adsabs/AstroCLIMB huggingface dataset:
Paper: Emergence of Microphysical Bulk Viscosity in Binary Neutron Star Postmerger Dynamics
Authors: Elias R. Most, Alexander Haber, Steven P. Harris, Ziyuan Zhang, Mark G. Alford, Jorge Noronha
Figure caption: Normalized gravitational-wave strain, ﹩{h}_{+}^{22}﹩, for the l = m = 2 component. Differences due to weak interactions in the postmerger are clearly visible. All times, t, are stated relative to the merger time and extraction radius r. The vertical lines indicate times of black hole formation.
Paper: Emergence of Microphysical Bulk Viscosity in Binary Neutron Star Postmerger Dynamics
Authors: Elias R. Most, Alexander Haber, Steven P. Harris, Ziyuan Zhang, Mark G. Alford, Jorge Noronha
Figure caption: Bulk viscous pressure correction Π relative to the equilibrium pressure in the postmerger phase when using the TMA EoS with Urca processes. The green contours denote the rest-mass density of the merger remnant in units of nuclear saturation at 3.6 ms relative to the time of merger t mer.
Paper: Detection of a 2.85 μm Feature on Five Spinel-rich Asteroids from JWST
Authors: Jonathan Gomez Barrientos, Katherine de Kleer, Bethany L. Ehlmann, Francois L. H. Tissot, Jessica Mueller
Figure caption: Comparison of the 2.85 μm features of Henan (top) and Klumpkea (bottom) from JWST with similar features seen in other solar system bodies. The normalized reflectance spectra of Bennu, Ryugu, Ceres, Vesta, and the Moon have been diluted to match the band depth of the JWST spectra. The spectrum of 433 Eros has been offset and lacks coverage between 2.55 and 2.85 μm due to atmospheric absorption.
Paper: Detection of a 2.85 μm Feature on Five Spinel-rich Asteroids from JWST
Authors: Jonathan Gomez Barrientos, Katherine de Kleer, Bethany L. Ehlmann, Francois L. H. Tissot, Jessica Mueller
Figure caption: JWST NIRSpec spectra of five L-type asteroids. The spectra have been corrected for thermal emission and normalized with respect to a reflected-sunlight model. The light- and dark-colored spectra correspond to the data acquired with the F170LP and F290LP filters, respectively. The five targets exhibit an absorption feature near 3 μm, which could be due to OH/H2O on their surfaces. The dashed blue lines indicate potential detector artifacts.
Paper: Detection of a 2.85 μm Feature on Five Spinel-rich Asteroids from JWST
Authors: Jonathan Gomez Barrientos, Katherine de Kleer, Bethany L. Ehlmann, Francois L. H. Tissot, Jessica Mueller
Figure caption: Modeling of the continuum of 2085 Henan. The black points correspond to the JWST data. The red curve is the best-fit continuum model, which consists of a reflected-light model and a thermal emission model.
Paper: Detection of a 2.85 μm Feature on Five Spinel-rich Asteroids from JWST
Authors: Jonathan Gomez Barrientos, Katherine de Kleer, Bethany L. Ehlmann, Francois L. H. Tissot, Jessica Mueller
Figure caption: Processing of the two NIRSpec spectra of 824 Anastasia from the filters F170LP and F290LP. A small offset is applied to the entire F170LP data in order to match the F290LP data in the overlapping region.
Paper: Detection of a 2.85 μm Feature on Five Spinel-rich Asteroids from JWST
Authors: Jonathan Gomez Barrientos, Katherine de Kleer, Bethany L. Ehlmann, Francois L. H. Tissot, Jessica Mueller
Figure caption: Top: comparison of the 2–5 μm spectrum of 458 Hercynia to the spectra of minerals and the spectra of aqueously altered CM, CO, and CV meteorites. The particle sizes of all mineral samples are <45 μm except for goethite, which is <125 μm. CM meteorites that have been heavily aqueously altered contain more phyllosillicates and exhibit a BC at shorter wavelengths. All meteorite samples were heated to minimize contamination from adsorbed terrestrial water. The meteorite and mineral spectra have been diluted to match the 3 μm band depth of 458 Hercynia. The dashed blue line corresponds to the BC of 458 Hercynia. Bottom: comparison of the 2–5 μm spectrum of 458 Hercynia to the spectra of three CAIs. The CAI spectra have also been diluted to match the 3 μm band depth of 458 Hercynia.
