adsabs/AstroCLIMB huggingface dataset:
Paper: Perfecting Our Set of Spectrophotometric Standard DA White Dwarfs
Authors: Annalisa Calamida, Thomas Matheson, Edward W. Olszewski, Abhijit Saha, Tim Axelrod, Clare Shanahan, Jay Holberg, Sean Points, Gautham Narayan, Konstantin Malanchev, Ryan Ridden-Harper, Nicola Gentile-Fusillo, Roberto Raddi, Ralph Bohlin, Armin Rest, Ivan Hubeny, Susana Deustua, John Mackenty, Elena Sabbi, Christopher W. Stubbs
Figure caption: Finding charts for 7 candidate DAWDs based on WFC3 drizzled F160W image cutouts centered on the star and covering an FoV of 26″ × 26″. Star Gaia DR3 magnitude and coordinates are labeled on the image. The yellow solid arrow points at the DAWD and the yellow line indicates 5″ on the image. The north and east directions are also shown.
Paper: Perfecting Our Set of Spectrophotometric Standard DA White Dwarfs
Authors: Annalisa Calamida, Thomas Matheson, Edward W. Olszewski, Abhijit Saha, Tim Axelrod, Clare Shanahan, Jay Holberg, Sean Points, Gautham Narayan, Konstantin Malanchev, Ryan Ridden-Harper, Nicola Gentile-Fusillo, Roberto Raddi, Ralph Bohlin, Armin Rest, Ivan Hubeny, Susana Deustua, John Mackenty, Elena Sabbi, Christopher W. Stubbs
Figure caption: Same as Figure 33 but for star WDFS1206-27.
Paper: Perfecting Our Set of Spectrophotometric Standard DA White Dwarfs
Authors: Annalisa Calamida, Thomas Matheson, Edward W. Olszewski, Abhijit Saha, Tim Axelrod, Clare Shanahan, Jay Holberg, Sean Points, Gautham Narayan, Konstantin Malanchev, Ryan Ridden-Harper, Nicola Gentile-Fusillo, Roberto Raddi, Ralph Bohlin, Armin Rest, Ivan Hubeny, Susana Deustua, John Mackenty, Elena Sabbi, Christopher W. Stubbs
Figure caption: Same as Figure 33 but for star WDFS2317-29.
Paper: Perfecting Our Set of Spectrophotometric Standard DA White Dwarfs
Authors: Annalisa Calamida, Thomas Matheson, Edward W. Olszewski, Abhijit Saha, Tim Axelrod, Clare Shanahan, Jay Holberg, Sean Points, Gautham Narayan, Konstantin Malanchev, Ryan Ridden-Harper, Nicola Gentile-Fusillo, Roberto Raddi, Ralph Bohlin, Armin Rest, Ivan Hubeny, Susana Deustua, John Mackenty, Elena Sabbi, Christopher W. Stubbs
Figure caption: Same as Figure 33 but for star WDFS1055-36.
Paper: Perfecting Our Set of Spectrophotometric Standard DA White Dwarfs
Authors: Annalisa Calamida, Thomas Matheson, Edward W. Olszewski, Abhijit Saha, Tim Axelrod, Clare Shanahan, Jay Holberg, Sean Points, Gautham Narayan, Konstantin Malanchev, Ryan Ridden-Harper, Nicola Gentile-Fusillo, Roberto Raddi, Ralph Bohlin, Armin Rest, Ivan Hubeny, Susana Deustua, John Mackenty, Elena Sabbi, Christopher W. Stubbs
Figure caption: Same as Figure 33 but for star WDFS1434-28.
Paper: Perfecting Our Set of Spectrophotometric Standard DA White Dwarfs
Authors: Annalisa Calamida, Thomas Matheson, Edward W. Olszewski, Abhijit Saha, Tim Axelrod, Clare Shanahan, Jay Holberg, Sean Points, Gautham Narayan, Konstantin Malanchev, Ryan Ridden-Harper, Nicola Gentile-Fusillo, Roberto Raddi, Ralph Bohlin, Armin Rest, Ivan Hubeny, Susana Deustua, John Mackenty, Elena Sabbi, Christopher W. Stubbs
Figure caption: Same as Figure 33 but for star WDFS1535-77.
