adsabs/AstroCLIMB huggingface dataset:
Paper: Seven Years of Coordinated Chandra–NuSTAR Observations of SN 2014C Unfold the Extreme Mass-loss History of Its Stellar Progenitor
Authors: Daniel Brethauer, Raffaella Margutti, Dan Milisavljevic, Michael F. Bietenholz, Ryan Chornock, Deanne L. Coppejans, Fabio De Colle, Aprajita Hajela, Giacomo Terreran, Felipe Vargas, Lindsay DeMarchi, Chelsea Harris, Wynn V. Jacobson-Galán, Atish Kamble, Daniel Patnaude, Michael C. Stroh
Figure caption: Broadband (0.5–40 keV) X-ray spectrum of SN 2014C acquired with coordinated CXO (black filled circles) and NuSTAR (magenta squares) observations spanning from δ t = 396 to 2307 days since explosion. In each panel, a thick blue line marks the best-fitting absorbed bremsstrahlung model with best-fitting spectral parameters reported in Appendix B, Table 5, and shown in Figures 3 and 4. There is an excess of emission with respect to this model (Figures 1 and 2), which, following Margutti et al. (2017), we associate the excess of emission around 6.7 keV to a Kα line transition in highly ionized Fe atoms with one or two electrons remaining. The best-fitting parameters of the Gaussian excess are reported in Appendix B, Table 6, and the observed flux evolution of the Fe emission is shown in Figure 6.
Paper: Seven Years of Coordinated Chandra–NuSTAR Observations of SN 2014C Unfold the Extreme Mass-loss History of Its Stellar Progenitor
Authors: Daniel Brethauer, Raffaella Margutti, Dan Milisavljevic, Michael F. Bietenholz, Ryan Chornock, Deanne L. Coppejans, Fabio De Colle, Aprajita Hajela, Giacomo Terreran, Felipe Vargas, Lindsay DeMarchi, Chelsea Harris, Wynn V. Jacobson-Galán, Atish Kamble, Daniel Patnaude, Michael C. Stroh
Figure caption: Broadband X-ray spectral evolution of SN 2014C as captured by CXO and NuSTAR observations at δt = 1029 days (left panel) to emphasize the Gaussian excess of emission centered around 6.7 keV within the empty black box (right panel), which, following Margutti et al. (2017), we associate to a Kα line transition in highly ionized Fe atoms with one or two electrons remaining. Data have been rebinned to show detail. This figure follows the same color scheme as in Figure 1.
Paper: Seven Years of Coordinated Chandra–NuSTAR Observations of SN 2014C Unfold the Extreme Mass-loss History of Its Stellar Progenitor
Authors: Daniel Brethauer, Raffaella Margutti, Dan Milisavljevic, Michael F. Bietenholz, Ryan Chornock, Deanne L. Coppejans, Fabio De Colle, Aprajita Hajela, Giacomo Terreran, Felipe Vargas, Lindsay DeMarchi, Chelsea Harris, Wynn V. Jacobson-Galán, Atish Kamble, Daniel Patnaude, Michael C. Stroh
Figure caption: Evolution of intrinsic neutral hydrogen column density with time as revealed by our broadband CXO+NuSTAR spectral modeling. The first epoch lacks NuSTAR coverage, which leads to a lower limit on the NHint ≳ 4 × 1022 cm−2 (Margutti et al. 2017). A gray dashed line marks a t −1.4 evolution to guide the eye.
Paper: Seven Years of Coordinated Chandra–NuSTAR Observations of SN 2014C Unfold the Extreme Mass-loss History of Its Stellar Progenitor
Authors: Daniel Brethauer, Raffaella Margutti, Dan Milisavljevic, Michael F. Bietenholz, Ryan Chornock, Deanne L. Coppejans, Fabio De Colle, Aprajita Hajela, Giacomo Terreran, Felipe Vargas, Lindsay DeMarchi, Chelsea Harris, Wynn V. Jacobson-Galán, Atish Kamble, Daniel Patnaude, Michael C. Stroh
Figure caption: Temperature evolution with time as revealed by our broadband X-ray modeling. From the first CXO observation, Margutti et al. (2017) inferred T > 10 keV, which we plot here. The dashed gray line marks a t −0.5 power-law decay to guide the eye.