Paper: The Physical Origin of the Periodic Activity for FRB 20180916B
Authors: Hao-Tian Lan, Zhen-Yin Zhao, Yu-Jia Wei, Fa-Yin Wang
Figure caption: The reduced χ 2 of different P and ﹩\dot{P}﹩. Top panel shows the result of epoch-folding method for different P and ﹩\dot{P}﹩ with the use of Equation (2). A higher χ 2 means that the period and its ﹩\dot{P}﹩ are more reliable respectively. Bottom panel is the two-dimensional Gaussian fitting results of the top panel.
Paper: The Physical Origin of the Periodic Activity for FRB 20180916B
Authors: Hao-Tian Lan, Zhen-Yin Zhao, Yu-Jia Wei, Fa-Yin Wang
Figure caption: The relationship between MJD and phase for the bursts observed by CHIME after folding with two different ﹩\dot{P}﹩. The bursts observed by CHIME are folded with Equation (2). The blue points represents the prior 56 bursts and the orange points represents the subsequent 55 bursts. The top panel shows an acceptable example with a period of 16.33 days and a ﹩\dot{P}﹩ of 1.0 × 10−5 day day−1. The bottom panel shows an unacceptable example with a period of 16.33 days and a ﹩\dot{P}﹩ of 8.6 × 10−5 day day−1. We can see in the bottom panel that the active window has a phase shift over time.
Paper: The Physical Origin of the Periodic Activity for FRB 20180916B
Authors: Hao-Tian Lan, Zhen-Yin Zhao, Yu-Jia Wei, Fa-Yin Wang
Figure caption: Constraints on the period derivative ﹩\dot{P}﹩ and period P. The range of period P is adopted from Table 1. The blue area is acceptable, which means that all of the subsequent 61 bursts can fall into the active window predicted by the earlier 61 bursts. The yellow area is not acceptable, which means that there are some bursts cannot fall into the active window predicted by the earlier 61 bursts.
Paper: The Physical Origin of the Periodic Activity for FRB 20180916B
Authors: Hao-Tian Lan, Zhen-Yin Zhao, Yu-Jia Wei, Fa-Yin Wang
Figure caption: The RM variation of the self-consistent model. The y-axis ΔRM = RM-RM0 represents the variation of RM. Here, RM0 = −115.8, which is the mean value of the nonevolving phase (Mckinven et al. 2023a). The blue and orange point shows the observational data from CHIME and LOFAR (Mckinven et al. 2023a; Gopinath et al. 2024). The red line shows the results calculated with use of our model and fitting parameters. The top panel shows the RM variation of radial magnetic field and the bottom panel shows the the RM variation of toroidal magnetic field.
Paper: The Physical Origin of the Periodic Activity for FRB 20180916B
Authors: Hao-Tian Lan, Zhen-Yin Zhao, Yu-Jia Wei, Fa-Yin Wang
Figure caption: Chromatic periodic activity for different telescopes: Effelsberg (Bethapudi et al. 2023; blue), Apertif (Pastor-Marazuela et al. 2021; orange), CHIME (CHIME/FRB Collaboration et al. 2019; CHIME/FRB Collaboration et al. 2020; Mckinven et al. 2023a; green), and LOFAR (Pastor-Marazuela et al. 2021; Pleunis et al. 2021; red). The period used for the folding is 16.33 days, which is the best-fitting result with epoch-folding method. The colored lines are kernel density estimations. The active window is narrower and earlier at higher frequencies up to 8 GHz.
Paper: The Physical Origin of the Periodic Activity for FRB 20180916B
Authors: Hao-Tian Lan, Zhen-Yin Zhao, Yu-Jia Wei, Fa-Yin Wang
Figure caption: Constraint on the internal magnetic field B int and period derivative ﹩{\dot{P}}_{\mathrm{pre}}﹩ for the free precession model. The blue line shows the relationship between B int and ﹩{\dot{P}}_{\mathrm{pre}}﹩ from Equation (4). The orange line represents the ﹩{\dot{P}}_{\mathrm{pre}}=9.4\times {10}^{-5}﹩ day day−1 and the orange area shows the acceptable value for ﹩{\dot{P}}_{\mathrm{pre}}﹩. The green line represents the ﹩{\dot{P}}_{\mathrm{pre}}=2.0\times {10}^{-5}﹩ day day−1 and the green area shows the acceptable value for ﹩{\dot{P}}_{\mathrm{pre}}﹩. The red line shows the B int = 1014.5 G and the red area represents the allowable region for the upper limit given by X-ray and γ-ray observation (Tavani et al. 2020).
