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Register a new userRefined fundamental parameters of Canopus from combined near-IR interferometry and spectral energy distribution
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Added by
Armando Domiciano de Souza
Publication date
2021
fields
Physics
and research's language is
English
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Canopus, the brightest and closest yellow supergiant to our Solar System, offers a unique laboratory for understanding the physics of evolved massive stars. The accurate and precise PIONIER data allowed us to simultaneously measure the angular diameter and the limb darkening (LD) profile using different analytical laws. We found that the power-law LD, being also in agreement with predictions from stellar atmosphere models, reproduces the interferometric data well. For this model we measured an angular diameter of $7.184 pm 0.0017 pm 0.029$ mas and an LD coefficient of $0.1438 pm 0.0015$, which are respectively $gtrsim 5$ and $sim15-25$ more precise than in our previous A&A paper on Canopus from 2008. From a dedicated analysis of the interferometric data, we also provide new constraints on the putative presence of weak surface inhomogeneities. Additionally, we analyzed the SED in a innovative way by simultaneously fitting the reddening-related parameters and the stellar effective temperature and gravity. We find that a model based on two effective temperatures is much better at reproducing the whole SED, from which we derived several parameters, including a new bolometric flux estimate. The Canopus angular diameter and LD measured in this work with PIONIER are the most precise to date, with a direct impact on several related fundamental parameters. Moreover, thanks to our joint analysis, we were able to determine a set of fundamental parameters that simultaneously reproduces both high-precision interferometric data and a good quality SED and, at the same time, agrees with stellar evolution models.
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We present comprehensive models of Herbig Ae star, HD 142666, which aim to simultaneously explain its spectral energy distribution (SED) and near-infrared (NIR) interferometry. Our new sub-milliarcsecond resolution CHARA (CLASSIC and CLIMB) interferometric observations, supplemented with archival shorter baseline data from VLTI/PIONIER and the Keck Interferometer, are modeled using centro-symmetric geometric models and an axisymmetric radiative transfer code. CHARAs 330 m baselines enable us to place strong constraints on the viewing geometry, revealing a disk inclined at 58 degrees from face-on with a 160 degree major axis position angle. Disk models imposing vertical hydrostatic equilibrium provide poor fits to the SED. Models accounting for disk scale height inflation, possibly induced by turbulence associated with magneto-rotational instabilities, and invoking grain growth to >1 micron size in the disk rim are required to simultaneously reproduce the SED and measured visibility profile. However, visibility residuals for our best model fits to the SED indicate the presence of unexplained NIR emission, particularly along the apparent disk minor axis, while closure phase residuals indicate a more centro-symmetric emitting region. In addition, our inferred 58 degree disk inclination is inconsistent with a disk-based origin for the UX Ori-type variability exhibited by HD 142666. Additional complexity, unaccounted for in our models, is clearly present in the NIR-emitting region. We propose the disk is likely inclined toward a more edge-on orientation and/or an optically thick outflow component also contributes to the NIR circumstellar flux.
Stellar models applied to large stellar surveys of the Milky Way need to be properly tested against a sample of stars with highly reliable fundamental stellar parameters. We have established a program aiming to deliver such a sample. We present new fundamental stellar parameters of nine dwarfs that will be used as benchmarks for large stellar surveys. One of these stars is the solar-twin 18Sco, which is one of the Gaia-ESO benchmarks. The goal is to reach a precision of 1% in Teff. This precision is important for accurate determinations of the full set of fundamental parameters and abundances of stars observed by the surveys. We observed HD131156 (xiBoo), HD146233 (18Sco), HD152391, HD173701, HD185395 (thetaCyg), HD186408 (16CygA), HD186427 (16CygB), HD190360 and HD207978 (15Peg) using the high angular resolution optical interferometric instrument PAVO/CHARA. We derived limb-darkening corrections from 3D model atmospheres and determined Teff directly from the Stefan-Boltzmann relation, with an iterative procedure to interpolate over tables of bolometric corrections. Surface gravities were estimated from comparisons to Dartmouth stellar evolution model tracks. We collected spectroscopic observations from the ELODIE spectrograph and estimated metallicities ([Fe/H]) from a 1D non-local thermodynamic equilibrium (NLTE) abundance analyses of unblended lines of neutral and singly ionized iron. For eight of the nine stars, we measure the Teff less than 1%, and for one star better than 2%. We determined the median uncertainties in logg and Fe/H as 0.015dex and 0.05dex, respectively. This study presents updated fundamental stellar parameters of nine dwarfs that can be used as a new set of benchmarks. All parameters were based on consistently combining interferometric observations, 3D limb-darkening modelling and spectroscopic analysis. The next paper will extend our sample to metal-rich giants.
