adsabs/AstroCLIMB huggingface dataset:
Paper: Predicting the Dominant Formation Mechanism of Multiplanetary Systems
Authors: Cheyanne Shariat, Yasuhiro Hasegawa, Bradley M. S. Hansen, Tze Yeung Mathew Yu, Renyu Hu
Figure caption: The mass concentration as a function of the orbital spacing for the simulated in situ (circle) and migration (triangle) systems (left) as compared to observed Kepler systems (right). The color bar represents the multiplicity of the system. On the left, biased simulation data show a power-law relationship between S  c  and S  s , and its slope is likely to be a function of multiplicity, especially for the in situ systems. On the right, the distributions of biased simulation data are denoted by the shaded regions. The Kepler observed systems are shown as the circles. The numbered squares display the SMs for 13 observed multiplanetary systems that host at least one (or more) planet(s) inside the habitable zone. They are (1) GJ 667C, (2) Trappist-1, (3) Teegarden’s Star, (4) GJ 1002, (5) Kepler-186, (6) GJ 1061, (7) Proxima Centauri, (8) K2-72, (9) GJ 273, (10) TOI-700, (11) Kepler-62, (12) LP 890-9, and (13) LHS 1140. See Appendix E for further details on these habitable planetary systems.
Paper: Predicting the Dominant Formation Mechanism of Multiplanetary Systems
Authors: Cheyanne Shariat, Yasuhiro Hasegawa, Bradley M. S. Hansen, Tze Yeung Mathew Yu, Renyu Hu
Figure caption: The CDFs of the Chambers (2001) SMs for “in situ” and “migration” simulations, before and after biasing the data. The raw migration data (black) and raw in situ data (blue) are compared to the biased migration data (dashed black) and the biased in situ data (dashed red). For the biased data, we require that the number of planets observed in the system is at least 2, making it a multiplanetary system. For the in situ data, we split it by the minimum number of observed planets, namely, three and four planets, which are shown in orange and green, respectively. The red (blue) shaded regions correspond to the ranges derived from analytic methods in Section 2.3 and are consistent with the migration (in situ) formation scenario. The artificial migration data are plotted by the dashed purple line, which shows some deviation from our analytical prediction at low S  c , while such deviation is not seen for S  s . For comparison purposes, the SMs of the Kepler data are also plotted (thick light-blue line).
Paper: Predicting the Dominant Formation Mechanism of Multiplanetary Systems
Authors: Cheyanne Shariat, Yasuhiro Hasegawa, Bradley M. S. Hansen, Tze Yeung Mathew Yu, Renyu Hu
Figure caption: The cumulative distributions of the mass concentration (S  c ;  left column) and orbital spacing (S  s ;  right column) of the biased simulation data compared to the observed Kepler sample, which are both split into two subgroups. The dotted blue lines are the biased in situ simulated systems, and the dashed blue lines are in situ systems selected for more systems with multiplicities greater than 3. The dotted red lines are the distributions of the biased migration simulation data, and the dashed red lines are the artificial migration systems generated to include higher multiplicities (see Section 3.4 for details). We compare this to the observed Kepler systems with different cutoffs. We split the observed systems based on those with S  s  < 30 (orange) and those with S  s  > 30 (light blue). For the observed distributions, we include shaded regions that represent Poisson error bars for each bin.
Paper: Predicting the Dominant Formation Mechanism of Multiplanetary Systems
Authors: Cheyanne Shariat, Yasuhiro Hasegawa, Bradley M. S. Hansen, Tze Yeung Mathew Yu, Renyu Hu
Figure caption: The planetary architectures of the simulated in situ multiplanetary systems before and after biasing. The planets outlined in black represent the observed planets after the simulations were biased using EPOS. All planets in a given row represent the architecture of the inherent system as a result of the in situ simulations. The sizes of the planets are scaled by the mass, and the horizontal axis represents their distance from the host star in astronomical units. We write the mass concentration (S  c ) and orbital spacing (S  s ) of the system after it was biased for each system on the left and those of the inherent system on the right. Note that the SMs change, often significantly, after observational bases are applied to the simulations.
Paper: Predicting the Dominant Formation Mechanism of Multiplanetary Systems
Authors: Cheyanne Shariat, Yasuhiro Hasegawa, Bradley M. S. Hansen, Tze Yeung Mathew Yu, Renyu Hu
Figure caption: The cumulative distributions of the mass concentration (S  c ;  left column) and orbital spacing (S  s ;  right column) of the biased simulation data, as well as the observed Kepler sample, which is split into two subgroups. The curves are the same as in Figure 4, but here we split the Kepler sample by those with S  c  > 70 (orange) and those with S  c  < 70 (light blue).