Paper: The Physical Origin of the Periodic Activity for FRB 20180916B
Authors: Hao-Tian Lan, Zhen-Yin Zhao, Yu-Jia Wei, Fa-Yin Wang
Figure caption: The relationship between mass ratio q and the period after the evolution of four years for orbit-induced spin model. The initial period is set as 16.33 days, which is the best-fitting results. The blue line shows the period after the evolution of 4 yr as a function of mass ratio q. The green line shows the period of 16.242 days, which is the temporal results of ﹩{\dot{P}}_{\mathrm{pre}}=-6.0\times {10}^{-5}﹩ day day−1. The green area is the acceptable range for mass ratio q.
Paper: The Physical Origin of the Periodic Activity for FRB 20180916B
Authors: Hao-Tian Lan, Zhen-Yin Zhao, Yu-Jia Wei, Fa-Yin Wang
Figure caption: The predicted burst numbers of forced precession model for different frequency bands: 110–188MHz (red), 400–800MHz (green), 1.36–2 GHz (orange), and 4–8 GHz (blue) under the assumption that the FRBs are emitted due to the curvature radiation. The frequency bands given in this figure are consistent with the frequency bands of LOFAR (Pastor-Marazuela et al. 2021; Pleunis et al. 2021), CHIME (CHIME/FRB Collaboration et al. 2019; CHIME/FRB Collaboration et al. 2020; Mckinven et al. 2023a), Apertif (Pastor-Marazuela et al. 2021), and Effelsberg (Bethapudi et al. 2023).
Paper: The Physical Origin of the Periodic Activity for FRB 20180916B
Authors: Hao-Tian Lan, Zhen-Yin Zhao, Yu-Jia Wei, Fa-Yin Wang
Figure caption: The schematic diagram of the self-consistent model for FRB 20180916B. The green circle corresponds to the neutron star with a ultralong rotation period. The orange circle represents the massive star with stellar wind shown as yellow part. The 16 days period is due to the ultralong rotation of the neutron star and the variation of the RM is attributed to the orbital motion of this binary system.
Paper: Gamma-Ray Bursts as Distance Indicators by a Statistical Learning Approach
Authors: Maria Giovanna Dainotti, Aditya Narendra, Agnieszka Pollo, Vahé Petrosian, Malgorzata Bogdan, Kazunari Iwasaki, Jason Xavier Prochaska, Enrico Rinaldi, David Zhou
Figure caption: The scatter matrix plot of the predictors at play, some showing strong correlations, while others show weak or no correlation. Each variable (the prompt Fluence; T 90; the prompt Peakflux; the plateau optical flux (﹩\mathrm{log}({F}_{a})﹩); its duration (﹩\mathrm{log}({T}_{a})﹩); the hydrogen column density (﹩\mathrm{log}({NH})﹩); the prompt Photon Index; and the temporal and spectral indices, α, and β, of the optical afterglow and plateau emissions, respectively) is plotted against every other. The stars next to the correlation value denote the significance level. One, two, or three stars denote the corresponding variables’ correlation is significant at 10%, 5% and 1% levels, respectively.
Paper: Gamma-Ray Bursts as Distance Indicators by a Statistical Learning Approach
Authors: Maria Giovanna Dainotti, Aditya Narendra, Agnieszka Pollo, Vahé Petrosian, Malgorzata Bogdan, Kazunari Iwasaki, Jason Xavier Prochaska, Enrico Rinaldi, David Zhou
Figure caption: The missing data in our sample. The pink boxes show the missing GRBs in relation to a given variable presented in the upper x-axis, while the blue boxes indicate GRBs with no missing data for a given GRB variable presented in the top axis. The bottom axis shows the number of missing GRBs per variable. The left axis represents the number of observations that have missing data for a specific set of predictors. The right axis represents the number of predictors that are missing for that row. For example, starting from the top row, there are 126 GRBs with no missing data, 14 GRBs with missing data in log10(NH), 2 GRBs with missing data in log10(Peak) and log10(NH), and so on. The corner number on the right of the X-axis (186) shows the total number of missing predictors in the data set, which is the sum of the numbers shown along the axis.
