adsabs/AstroCLIMB huggingface dataset:
Paper: Unresolved Binaries and Multiples in the Intermediate Mass Range in Open Clusters: Pleiades, Alpha Per, Praesepe, and NGC 1039
Authors: Alina A. Malofeeva, Varvara O. Mikhnevich, Giovanni Carraro, Anton F. Seleznev
Figure caption: The (H–W2)–W1 vs. W2–(BP–K) diagram for the probable members of the Alpha Persei (gray dots). Lines and designations are the same as in Figure 3. The upper lines correspond to the binary and multiple stars with a primary component of 1.9 M ⊙. The lower lines correspond to the binary and multiple stars with a primary component of 0.5 M ⊙.(The data used to create this figure are available.)
Paper: Unresolved Binaries and Multiples in the Intermediate Mass Range in Open Clusters: Pleiades, Alpha Per, Praesepe, and NGC 1039
Authors: Alina A. Malofeeva, Varvara O. Mikhnevich, Giovanni Carraro, Anton F. Seleznev
Figure caption: The (H–W2)–W1 vs. W2–(BP–K) diagram for the probable members of the Praesepe (gray dots). Lines and designations are the same as in Figure 3. The upper lines correspond to the binary and multiple stars with a primary component of 1.4 M ⊙. The lower lines correspond to the binary and multiple stars with a primary component of 0.7 M ⊙.(The data used to create this figure are available.)
Paper: Unresolved Binaries and Multiples in the Intermediate Mass Range in Open Clusters: Pleiades, Alpha Per, Praesepe, and NGC 1039
Authors: Alina A. Malofeeva, Varvara O. Mikhnevich, Giovanni Carraro, Anton F. Seleznev
Figure caption: W2–(BP–K) vs. (H–W2)–W1 diagram for the sample of the Pleiades probable members. Solid lines are for constant q values. These lines of constant q values refer to the Bressan et al. (2012) isochrone with ﹩\mathrm{log}t=8.116﹩. q values are 0.0, 0.2, 0.4, 0.6, 0.8, and 1.0 (from the right to the left).
Paper: Unresolved Binaries and Multiples in the Intermediate Mass Range in Open Clusters: Pleiades, Alpha Per, Praesepe, and NGC 1039
Authors: Alina A. Malofeeva, Varvara O. Mikhnevich, Giovanni Carraro, Anton F. Seleznev
Figure caption: The distribution of the component mass ratio q and its fitting by a Gaussian for the Pleiades. Solid line (case (a))—stars with 0 < q < 0.2 are considered as binaries; dashed line (case (b))—stars with 0 < q < 0.2 are added to singles.
Paper: Unresolved Binaries and Multiples in the Intermediate Mass Range in Open Clusters: Pleiades, Alpha Per, Praesepe, and NGC 1039
Authors: Alina A. Malofeeva, Varvara O. Mikhnevich, Giovanni Carraro, Anton F. Seleznev
Figure caption: The distribution of the component mass ratio q and the Gaussian fit for the Alpha Persei cluster. Designations are the same as in Figure 4.
Paper: Unresolved Binaries and Multiples in the Intermediate Mass Range in Open Clusters: Pleiades, Alpha Per, Praesepe, and NGC 1039
Authors: Alina A. Malofeeva, Varvara O. Mikhnevich, Giovanni Carraro, Anton F. Seleznev
Figure caption: The diagram (H–W2)–W1 vs. W2–(BP–K) for the probable members of NGC 1039 (gray dots) with the thin black lines for constant q values of 0.0, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, and 1.0 (from the right to left), and with the boundaries of the area of star counts. An upper line corresponds to binary and multiple stars with the primary component of 1.3 M ⊙. A lower line corresponds to binary and multiple stars with the primary component of 0.5 M ⊙. The blue and orange lines designate triple and quadruple systems with equal components, respectively.(The data used to create this figure are available.)