High-resolution observations by visible and near-infrared interferometers of both single stars and binaries have made significant contributions to the foundations that underpin many aspects of our knowledge of stellar structure and evolution for cool stars. The CS16 splinter on this topic reviewed contributions of optical interferometry to date, examined highlights of current research, and identified areas for contributions with new observational constraints in the near future.
Benchmark stars are crucial as validating standards for current as well as future large stellar surveys of the Milky Way. However, the number of suitable metal-poor benchmarks is currently limited. We aim to construct a new set of metal-poor benchmarks, based on reliable interferometric effective temperature ($T_text{eff}$) determinations and a homogeneous analysis with a desired precision of $1%$ in $T_text{eff}$. We observed ten late-type metal-poor dwarf and giants: HD2665, HD6755, HD6833, HD103095, HD122563, HD127243, HD140283, HD175305, HD221170, and HD224930. Only three of the ten stars (HD103095, HD122563, and HD140283) have previously been used as benchmarks. For the observations, we used the high angular resolution optical interferometric instrument PAVO at the CHARA array. We modelled angular diameters using 3D limb darkening models and determined $T_text{eff}$ directly from the Stefan-Boltzmann relation, with an iterative procedure to interpolate over tables of bolometric corrections. Surface gravities ($log(g)$) were estimated from comparisons to Dartmouth stellar evolution model tracks. We collected spectroscopic observations from the ELODIE and FIES spectrographs and estimated metallicities ($mathrm{[Fe/H]}$) from a 1D non-LTE abundance analysis of unblended lines of neutral and singly ionized iron. We inferred $T_text{eff}$ to better than $1%$ for five of the stars (HD103095, HD122563, HD127243, HD140283, and HD224930). The $T_text{eff}$ of the other five stars are reliable to between $2-3%$; the higher uncertainty on the $T_text{eff}$ for those stars is mainly due to their having a larger uncertainty in the bolometric fluxes. We also determined $log(g)$ and $mathrm{[Fe/H]}$ with median uncertainties of $0.03,mathrm{dex}$ and $0.09,mathrm{dex}$, respectively. These ten stars can, therefore, be adopted as a new, reliable set of metal-poor benchmarks.
A fundamental challenge for wide-field imaging surveys is obtaining follow-up spectroscopic observations: there are > $10^9$ photometrically cataloged sources, yet modern spectroscopic surveys are limited to ~few x $10^6$ targets. As we approach the Large Synoptic Survey Telescope (LSST) era, new algorithmic solutions are required to cope with the data deluge. Here we report the development of a machine-learning framework capable of inferring fundamental stellar parameters (Teff, log g, and [Fe/H]) using photometric-brightness variations and color alone. A training set is constructed from a systematic spectroscopic survey of variables with Hectospec/MMT. In sum, the training set includes ~9000 spectra, for which stellar parameters are measured using the SEGUE Stellar Parameters Pipeline (SSPP). We employed the random forest algorithm to perform a non-parametric regression that predicts Teff, log g, and [Fe/H] from photometric time-domain observations. Our final, optimized model produces a cross-validated root-mean-square error (RMSE) of 165 K, 0.39 dex, and 0.33 dex for Teff, log g, and [Fe/H], respectively. Examining the subset of sources for which the SSPP measurements are most reliable, the RMSE reduces to 125 K, 0.37 dex, and 0.27 dex, respectively, comparable to what is achievable via low-resolution spectroscopy. For variable stars this represents a ~12-20% improvement in RMSE relative to models trained with single-epoch photometric colors. As an application of our method, we estimate stellar parameters for ~54,000 known variables. We argue that this method may convert photometric time-domain surveys into pseudo-spectrographic engines, enabling the construction of extremely detailed maps of the Milky Way, its structure, and history.
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