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	7
{ "engine": "keplerian", "instruments": [ { "gamma_ms": -9.5, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 3.6 } ], "integrator_preference": "whfast", "los_axis": "x", "metadata": {}, "noise": { "gp": { "Q0": 1, "dQ": 0.1, "f": 0.5, ...	{ "n_obs": 85, "real_data": true }	keplerian	false	train	[ "inst_A" ]	3.6	{ "rv_semantics": "rv_only" }	1	85	1	2,029.5777	{ "instruments": [ "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "...	178.8	real_012.json	1.148	real	radial-velocity-planet-detection	real_012	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	1
{ "engine": "keplerian", "instruments": [ { "gamma_ms": 12.85, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 0.89 }, { "gamma_ms": -0.82, "label": "inst_B", "sigma_jitter_ms": 0, "sigma_white_ms": 0.61 } ], "integrator_preference": "wh...	{ "n_obs": 373, "real_data": true }	keplerian	false	train	[ "inst_A", "inst_B" ]	0.66	{ "rv_semantics": "rv_only" }	2	373	2	4,850.806954	{ "instruments": [ "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "...	28.82	real_013.json	0.77	real	radial-velocity-planet-detection	real_013	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	7
{ "engine": "keplerian", "instruments": [ { "gamma_ms": 11.35, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 1.3 }, { "gamma_ms": -7.5, "label": "inst_B", "sigma_jitter_ms": 0, "sigma_white_ms": 4.5 } ], "integrator_preference": "whfas...	{ "n_obs": 207, "real_data": true }	keplerian	false	train	[ "inst_A", "inst_B" ]	3.9	{ "rv_semantics": "rv_only" }	2	207	1	3,694.004547	{ "instruments": [ "inst_B", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_B", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "...	358	real_014.json	1.02	real	radial-velocity-planet-detection	real_014	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	3
{ "engine": "keplerian", "instruments": [ { "gamma_ms": 0, "label": "inst_A", "sigma_jitter_ms": 0, "sigma_white_ms": 3.1 } ], "integrator_preference": "whfast", "los_axis": "x", "metadata": {}, "noise": { "gp": { "Q0": 1, "dQ": 0.1, "f": 0.5, "p...	{ "n_obs": 52, "real_data": true }	keplerian	false	train	[ "inst_A" ]	3.1	{ "rv_semantics": "rv_only" }	1	52	2	3,063.68	{ "instruments": [ "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "inst_A", "...	102.72	real_015.json	0.85	real	radial-velocity-planet-detection	real_015	Infer the planetary system from radial-velocity observations, including planet count and orbital parameters.	4

End of preview.

Dataset Card for Stargazer

Stargazer is a scalable environment for evaluating AI agents on dynamic, iterative physics-grounded model-fitting tasks using inference on radial-velocity (RV) time series data.

Paper: Stargazer: A Scalable Model-Fitting Benchmark Environment for AI Agents under Astrophysical Constraints
Project Page: https://aips-uoft.github.io/Stargazer/
Repository: https://github.com/AIPS-UofT/Stargazer

Overview

Stargazer comprises 120 tasks across three difficulty tiers, including 20 real archival cases, covering diverse scenarios ranging from high-SNR single-planet systems to complex multi-planetary configurations requiring involved low-SNR analysis.

Total tasks: 120
License: cc-by-4.0

This release includes benchmark tasks built from both generated systems and archival RV systems, presented as one benchmark collection. Each row is one benchmark task with the original task payload preserved.

Usage

To run a single task by ID using the official repository:

python run_agent_batch_hard_timeout.py \
    --model gpt-5-mini \
    --task-ids seed22_diff4 \
    --verbose \
    --output-dir results_debug

To run all difficulty-1 tasks with 10 parallel workers:

python run_agent_batch_hard_timeout.py \
    --model gpt-5-mini \
    --count 1000 \
    --difficulties 1 \
    --workers 10 \
    --output-dir results_diff1

What Each Row Contains

Each row keeps the original benchmark structure:

config
observations
difficulty_details
meta

It also adds a few summary fields for filtering in the Hugging Face viewer:

task_id
truth_difficulty
num_observations
num_instruments
num_planets
engine
has_gp_noise

Notes

Tasks in this release may contain up to 7 planets
This is a benchmark release, not a training corpus
Ground-truth configuration fields are included, so they should not be exposed to the evaluated agent

Citation

@article{liu2026stargazer,
  title   = {Stargazer: A Scalable Model-Fitting Benchmark Environment for AI Agents under Astrophysical Constraints},
  author  = {Liu, Xinge and Zhang, Terry Jingchen and Sch{\"o}lkopf, Bernhard and Jin, Zhijing and Menou, Kristen},
  year    = {2026},
  journal = {arXiv preprint arXiv:2604.15664},
  url     = {https://arxiv.org/abs/2604.15664}
}

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Paper for liuxinge/Stargazer

Stargazer: A Scalable Model-Fitting Benchmark Environment for AI Agents under Astrophysical Constraints

Paper • 2604.15664 • Published 5 days ago • 2