Paper: Perfecting Our Set of Spectrophotometric Standard DA White Dwarfs
Authors: Annalisa Calamida, Thomas Matheson, Edward W. Olszewski, Abhijit Saha, Tim Axelrod, Clare Shanahan, Jay Holberg, Sean Points, Gautham Narayan, Konstantin Malanchev, Ryan Ridden-Harper, Nicola Gentile-Fusillo, Roberto Raddi, Ralph Bohlin, Armin Rest, Ivan Hubeny, Susana Deustua, John Mackenty, Elena Sabbi, Christopher W. Stubbs
Figure caption: Same as Figure 33 but for star WDFS1930-52.
Paper: Perfecting Our Set of Spectrophotometric Standard DA White Dwarfs
Authors: Annalisa Calamida, Thomas Matheson, Edward W. Olszewski, Abhijit Saha, Tim Axelrod, Clare Shanahan, Jay Holberg, Sean Points, Gautham Narayan, Konstantin Malanchev, Ryan Ridden-Harper, Nicola Gentile-Fusillo, Roberto Raddi, Ralph Bohlin, Armin Rest, Ivan Hubeny, Susana Deustua, John Mackenty, Elena Sabbi, Christopher W. Stubbs
Figure caption: Same as Figure 33 but for star WDFS1837-70.
Paper: Quijote-PNG: Quasi-maximum Likelihood Estimation of Primordial Non-Gaussianity in the Nonlinear Dark Matter Density Field
Authors: Gabriel Jung, Dionysios Karagiannis, Michele Liguori, Marco Baldi, William R. Coulton, Drew Jamieson, Licia Verde, Francisco Villaescusa-Navarro, Benjamin D. Wandelt
Figure caption: The stability of Fisher constraints under variations of the number of simulations. In the left panels, we vary the number of simulations used to calculate numerical derivatives, while on the right panels we vary the number of simulations used to measure covariances. All error bars are normalized by the result obtained using the full data set, see Table 7 for actual values. The top, middle, and bottom rows correspond respectively to power spectrum only, bispectrum only, and combined power spectrum and bispectrum analyses. Each column corresponds to the constraints on one parameter, and they are all analyzed jointly. We consider five different numbers of simulations to compute derivatives (from 25–500) and covariances (from 500–8000), each number corresponding to its own color and marker. We include scales down to ﹩{k}_{\max }=0.5\,h\,{\mathrm{Mpc}}^{-1}﹩.
Paper: Quijote-PNG: Quasi-maximum Likelihood Estimation of Primordial Non-Gaussianity in the Nonlinear Dark Matter Density Field
Authors: Gabriel Jung, Dionysios Karagiannis, Michele Liguori, Marco Baldi, William R. Coulton, Drew Jamieson, Licia Verde, Francisco Villaescusa-Navarro, Benjamin D. Wandelt
Figure caption: The correlation matrix of the power spectrum P(k) and modal bispectrum coefficients β  n  of the QUIJOTE simulations for different ﹩{k}_{\max }﹩. We include a similar number of bispectrum modes in each case, using polynomial basis functions up to a degree of 12.
Paper: Quijote-PNG: Quasi-maximum Likelihood Estimation of Primordial Non-Gaussianity in the Nonlinear Dark Matter Density Field
Authors: Gabriel Jung, Dionysios Karagiannis, Michele Liguori, Marco Baldi, William R. Coulton, Drew Jamieson, Licia Verde, Francisco Villaescusa-Navarro, Benjamin D. Wandelt
Figure caption: The convergence of constraints on cosmological parameters and PNG as a function of the number of modes used for the modal bispectrum estimation. The top row corresponds to the bispectrum-only case, while the bottom row also includes the power spectrum information. Note the difference in scale between the top and bottom rows. For each parameter, error bars are divided by the corresponding minimum; see Table 2 for the actual values. From left to right, each data point corresponds to include polynomials of 1 degree higher in the modal basis.
