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Record W2969713627 · doi:10.3847/1538-3881/ab3b0f

Precise Radial Velocities of Cool Low-mass Stars with iSHELL

2019· article· en· W2969713627 on OpenAlexaff
Bryson Cale, Peter Plavchan, Danny LeBrun, Jonathan Gagné, Peter Gao, Angelle Tanner, Charles Beichman, Sharon X. Wang, Eric Gaidos, Johanna Teske, David R. Ciardi, Gautam Vasisht, Stephen R. Kane, Kaspar von Braun

Bibliographic record

VenueThe Astronomical Journal · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsExoplanetPhysicsSpectrographStarsAstrophysicsRadial velocityAstronomyEffective temperaturePlanetVery Large TelescopeStarspotLuminositySpectral lineGalaxy

Abstract

fetched live from OpenAlex

Abstract The coolest dwarf stars are intrinsically faint at visible wavelengths and exhibit rotationally modulated stellar activity from spots and plages. It is advantageous to observe these stars at near-infrared (NIR) wavelengths (1–2.5 μ m) where they emit the bulk of their bolometric luminosity and are most quiescent. In this work, we describe our methodology and results in obtaining precise radial velocity (RV) measurements of low-mass stars using K -band spectra taken with the R ∼ 80,000 iSHELL spectrograph and the NASA Infrared Telescope Facility using a methane isotopologue gas cell in the calibration unit. Our novel analysis pipeline extracts RVs by minimizing the rms of the residuals between the observed spectrum and a forward model. The model accounts for the gas cell, tellurics, blaze function, multiple sources of quasi-sinusoidal fringing, and line spread function of the spectrograph. The stellar template is derived iteratively using the target observations themselves through averaging barycenter-shifted residuals. We have demonstrated 5 m s −1 precision over one-year timescales for the M4 dwarf Barnard’s Star and K dwarf 61 Cygni A, and 3 m s −1 over a month for the M2 dwarf GJ 15 A. This work demonstrates the potential for iSHELL to determine dynamical masses for candidate exoplanets discovered with the NASA Transiting Exoplanet Survey Satellite mission, and to search for exoplanets orbiting moderately active and/or young K & M dwarfs.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.189
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations47
Published2019
Admission routes1
Has abstractyes

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