Paper: Seven Years of Coordinated Chandra–NuSTAR Observations of SN 2014C Unfold the Extreme Mass-loss History of Its Stellar Progenitor
Authors: Daniel Brethauer, Raffaella Margutti, Dan Milisavljevic, Michael F. Bietenholz, Ryan Chornock, Deanne L. Coppejans, Fabio De Colle, Aprajita Hajela, Giacomo Terreran, Felipe Vargas, Lindsay DeMarchi, Chelsea Harris, Wynn V. Jacobson-Galán, Atish Kamble, Daniel Patnaude, Michael C. Stroh
Figure caption: Evolution of 0.3–100 keV X-ray luminosity with time as revealed by our broadband spectral modeling. Very early Swift-XRT observations acquired at δ t = 7–20 days led to L  x  < 4.41 × 1039 erg s−1 (Margutti et al. 2017). A gray dashed line marks a ∝ t −1 decay to guide the eye.
Paper: Photometric Objects Around Cosmic Webs (PAC) Delineated in a Spectroscopic Survey. III. Accurate Measurement of Galaxy Stellar Mass Function with the Aid of Cosmological Redshift Surveys
Authors: Kun Xu, Y. P. Jing, Hongyu Gao
Figure caption: Comparing w p (blue) and PAC ﹩{\bar{n}}_{2}{w}_{{\rm{p}}}﹩ (red) measurements of the Full (DECaLS+BASS+MzLS) sample (dots) and DECaLS-only sample (triangles). The measurements are shown in the top panel, and the relative offsets of the Full sample from the DECaLS sample are shown in the bottom panel. The comparisons are for pop1 with 1010.8 M ⊙ and pop2 with 1011.4 M ⊙ at z  s  < 0.2. w p is divided by 5000 for better comparison.
Paper: Photometric Objects Around Cosmic Webs (PAC) Delineated in a Spectroscopic Survey. III. Accurate Measurement of Galaxy Stellar Mass Function with the Aid of Cosmological Redshift Surveys
Authors: Kun Xu, Y. P. Jing, Hongyu Gao
Figure caption: The same as Figure A1 but for LOWZ.
Paper: Photometric Objects Around Cosmic Webs (PAC) Delineated in a Spectroscopic Survey. III. Accurate Measurement of Galaxy Stellar Mass Function with the Aid of Cosmological Redshift Surveys
Authors: Kun Xu, Y. P. Jing, Hongyu Gao
Figure caption: The same as Figure A1 but for CMASS.
Paper: Collisional Growth Efficiency of Dust Aggregates and Its Independence of the Strength of Interparticle Rolling Friction
Authors: Sota Arakawa, Hidekazu Tanaka, Eiichiro Kokubo
Figure caption: Total energy dissipation due to particle interactions from the start to the end of the simulations. The total energy dissipation due to all particle interactions, E dis,tot, is given by E dis,tot ≡ E dis,r + E dis,s + E dis,t + E dis,c + E dis,v, where E dis,r, E dis,s, E dis,t, E dis,c, and E dis,v are the energy dissipations due to rolling friction, sliding friction, twisting friction, connection and disconnection of particles, and viscous drag force, respectively. Here we set ﹩{{B}_{\mathrm{off}}}^{2}=3/12﹩.
Paper: The ALMA Survey of 70 μm Dark High-mass Clumps in Early Stages (ASHES). VII. Chemistry of Embedded Dense Cores
Authors: Shanghuo Li, Patricio Sanhueza, Xing Lu, Chang Won Lee, Qizhou Zhang, Stefano Bovino, Giovanni Sabatini, Tie Liu, Kee-Tae Kim, Kaho Morii, Daniel Tafoya, Ken'ichi Tatematsu, Takeshi Sakai, Junzhi Wang, Fei Li, Andrea Silva, Natsuko Izumi, David Allingham
Figure caption: The column densities of each molecule plotted against each other. The black and red points represent the prestellar and protostellar cores, respectively.