Paper: Quijote-PNG: Quasi-maximum Likelihood Estimation of Primordial Non-Gaussianity in the Nonlinear Dark Matter Density Field
Authors: Gabriel Jung, Dionysios Karagiannis, Michele Liguori, Marco Baldi, William R. Coulton, Drew Jamieson, Licia Verde, Francisco Villaescusa-Navarro, Benjamin D. Wandelt
Figure caption: Impact of PNG on the matter bispectrum at z = 1 (ratio NG/G, averaged from 500 N-body simulations). We show the local (top rows), equilateral (middle rows), and orthogonal (bottom rows) shapes.
Paper: Quijote-PNG: Quasi-maximum Likelihood Estimation of Primordial Non-Gaussianity in the Nonlinear Dark Matter Density Field
Authors: Gabriel Jung, Dionysios Karagiannis, Michele Liguori, Marco Baldi, William R. Coulton, Drew Jamieson, Licia Verde, Francisco Villaescusa-Navarro, Benjamin D. Wandelt
Figure caption: The unbiasedness of the quasi-maximum likelihood estimator (Equation (13)), when measuring cosmological parameters and PNG amplitudes. We use the power spectrum and the bispectrum jointly, up to ﹩{k}_{\max }=0.5\,h\,{\mathrm{Mpc}}^{-1}﹩. Each individual column corresponds to a given parameter (cosmological or PNG). To be exact, we show the difference between the expected and measured values, divided by the respective Fisher error bar. Each panel corresponds to a different cosmology of the data samples (i.e., one with Gaussian initial conditions and the three types of PNG). For each of them, we analyze five independent data sets of 100 realizations, each being indicated by its own color and marker.
Paper: Quijote-PNG: Quasi-maximum Likelihood Estimation of Primordial Non-Gaussianity in the Nonlinear Dark Matter Density Field
Authors: Gabriel Jung, Dionysios Karagiannis, Michele Liguori, Marco Baldi, William R. Coulton, Drew Jamieson, Licia Verde, Francisco Villaescusa-Navarro, Benjamin D. Wandelt
Figure caption: The difference between the modal bispectrum coefficients of the QUIJOTE N-body simulations (average from 8000 simulations at fiducial cosmology) and their theoretical prediction computed at the tree level, divided by their respective standard deviation. Note the different vertical scales of each plot.
Paper: Quijote-PNG: Quasi-maximum Likelihood Estimation of Primordial Non-Gaussianity in the Nonlinear Dark Matter Density Field
Authors: Gabriel Jung, Dionysios Karagiannis, Michele Liguori, Marco Baldi, William R. Coulton, Drew Jamieson, Licia Verde, Francisco Villaescusa-Navarro, Benjamin D. Wandelt
Figure caption: Impact of PNG on the matter power spectrum at z = 1 (ratio NG/G, averaged from 500 N-body simulations). We show the local (green), equilateral (orange), and orthogonal (purple) shapes. Solid and dashed lines correspond, respectively, to positive and negative f NL values (±100).
Paper: Quijote-PNG: Quasi-maximum Likelihood Estimation of Primordial Non-Gaussianity in the Nonlinear Dark Matter Density Field
Authors: Gabriel Jung, Dionysios Karagiannis, Michele Liguori, Marco Baldi, William R. Coulton, Drew Jamieson, Licia Verde, Francisco Villaescusa-Navarro, Benjamin D. Wandelt
Figure caption: Impact of PNG on the modal bispectrum coefficients (ratio NG/G, averaged from 500 N-body simulations) at z = 1. The vertical black lines show the standard errors for 500 Gaussian fiducial simulations and for most modes these are unobservably small.
