Probing Galactic variations in the fine-structure constant using solar twin stars: methodology and results
Abstract
The rich absorption spectra of Sun-like stars are enticing probes for variations in the fine-structure constant, α, which gauges the strength of electromagnetism. While individual line wavelengths are sensitive to α, they are also sensitive to physical processes in the stellar atmospheres, which has precluded their use so far. Here we demonstrate a new differential approach using solar twins: velocity separations between close pairs of transitions are compared across stars with very similar physical properties, strongly suppressing astrophysical and instrumental systematic errors. We utilize 423 archival exposures of 18 solar twins from the High-Accuracy Radial velocity Planetary Searcher (HARPS), in which calibration errors can be reduced to ≲3 m s-1. For stars with ≈10 high-signal-to-noise ratio spectra (≥200 per pixel), velocity separations between pairs are measured with ≈10 m s-1 statistical precision. A companion paper assesses a range of systematic error sources using 130 stars, with a greater range of stellar parameters, providing accurate corrections for astrophysical effects and a residual, intrinsic star-to-star scatter of 0-13 m s-1. Within these uncertainties, we find no evidence for velocity separation differences in 17 transition pairs between solar twins. In a second companion paper, this is found to limit local (≲50 pc) variations in α to ≈50 parts per billion, ~2 orders of magnitude less than other Galactic constraints.
- Publication:
-
Monthly Notices of the Royal Astronomical Society
- Pub Date:
- February 2023
- DOI:
- 10.1093/mnras/stac2458
- arXiv:
- arXiv:2210.08275
- Bibcode:
- 2023MNRAS.519.1238B
- Keywords:
-
- methods: observational;
- stars: solar-type;
- Astrophysics - Solar and Stellar Astrophysics;
- Astrophysics - Astrophysics of Galaxies;
- Physics - Atomic Physics
- E-Print:
- 15 pages, 5 figures. Accepted by MNRAS. The VarConLib (Varying Constants Library) software used in this work is available at https://github.com/DBerke/varconlib. The measurements and results in this work are available at https://github.com/DBerke/Berke_et_alia_2022_supplemental_data