adsabs/AstroCLIMB huggingface dataset:
Paper: Cosmological Constraints from the BOSS DR12 Void Size Function
Authors: Sofia Contarini, Alice Pisani, Nico Hamaus, Federico Marulli, Lauro Moscardini, Marco Baldi
Figure caption: Median void counts as a function of their cleaned radius, measured from 100 mocks of the MultiDark PATCHY simulation and for the two redshift ranges considered this analysis: 0.2 < z ≤ 0.45 (left) and 0.45 < z < 0.65 (right). For each panel, we represent the median void number counts as orange diamonds, with error bars given by their standard deviation across the different PATCHY realizations. We indicate with a green line the calibrated void size function model, dependent on the value of b eff σ 8 of the redshift-selected sample of galaxies. The green shaded area represents the 68% confidence region around the calibrated model, determined by the confidence contour reported in the right panel of Figure 3.
Paper: HOW-MHD: A High-order WENO-based Magnetohydrodynamic Code with a High-order Constrained Transport Algorithm for Astrophysical Applications
Authors: Jeongbhin Seo, Dongsu Ryu
Figure caption: Power spectra of the density, P  ρ (k) (left panel), the kinetic energy, ﹩{P}_{{E}_{K}}(k)﹩ (middle panel), and the magnetic energy, ﹩{P}_{{E}_{B}}(k)﹩ (right panel), in the isothermal turbulence with the isothermal MHD code (red lines) and the adiabatic turbulence with the adiabatic MHD code (blue lines). See the main text for the setup of the turbulences. The results from simulations with 256 × 256 × 256 grid cells using the isothermal and adiabatic codes with CT6 are shown. The solid lines show the spectra averaged over 1.5 ≤ t/t cross ≤ 2.5, during which both the turbulences are characterized by M turb ≈ 1 and β  p  = 1. The dashed lines draw the spectra averaged over 3.5 ≤ t/t cross ≤ 4, when M turb ≈ 1 for the isothermal turbulence but M turb < 1 for the adiabatic turbulence. The short black lines draw the slope of the Kolmogorov spectrum.
Paper: Cosmological Constraints from the BOSS DR12 Void Size Function
Authors: Sofia Contarini, Alice Pisani, Nico Hamaus, Federico Marulli, Lauro Moscardini, Marco Baldi
Figure caption: Void counts as a function of their cleaned radius measured in the BOSS DR12 galaxy distribution, for the two redshift subsamples considered in this analysis: 0.2 < z ≤ 0.45 (left) and 0.45 < z < 0.65 (right). For each panel, we report with red circles the measured void size function, with error bars computed by rescaling those associated with the corresponding PATCHY void counts. We show in blue the void size function model calibrated with the PATCHY mock catalogs and dependent on the value of b eff σ 8 of the redshift-selected sample of galaxies. In this case, the best-fit model (solid line) and its 68% confidence region (shaded) are computed by fitting the measured void counts with a ΛCDM cosmology and leaving the parameters σ 8 and Ωm free (see the relaxed calibration case of Section 3.4).
Paper: Cosmological Constraints from the BOSS DR12 Void Size Function
Authors: Sofia Contarini, Alice Pisani, Nico Hamaus, Federico Marulli, Lauro Moscardini, Marco Baldi
Figure caption: Visual representation of the distribution of galaxies and voids in the BOSS DR12 data set and the MultiDark PATCHY simulations from a redshift range 0.2 < z < 0.75 and within a slice of width 200 h −1 Mpc. In the upper-left panels we show the northern and the southern galactic caps covered by BOSS, while in the lower-right panels the corresponding regions reproduced by one of the PATCHY mocks are shown. For each of the four represented sky areas, we indicate the cosmic voids identified in the distribution of galaxies by filled circles, post-processed with the cleaning procedure. For those voids that only partially intersect with the selected slice, we additionally show a dashed circle to indicate their full size that extends beyond the slice.