Paper: Quijote-PNG: Quasi-maximum Likelihood Estimation of Primordial Non-Gaussianity in the Nonlinear Dark Matter Density Field
Authors: Gabriel Jung, Dionysios Karagiannis, Michele Liguori, Marco Baldi, William R. Coulton, Drew Jamieson, Licia Verde, Francisco Villaescusa-Navarro, Benjamin D. Wandelt
Figure caption: Joint constraints on cosmological parameters and PNG from the power spectrum and the modal bispectrum for different ﹩{k}_{\max }﹩ at z = 1.
Paper: The Quantitative Relation of the Time Profiles of Intensities in the Well-connected Solar Energetic Particle Events
Authors: Yang Wang, Dan Lyu, Xinghui Wu, Gang Qin
Figure caption: The four panels from top to bottom represent the distribution of duration time of the rising phase in SEP intensities for 13–16, 20–25, 32–40, and 40–64 MeV protons, respectively. The x-axis indicates the duration time of the rising phase in SEP intensities, and the y-axis indicates the number of energetic proton events corresponding to each time interval.
Paper: The Quantitative Relation of the Time Profiles of Intensities in the Well-connected Solar Energetic Particle Events
Authors: Yang Wang, Dan Lyu, Xinghui Wu, Gang Qin
Figure caption: The fitting of parameters in energetic proton intensities. The x-axis represents parameter b and the y-axis represents parameter c. The four panels from top to bottom represent the parameters of the intensities of 13–16 MeV, 20–25 MeV, 32–40 MeV, and 40–64 MeV protons, respectively. The dots represent data, and dotted lines represent the fitting results.
Paper: The Quantitative Relation of the Time Profiles of Intensities in the Well-connected Solar Energetic Particle Events
Authors: Yang Wang, Dan Lyu, Xinghui Wu, Gang Qin
Figure caption: From top to bottom: the SEP intensities (panels 1 to 4), magnetic field intensity (panel 5), and solar wind speed (panel 6) in 2011 November 3 event. OMNI data are used instead of the plasma data observed by SOHO to improve the statistics.
Paper: Evolution, Structure, and Topology of Self-generated Turbulent Reconnection Layers
Authors: Raheem Beg, Alexander J. B. Russell, Gunnar Hornig
Figure caption: Comparison of different measures of the characteristic reconnection layer thickness 〈δ y〉. The right panel compares 〈δ y〉 (left axis) with the global reconnection rate V rec (right axis) over time. The left panel is a close-up of the 〈δ y〉 curves in the right panel over 〈δ y〉 ∈ [0, 0.012]. Dark red: current density strength j; orange: vorticity strength ω; yellow: outflow velocity ∣v  x ∣; light blue: energy of the magnetic field fluctuations ﹩{\tilde{E}}_{m};﹩ dark blue: energy of the kinetic fluctuations ﹩{\tilde{E}}_{k};﹩ pink (dotted): unsigned turbulent electromotive force (EMF) ﹩\left|-{\left(\mathop{{\boldsymbol{v}}}\limits^{\sim }\times \mathop{{\boldsymbol{B}}}\limits^{\sim }\right)}_{z}\right|;﹩ purple (dotted): positive turbulent EMF ﹩\max \left\{-{\left(\mathop{{\boldsymbol{v}}}\limits^{\sim }\times \mathop{{\boldsymbol{B}}}\limits^{\sim }\right)}_{z},0\right\};﹩ dark green: squashing factor ﹩{Q}_{{z}_{0}}^{100}﹩ for z 0 = −0.5; turquoise: Poincaré section count ﹩{{ \mathcal N }}_{S}﹩ for n = 2000 iterations; and black (dashed): global reconnection rate V rec. The vertical dotted lines mark times of interest: (b) 2.5D nonlinear tearing instability onset (t = 0.4); (c) turbulent reconnection onset (t = 1.0); (e) SGTR onset (t = 2.4); and (f) “pure” SGTR onset (t = 3.0).
