Abstract The element abundances of stars, particularly the refractory elements (e.g., Fe, Si, and Mg), play an important role in connecting stars to their planets. Most Sun-like stars do not have refractory abundance measurements since obtaining a large sample of high-resolution spectra is difficult with oversubscribed observing resources. In this work we infer abundances for C, N, O, Na, Mn, Cr, Si, Fe, Ni, Mg, V, Ca, Ti, Al, and Y for solar analogs with Gaia Radial Velocity Spectrometer (RVS) spectra (R= 11,200) usingTheCannon, a data-driven method. We train a linear model on a reference set of 34 stars observed by Gaia RVS with precise abundances measured from previous high-resolution spectroscopic efforts (R> 30,000–110,000). We then apply this model to several thousand Gaia RVS solar analogs. This yields abundances with average upper limit precisions of 0.04–0.1 dex for 17,412 stars, 50 of which are identified planet (candidate) hosts. We subsequently test the relative refractory depletion of these stars with increasing element condensation temperature compared to the Sun. The Sun remains refractory depleted compared to other Sun-like stars regardless of our current knowledge of the planets they host. This is inconsistent with theories of various types of planets locking up or sequestering refractories. Furthermore, we find no significant abundance differences between identified close-in giant planet hosts, giant planet hosts, and terrestrial/small planet hosts with the rest of the sample within our precision limits. This work demonstrates the utility of data-driven learning for future exoplanet composition and demographics studies.
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Staring at the Sun with the Keck Planet Finder: An Autonomous Solar Calibrator for High Signal-to-noise Sun-as-a-star Spectra
Abstract Extreme precision radial velocity (EPRV) measurements contend with internal noise (instrumental systematics) and external noise (intrinsic stellar variability) on the road to 10 cm s−1“exo-Earth” sensitivity. Both of these noise sources are well-probed using “Sun-as-a-star” RVs and cross-instrument comparisons. We built the Solar Calibrator (SoCal), an autonomous system that feeds stable, disk-integrated sunlight to the recently commissioned Keck Planet Finder (KPF) at the W. M. Keck Observatory. With SoCal, KPF acquires signal-to-noise ratio (S/N) ∼ 1200,R= 98,000 optical (445–870 nm) spectra of the Sun in 5 s exposures at unprecedented cadence for an EPRV facility using KPF’s fast readout mode (<16 s between exposures). Daily autonomous operation is achieved by defining an operations loop using state machine logic. Data affected by clouds are automatically flagged using a reliable quality control metric derived from simultaneous irradiance measurements. Comparing solar data across the growing global network of EPRV spectrographs with solar feeds will allow EPRV teams to disentangle internal and external noise sources and benchmark spectrograph performance. To facilitate this, all SoCal data products are immediately available to the public on the Keck Observatory Archive. We compared SoCal RVs to contemporaneous RVs from NEID, the only other immediately public EPRV solar data set. We find agreement at the 30–40 cm s−1level on timescales of several hours, which is comparable to the combined photon-limited precision. Data from SoCal were also used to assess a detector problem and wavelength calibration inaccuracies associated with KPF during early operations. Long-term SoCal operations will collect upwards of 1000 solar spectra per six-hour day using KPF’s fast readout mode, enabling stellar activity studies at high S/N on our nearest solar-type star.
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- Award ID(s):
- 2034278
- PAR ID:
- 10508960
- Publisher / Repository:
- Publications of the Astronomical Society of the Pacific
- Date Published:
- Journal Name:
- Publications of the Astronomical Society of the Pacific
- Volume:
- 135
- Issue:
- 1054
- ISSN:
- 0004-6280
- Page Range / eLocation ID:
- 125002
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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