Paper: Predicting the Dominant Formation Mechanism of Multiplanetary Systems
Authors: Cheyanne Shariat, Yasuhiro Hasegawa, Bradley M. S. Hansen, Tze Yeung Mathew Yu, Renyu Hu
Figure caption: Triangle plot of the parameters used to train the kNN model to predict the dominant formation mechanism. The features of the multiplanetary systems that were inputted into the various ML models include the (1) average period (P av), (2) mass ratio between the farthest and closest planet (m out/m in), (3) semimajor axis ratio between the farthest and closest planet (a out/a in), (4) mass concentration (S  c ), and (5) orbital spacing (S  s ).
Paper: Predicting the Dominant Formation Mechanism of Multiplanetary Systems
Authors: Cheyanne Shariat, Yasuhiro Hasegawa, Bradley M. S. Hansen, Tze Yeung Mathew Yu, Renyu Hu
Figure caption: Detection combinations and probabilities for an example multiplanetary system. Observing the innermost planet is the most likely scenario (60.11%). Observing the inner two planets is the most probable (8%) multiplanet observation to be made by Kepler.
Paper: On the Maximum Black Hole Mass at Solar Metallicity
Authors: Amedeo Romagnolo, Alex C. Gormaz-Matamala, Krzysztof Belczynski
Figure caption: ZAMS mass–final star mass (end of C burning) relation at solar metallicity Z = 0.014. Our updated MESA models are shown with blue points (final mass of a star equals mass of a BH: no supernova) and blue stars (upper limit on mass of a BH, where blue squares show our estimates of NS/BH mass after supernova). Our two updated GENEC models are shown with red squares. Predictions from both codes match. We predict a monotonic growth of the BH mass as a function of its ZAMS mass. The predicted maximum BH mass in our models is ﹩{M}_{\mathrm{BH},\max }=28.3﹩                   M ⊙ and comes from a ZAMS mass M ZAMS ∼ 300 M ⊙. As a comparison we also show the models from Bavera et al. (2023) for single star evolution (yellow line) and from Martinet et al. (2023; green triangles): note that these models predict considerably different BH masses than our models.
Paper: On the Maximum Black Hole Mass at Solar Metallicity
Authors: Amedeo Romagnolo, Alex C. Gormaz-Matamala, Krzysztof Belczynski
Figure caption: Left: H-R diagram for selected MESA models. Colors correspond to various wind-mass-loss prescriptions used in our study. Note that stars with initial masses M ZAMS ≲ 60 M ⊙ are subject to significant radial expansion, while more-massive stars do not expand during evolution. Right: fraction of ZAMS mass lost through given wind-mass-loss prescription (color coded as shown in the figure). Note that majority of mass loss for most-massive stars (M ZAMS ≳ 60 M ⊙) is expected by H-rich thick winds and by H-poor thick winds (for which we use recent updated formulae).
Paper: On the Maximum Black Hole Mass at Solar Metallicity
Authors: Amedeo Romagnolo, Alex C. Gormaz-Matamala, Krzysztof Belczynski
Figure caption: ZAMS mass–final star mass (end of core C burning) relation at Z ⊙. On the left-hand plot we compare the results of our simulations between different initial rotation velocities at ZAMS. On the right-hand plot, instead, we compare the results from the simulations made with different values for the convective overshooting parameter α ov. The dotted lines represent nonrotating stars with α ov ≤ 0.2.
Paper: On the Maximum Black Hole Mass at Solar Metallicity
Authors: Amedeo Romagnolo, Alex C. Gormaz-Matamala, Krzysztof Belczynski
Figure caption: Comparison of old and new wind prescriptions for thin (left panel) and thick (right panel) winds.
Paper: On the Maximum Black Hole Mass at Solar Metallicity
Authors: Amedeo Romagnolo, Alex C. Gormaz-Matamala, Krzysztof Belczynski
Figure caption: Adopted line-driven wind-mass-loss prescription for massive stars at solar metallicity (Z = 0.014). For stars below 10 kK dust-driven winds will prevail and we will use de Jager et al. (1988). See Section 2.1 for details.