Paper: HOW-MHD: A High-order WENO-based Magnetohydrodynamic Code with a High-order Constrained Transport Algorithm for Astrophysical Applications
Authors: Jeongbhin Seo, Dongsu Ryu
Figure caption: Time evolution of M turb, ﹩{(\rho -{\rho }_{0})}_{\mathrm{rms}}﹩, the kinetic energy, and the magnetic energy in the isothermal turbulence with the isothermal MHD code (red lines) and the adiabatic turbulence with the adiabatic MHD code (blue lines). See the main text for the setup of the turbulences. The results from simulations with 256 × 256 × 256 grid cells using the isothermal and adiabatic codes with CT6 are shown. The vertical dotted lines mark the time when the images in Figure 17 are drawn. The shaded regions cover the periods over which the power spectra in Figure 18 are calculated.
Paper: HOW-MHD: A High-order WENO-based Magnetohydrodynamic Code with a High-order Constrained Transport Algorithm for Astrophysical Applications
Authors: Jeongbhin Seo, Dongsu Ryu
Figure caption: 2D slice images of the kinetic energy (top panels) and the magnetic energy (bottom panels) in the isothermal turbulence with the isothermal MHD code (left panels) and the adiabatic turbulence with the adiabatic MHD code (right panels), both having M turb ≈ 1 and β  p  = 1, from simulations with 256 × 256 × 256 grid cells using codes with CT6. See the main text for the setup of the turbulences.
Paper: Systematic Multiepoch Monitoring of LkCa 15: Dynamic Dust Structures on Solar System Scales
Authors: Steph Sallum, Josh Eisner, Andy Skemer, Ruth Murray-Clay
Figure caption: Position angle evolution of three-point-source model fits compared to orbiting and stationary scenarios. Scattered points with error bars show best-fit position angles of three-point-source models fit to each L-band (red), K-band (green), and H-band (blue) epoch. The first three sets of points show the fit results published in Kraus & Ireland (2012), which we include since they were used for the orbital fitting published in Sallum et al. (2015a). Gold, turquoise, and purple shaded curves show the best-fit orbits to the LkCa 15 b, c, and d candidates identified in Sallum et al. (2015a), respectively. Horizontal dotted lines indicate constant position angles. Solid curves show ∼20 au Keplerian orbits aligned with the outer disk (Section 6.2.1). As discussed in Section 6.2.1, although we only fit three-point-source geometric models at any given epoch, we include the four Keplerian orbits to illustrate the expected signal for forward scattering by clumps orbiting through the disk.
Paper: Systematic Multiepoch Monitoring of LkCa 15: Dynamic Dust Structures on Solar System Scales
Authors: Steph Sallum, Josh Eisner, Andy Skemer, Ruth Murray-Clay
Figure caption: Comparison of observed reconstructed images in combined data sets from each band to simulated reconstructions of best-fit models for the same data sets. Columns from left to right show images reconstructed from (1) combined data sets from each band, (2) simulated noiseless observations of the best-fit three-point-source model, (3) simulated noisy observations of the best-fit three-point-source model, (4) simulated noiseless observations of the best-fit Gaussian ring model, (5) simulated noisy observations of the best-fit Gaussian ring model, and (6) simulated observations of the null, point-source model, with noise added to match the scatter in the real data. From top to bottom, rows correspond to the 2019-01 H-band, 2015-02 K s-band, and 2014–2020 combined ﹩{L}^{{\prime} }﹩ data sets. Comparison of the noiseless and noisy reconstructions illustrates the different effects that signal-to-noise ratio and Fourier coverage have on imaging quality. Comparison of the images reconstructed from the data to those in column (6) illustrates (qualitatively) the significance of the detections given the systematic effects of SQUEEZE and the signal-to-noise ratio of each data set. The reconstructions in columns (1), (3), and (5) are identical to those shown in Figure 6.