Paper: Gamma-Ray Bursts as Distance Indicators by a Statistical Learning Approach
Authors: Maria Giovanna Dainotti, Aditya Narendra, Agnieszka Pollo, Vahé Petrosian, Malgorzata Bogdan, Kazunari Iwasaki, Jason Xavier Prochaska, Enrico Rinaldi, David Zhou
Figure caption: Left panel: luminosity vs redshift for 103 GRBs. The luminosities calculated using z  obs  and z  pred  are shown with blue and red points, respectively. The orange and purple points represent the luminosities of z  obs  and z  pred , respectively, which are lower than the luminosity threshold given by the flux limit of 1.25 × 10−14 erg/cm2. The arrows connect a GRB’s z  obs  and luminosity value with its predicted values. Right panel: τ versus k, where k defines the power of the g(z) function for the luminosity evolution. The red curve shows results for the GRBs with observed z  obs , while the blue curve yields the corresponding function using z  pred . The τ = 0 values are obtained at k=3.07 for the GRBs with z  obs  and 3.06 for z  pred .
Paper: Gamma-Ray Bursts as Distance Indicators by a Statistical Learning Approach
Authors: Maria Giovanna Dainotti, Aditya Narendra, Agnieszka Pollo, Vahé Petrosian, Malgorzata Bogdan, Kazunari Iwasaki, Jason Xavier Prochaska, Enrico Rinaldi, David Zhou
Figure caption: Left panel: the z  obs  vs z  pred  scatterplot for 103 GRBs. The red triangles indicate the GRBs with δ z  pred /z  pred >1. Right panel: the relative influence of each variable on the predicted results.
Paper: Gamma-Ray Bursts as Distance Indicators by a Statistical Learning Approach
Authors: Maria Giovanna Dainotti, Aditya Narendra, Agnieszka Pollo, Vahé Petrosian, Malgorzata Bogdan, Kazunari Iwasaki, Jason Xavier Prochaska, Enrico Rinaldi, David Zhou
Figure caption: Left panel: the corrected LF. The orange and purple dots represent the corrected LF obtained from z  obs  and z  pred , respectively. Right panel: the LF combined from the z  obs  and the simulated z  pred . The black and gray points show the raw LF distribution and the EPL-corrected LF, respectively. The black and gray lines show the SBPL fits for the raw and corrected LF, respectively.
Paper: Gamma-Ray Bursts as Distance Indicators by a Statistical Learning Approach
Authors: Maria Giovanna Dainotti, Aditya Narendra, Agnieszka Pollo, Vahé Petrosian, Malgorzata Bogdan, Kazunari Iwasaki, Jason Xavier Prochaska, Enrico Rinaldi, David Zhou
Figure caption: The orange and purple dots show the density rates obtained from z  obs  and z  pred , respectively. Top panel: the density-rate evolution for our sample, compared with other published density-rate evolutions for GRBs only. Bottom panel: the density-rate evolution for our GRB sample compared with the published SFR.
Paper: Gamma-Ray Bursts as Distance Indicators by a Statistical Learning Approach
Authors: Maria Giovanna Dainotti, Aditya Narendra, Agnieszka Pollo, Vahé Petrosian, Malgorzata Bogdan, Kazunari Iwasaki, Jason Xavier Prochaska, Enrico Rinaldi, David Zhou
Figure caption: Left panel: the cross-validated RMSE vs the correlation coefficient between z  obs  and z  pred  for 16,511 formulas. The red points show the formulas selected based on the correlation and RMSE cutoff (shown by the black lines). Right panel: the same results of the left panel but on a separate and unseen test set. The red lines show the highest correlation and lowest RMSE obtained on test set.
Paper: Gamma-Ray Bursts as Distance Indicators by a Statistical Learning Approach
Authors: Maria Giovanna Dainotti, Aditya Narendra, Agnieszka Pollo, Vahé Petrosian, Malgorzata Bogdan, Kazunari Iwasaki, Jason Xavier Prochaska, Enrico Rinaldi, David Zhou
Figure caption: Left panel: the z  obs  vs z  pred  scatterplot for a training set of 147 GRBs. Right panel: the z  obs  vs z  pred  scatterplot for a test set of 17 GRBs.
