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harps-interp-t02-grid

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astronomy
stellar-spectra
synthetic-spectra
turbospectrum
marcs
zarr
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The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code:   StreamingRowsError
Exception:    TypeError
Message:      Couldn't cast array of type
struct<level: int64, checksum: bool>
to
{'endian': Value('string'), 'typesize': Value('int64'), 'cname': Value('string'), 'clevel': Value('int64'), 'shuffle': Value('string'), 'blocksize': Value('int64')}
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 544, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 3052, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 558, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_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 2315, in cast_table_to_schema
                  cast_array_to_feature(
                  ~~~~~~~~~~~~~~~~~~~~~^
                      table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                      feature,
                      ^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
                  return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
                                           ~~~~^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2121, in cast_array_to_feature
                  casted_array_values = _c(array.values, feature.feature)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
                  return func(array, *args, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2071, in cast_array_to_feature
                  _c(children[name] if name in array_fields else null_array, subfeature)
                  ~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
                  return func(array, *args, **kwargs)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2161, in cast_array_to_feature
                  raise TypeError(f"Couldn't cast array of type\n{_short_str(array.type)}\nto\n{_short_str(feature)}")
              TypeError: Couldn't cast array of type
              struct<level: int64, checksum: bool>
              to
              {'endian': Value('string'), 'typesize': Value('int64'), 'cname': Value('string'), 'clevel': Value('int64'), 'shuffle': Value('string'), 'blocksize': Value('int64')}

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HARPS-range synthetic intensity grid on interpolated MARCS atmospheres (harps-interp-t02, v2)

v2 (2026-10-31) adds molecular CN and CH lines below 4200 A, which v1 (git tag v1-no-blue-molecules) lacked: the spectra below 4250 A were re-synthesised over 3780-4350 A with the extended line lists and spliced in.

299,986 LTE Turbospectrum spectra of the emergent specific intensity I(lambda, mu), 3780.00-6910.00 A at 0.010 A sampling (313,001 pixels), not convolved with any instrumental or rotational profile. Training set for the SPICE spectral emulator (https://arxiv.org/abs/2511.10998).

How the spectra were made

  • Parameters: a Latin hypercube over Teff 3000-8000 K, log g -0.5 to 5.25, [Fe/H] -5 to +1, vmicro 1-5 km/s and six abundance offsets (table below), one random exact mu per spectrum; points without a complete MARCS bracket were removed.
  • Atmospheres: MARCS standard-composition models interpolated to each (Teff, log g, [Fe/H]) with Masseron's interpol_modeles (linear in Teff, log g, [Fe/H] between the 8 bracketing models) instead of the nearest node. Fixed microturbulence label t02 (2 km/s) for all atmospheres; spherical 1 Msun models below log g 3, plane-parallel at and above. Brackets with missing (unconverged) MARCS models are widened by up to 2 node steps; marcs_interp records it (counts: 1: 238495, 2: 38021, 3: 23470). 144,732 spectra have log g < 3 (spherical).
  • Synthesis: Turbospectrum (babsma + bsyn) in Intensity mode, LTE; solar abundances Magg et al. (2022). Line lists: Gaia-ESO atomic list (nlte_ges_linelist_jmg16jan2026_I_II, used in LTE), VALD 3700-4200 A, hydrogen lines (Hlinedata) and the Gaia-ESO molecular lists (C2, CN, CH, NH, OH, MgH, SiH, CaH, TiO, VO, ZrO), which start at 4200 A, extended below 4200 A with CN violet (Brooke et al. 2014) and CH (Masseron et al. 2014) lines from Kurucz's files, put on the Gaia-ESO conventions (CN log gf +0.29 dex, CH unchanged; checked line by line in 4200-4300 A).
  • Continuum: continuum = flux / normalised flux as printed by Turbospectrum (normalised flux has 5 decimals, so below ~3150 K the continuum is coarse in saturated pixels).

Contents

One Zarr v3 store, harps_interp_t02.zarr:

array shape
flux (299986, 313001) float32 emergent intensity at mu (unnormalized_intensity, relative)
continuum (299986, 313001) float32 continuum intensity
wavelength (313001,) float32 A
params / param_names (299986, 22) float32 per-spectrum parameters (below)
model_id, run_index, source_physics_hash (299986,) row identity and lineage
provenance/ configs, line-list / atmosphere / software manifests of the synthesis runs

Chunks hold 128 spectra x all wavelengths (Blosc zstd). Read with e.g. zarr.open_group("harps_interp_t02.zarr", mode="r")["flux"][i0:i1].

parameter min max meaning
teff 3000 8000 effective temperature (K); also the atmosphere's (interpolated) Teff
logg -0.5 5.25 surface gravity log g (cgs dex); also the atmosphere's
feh -5 1 [Fe/H]: metallicity of the line formation and of the (interpolated) atmosphere
vmicro 1 5 microturbulence of the line formation (km/s); the atmosphere is always the xi = 2 km/s MARCS model
turbvel 1 5 (bookkeeping)
t_value 2 2 (bookkeeping)
a -0.4 0.8 [alpha/Fe] (bsyn ALPHA/Fe keyword: O Ne Mg Si S Ar Ca Ti)
c -1 1 [C/Fe]: A(C) = 8.56 + [Fe/H] + c
n -0.5 1 [N/Fe]: A(N) = 7.98 + [Fe/H] + n
o -0.4 0.8 oxygen relative to the alpha enhancement: A(O) = 8.77 + [Fe/H] + a + o (so [O/Fe] = a + o)
r -0.4 1 [r/Fe] (bsyn R-PROCESS keyword)
s -0.5 1 [s/Fe] (bsyn S-PROCESS keyword)
mu 0.01 1 cosine of the viewing angle of the emergent intensity (one exact mu per spectrum)
marcs_fe_h -5 1 atmosphere [Fe/H] (= feh)
marcs_a_fe 0 0.4 [alpha/Fe] of the MARCS standard composition at this [Fe/H] (blended between nodes)
marcs_c_fe 0 0 (bookkeeping)
marcs_n_fe 0 0 (bookkeeping)
marcs_o_fe 0 0.4 (bookkeeping)
marcs_teff 3000 8000 atmosphere Teff (= teff: interpolated at the requested point)
marcs_logg -0.5 5.25 atmosphere log g (= logg)
marcs_turb 2 2 atmosphere microturbulence label (always 2 km/s)
marcs_interp 1 3 atmosphere bracket: 0 = MARCS node used as is, 1 + k = interpolated with k widening steps

Known gaps

  • 73 spectra (Teff 3000-3167 K) have non-finite values in continuum at 2-415 pixels (their flux is finite): in saturated pixels Turbospectrum's 5-decimal normalised flux rounds to 0, so continuum = flux / normalised flux is infinite. Rows are listed in known_issues/nonfinite_continuum_rows.csv; mask the pixels or skip the rows.
  • Below 4200 A only CN (12C14N) and CH (12CH, 13CH) lines were added: 13C14N, 12C15N, NH and OH are absent there (the Kurucz isotopologue CN lines do not match the Gaia-ESO ones and could not be calibrated).
  • Rows whose Turbospectrum chemical equilibrium did not converge (cool stars near C/O = 1) are absent (a handful).

Provenance

Generated by the Turbospectrum_NLTE pipeline (git 96fe916441aa), schema 1.0.0; see provenance/ and the store attributes for the full configuration. Contact: Maja Jablonska.
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