Paper: Reevaluating the Origin of Detectable Cataclysmic Variables in Globular Clusters: Testing the Importance of Dynamics
Authors: Liliana Rivera Sandoval, Diogo Belloni, Miriam Ramos Arevalo
Figure caption: Relations between n CV and γ, cluster mass, and central density for all clusters (top panels), CC GCs (middle panels), and non-CC GCs (bottom panels). The power-law fit is represented with a solid blue line, the constant fit with a dotted–dashed orange line, and the linear fit with a dashed green line. Purple and yellow points in the top panels refer to models by Belloni et al. (2019) using the Kroupa and Standard initial binary populations, respectively. Error bars in those model points are Poisson errors.
Paper: Reevaluating the Origin of Detectable Cataclysmic Variables in Globular Clusters: Testing the Importance of Dynamics
Authors: Liliana Rivera Sandoval, Diogo Belloni, Miriam Ramos Arevalo
Figure caption: Relation between n CV vs. cluster variables but for “bright” CVs in the sample of Table 1, i.e., those brighter than optical absolute magnitude 9. Symbols, colors, and lines have the same meaning as Figure 1.
Paper: Reevaluating the Origin of Detectable Cataclysmic Variables in Globular Clusters: Testing the Importance of Dynamics
Authors: Liliana Rivera Sandoval, Diogo Belloni, Miriam Ramos Arevalo
Figure caption: Relation between n CV vs cluster variables but for all the CVs listed in the Appendix, regardless of whether they have been detected in just one or more bands. Symbols, colors, and lines have the same meaning as Figure 1.
Paper: The Optical to Infrared 0.6–5.3 μm Dust Extinction Law of the Milky Way with JWST NIRSpec: Westerlund 2
Authors: Shu Wang, Xiaodian Chen
Figure caption: Top: the determined extinction curves of 384 extinction pairs colored by the number density. The left and right panels are extinction curves of 1–2 μm and 2–5.3 μm, respectively. The black lines are the power-law-type curves with α = 1.98 (dotted), 2.28 (long dashed), and 1.74 (dashed–dotted), respectively. The thick blue, orange, and magenta lines are the observed extinction curves for α = 1.98, 2.28, and 1.74, respectively. Bottom: the distribution of the difference Δ between the parameterized power-law-type curves and the observed extinction curves. The blue, orange, and magenta lines correspond to α = 1.98, 2.28, and 1.74, respectively.
Paper: The Optical to Infrared 0.6–5.3 μm Dust Extinction Law of the Milky Way with JWST NIRSpec: Westerlund 2
Authors: Shu Wang, Xiaodian Chen
Figure caption: The example of selecting extinction pairs. Left: an example of SED pairing. ﹩{F}_{i}^{{\prime} }﹩ (blue dashed line) and ﹩{F}_{j}^{{\prime} }﹩ (red line) are the processed SED of index i and j, respectively. The blue solid line is the extincted SED ﹩{F}_{i}^{{\prime} }\times {10}^{-0.4{A}_{\lambda }}﹩ of index i, which matches with the ﹩{F}_{j}^{{\prime} }﹩. Right: the distribution of ΔA  V  with the RMSE for 627 × 627 pairs. The pairs located in the red box area with ∣ΔA  V ∣ > 6.2 mag and RMSE < 0.5 are selected as the sample for further measuring the extinction law.
Paper: The Optical to Infrared 0.6–5.3 μm Dust Extinction Law of the Milky Way with JWST NIRSpec: Westerlund 2
Authors: Shu Wang, Xiaodian Chen
Figure caption: Top: the extinction curves for 0.6–2.0 μm (left) and 2.0–5.3 μm (right), respectively. Red, green, and blue dotted lines are our nonparameterized α-dependent extinction curves with α = 1.98, 2.07, and 1.61, respectively. Black solid lines and black dashed lines are the parameterized extinction laws of Wang & Chen (2019; α = 2.07) and Cardelli et al. (1989; α = 1.61), respectively. Bottom: the differences Δ between the power-law extinction laws and our nonparameterized α-dependent extinction curves. Green dotted lines and blue dotted lines are for α = 2.07 and 1.61, respectively. The gray shading presents the 1σ scatter of the α = 1.98 extinction curve.