Paper: Gamma-Ray Bursts as Distance Indicators by a Statistical Learning Approach
Authors: Maria Giovanna Dainotti, Aditya Narendra, Agnieszka Pollo, Vahé Petrosian, Malgorzata Bogdan, Kazunari Iwasaki, Jason Xavier Prochaska, Enrico Rinaldi, David Zhou
Figure caption: The scatterplot between z  obs  and z  pred . Left panel: predictions of 147 GRBs, before removal of catastrophic outliers and bias correction Right panel: the correlation for 136 GRBs after removal of catastrophic outliers and application of bias correction.
Paper: Gamma-Ray Bursts as Distance Indicators by a Statistical Learning Approach
Authors: Maria Giovanna Dainotti, Aditya Narendra, Agnieszka Pollo, Vahé Petrosian, Malgorzata Bogdan, Kazunari Iwasaki, Jason Xavier Prochaska, Enrico Rinaldi, David Zhou
Figure caption: LASSO-based predictor selection, showing the weights assigned to the different variables.
Paper: The First Quenched Galaxies: When and How?
Authors: Lizhi Xie, 利智 谢, Gabriella De Lucia, Fabio Fontanot, Michaela Hirschmann, Yannick M. Bahé, Michael L. Balogh, Adam Muzzin, Benedetta Vulcani, Devontae C. Baxter, Ben Forrest, Gillian Wilson, Gregory H. Rudnick, M. C. Cooper, Umberto Rescigno
Figure caption: Quenched fractions as a function of redshift. Different colors represent galaxies of different stellar masses. Vertical error bars show the standard deviations obtained for 100 randomly selected subsamples. Shaded regions show the uncertainties in quiescent fractions from slightly different cuts in the UVJ diagram (more details in Section 3.1). The dashed–dotted line shows results from a GAEA run where accretion disk feedback is switched off. Dotted and dashed lines show the quenched fractions measured from TNG300 and TNG100, respectively. Error boxes are observed quenched fractions for UltraVISTA DR1 and 3D-HST survey from Martis et al. (2016).
Paper: The First Quenched Galaxies: When and How?
Authors: Lizhi Xie, 利智 谢, Gabriella De Lucia, Fabio Fontanot, Michaela Hirschmann, Yannick M. Bahé, Michael L. Balogh, Adam Muzzin, Benedetta Vulcani, Devontae C. Baxter, Ben Forrest, Gillian Wilson, Gregory H. Rudnick, M. C. Cooper, Umberto Rescigno
Figure caption: The top, middle, and bottom panels show the fraction of AGN hosts (﹩\mathrm{log}{L}_{\mathrm{bol}}/[\mathrm{erg}\,{{\rm{s}}}^{-1}]\gt 44﹩), the fraction of galaxies that have experienced recent mergers with a mass ratio larger than 1/100, and the fraction of satellites, respectively. Solid, dotted, and dashed lines correspond to the total, quenched, and newly quenched galaxy populations. Color code is the same as in Figure 1. Red and blue circles show observationally estimated AGN fractions with ﹩44\lt \mathrm{log}{L}_{\mathrm{bol}}/[\mathrm{erg}\,{{\rm{s}}}^{-1}]\lt 45.5﹩ for massive and Milky Way–mass galaxies (Ji et al. 2022). Orange open and filled squares show AGN fractions with ﹩\mathrm{log}{L}_{{\rm{X}}}/[\mathrm{erg}\,{{\rm{s}}}^{-1}]\gt 42﹩ for star-forming and quenched galaxies (Aird et al. 2022). These studies are based on X-ray-selected AGN fractions and should be intended as lower limits for the overall AGN fractions. The model predictions, however, are the upper limits of the actual AGN population.
Paper: The First Quenched Galaxies: When and How?
Authors: Lizhi Xie, 利智 谢, Gabriella De Lucia, Fabio Fontanot, Michaela Hirschmann, Yannick M. Bahé, Michael L. Balogh, Adam Muzzin, Benedetta Vulcani, Devontae C. Baxter, Ben Forrest, Gillian Wilson, Gregory H. Rudnick, M. C. Cooper, Umberto Rescigno
Figure caption: Evolution of three representative galaxies. The upper and lower panels show the evolution of sSFR and the SMBH accretion rate associated with the disk accretion mode normalized by stellar mass. The sSFR is indicated by solid and dotted lines when a galaxy is classified as central or satellite, respectively. The gray dashed line in the upper panel is the separation between quenched and star-forming galaxies. Large and small triangles in the lower panel indicate merger events with mass ratios above 0.3 and 0.01. Color code is the same as in Figure 1.