Paper: Collisional Growth Efficiency of Dust Aggregates and Its Independence of the Strength of Interparticle Rolling Friction
Authors: Sota Arakawa, Hidekazu Tanaka, Eiichiro Kokubo
Figure caption: Collisional growth efficiency, f gro, for different settings of ξ crit, B off, and v col.
Paper: Collisional Growth Efficiency of Dust Aggregates and Its Independence of the Strength of Interparticle Rolling Friction
Authors: Sota Arakawa, Hidekazu Tanaka, Eiichiro Kokubo
Figure caption: Snapshots of the collisional outcomes. Here we set v col = 39.8  m s−1 and ﹩{{B}_{\mathrm{off}}}^{2}=6/12﹩. Panels (a)–(d) are the time series of snapshots for ξ crit = 0.2  nm, 0.8  nm, 3.2  nm, and 12.8  nm, respectively. The time interval for each snapshot is 0.40  μs.
Paper: Collisional Growth Efficiency of Dust Aggregates and Its Independence of the Strength of Interparticle Rolling Friction
Authors: Sota Arakawa, Hidekazu Tanaka, Eiichiro Kokubo
Figure caption: Dependence of E r,crit and E roll on ξ crit.
Paper: Collisional Growth Efficiency of Dust Aggregates and Its Independence of the Strength of Interparticle Rolling Friction
Authors: Sota Arakawa, Hidekazu Tanaka, Eiichiro Kokubo
Figure caption:  B off-weighted collisional growth efficiency (panel (a)) and collisional growth efficiency for oblique collisions (﹩{{B}_{\mathrm{off}}}^{2}=3/12﹩ for panel (b), ﹩{{B}_{\mathrm{off}}}^{2}=6/12﹩ for panel (c), and ﹩{{B}_{\mathrm{off}}}^{2}=9/12﹩ for panel (d)).
Paper: Solar-cycle-related Variation of Differential Rotation of the Chromosphere
Authors: Miao Wan, Peng-xin Gao
Figure caption: Synoptic image of Ca II K intensity at CR 1394 (1957 November December). The two white dashed lines indicate the latitudes of ±40°.
Paper: X-Ray Reverberation Mapping of Ark 564 Using Gaussian Process Regression
Authors: Collin Lewin, Erin Kara, Dan Wilkins, Guglielmo Mastroserio, Javier A. García, Rachel C. Zhang, William N. Alston, Riley Connors, Thomas Dauser, Andrew Fabian, Adam Ingram, Jiachen Jiang, Anne Lohfink, Matteo Lucchini, Christopher S. Reynolds, Francesco Tombesi, Michiel van der Klis, Jingyi Wang
Figure caption: (Left) Data-to-model ratios of the XMM-Newton (orange) and NuSTAR FPMA, FPMB (black, purple) flux spectra combined across observations when fit simultaneously with the time lags for each of our three models. (Right) The resulting fit residuals on the high-frequency time lags (0.2–0.9 mHz) for each instrument is shown in the right six panels. The inclusion of a single-temperature blackbody (middle) with zbbody dramatically improves the fit, but show residuals on a feature near 1 keV, motivating the inclusion of an additional Gaussian component (bottom), further improving the residuals on the reflection features. The model of the time lags does not change significantly, but struggles to fully replicate the feature near 1 keV.