Paper: Unresolved Binaries and Multiples in the Intermediate Mass Range in Open Clusters: Pleiades, Alpha Per, Praesepe, and NGC 1039
Authors: Alina A. Malofeeva, Varvara O. Mikhnevich, Giovanni Carraro, Anton F. Seleznev
Figure caption: The lower parts of the W2–(BP–K) vs. (H–W2)–W1 diagram for all four clusters. (a) Pleiades. (b) Alpha Persei. (c) Praesepe. (d) NGC 1039. Gray dots indicate cluster stars, while black lines are theoretical lines of constant q values. The red lines are the probable “correct” lines of constant q values plotted by eye following the cluster sequence. The green lines outline the probable region occupied by binary systems with the secondary component of the mass lower than 0.1 M ⊙.
Paper: Unresolved Binaries and Multiples in the Intermediate Mass Range in Open Clusters: Pleiades, Alpha Per, Praesepe, and NGC 1039
Authors: Alina A. Malofeeva, Varvara O. Mikhnevich, Giovanni Carraro, Anton F. Seleznev
Figure caption: The distribution of the component mass ratio q and its fitting by a Gaussian for NGC 1039. Solid line is for case (a) while dashed line is for case (b).
Paper: Unresolved Binaries and Multiples in the Intermediate Mass Range in Open Clusters: Pleiades, Alpha Per, Praesepe, and NGC 1039
Authors: Alina A. Malofeeva, Varvara O. Mikhnevich, Giovanni Carraro, Anton F. Seleznev
Figure caption: The NGC 1039 CMD (left) and the diagram W2–(BP–K) vs. (H–W2)–W1 (right). The solid line represents the theoretical isochrone overimposed for the set of cluster parameters from Dias et al. (2021). The blue dots mark the same stars on both diagrams.
Paper: Unresolved Binaries and Multiples in the Intermediate Mass Range in Open Clusters: Pleiades, Alpha Per, Praesepe, and NGC 1039
Authors: Alina A. Malofeeva, Varvara O. Mikhnevich, Giovanni Carraro, Anton F. Seleznev
Figure caption: The distribution of the component mass ratio q and the Gaussian fit for the Praesepe cluster. Designations are the same as in Figure 4.
Paper:  LOTUS: A (Non-) LTE Optimization Tool for Uniform Derivation of Stellar Atmospheric Parameters
Authors: Yangyang Li, 扬洋 李, Rana Ezzeddine
Figure caption: Box plots showing the NLTE corrections of stars considered in this work for stellar parameters T eff, ﹩\mathrm{log}g﹩, [Fe/H], and v mic as derived using LOTUS. Box plots are color-coded for two ranges of T eff for each ﹩\mathrm{log}g﹩ range, indicated at the top of each column. For intervals with only one star from our sample, boxes are replaced with dots and their error bars.
Paper:  LOTUS: A (Non-) LTE Optimization Tool for Uniform Derivation of Stellar Atmospheric Parameters
Authors: Yangyang Li, 扬洋 李, Rana Ezzeddine
Figure caption: NLTE corrections Δ[Fe/H] vs. [Fe/H]LTE determined for this work’s star sample using LOTUS. Different markers indicate stars from different studies as indicated. The yellow dashed line is a linear fit from Ezzeddine et al. (2017) for stars with [Fe/H] < −4.0. The blue dotted–dashed line is our fit to the stars for [Fe/H] < −0.5, and the black dotted line is our fit to the stars with [Fe/H] < −2.0.
Paper:  LOTUS: A (Non-) LTE Optimization Tool for Uniform Derivation of Stellar Atmospheric Parameters
Authors: Yangyang Li, 扬洋 李, Rana Ezzeddine
Figure caption: Derived stellar parameter uncertainties as a functions of the number of Fe I lines and S/N in our sample of stars from Section 4, in addition to metal-poor stars with high S/N from Ezzeddine et al. (2020).