Paper: Systematic Multiepoch Monitoring of LkCa 15: Dynamic Dust Structures on Solar System Scales
Authors: Steph Sallum, Josh Eisner, Andy Skemer, Ruth Murray-Clay
Figure caption: The shaded region shows the multiplicative signal-to-noise penalty (Equation (7)) for an SDI-detected Hα excess as a function of the contrast ratio of accretion-tracing Hα and continuum forward-scattered light, as well as the stellar Hα-to-continuum ratio (f *;  thickness of shaded region). The stellar Hα-to-continuum ratio was varied from 1 (no stellar accretion signature) to 2. The vertical line shows the continuum contrast to Hα contrast ratio estimate for the 2014 LkCa 15 b detection (Section 6.1.2). Because of forward-scattering contributions at Hα and in the continuum image subtracted during the SDI process, performing SDI in the presence of forward-scattered light can suppress the signal-to-noise ratio significantly. This effect is not necessarily taken into account during conventional SDI signal-to-noise estimates.
Paper: Systematic Multiepoch Monitoring of LkCa 15: Dynamic Dust Structures on Solar System Scales
Authors: Steph Sallum, Josh Eisner, Andy Skemer, Ruth Murray-Clay
Figure caption: Comparison of the observed reconstructed image for the combined ﹩{L}^{{\prime} }﹩ data set (left) to simulated reconstructions of best-fit one-ring (right) and two-ring (center) models. The two-ring scenario results in a pronounced outer arc to the northwest of the star, at approximately twice the separation of the bright inner arc, and at the same location where an outer arc is seen in the data. The two-ring model also results in a slightly more pronounced emission to the southeast of the star at a similar angular separation. It is worth noting that the combined ﹩{L}^{{\prime} }﹩ data set has the highest sensitivity to this outer ring component (which roughly coincides with LkCa 15's ∼50 au disk), so individual epochs may not show such noticeable changes in the image reconstructions between the two scenarios.
Paper: Systematic Multiepoch Monitoring of LkCa 15: Dynamic Dust Structures on Solar System Scales
Authors: Steph Sallum, Josh Eisner, Andy Skemer, Ruth Murray-Clay
Figure caption: Images show example reconstructed ﹩{L}^{{\prime} }﹩-band images with hollow circles indicating the best-fit three-point-source model positions. The position angles of the circles in each panel correspond to the red points in Figure 7. The three-point-source model positions generally overlap with bright regions in all of the reconstructions. However, since the model requires all off-axis flux to be concentrated in three delta functions, the point sources do not necessarily always fall on the brightest pixels.
Paper: Magnetic Field Measurements of Low-mass Stars from High-resolution Near-infrared IGRINS Spectra
Authors: Eunkyu Han, Ricardo López-Valdivia, Gregory N. Mace, Daniel T. Jaffe
Figure caption: Sample Zeeman broadening measurements of GJ 388. The top panel shows the IGRINS K-band region of interest with each atomic line position marked. The smaller bottom panels are the zoom-in view of individual lines with each line and its g eff value marked. Solid red lines are the best-fit double-Lorentzian and the dashed red lines are the component single-Lorentizans. The grayed panels are excluded from the final statistics due to being a bad measurement or below the detection limit. The weighted average and uncertainty for this target are 2.64 ± 0.59 kG.
Paper: Magnetic Field Measurements of Low-mass Stars from High-resolution Near-infrared IGRINS Spectra
Authors: Eunkyu Han, Ricardo López-Valdivia, Gregory N. Mace, Daniel T. Jaffe
Figure caption: A sample plot of the Ti line showing how its EW and EW ratio changes as a function of the magnetic field strengths. The upper panel shows the measured Ti EWs from MOOGStokes (in blue) and the adjusted EWs (in black) using the residual EWs. The bottom panel shows the EW-B relation of the same Ti line using the adjusted EWs. The red star indicates the measured EW ratio from observation and its corresponding magnetic field strength.