Paper: X-Ray Reverberation Mapping of Ark 564 Using Gaussian Process Regression
Authors: Collin Lewin, Erin Kara, Dan Wilkins, Guglielmo Mastroserio, Javier A. García, Rachel C. Zhang, William N. Alston, Riley Connors, Thomas Dauser, Andrew Fabian, Adam Ingram, Jiachen Jiang, Anne Lohfink, Matteo Lucchini, Christopher S. Reynolds, Francesco Tombesi, Michiel van der Klis, Jingyi Wang
Figure caption: Lag-energy spectra (0.3–0.9 mHz) computed from the NuSTAR data using Gaussian processes to generate realizations that include data in the low-Earth orbit gaps (black) vs. using the immediately available, continuous chunks (orange). Both approaches give comparable results, but Gaussian processes result in slightly larger uncertainties.
Paper: X-Ray Reverberation Mapping of Ark 564 Using Gaussian Process Regression
Authors: Collin Lewin, Erin Kara, Dan Wilkins, Guglielmo Mastroserio, Javier A. García, Rachel C. Zhang, William N. Alston, Riley Connors, Thomas Dauser, Andrew Fabian, Adam Ingram, Jiachen Jiang, Anne Lohfink, Matteo Lucchini, Christopher S. Reynolds, Francesco Tombesi, Michiel van der Klis, Jingyi Wang
Figure caption: The XMM-Newton and NuSTAR flux spectra from 0.5−40 keV with the best-fit model (upper) and corresponding data-to-model ratio (lower). The total model (tbabs∗(zbbody+zgauss)+reltransDCp) is shown by a solid line, with model components tbabs∗zbbody (blackbody component to fit the soft excess), tbabs∗zgauss, and reltransDCp shown by dashed–dotted, dotted, and dashed lines, respectively.
Paper: X-Ray Reverberation Mapping of Ark 564 Using Gaussian Process Regression
Authors: Collin Lewin, Erin Kara, Dan Wilkins, Guglielmo Mastroserio, Javier A. García, Rachel C. Zhang, William N. Alston, Riley Connors, Thomas Dauser, Andrew Fabian, Adam Ingram, Jiachen Jiang, Anne Lohfink, Matteo Lucchini, Christopher S. Reynolds, Francesco Tombesi, Michiel van der Klis, Jingyi Wang
Figure caption: The new NuSTAR spectra (black) and XMM-Newton spectra before and after the release of the current calibration file, including the correction to the effective area (orange and purple, respectively) fit to a power law. Without the correction, the XMM-Newton spectra exceeds the NuSTAR spectra above roughly 7 keV by ∼20%. This discrepancy nearly halves with the effective area correction.
Paper: X-Ray Reverberation Mapping of Ark 564 Using Gaussian Process Regression
Authors: Collin Lewin, Erin Kara, Dan Wilkins, Guglielmo Mastroserio, Javier A. García, Rachel C. Zhang, William N. Alston, Riley Connors, Thomas Dauser, Andrew Fabian, Adam Ingram, Jiachen Jiang, Anne Lohfink, Matteo Lucchini, Christopher S. Reynolds, Francesco Tombesi, Michiel van der Klis, Jingyi Wang
Figure caption: Posterior distributions from the MCMC of fitting the time lags with the flux spectra. The plots on the diagonal show the histogram for each model parameter, dashed vertical lines corresponding to the median and 1σ from the median. The off-diagonal plots are projections of the 2D distributions between any two parameters, with contours of equal probability. An enlarged 1D mass posterior is shown in the upper right.
Paper: X-Ray Reverberation Mapping of Ark 564 Using Gaussian Process Regression
Authors: Collin Lewin, Erin Kara, Dan Wilkins, Guglielmo Mastroserio, Javier A. García, Rachel C. Zhang, William N. Alston, Riley Connors, Thomas Dauser, Andrew Fabian, Adam Ingram, Jiachen Jiang, Anne Lohfink, Matteo Lucchini, Christopher S. Reynolds, Francesco Tombesi, Michiel van der Klis, Jingyi Wang
Figure caption: Background-subtracted broadband NuSTAR FPMA+FPMB light curves (black; left axis) for the new 410 ks observation—with each point representing data averaged over single orbit—and two partially simultaneous XMM-Newton observations (orange; right axis) with an exposure totaling 230 ks in 400 s bins. The inlay shows the data for five NuSTAR orbits with less coarse binning, including the low-Earth orbit data gaps motivating the use of Gaussian process regression. The source is highly variable, with multiple flares occurring throughout the observations.
