Featureless stars: flux calibration for extremely large telescopes

ABSTRACT The spectrophotometric flux calibration of recent spectroscopic surveys has reached a limiting systematic precision of approximately $1-3$ per cent, and is often biased near the wavelengths associated with H i Balmer absorption. As we prepare for the next generation of imaging and spectroscopic surveys, and high-precision cosmology experiments, we must find a way to address this systematic. Towards this goal, we have identified a global network of 29 bright ($G< 17.5$) featureless white dwarf stars that have a spectral energy distribution consistent with an almost pure blackbody form over the entire optical and near-infrared wavelength range. Based on this sample, we have computed the systematic uncertainty and AB magnitude offsets associated with Gaia, SDSS, SMSS, Pan-STARRS, DES, and 2MASS, and we have also checked the consistency of our objects with both GALEX and WISE. The magnitude range of the featureless stars reported here are ideally suited to observations taken with the forthcoming generation of extremely large telescopes, as well as calibrating the survey data acquired by the Rubin, Euclid, and Roman observatories. Finally, all of the high-precision spectrophotometric standard stars reported here have been included in the latest release of the pypeit data reduction pipeline.

Institutions

Publication Details

Journal
Monthly Notices of the Royal Astronomical Society
Published
2025-12-18
DOI
https://doi.org/10.1093/mnras/staf2246
Primary Topic
Astronomy and Astrophysical Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Featureless stars: flux calibration for extremely large telescopes

Monthly Notices of the Royal Astronomical Society
Astronomy and Astrophysical Research
article

Featureless stars: flux calibration for extremely large telescopes

article en

Abstract

ABSTRACT The spectrophotometric flux calibration of recent spectroscopic surveys has reached a limiting systematic precision of approximately $1-3$ per cent, and is often biased near the wavelengths associated with H i Balmer absorption. As we prepare for the next generation of imaging and spectroscopic surveys, and high-precision cosmology experiments, we must find a way to address this systematic. Towards this goal, we have identified a global network of 29 bright ($G< 17.5$) featureless white dwarf stars that have a spectral energy distribution consistent with an almost pure blackbody form over the entire optical and near-infrared wavelength range. Based on this sample, we have computed the systematic uncertainty and AB magnitude offsets associated with Gaia, SDSS, SMSS, Pan-STARRS, DES, and 2MASS, and we have also checked the consistency of our objects with both GALEX and WISE. The magnitude range of the featureless stars reported here are ideally suited to observations taken with the forthcoming generation of extremely large telescopes, as well as calibrating the survey data acquired by the Rubin, Euclid, and Roman observatories. Finally, all of the high-precision spectrophotometric standard stars reported here have been included in the latest release of the pypeit data reduction pipeline.

Monthly Notices of the Royal Astronomical SocietyVol. 546(2)
Florida State University (US), Lawrence Berkeley National Laboratory (US), University of California, Santa Cruz (US), Durham University (GB), Kavli Institute for the Physics and Mathematics of the Universe (JP), National Astronomical Observatory of Japan (JP)
Affordable and clean energy
Openalex Percentile: Top 33%
Astronomy and Astrophysical Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.