Paper: Magnetic Field Measurements of Low-mass Stars from High-resolution Near-infrared IGRINS Spectra
Authors: Eunkyu Han, Ricardo López-Valdivia, Gregory N. Mace, Daniel T. Jaffe
Figure caption: A sample plot of the MOOGStokes models that were used to build the EW-B field relationships. The top and the middle rows show the MOOGStokes models covering parts of the IGRINS H and K band, respectively. The grayed regions mark the atomic lines of interest. The bottom panels are the zoomed-in plots of a selection of atomic lines. The dashed lines indicate the location of the line center and the dotted lines around the dashed lines indicate the boundaries used to calculate the EW. The model parameters shown in the plot are Teff = 3300 K, vsini = 0 km s−1, and B = 0.5, 2.5, and 4.5 kG.
Paper: Magnetic Field Measurements of Low-mass Stars from High-resolution Near-infrared IGRINS Spectra
Authors: Eunkyu Han, Ricardo López-Valdivia, Gregory N. Mace, Daniel T. Jaffe
Figure caption: Sample Zeeman intensification measurements of GJ 388 using the IGRINS H-band spectrum. The top panel shows the position of each atomic line (in blue) that is used in the measurements. The continuum level is marked with a solid red line. The smaller bottom panels are the zoom-in view of the individual line. The dashed line is the central wavelength of each atomic line and the dotted lines are the boundaries used to measure the EW.
Paper: Magnetic Field Measurements of Low-mass Stars from High-resolution Near-infrared IGRINS Spectra
Authors: Eunkyu Han, Ricardo López-Valdivia, Gregory N. Mace, Daniel T. Jaffe
Figure caption: Comparison of vsini measurements from this work to values from Shulyak et al. (2019). The bottom panel shows the difference between Shulyak et al. (2019) and this work.
Paper: Magnetic Field Measurements of Low-mass Stars from High-resolution Near-infrared IGRINS Spectra
Authors: Eunkyu Han, Ricardo López-Valdivia, Gregory N. Mace, Daniel T. Jaffe
Figure caption: The same plot as in Figure 6 but for the K-band spectrum. The grayed panels are excluded from the measurement due to the bad quality of the data.
Paper: Magnetic Field Measurements of Low-mass Stars from High-resolution Near-infrared IGRINS Spectra
Authors: Eunkyu Han, Ricardo López-Valdivia, Gregory N. Mace, Daniel T. Jaffe
Figure caption: Compiled magnetic field strength measurements of M dwarfs using Zeeman broadening and intensification from literature. See Kochukhov (2021) and Reiners et al. (2022) for the references.
Paper: Stellar Rotation and Structure of the α Persei Complex: When Does Gyrochronology Start to Work?
Authors: Andrew W. Boyle, Luke G. Bouma
Figure caption: Upper left: the Pleiades, α Per’s core, and Meingast et al.’s (2021) tidal tails on a CAMD. Field stars are taken from the Gaia Catalog of Nearby Stars (Gaia Collaboration et al. 2021) and are plotted in gray. Tidal tail stars that fall on the Pleiades sequence or below are likely field contaminants and have been removed. Upper right: the median XYZ distance between α Per’s leading tidal tail and the core over the last 100 Myr. Middle right: the median XYZ distance between α Per’s trailing tidal tail and the core over the last 100 Myr. The faint, dashed lines in the upper- and middle-right panels represent the uncertainty in the back-integration. Bottom left: the rotation sequence of the tidal tails compared to that of the core and the Pleiades. Possible binaries have been removed following the procedure defined in Section 6.1. Bottom right: LAMOST metallicity measurements for Praesepe, α Per’s core, and the tidal tails.
Paper: Stellar Rotation and Structure of the α Persei Complex: When Does Gyrochronology Start to Work?