Paper: X-Ray Reverberation Mapping of Ark 564 Using Gaussian Process Regression
Authors: Collin Lewin, Erin Kara, Dan Wilkins, Guglielmo Mastroserio, Javier A. García, Rachel C. Zhang, William N. Alston, Riley Connors, Thomas Dauser, Andrew Fabian, Adam Ingram, Jiachen Jiang, Anne Lohfink, Matteo Lucchini, Christopher S. Reynolds, Francesco Tombesi, Michiel van der Klis, Jingyi Wang
Figure caption: Lag-energy spectra from each instrument in three frequency ranges (black), modeled with reltransDCp by fitting the flux spectra with the lag-energy spectra (orange). The XMM-Newton time lags are calculated using the entire 0.5–10 keV energy range, vs. 3–14 keV for the NuSTAR time lags to maximize signal to noise.
Paper: X-Ray Reverberation Mapping of Ark 564 Using Gaussian Process Regression
Authors: Collin Lewin, Erin Kara, Dan Wilkins, Guglielmo Mastroserio, Javier A. García, Rachel C. Zhang, William N. Alston, Riley Connors, Thomas Dauser, Andrew Fabian, Adam Ingram, Jiachen Jiang, Anne Lohfink, Matteo Lucchini, Christopher S. Reynolds, Francesco Tombesi, Michiel van der Klis, Jingyi Wang
Figure caption: An example of a single light-curve realization drawn from the trained Gaussian process posterior is shown in orange, with the prediction formed by averaging over 5000 samples shown in purple with a 1σ shaded region in this distribution. In practice, we do not average over the samples themselves as shown here (we wish to use the variability in each sample) in order to calculate the time lags, but instead average the Fourier products across realizations.
Paper: X-Ray Reverberation Mapping of Ark 564 Using Gaussian Process Regression
Authors: Collin Lewin, Erin Kara, Dan Wilkins, Guglielmo Mastroserio, Javier A. García, Rachel C. Zhang, William N. Alston, Riley Connors, Thomas Dauser, Andrew Fabian, Adam Ingram, Jiachen Jiang, Anne Lohfink, Matteo Lucchini, Christopher S. Reynolds, Francesco Tombesi, Michiel van der Klis, Jingyi Wang
Figure caption: NuSTAR spectra (black) from the new 410 ks observation and the XMM-Newton spectra from the first and second 115 ks observations (orange and purple, respectively) fit to a simple, steep (Γ  =  2.57) power law with Galactic absorption.
Paper: Power Anisotropy, Dispersion Signature and Turbulence Diffusion Region in the 3D Wavenumber Domain of Space Plasma Turbulence
Authors: Rong Lin, Jiansen He, Xingyu Zhu, Lei Zhang, Die Duan, Fouad Sahraoui, Daniel Verscharen
Figure caption: Time series of the MMS2 observations in GSE coordinates of (a) the magnetic field, (b) the electric field, (c, d) the velocities of the electrons and ions, where the wider background lines denote the measurements and the thinner lines are the resampled data, (e) the ion number density, (f, g) the temperature of the ions and electrons, (h) power spectra of the measured magnetic and electric fluctuations, and (i) power spectrum of the measured ion-velocity fluctuations together with the noise level estimated with the method by Gershman et al. (2018). During the time interval, the directions of the background magnetic field and bulk flow of particles stayed nearly stationary. The power of the electric field fluctuations is normalized by the Alfvén speed. A sliding Hamming window is applied to the time sequences before calculating the power spectral densities.