Paper: Evolution, Structure, and Topology of Self-generated Turbulent Reconnection Layers
Authors: Raheem Beg, Alexander J. B. Russell, Gunnar Hornig
Figure caption: Normalized mean profiles in the y-direction across the reconnection layer, over the SGTR phase t ∈ [2.4, 5.0] (after label (e) in Figure 2). Dark red (dashed): current density strength j; orange: vorticity strength ω; yellow (dashed): outflow velocity absolute value ∣v  x ∣; light blue: energy of the magnetic field fluctuations ﹩{\mathop{E}\limits^{\sim }}_{m};﹩ dark blue (dashed): energy of the kinetic fluctuations ﹩{\mathop{E}\limits^{\sim }}_{k};﹩ pink: turbulent EMF ﹩-{\left(\mathop{{\boldsymbol{v}}}\limits^{\sim }\times \mathop{{\boldsymbol{B}}}\limits^{\sim }\right)}_{z};﹩ dark green (dashed): squashing factor ﹩{Q}_{{z}_{0}}^{100}﹩ for z 0 = −0.5; and turquoise: Poincaré section count ﹩{{ \mathcal N }}_{S}﹩ for n = 2000 iterations.
Paper: Evolution, Structure, and Topology of Self-generated Turbulent Reconnection Layers
Authors: Raheem Beg, Alexander J. B. Russell, Gunnar Hornig
Figure caption: Poincaré sections of the field line mapping ﹩{F}_{{z}_{0}}^{n}﹩ for all iterations up to n = 2000 at the bottom boundary z 0 = −0.5 for two selected times during the dynamic transition phase t = 1.0−2.4 (labels (c)–(e) in Figure 2). The multicolored dots, seeded over x ∈ [−0.42, 0.42] at y = 0.0, spread over the RCV that is topologically identified with the reconnection layer; points with the same color correspond to the same field line. This RCV rapidly expands after the turbulent reconnection onset t = 1.0 (left panel) and becomes (almost) fully stochastic by t = 1.8 (right panel). The black dots, seeded within the upper and lower flux ropes, lie on simple contours of laminar flux surfaces.
Paper: Evolution, Structure, and Topology of Self-generated Turbulent Reconnection Layers
Authors: Raheem Beg, Alexander J. B. Russell, Gunnar Hornig
Figure caption: Mean profiles of the fluctuation variables in the y-direction across the reconnection layer, over the SGTR phase t ∈ [2.4, 5.0] (after label (e) in Figure 2). Pink: turbulent EMF ﹩-{\left(\mathop{{\boldsymbol{v}}}\limits^{\sim }\times \mathop{{\boldsymbol{B}}}\limits^{\sim }\right)}_{z};﹩ light blue: energy of the magnetic field fluctuations ﹩{\mathop{E}\limits^{\sim }}_{m};﹩ dark blue (dashed): energy of the kinetic fluctuations ﹩{\mathop{E}\limits^{\sim }}_{k};﹩ and gray (dotted): turbulent energy fluctuation ratio ﹩\langle {\mathop{E}\limits^{\sim }}_{m}\rangle /\langle {\mathop{E}\limits^{\sim }}_{k}\rangle ﹩ (right axis).
Paper: Evolution, Structure, and Topology of Self-generated Turbulent Reconnection Layers
Authors: Raheem Beg, Alexander J. B. Russell, Gunnar Hornig
Figure caption: The squashing factor ﹩{Q}_{{z}_{0}}^{1}﹩ with z 0 = −0.5 at t = 4.0. The left panel is plotted at the bottom boundary z = −0.5. The right panel is plotted at the midplane z = 0.0, assuming each field line connecting (x 0, y 0) to ﹩{F}_{{z}_{0}}^{1}({x}_{0},{y}_{0})﹩ is identified with value ﹩{Q}_{{z}_{0}}^{1}﹩.