Paper: The Optical to Infrared 0.6–5.3 μm Dust Extinction Law of the Milky Way with JWST NIRSpec: Westerlund 2
Authors: Shu Wang, Xiaodian Chen
Figure caption: Same as Figure 3, but adopting the flat IR extinction law of Wang et al. (2015a; thick black solid line) to find extinction pairs. Top: the determined extinction curves of the 115 selected extinction pairs colored by the number density. The left and right panels are extinction curves of 1–2 μm and 2–5.3 μm, respectively. The black lines are the power-law-type curves with α = 2.03 (dotted), 2.27 (long dashed), and 1.77 (dashed–dotted), respectively. The thick blue, orange, and magenta lines are the observed extinction curves for α = 2.03, 2.27, and 1.77, respectively. Bottom: the distribution of the difference Δ between the parameterized power-law-type curves and the observed extinction curves. The blue, orange, and magenta lines correspond to α = 2.03, 2.27, and 1.77, respectively.
Paper: The Optical to Infrared 0.6–5.3 μm Dust Extinction Law of the Milky Way with JWST NIRSpec: Westerlund 2
Authors: Shu Wang, Xiaodian Chen
Figure caption: Left: distribution of the average near-IR power law index α with the cutoff wavelength λ. Right: distribution of the total-to-selective extinction ratio R  V  with the near-IR power-law index α.
Paper: The Optical to Infrared 0.6–5.3 μm Dust Extinction Law of the Milky Way with JWST NIRSpec: Westerlund 2
Authors: Shu Wang, Xiaodian Chen
Figure caption: The distribution of the CER k  λ  with the near-IR power-law index α at six JWST NIRcam bands, where λ are F150W, F277W, F356W, F444W, F090W, and F070W, respectively, from the upper left to the lower right. The red lines are the linear fit lines.
Paper: Predicting the Dominant Formation Mechanism of Multiplanetary Systems
Authors: Cheyanne Shariat, Yasuhiro Hasegawa, Bradley M. S. Hansen, Tze Yeung Mathew Yu, Renyu Hu
Figure caption: The normalized density distribution of the period ratios (﹩{P}_{j+1}/{P}_{j},j\in {\mathbb{Z}}﹩) for all adjacent planets. The migration (solid red) and in situ (solid blue) simulations are compared to the Kepler migration systems (light orange) and Kepler in situ systems (light blue). The observed systems have Poisson error bars (﹩\sqrt{n}﹩ for each bin) overplotted.
Paper: A Short Intense Dynamo at the Onset of Crystallization in White Dwarfs
Authors: J. R. Fuentes, Matias Castro-Tapia, Andrew Cumming
Figure caption: Temporal evolution of the dimensionless composition flux at the solid–liquid interface, τ. Results are shown for a cooling model of a 0.9M ⊙ white dwarf obtained with the MESA stellar evolution code. As discussed in Fuentes et al. (2023) and Castro-Tapia et al. (2024), there is a rapid transition between τ > 1, where convection is efficient, and τ < 1, the regime of inefficient thermohaline convection. Note that the small fluctuations are numerical artefacts due to the chemical separation that happens in discrete events in the code. For comparison, we include the analytic prediction for τ using Mestel’s law for cooling white dwarfs (Equation (3), with T  i  = 7 × 106 K, and α = 0.1 Gyr).
Paper: A Short Intense Dynamo at the Onset of Crystallization in White Dwarfs
Authors: J. R. Fuentes, Matias Castro-Tapia, Andrew Cumming
Figure caption: Top panel: temporal evolution of the core mass, ﹩{M}_{\mathrm{core}}﹩, core radius, ﹩{R}_{\mathrm{core}}﹩, and outer radius of the convection zone, R out, once the white dwarf begins to crystallize. Results are shown for a cooling model of a 0.9M ⊙ white dwarf obtained with the MESA stellar evolution code. For R out we show two curves, corresponding to two different ways of determining the extent of the convection zone (the Ledoux criterion or just the unstable composition gradient ignoring the thermal buoyancy). Bottom panel: chemical profiles of the C/O abundances at different times since the onset of crystallization for the model using the Ledoux criterion shown in the top panel. The profiles at t − t crys = 0.3 Gyr are shown during the regime of thermohaline convection (see the text).