Paper:  LOTUS: A (Non-) LTE Optimization Tool for Uniform Derivation of Stellar Atmospheric Parameters
Authors: Yangyang Li, 扬洋 李, Rana Ezzeddine
Figure caption: Comparison of our derived stellar parameters, T eff, ﹩\mathrm{log}g﹩, and [Fe/H], using LOTUS to reference literature values derived nonspectroscopically (for T eff and ﹩\mathrm{log}g﹩) for HD122564, HD140283, and Arcturus. The mean NLTE values (red dashed lines) with their 1σ confidence intervals (red shadow areas) and our mean LTE values (blue dashed lines) with their 1σ confidence intervals (blue shadow areas), compared to to reference stellar parameters (black dots with error bars) for references on the x-axis. References are as follows: Q1996 for Quirrenbach et al. (1996); G1999 for Griffin & Lynas-Gray (1999); L2008 for Lacour et al. (2008); R2011 for Ramirez & Allende Prieto (2011); C2012 for Creevey et al. (2012); F2013 for Frebel et al. (2013); H2015 for Heiter et al. (2015); C2015 for Creevey et al. (2015); A2016 for Amarsi et al. (2016); K2018 for Karovicova et al. (2018); C2019 for Creevey et al. (2019); K2020 for Karovicova et al. (2020).
Paper:  LOTUS: A (Non-) LTE Optimization Tool for Uniform Derivation of Stellar Atmospheric Parameters
Authors: Yangyang Li, 扬洋 李, Rana Ezzeddine
Figure caption: Differences (in mÅ) between the interpolated EWs (using interpolators chosen at the lowest BIC values) and the EWs from NLTE theoretical calculations computed directly using MULTI2.3. Each violin plot shows the distribution of the means of such differences for a random 4000 nodes within the spectral type interval of the precomputed EW library. Red lines are marked as the means of the distributions while purple lines are for the medians. The differences are shown for different metallicity ranges as indicated in each panel.
Paper:  LOTUS: A (Non-) LTE Optimization Tool for Uniform Derivation of Stellar Atmospheric Parameters
Authors: Yangyang Li, 扬洋 李, Rana Ezzeddine
Figure caption: Iron abundances determined from Fe I (black circles) and Fe II (red circles) line vs. reduced equivalent widths (upper panel) and excitation potential energies χ (lower panel) for selected lines in the metal-poor benchmark star HD122563. The parameters indicated on the top are the optimal values derived using the global minimization (differential evolution) algorithm in LOTUS. Dotted lines are the best linear fits to the Fe I lines in each panel. The labels at the upper left corner of each panel are the slopes of the fits and their corresponding standard deviations.
Paper:  LOTUS: A (Non-) LTE Optimization Tool for Uniform Derivation of Stellar Atmospheric Parameters
Authors: Yangyang Li, 扬洋 李, Rana Ezzeddine
Figure caption: Computed NLTE EW dependence as a function of T eff, ﹩\mathrm{log}g﹩, v mic for the Fe I line at 4070.77 Å, and EP = 3.24 eV (left), and the Fe II line at 6247.55 Å with EP = 3.89 eV (right). Both lines have been computed at a fixed [Fe/H] = −2.0.
Paper:  LOTUS: A (Non-) LTE Optimization Tool for Uniform Derivation of Stellar Atmospheric Parameters
Authors: Yangyang Li, 扬洋 李, Rana Ezzeddine
Figure caption: Differences in ﹩\mathrm{log}g﹩ and T eff between values derived using LOTUS versus reference values from Hawkins et al. (2016) for five GES metal-poor stars in their sample. Blue circles are LTcE differences, while red squares are NLTE. Dashed lines in both panels are the zero baselines. Average systematic offsets are included in the text of each panel.