Paper: Expansion of Accreting Main-sequence Stars during Rapid Mass Transfer
Authors: Mike Y. M. Lau, Ryosuke Hirai, Ilya Mandel, Christopher A. Tout
Figure caption: H-R diagrams showing the evolution of rapidly accreting MS stellar models with initial masses M 0 = 2, 5, and 20 M ⊙ (panels (a)–(c)). Each panel shows five different accretion rates as indicated by the legend. The timescale ratio t th/t acc (defined by Equation (1)) is shown for each model at maximum radius, demonstrating that contraction begins when it decreases to approximately unity. The dotted line in each panel shows the ZAMS with masses labeled in units of M ⊙. In panel (b), stellar profiles at the diamond markers along the purple track are shown in Figure 3.
Paper: Expansion of Accreting Main-sequence Stars during Rapid Mass Transfer
Authors: Mike Y. M. Lau, Ryosuke Hirai, Ilya Mandel, Christopher A. Tout
Figure caption: The maximum radius, R max, as a function of accretion rate, ﹩\dot{M}﹩, reached by accretors with different initial masses, M 0. Models with lower ﹩\dot{M}﹩ that do not expand to their Hayashi limits are plotted as dots and lie close to the empirical fits we provide (Equation (10)). High-﹩\dot{M}﹩ models that expand along the Hayashi line (crosses) do not retain a memory of their initial masses and lie close to our semianalytical formula (Equation (7b); black line), although there are deviations for M 0 < 4 M ⊙.
Paper: Expansion of Accreting Main-sequence Stars during Rapid Mass Transfer
Authors: Mike Y. M. Lau, Ryosuke Hirai, Ilya Mandel, Christopher A. Tout
Figure caption: The parameter space explored in this study. Each point represents one of 130 models we computed. The abscissa shows the initial mass, while the ordinate parameterizes ﹩\dot{M}﹩ in terms of the ratio of the accretor’s initial Kelvin–Helmholtz timescale to the accretion timescale. Red markers are accretors that experience extreme inflation toward the Hayashi line, and blue markers are accretors that do not. The bifurcating timescale ratio is contained within the shaded region. That this region is mainly located where t KH/t acc ≫ 10 suggests that a large range of ﹩\dot{M}﹩ could result in more conservative mass transfer than assumed by Hurley et al. (2002), as discussed inSection 4.1.
Paper: Expansion of Accreting Main-sequence Stars during Rapid Mass Transfer
Authors: Mike Y. M. Lau, Ryosuke Hirai, Ilya Mandel, Christopher A. Tout
Figure caption: Radius (solid lines) and luminosity (dashed lines) evolution of an initially 12 M ⊙ accretor. The abscissa shows the accretor mass, which is proportional to time (fully conservative accretion is assumed). Line colors correspond to different accretion rates, while the dot along the curve indicates the maximum radius point.
Paper: Expansion of Accreting Main-sequence Stars during Rapid Mass Transfer
Authors: Mike Y. M. Lau, Ryosuke Hirai, Ilya Mandel, Christopher A. Tout
Figure caption: Density (top panel) and luminosity (bottom panel) profiles of an M 0 = 5 M ⊙ model accreting at a rate of ﹩\dot{M}=1.61\times {10}^{-3}\,{M}_{\odot }\,{\mathrm{yr}}^{-1}﹩ at different stages of its evolution. The line color changes from indigo to yellow from earlier to later models. Dashed lines indicate convective regions. The positions of the models on the H-R diagram are marked on the purple line in Figure 2(b). The vertical dashed line shows the initial stellar radius, R 0 = 2.6 R ⊙, and the diamond markers show R eff as defined by Equation (2).
Paper: Expansion of Accreting Main-sequence Stars during Rapid Mass Transfer
Authors: Mike Y. M. Lau, Ryosuke Hirai, Ilya Mandel, Christopher A. Tout
Figure caption: Mass–luminosity relation for rapidly accreting models during their expansion along the Hayashi line up to their maximum radii. Lines of the same color show models with the same initial masses but different accretion rates. The black line shows a power-law fit to models with larger initial masses.