Paper: Evidence That Shocks Destroy Small PAH Molecules in Low-luminosity Active Galactic Nuclei
Authors: Lulu Zhang, Luis C. Ho, Aigen Li
Figure caption: The PAH band ratios 6.2 μm/7.7 μm and 11.3 μm/7.7 μm for AGN spaxels, color coded according to (a) the line ratio H2 S(0, 1, 2)/PAH 7.7 μm, which is an indicator of shock strength, and (b) the combination of H2 S(0, 1, 2)/PAH 7.7 μm × [Ne III]/[Ne II], which is an indicator of the combined effects of shocks and radiative effects.
Paper: Evidence That Shocks Destroy Small PAH Molecules in Low-luminosity Active Galactic Nuclei
Authors: Lulu Zhang, Luis C. Ho, Aigen Li
Figure caption: The PAH band ratios 6.2 μm/7.7 μm and 11.3 μm/7.7 μm for AGN spaxels that have measurements of the strength of nuclear activity, color coded according to the (a) bolometric luminosity (L bol) and (b) Eddington ratio (L bol/L Edd) of the AGN.
Paper: Evidence That Shocks Destroy Small PAH Molecules in Low-luminosity Active Galactic Nuclei
Authors: Lulu Zhang, Luis C. Ho, Aigen Li
Figure caption: Dependence of PAH deficit of AGN spaxels, defined as the offset between the observed integrated (5–20 μm) PAH luminosity and that predicted from the extinction-corrected FUV luminosity based on the L PAH–L FUV relation of SFG spaxels (Figure 6; Equation (1)) vs. (a) shock strength, H2 S(0, 1, 2)/PAH 7.7 μm, and (b) the combined effects of shocks and radiative excitation, H2 S(0, 1, 2)/PAH 7.7 μm × [Ne III]/[Ne II]. The points with a black dot pertain to the central-most spaxel of each AGN.
Paper: Evidence That Shocks Destroy Small PAH Molecules in Low-luminosity Active Galactic Nuclei
Authors: Lulu Zhang, Luis C. Ho, Aigen Li
Figure caption: Statistics of mid-IR diagnostic line ratios as measured in the central-most, inner (10″ × 10″) region compared to those measured in the remaining outer region. The line ratio H2 S(0, 1, 2)/PAH 7.7 μm is sensitive to shocks, while the combined diagnostic H2 S(0, 1, 2)/PAH 7.7 μm × [Ne III]/[Ne II] reflects the joint influence of shocks and radiative effects. This plot illustrates that these indicators are even more prominent in the inner region.
Paper: Evidence That Shocks Destroy Small PAH Molecules in Low-luminosity Active Galactic Nuclei
Authors: Lulu Zhang, Luis C. Ho, Aigen Li
Figure caption: Illustration of the PAH decomposition for (a) NGC 4736 and (b) NGC 3351. NGC 4736 exhibits stronger PAH emission at 11.3 μm and longer wavelengths than NGC 3351.
Paper: Lanthanide Features in Near-infrared Spectra of Kilonovae
Authors: Nanae Domoto, Masaomi Tanaka, Daiji Kato, Kyohei Kawaguchi, Kenta Hotokezaka, Shinya Wanajo
Figure caption: Left: final abundances of our L model as a function of mass number. Black circles show the r-process residual pattern (Prantzos et al. 2020), which are scaled to match those for the L model at A = 88. Right: abundances at t = 1.5 days as a function of atomic number. Abundances of an r-process-deficient star HD 122563 (diamonds, Honda et al. 2006; Ge from Cowan et al. 2005; Cd and Lu from Roederer et al. 2012) are also shown for comparison, and are scaled to match those for the L model at Z = 40.
Paper: Lanthanide Features in Near-infrared Spectra of Kilonovae
Authors: Nanae Domoto, Masaomi Tanaka, Daiji Kato, Kyohei Kawaguchi, Kenta Hotokezaka, Shinya Wanajo
Figure caption: Sobolev optical depth of bound–bound transitions for the L model calculated with the theoretical line list (Tanaka et al. 2020                       Z = 30–88, top) and those calculated with the hybrid line list (Z = 20–88, bottom, Section 2.3). The ions with large contributions are shown with colors. The left panels show the results with the density of ρ = 10−14 g cm−3 and the temperature of T = 5000 K at t = 1.5 days, while the right panels show those with ρ = 10−15 g cm−3 and T = 3000 K at t = 3.5 days.