Paper:  LOTUS: A (Non-) LTE Optimization Tool for Uniform Derivation of Stellar Atmospheric Parameters
Authors: Yangyang Li, 扬洋 李, Rana Ezzeddine
Figure caption: A flow diagram describing the working modules of LOTUS. Three main modules are used to derive the stellar parameters and their uncertainties: (i) an interpolation module, (ii) a global minimization module, and (iii) an uncertainty estimation module. Input includes EW measurements of Fe I and Fe II of the absorption lines measured in the spectra. Users can define the number of σ clipping required to remove outliers (see Section 2.4.3 for details). Additionally, a halt condition for the value of the smallest allowable minimization function threshold can also be defined by users (see Section 2.4.3 for details).
Paper:  LOTUS: A (Non-) LTE Optimization Tool for Uniform Derivation of Stellar Atmospheric Parameters
Authors: Yangyang Li, 扬洋 李, Rana Ezzeddine
Figure caption: Same as in Figure 7 for the CHARA sample stars from Karovicova et al. (2020, 2021a, 2021b).
Paper:  LOTUS: A (Non-) LTE Optimization Tool for Uniform Derivation of Stellar Atmospheric Parameters
Authors: Yangyang Li, 扬洋 李, Rana Ezzeddine
Figure caption: Marginalized posterior distributions of the stellar parameters of HD122563 based on the log-likelihood function in Equation (6). 1σ, 2σ, and 3σ uncertainty regions are denoted as solid contours in the 2D plot. The histograms show the marginalized posterior distributions for each parameter, respectively. Blue intersecting lines show the values obtained from our global optimization module.
Paper:  LOTUS: A (Non-) LTE Optimization Tool for Uniform Derivation of Stellar Atmospheric Parameters
Authors: Yangyang Li, 扬洋 李, Rana Ezzeddine
Figure caption: Same as in Figure 7 for the GES-K2 sample stars from Worley et al. (2020).
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Simulated RV time-series for HIP 73184 (HD 131977) for Architecture I as observed by the three telescopes in its hemisphere (one each at Las Campanas, Sutherland, and Siding Spring). This star was chosen, as it has the median number of observations (2724) for the architecture. Note, only “white” noise is included in this simulation, despite the apparent correlated noise by eye during some seasons. The appearance of correlated noise could be partially due to the variable single measurement uncertainties from airmass extinction for a fixed exposure time over the course of a season.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: The locations on the sky of all green and yellow list stars. Open circles represent green list targets, color coded by effective temperature, while the yellow list stars are depicted by the gray points. While the thin disk of nearby stars is effectively isotropic on the sky, the green prime list of 101 nearby bright stars shows some minor clustering on the sky, which can impact RV survey efficiency.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Nightly weather probabilities for each site included in our simulations.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Outline of the simulation pipeline, including the exposure time calculator (ETC) and dispatch scheduler.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Representative illustration of number and diameter of telescope in the architectures.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Observations of HIP 73184 (HD 131977) in the Architecture I simulation at Siding Spring Observatory. Local sunrise/set, star rise/set, and observation times for each day are shown.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Site locations.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Top left, top right, bottom left: comparison of the distribution of the number of observations between each architecture presented in Section 2.4 for the three spectrograph assumptions, respectively: the architecture-defined spectrograph with an RV precision photon-noise requirement and no minimum S/N-phot per spectral resolution element requirement (top left), the architecture-defined spectrograph with both an RV precision photon-noise requirement and a minimum S/N-phot per spectral resolution element requirement (top right), and the baseline instrument spectrograph with only an RV precision photon-noise requirement and no minimum S/N-phot per spectral resolution element requirement (bottom right). The boxes show the 25th/75th percentiles, with the median marked in orange. The whiskers extend from the 5th to the 95th percentiles, and the circles show below the 5th or above the 95th percentiles. For all architectures, the number of observations is summed across all telescopes for the specified architecture. Bottom right: comparison of the median number of observations between each architecture presented in Section 2.4 for the three spectrograph and survey requirements combination assumptions considered: the architecture-defined spectrograph with both an RV precision photon-noise requirement and a minimum S/N-phot per spectral resolution element requirement (red line), the architecture-defined spectrograph with only an RV precision photon-noise requirement and no minimum S/N-phot per spectral resolution element requirement (blue line), and a baseline instrument spectrograph with only an RV precision photon-noise requirement and no minimum S/N-phot per spectral resolution element requirement (black line). The number of observations from an effective cadence of once per night per architecture (3653 epochs) is shown by the dashed horizontal line.