Authors: Andrew W. Boyle, Luke G. Bouma
Figure caption: The upper region in Theia 133. Both the rotation and CAMD sequences show that the upper region is a similar age as α Per, and the back-integration shows that the median positions of the two regions used to be within ∼30 pc of each other. The faint, dashed lines in the upper-right panel represent the uncertainty in the back-integration and are derived from 64 different runs of the back-integration, where in each run we change one of the input parameters by 1σ. Of the 418 stars in this region, 85 fall below the Pleiades on the CAMD and have been removed as likely field-star contaminants. Possible binaries have been removed following the procedure defined in Section 6.1. See Appendix B and Figure 18 for more discussion on the viability of our back-integrations at young ages.
Paper: Stellar Rotation and Structure of the α Persei Complex: When Does Gyrochronology Start to Work?
Authors: Andrew W. Boyle, Luke G. Bouma
Figure caption: The lower region’s color–absolute magnitude, back-integration, rotation, and metallicity sequences. The faint, dashed lines in the upper-right panel represent the uncertainty in the back-integration. All stars in this region that fall below α Per’s sequence on the CAMD have been removed as they are likely field contaminants, leading to a true-positive rate of 74%, which is in agreement with the rotation period derived true-positive rate for Kounkel & Covey (2019). Possible binaries have been removed following the procedure defined in Section 6.1.
Paper: Stellar Rotation and Structure of the α Persei Complex: When Does Gyrochronology Start to Work?
Authors: Andrew W. Boyle, Luke G. Bouma
Figure caption: The UVW velocity evolution of test particles over 100 Myr. The initial velocity difference of the test particles almost doubles by 100 Myr, signaling that coeval structures can have large velocity differences even at relatively young ages.
Paper: Stellar Rotation and Structure of the α Persei Complex: When Does Gyrochronology Start to Work?
Authors: Andrew W. Boyle, Luke G. Bouma
Figure caption: Upper left: the Pleiades, α Per’s core, and POB3-2 on a CAMD. Field stars are taken from the Gaia Catalog of Nearby Stars (Gaia Collaboration et al. 2021) and are plotted in gray. Upper right: the median XYZ distance between POB3-2 and the core over the last 100 Myr. The faint, dashed lines represent the uncertainty in the back-integration. Bottom left: the rotation sequence of POB3-2 compared to that of the core and the Pleiades. Possible binaries have been removed for the core and the Pleiades but not for POB3-2. Bottom right: LAMOST metallicity measurements for Praesepe, α Per’s core, and POB3-2.
Paper: Stellar Rotation and Structure of the α Persei Complex: When Does Gyrochronology Start to Work?
Authors: Andrew W. Boyle, Luke G. Bouma
Figure caption: The motions of each region of Theia 133 we analyzed. Gray points represent all stars in our sample for which getting valid rotation periods was possible while colored points are the rotationally confirmed members in the regions themselves. The arrows represent the median UVW velocities of each region after subtracting the local standard of rest, and their sizes are proportional to the magnitude of each region’s median velocity. The Sun is spatially located at the origin and is represented by the ⊙ symbol.
Paper: Stellar Rotation and Structure of the α Persei Complex: When Does Gyrochronology Start to Work?
Authors: Andrew W. Boyle, Luke G. Bouma
Figure caption: The mass distribution of the 50% of rotationally confirmed tidal tail members closest to α Per’s core vs. the 50% of members farthest away from α Per’s core. The similarity between the two distributions is more consistent with tidal tail formation through gas expulsion than slow evaporation (see Section 9.4.2).
Paper: Stellar Rotation and Structure of the α Persei Complex: When Does Gyrochronology Start to Work?
Authors: Andrew W. Boyle, Luke G. Bouma
Figure caption: The LAMOST DR7 effective temperature vs. metallicity sequence for Praesepe, α Per, and the Pleiades. α Per’s metallicity sequence here comprises stars from the core, upper region, lower region, and tails. α Per has a similar metallicity as the Pleiades, and is significantly more metal-poor than Praesepe.
Paper: Stellar Rotation and Structure of the α Persei Complex: When Does Gyrochronology Start to Work?
Authors: Andrew W. Boyle, Luke G. Bouma
Figure caption: The different regions analyzed to determine α Per’s morphology. The gray points indicate all stars in our sample, and the black points are the stars that compose each region. The tidal tails in the top row have a 10 pc radius hole at the center where the core stars have been removed.