Paper: Evolution, Structure, and Topology of Self-generated Turbulent Reconnection Layers
Authors: Raheem Beg, Alexander J. B. Russell, Gunnar Hornig
Figure caption: Comparison plots of the squashing factor ﹩{Q}_{{z}_{0}}^{1}﹩ with z 0 = −0.5 and the RCV boundaries at z = 0.0 over time. The bottom panel is a close-up of the reconnection layer at t = 2.4. The RCV boundaries are approximated by contours of the Poincaré section count ﹩{{ \mathcal N }}_{S}=0.5﹩ for n = 2000 iterations (white). The interior contours of the RCV coincide with the stochastic separatrices or laminar flux rope boundaries, whereas ﹩{Q}_{{z}_{0}}^{1}﹩ highlights the flux rope structures within the reconnection layer.
Paper: Evolution, Structure, and Topology of Self-generated Turbulent Reconnection Layers
Authors: Raheem Beg, Alexander J. B. Russell, Gunnar Hornig
Figure caption: Close-ups of the color map ﹩{C}_{{z}_{0}}^{1}﹩ at the bottom boundary z 0 = −0.5 during the 3D kink instability of the CFR. Prior to the turbulent reconnection onset t = 1.0 (label (c) in Figure 2), the CFR is stable and has a cat-eye cross section with an elliptical core. The top-left panel at t = 1.0 also picks up the smaller flux rope to the left of the CFR, which accelerates to the left and soon exits the close-up window. After t = 1.2, the CFR axis moves to the left, and the cross section becomes increasingly deformed with a growing outer structure. By t = 1.5 (label (d) in Figure 2), the CFR breaks down; the axis either disappears within the stochastic field or it can no longer be detected with the color map.
Paper: Evolution, Structure, and Topology of Self-generated Turbulent Reconnection Layers
Authors: Raheem Beg, Alexander J. B. Russell, Gunnar Hornig
Figure caption: Evolution of the CFR axis  x  axis on various plane projections over t = 1.0−1.4. The 3D kink instability occurs at t = 1.0 (label (c) in Figure 2). Solid curves represent the CFR axis, and the dotted horizontal lines or circles denote the center of mass  x  center of the CFR axis. The CFR evolves from a straight flux rope prior to t = 1.0 to a fully 3D helical kink, which is asymmetric and weakly nonlinear. The helix rapidly grows in amplitude after t = 1.2 with dominant wavenumber k  z /(2π) = 7 while moving to the left on the x-y plane. At t = 1.5 onward (label (d) in Figure 2), the axis cannot be detected.
Paper: Evolution, Structure, and Topology of Self-generated Turbulent Reconnection Layers
Authors: Raheem Beg, Alexander J. B. Russell, Gunnar Hornig
Figure caption: Two-dimensional slices of variables highlighting the stochastic layer, corresponding with the outer thickness scale, at t = 2.5. The top and bottom panels of each subfigure are slices at z = −0.5 and x = 0.0, respectively. Subfigure (a): squashing factor ﹩{Q}_{{z}_{0}}^{100}﹩ with z 0 = −0.5 approximated over 3D space; the stochastic separatrices are estimated using contours ﹩{Q}_{{z}_{0}}^{100}\,=\,5\times {10}^{6}﹩ (pink). Subfigure (b): Poincaré section count ﹩{{ \mathcal N }}_{S}﹩ for n = 2000 iterations; contours of ﹩{{ \mathcal N }}_{S}=0.5﹩ (black) approximate the boundary of the RCV.
Paper: Binary Evolution and Blue Stragglers in Different Regions of the Color–Magnitude Diagrams of Globular Clusters with Different Ages
Authors: Dengkai Jiang
Figure caption: Similar to Figure 7 but compared with the number distribution of the theoretical BSs in the simulations with different initial mass-ratio distributions. The left, middle, and right panels present the simulations with a constant mass-ratio distribution (set 1), an uncorrelated distribution (set 2), and a rising mass-ratio distribution (set 3), respectively. The red and blue points shows the BSs observed along the red and blue sequences by Dalessandro et al. (2013). The theoretical fractions (f) and the observed fraction (f obs) for the BSs below the ZAMS+0.75 are shown in the figure.