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Comparison across architecture simulations for the observable nights fraction: the number of nights in which a star is observed divided by the number of nights that star could be observed. A value of 1 means that for every night a star is observable by at least one telescope (e.g., a telescope had time allocated, was not weathered out, and the star was above the pointing limits), at least one or more of the telescopes in the architecture observes it in our simulations. If more than one telescope observes the same star on the same night, that star does not get double-counted, so the maximum possible fraction is 1.0. Given that each telescope site is modeled independently, we do not optimize this quantity (e.g., we do not prioritize a particular star at a given telescope higher if the other two to five telescopes are weathered out). The three box plots are for the distribution of observation fractions under different spectrograph instrument configurations, as in Figure 12, while the line graph shows the medians for all. The color scheme is the same as in Figure 12 as well. The observable nights fraction is an approximate comparison of the survey efficiency for the given target list. No star in any architecture is observed for 100% of possible nights.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Comparison across architecture simulations for minimum reflex velocity semiamplitude sensitivity at a nominal S/N-detect of 10, as inferred from Equations (1) and (2) for the number of observations per star and architecture single measurement precision. The box plots show the distribution of target stars under the different instrument configurations, while the line graph shows just the medians for all configurations, in the same layout as in Figure 12. Lower values are better, as they indicate sensitivity to smaller and/or more distant planets.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Comparison across architecture simulations for the maximum S/N (S/N-detect) for a planet detection at a nominal reflex velocity semiamplitude of 0.1 m s−1, as inferred from Equations (1) and (2). The box plots show the distribution of target stars under the different instrument configurations, while the line graph shows just the medians for all configurations, as in Figure 12. Higher values are better, as they indicate stronger detections of a planet at the nominal semiamplitude.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Histograms of our sensitivity calculations from the observations. Top: smallest semiamplitude K for which a planet with a period much shorter than our 10 yr survey could be found at an S/N-detect of 10. Bottom: the S/N-detect at which a planet with a period much shorter than our 10 yr survey could be detected at if it had a semiamplitude of 10 cm s−1. In both cases, these values are calculated from Equation (1).
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Comparison across architecture simulations and P-mode oscillation assumptions for median number of observations (top), and minimum reflex velocity semiamplitude sensitivity (bottom). The 5 minutes (left) and 10 minutes (right) graphs use the same vertical scale for ease of comparison.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Simulated observation cadence and nightly availability for HIP 73184 (HD 131977) for Architecture I observed by three telescopes (one each at Las Campanas, Sutherland, and Siding Spring). Observations here are binned into 30.4375 day “months;” actual observations were never more than one per night.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Top: histograms of exposure times per star calculated individually at each site. Bottom: how “efficiently” each star was observed—that is, for what fraction of nights where a star could be observed from at least one site it was observed at least once.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Histograms of how often a given star was observed. Individual sites are shown (top), as well as groupings of different sites (bottom), with the six telescope grouping being the full architecture.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Same as Figure 9, but for Architecture IIa.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Same as Figure 11, but for Architecture IIa.
Paper: Simulations for Planning Next-generation Exoplanet Radial Velocity Surveys
Authors: Patrick D Newman, Peter Plavchan, Jennifer A. Burt, Johanna Teske, Eric E. Mamajek, Stephanie Leifer, B. Scott Gaudi, Gary Blackwood, Rhonda Morgan
Figure caption: Same as Figure 10, but for Architecture IIb.