Paper: A Short Intense Dynamo at the Onset of Crystallization in White Dwarfs
Authors: J. R. Fuentes, Matias Castro-Tapia, Andrew Cumming
Figure caption: Intensity of the magnetic field generated at the onset of crystallization, as a function of the white dwarf's mass. The solid line corresponds to predictions from Equation (24), where the physical parameters above the crystallization front were extracted from a grid of MESA models. The shaded region corresponds to the uncertainties in the predictions due to the dispersion in the measurements of the dimensionless composition flux τ at the early phase of crystallization. We include measurements of observed magnetic fields in isolated white dwarfs taken from Bagnulo & Landstreet (2022). We classified the observational data in four different groups (H- and He-rich, and whether they are crystallizing or not based on the age at which the MESA models begin crystallization).
Paper: Electron and Proton Energization in 3D Reconnecting Current Sheets in Semirelativistic Plasma with Guide Magnetic Field
Authors: Gregory R. Werner, Dmitri A. Uzdensky
Figure caption: (a) Net gain in U  Bz  vs. B  gz , in 2Dxy (blue triangles), 3D (magenta circles), and 2Dyz (red diamonds showing zero gain). (b) Net gain in U  E (B  gz ). (c) For 2Dxy only, U  E (t) vs. time, for different B  gz , normalized to the ultimately released magnetic energy (not shown: in 2Dyz and 3D, U  E (t) remains relatively small). U  E  dissipates only after most of U  Bxy  has dissipated, as indicated by the circles placed where ΔU  Bxy (t) = 0.75ΔU  Bxy (20L/c). (d) For 2Dxy, the plasmoid E  y  as a function of B  gz , estimated from Equations (1)–(2) (solid line), compared with the maximum E  y  measured in simulations (triangles). (To reduce sensitivity to noise, the maximum was measured over time of the 99th percentile of ∣E  y ∣.)
Paper: Electron and Proton Energization in 3D Reconnecting Current Sheets in Semirelativistic Plasma with Guide Magnetic Field
Authors: Gregory R. Werner, Dmitri A. Uzdensky
Figure caption: The net gain in (a) electron and (b) ion energy, vs. B  gz , normalized by initial transverse magnetic energy U  Bxy0, over the full T = 20 L/c. (c) The electron gain fraction q  e  vs. B  gz . (d) q  e  for each third (in terms of ΔU  Bxy ) of each simulation (the smallest markers, shifted left, show q  e  in the first third; the largest, shifted right, show the last third). 2Dyz cases with B  gz /B 0 > 0.5, hence negligible energization, are omitted.
Paper: Electron and Proton Energization in 3D Reconnecting Current Sheets in Semirelativistic Plasma with Guide Magnetic Field
Authors: Gregory R. Werner, Dmitri A. Uzdensky
Figure caption: (a) U  Bxy (t) for selected simulations (B  gz  is labeled for each). Three (differently seeded) 2Dyz simulations with B  gz  = 0 demonstrate the enhanced stochastic variability of DKI. (b) ∣ΔU  Bxy ∣ (large symbols) and ΔU ptcl (small symbols) vs. B  gz , normalized to U  Bxy0, the initial transverse magnetic energy.
Paper: A Relativistic Double Neutron Star Binary PSR J1846-0513
Authors: D. Zhao, N. Wang, J. P. Yuan, D. Li, P. Wang, M. Y. Xue, W. W. Zhu, C. C. Miao, W. M. Yan, J. B. Wang, J. M. Yao, Q. D. Wu, S. Q. Wang, S. N. Sun, F. F. Kou, Y. T. Chen, S. J. Dang, Y. Feng, Z. J. Liu, X. L. Miao, L. Q. Meng, M. Yuan, C. H. Niu, J. R. Niu, L. Qian, S. Wang, X. Y. Xie, Y. F. Xiao, Y. L. Yue, S. P. You, X. H. Yu, R. S. Zhao, R. Yuen, X. Zhou, L. Zhang, Y. B. Wang, J. F. Wu, Z. Y. Gan, Z. Y. Sun, C. J. Wang
Figure caption: Polarization profiles for pulsar J1846−0513. The black, red, and blue lines in the lower panel represent the total intensity, linearly polarized intensity, and circularly polarized intensity, respectively. All profiles have been normalized by the peak intensity of the average pulse profile. The black dots with error bars in the upper panel indicate the position angle (PA) of the linearly polarized emission.
