Precision Stellar Characterization of FGKM Stars using an Empirical Spectral Library (1701.00922v1)

Abstract: Classification of stars, by comparing their optical spectra to a few dozen spectral standards, has been a workhorse of observational astronomy for more than a century. Here, we extend this technique by compiling a library of optical spectra of 404 touchstone stars observed with Keck/HIRES by the California Planet Search. The spectra are high-resolution (R~60000), high signal-to-noise (SNR~150/pixel), and registered onto a common wavelength scale. The library stars have properties derived from interferometry, asteroseismology, LTE spectral synthesis, and spectrophotometry. To address a lack of well-characterized late K-dwarfs in the literature, we measure stellar radii and temperatures for 23 nearby K-dwarfs, using SED modeling and Gaia parallaxes. This library represents a uniform dataset spanning the spectral types ~M5--F1 (Teff ~ 3000-7000K, Rstar ~ 0.1-1.6 Rsun). We also present "Empirical SpecMatch" (SpecMatch-Emp), a tool for parameterizing unknown spectra by comparing them against our spectral library. For FGKM stars, SpecMatch-Emp achieves accuracies of 100 K in effective temperature (Teff), 15% in stellar radius (Rstar), and 0.09 dex in metallicity [Fe/H]. Because the code relies on empirical spectra it performs particularly well for stars ~K4 and later which are challenging to model with existing spectral synthesizers, reaching accuracies of 70 K in Teff, 10% in Rstar, and 0.12 dex in [Fe/H]. We also validate the performance of SpecMatch-Emp, finding it to be robust at lower spectral resolution and SNR, enabling the characterization of faint late-type stars. Both the library and stellar characterization code are publicly available.

Precision Stellar Characterization of FGKM Stars using an Empirical Spectral Library

The paper "Precision Stellar Characterization of FGKM Stars using an Empirical Spectral Library" presents an innovative methodology known as "Empirical SpecMatch" (SpecMatch-Emp) for precise stellar characterization using an extensive spectral library. This paper addresses significant gaps in stellar modeling, especially for late K-dwarfs and cooler stars like M dwarfs, which present challenges for current theoretical models due to their complex optical spectra.

Overview of Methodology

The authors compiled a comprehensive library consisting of 404 high-resolution spectra ($R \approx 60000$) with high signal-to-noise ratios (SNR $\approx$ 150/pixel), captured using the Keck/HIRES instrument as part of the California Planet Search. This library spans spectral types M5 to F1, targeting effective temperatures between approximately 3000 K and 7000 K and stellar radii from approximately 0.1 to 16 R_⊕.

The paper introduces SpecMatch-Emp, a computational technique that enables the parameterization of unknown stellar spectra by direct comparison against this empirical library. This approach circumvents the inaccuracies associated with synthetic spectral models, particularly for late K-dwarfs and M-dwarfs, by leveraging empirical data.

Notable Results

SpecMatch-Emp achieves remarkable precision across various stellar parameters: effective temperatures (T_eff) are accurate to within 100 K, while stellar radii (R_⋆) and metallicity ([Fe/H]) reach accuracies of 15% and 0.09 dex, respectively. For stars of spectral type around K4 and later, known for their modeling difficulties, the algorithm's accuracy improves to about 70 K for T_eff, 10% for R_⋆, and 0.12 dex for [Fe/H].

The authors meticulously verified SpecMatch-Emp's robustness by simulating a range of observational conditions. They demonstrated that the algorithm maintains accuracy even at lower SNRs, as low as 10/pixel, and with reduced spectral resolution down to $R = 20000$, lending significant credibility to its practical applicability in various observational settings.

Implications and Future Developments

The implications of SpecMatch-Emp extend both theoretically and practically. Empirically-driven characterization, as opposed to model-dependent methods, opens avenues for refining observational techniques and offers more reliable benchmarks for testing theoretical models of stellar structure and evolution. Furthermore, the paper highlights the importance of leveraging empirical data to enhance the accuracy of stellar parameters, fostering advancements in both stellar astrophysics and exoplanetary science.

Practically, this method holds promising applications in upcoming transit surveys such as the Transiting Exoplanet Survey Satellite (TESS), which will focus on late-type stars, particularly M dwarfs. The enhanced characterization accuracy provided by SpecMatch-Emp could significantly improve our understanding of these stars and their planetary systems.

Conclusions

The development of SpecMatch-Emp represents a valuable contribution to stellar astrophysics, blending empirical data with sophisticated matching algorithms to overcome longstanding challenges in stellar characterization. While current applications are confined to parameters spanned by the library stars, continuous updates to the library with refined stellar parameters and expanded datasets promise to enhance its scope and accuracy further. Future work may include addressing instrumental broadening explicitly, broadening the applicability of SpecMatch-Emp to even wider observational contexts.