Paper: Detecting Exoplanets Closer to Stars with Moderate Spectral Resolution Integral-field Spectroscopy
Authors: Shubh Agrawal, Jean-Baptiste Ruffio, Quinn M. Konopacky, Bruce Macintosh, Dimitri Mawet, Eric L. Nielsen, Kielan K. W. Hoch, Michael C. Liu, Travis S. Barman, William Thompson, Alexandra Z. Greenbaum, Christian Marois, Jenny Patience
Figure caption: Schematic of the components of our forward model for a specific spatial location, used in this work and discussed in Section 3.3. Other than in the bottom right-hand panel, each spectrum corresponds to a column of the FM matrix M  ψ . Here, we consider a single exposure of the M dwarf HD 148352 B that was detected in this work (Section 3.6). Top left-hand panel: the planet model (Section 3.3.1), which is not high-pass filtered and consists of the product of a BT-Settl atmospheric model (Allard et al. 2011; Allard 2013) and the telluric spectrum (Section 3.3.3). Top right-hand panel: the starlight model (Section 3.3.2), which is a combination of 10 different spline components to modulate the speckle continuum; we show only five in this schematic for clarity, which are labeled SC1, SC2, ..., SC5 (i.e., in the model that we use, we have 10 components SC1, SC2, ..., SC10). Bottom left-hand panel: the principal components of the residuals (Section 3.3.3) that are obtained from a preliminary fit over a disjoint area. Bottom right-hand panel: a linear combination fits the spectral data at the spaxel.
Paper: Detecting Exoplanets Closer to Stars with Moderate Spectral Resolution Integral-field Spectroscopy
Authors: Shubh Agrawal, Jean-Baptiste Ruffio, Quinn M. Konopacky, Bruce Macintosh, Dimitri Mawet, Eric L. Nielsen, Kielan K. W. Hoch, Michael C. Liu, Travis S. Barman, William Thompson, Alexandra Z. Greenbaum, Christian Marois, Jenny Patience
Figure caption: Sensitivity curve (green) at 8 × σ  p  for HD 148352 as a function of angular separation from the host star, overlaid with the raw point-spread function profile of the host star (blue), which quantifies speckle intensity. Each data point corresponds to an individual spaxel in the combined detection map. As discussed in 4.1, the choice of this detection threshold (8σ  p ) accounts for the non-Gaussianity of the S/N residuals and is equivalent to 5σ assuming Gaussian noise. Based on the best-fit parameters from Figure 6, the model parameters were specifically set for this plot to RV  =   − 8.6 km s−1, T eff = 3200 K, and ﹩\mathrm{log}g\,=\,5﹩. The detected M dwarf (red) is about an order of magnitude brighter than our sensitivity limit and 1–1.5 orders of magnitude lower than the speckle noise. The sensitivity curves rise at wider separations because we effectively have fewer images at the edge, due to dithering between sequences of images.
Paper: Detecting Exoplanets Closer to Stars with Moderate Spectral Resolution Integral-field Spectroscopy
Authors: Shubh Agrawal, Jean-Baptiste Ruffio, Quinn M. Konopacky, Bruce Macintosh, Dimitri Mawet, Eric L. Nielsen, Kielan K. W. Hoch, Michael C. Liu, Travis S. Barman, William Thompson, Alexandra Z. Greenbaum, Christian Marois, Jenny Patience
Figure caption: Probability distribution function of residual S/N values (a) for all (but one) of our targets individually, and (b) for Ophiuchus, Taurus, and all targets; (b) also shows the tail (purple) of the survey histogram that was fitted to an exponential decay (blue) to get extrapolated values at under-sampled S/Ns. We do not include the contribution from Em* SR 9 because the values are biased by the bright binary companion and mask HD 148352 B. The ideal Gaussian behavior is shown by the black-dashed bell curve.