Paper: A Relativistic Double Neutron Star Binary PSR J1846-0513
Authors: D. Zhao, N. Wang, J. P. Yuan, D. Li, P. Wang, M. Y. Xue, W. W. Zhu, C. C. Miao, W. M. Yan, J. B. Wang, J. M. Yao, Q. D. Wu, S. Q. Wang, S. N. Sun, F. F. Kou, Y. T. Chen, S. J. Dang, Y. Feng, Z. J. Liu, X. L. Miao, L. Q. Meng, M. Yuan, C. H. Niu, J. R. Niu, L. Qian, S. Wang, X. Y. Xie, Y. F. Xiao, Y. L. Yue, S. P. You, X. H. Yu, R. S. Zhao, R. Yuen, X. Zhou, L. Zhang, Y. B. Wang, J. F. Wu, Z. Y. Gan, Z. Y. Sun, C. J. Wang
Figure caption: The m  p –m  c  diagram. The blue solid line represents the measured ﹩\dot{\omega }﹩ = 0.8956(8), and the red dashed line represents the measurement error of ﹩\dot{\omega }﹩. The gray area is excluded due to sin ≤1.
Paper: A Relativistic Double Neutron Star Binary PSR J1846-0513
Authors: D. Zhao, N. Wang, J. P. Yuan, D. Li, P. Wang, M. Y. Xue, W. W. Zhu, C. C. Miao, W. M. Yan, J. B. Wang, J. M. Yao, Q. D. Wu, S. Q. Wang, S. N. Sun, F. F. Kou, Y. T. Chen, S. J. Dang, Y. Feng, Z. J. Liu, X. L. Miao, L. Q. Meng, M. Yuan, C. H. Niu, J. R. Niu, L. Qian, S. Wang, X. Y. Xie, Y. F. Xiao, Y. L. Yue, S. P. You, X. H. Yu, R. S. Zhao, R. Yuen, X. Zhou, L. Zhang, Y. B. Wang, J. F. Wu, Z. Y. Gan, Z. Y. Sun, C. J. Wang
Figure caption: The best postfit timing residuals of PSR J1846−0513. The top and bottom panels show plots for MJD and orbital phase vs. postfit residuals, respectively.
Paper: A Relativistic Double Neutron Star Binary PSR J1846-0513
Authors: D. Zhao, N. Wang, J. P. Yuan, D. Li, P. Wang, M. Y. Xue, W. W. Zhu, C. C. Miao, W. M. Yan, J. B. Wang, J. M. Yao, Q. D. Wu, S. Q. Wang, S. N. Sun, F. F. Kou, Y. T. Chen, S. J. Dang, Y. Feng, Z. J. Liu, X. L. Miao, L. Q. Meng, M. Yuan, C. H. Niu, J. R. Niu, L. Qian, S. Wang, X. Y. Xie, Y. F. Xiao, Y. L. Yue, S. P. You, X. H. Yu, R. S. Zhao, R. Yuen, X. Zhou, L. Zhang, Y. B. Wang, J. F. Wu, Z. Y. Gan, Z. Y. Sun, C. J. Wang
Figure caption: Panel (a): the black solid line is obtained from Equation (4). The blue points represent the relationship between the spin period and orbital period of recycled pulsars in known DNS systems. Panel (b): plot for orbital eccentricity as a function of orbital period for the recycled DNS systems. The red star represents PSR J1846−0513. DNS systems in globular clusters are not considered in our sample, because the complex situation in globular clusters may lead to inaccuracy in the eccentricity near the other stars in these systems.
Paper: A Relativistic Double Neutron Star Binary PSR J1846-0513
Authors: D. Zhao, N. Wang, J. P. Yuan, D. Li, P. Wang, M. Y. Xue, W. W. Zhu, C. C. Miao, W. M. Yan, J. B. Wang, J. M. Yao, Q. D. Wu, S. Q. Wang, S. N. Sun, F. F. Kou, Y. T. Chen, S. J. Dang, Y. Feng, Z. J. Liu, X. L. Miao, L. Q. Meng, M. Yuan, C. H. Niu, J. R. Niu, L. Qian, S. Wang, X. Y. Xie, Y. F. Xiao, Y. L. Yue, S. P. You, X. H. Yu, R. S. Zhao, R. Yuen, X. Zhou, L. Zhang, Y. B. Wang, J. F. Wu, Z. Y. Gan, Z. Y. Sun, C. J. Wang
Figure caption: Mass–mass diagram of known DNS, NS-WD systems, and PSR J1846−0513. The red and blue dots represent the masses of the PSR J1846−0513 and its companion, respectively, at inclination angles of i = 90° and i = 60°. The systems in the globular cluster are not considered in the plot.