Paper: Binary Evolution and Blue Stragglers in Different Regions of the Color–Magnitude Diagrams of Globular Clusters with Different Ages
Authors: Dengkai Jiang
Figure caption: Comparison of the two kinds of BS binaries with the observations of NGC 362. Gray circles and crosses show the theoretical locations of the MT and post-MT BS binaries at 11.5 Gyr, respectively. Black dashed–dotted, black dotted, and gray solid lines show the ZAMS, ZAMS+0.75, and 11.5 Gyr isochrone, respectively. The red and blue points shows the BSs observed along the red and blue sequences by Dalessandro et al. (2013). The observed samples have been transferred into the absolute plane by comparing the locations of the theoretical and observed MSTO (gray solid and black dashed lines).
Paper: Binary Evolution and Blue Stragglers in Different Regions of the Color–Magnitude Diagrams of Globular Clusters with Different Ages
Authors: Dengkai Jiang
Figure caption: Similar to Figure 4 but compared with theoretical locations of single BSs from the contact (green open stars) and unstable MT (green plus signs) merger channels.
Paper: Binary Evolution and Blue Stragglers in Different Regions of the Color–Magnitude Diagrams of Globular Clusters with Different Ages
Authors: Dengkai Jiang
Figure caption: Comparison of the observed CMD of NGC 362 with the theoretical BS distributions of eight subsamples. These subsamples are randomly extracted from Figure 7, and the total number of BSs for each subsample is the same as for the observed sample. The theoretical fractions (f) for the BSs below the ZAMS+0.75 are shown in each figure. The red and blue points shows the BSs observed along the red and blue sequences by Dalessandro et al. (2013).
Paper: Preemergence Signatures of Horizontal Divergent Flows in Solar Active Regions
Authors: T. Rees-Crockford, C. J. Nelson, M. Mathioudakis
Figure caption: Location of each AR analyzed here during the studied time period. The color, line style, and marker corresponding to each AR are included in the legend on the right-hand side.
Paper: Binary Evolution and Blue Stragglers in Different Regions of the Color–Magnitude Diagrams of Globular Clusters with Different Ages
Authors: Dengkai Jiang
Figure caption: Locations of the two kinds of unresolved BS binaries with their masses (shown by colors) at 10 Gyr. The upper panels show the unresolved MT BS binaries, while the lower panels show the unresolved post-MT BS binaries. The colors in the left, middle, and right panels represent the total masses of the binaries, BS components, and companions, respectively. Black dashed–dotted, black dotted, and gray solid lines show the ZAMS, ZAMS+0.75, and 10 Gyr isochrone, respectively. For comparison, the locations of two kinds of unresolved BS binaries are also shown in these panels as gray points.
Paper: Binary Evolution and Blue Stragglers in Different Regions of the Color–Magnitude Diagrams of Globular Clusters with Different Ages
Authors: Dengkai Jiang
Figure caption: Distributions of the masses for the two kinds of BS binaries at 11.5 Gyr. The left, middle, and right panels show the distribution of the total masses of the binaries, the BS components, and the companions, respectively. Red dashed–dotted and blue solid lines represent the MT and post-MT BS binaries, respectively. The theoretical numbers have been normalized by the total number of MT BS and post-MT BS binaries.
Paper: Binary Evolution and Blue Stragglers in Different Regions of the Color–Magnitude Diagrams of Globular Clusters with Different Ages
Authors: Dengkai Jiang
Figure caption: Distributions of the formation times of BSs in the MT and post-MT BS binaries at 11.5 Gyr. Red dashed–dotted and blue solid lines represent the MT and post-MT BS binaries, respectively. The theoretical numbers have been normalized by the total number of MT and post-MT BS binaries.