Paper: Lanthanide Features in Near-infrared Spectra of Kilonovae
Authors: Nanae Domoto, Masaomi Tanaka, Daiji Kato, Kyohei Kawaguchi, Kenta Hotokezaka, Shinya Wanajo
Figure caption: Mean values of log gf (left) and of lower energies of transitions (right) for all the lines of singly ionized ions as a function of atomic number. Colors at the top show the valence shells with the orbital angular momenta l for singly ionized ions. Red circles indicate the elements that produce strong transitions in our analysis (see the text).
Paper: Lanthanide Features in Near-infrared Spectra of Kilonovae
Authors: Nanae Domoto, Masaomi Tanaka, Daiji Kato, Kyohei Kawaguchi, Kenta Hotokezaka, Shinya Wanajo
Figure caption: The number of lines (orange) and mean value of log gf (green) for singly ionized ions as a function of complexity.
Paper: Lanthanide Features in Near-infrared Spectra of Kilonovae
Authors: Nanae Domoto, Masaomi Tanaka, Daiji Kato, Kyohei Kawaguchi, Kenta Hotokezaka, Shinya Wanajo
Figure caption: Same as Figure 12, but for Ce III.
Paper: Lanthanide Features in Near-infrared Spectra of Kilonovae
Authors: Nanae Domoto, Masaomi Tanaka, Daiji Kato, Kyohei Kawaguchi, Kenta Hotokezaka, Shinya Wanajo
Figure caption: Same as Figure 12, but for Zr I. Kurucz’s atomic data are used instead of the VALD database for comparison in the right panel. The energy levels of 4d 25s5p above 4 eV for the HULLAC results are not shown and not used for the calibration because of strong mixing with high-lying levels of other configurations.
Paper: Lanthanide Features in Near-infrared Spectra of Kilonovae
Authors: Nanae Domoto, Masaomi Tanaka, Daiji Kato, Kyohei Kawaguchi, Kenta Hotokezaka, Shinya Wanajo
Figure caption: Same as Figure 12, but for La III.
Paper: Lanthanide Features in Near-infrared Spectra of Kilonovae
Authors: Nanae Domoto, Masaomi Tanaka, Daiji Kato, Kyohei Kawaguchi, Kenta Hotokezaka, Shinya Wanajo
Figure caption: Same as Figure 12, but for Zr II. Kurucz’s atomic data are used instead of the VALD database for comparison in the right panel.
Paper: Lanthanide Features in Near-infrared Spectra of Kilonovae
Authors: Nanae Domoto, Masaomi Tanaka, Daiji Kato, Kyohei Kawaguchi, Kenta Hotokezaka, Shinya Wanajo
Figure caption: Same as Figure 12, but for Ba II.
Paper: Lanthanide Features in Near-infrared Spectra of Kilonovae
Authors: Nanae Domoto, Masaomi Tanaka, Daiji Kato, Kyohei Kawaguchi, Kenta Hotokezaka, Shinya Wanajo
Figure caption: Same as Figure 12, but for Y II.
Paper: Determining the Core Structure and Nuclear Equation of State of Rotating Core-collapse Supernovae with Gravitational Waves by Convolutional Neural Networks
Authors: Yang-Sheng Chao, 仰生 趙, Chen-Zhi Su, 晨知 蘇, Ting-Yuan Chen, 莛元 陳, Daw-Wei Wang, 道維 王, Kuo-Chuan Pan, 國全 潘
Figure caption: Four different grouping types of EoSs. Each column indicates a grouping type, where EoS names with the same color are considered to be the same group. The predicted accuracy in the last line shows how well our CNN model could classify these groups for each type.