adsabs/AstroCLIMB huggingface dataset:
Paper: An Extension of Gmunu: General-relativistic Resistive Magnetohydrodynamics Based on Staggered-meshed Constrained Transport with Elliptic Cleaning
Authors: Patrick Chi-Kit Cheong, 志杰 張, David Yat Tung Pong, Anson Ka Long Yip, Tjonnie Guang Feng Li
Figure caption: Comparison of the initial and final (t = 10 ms) magnetic fields with different divergence-free handling approaches, namely, the hyperbolic cleaning, cell-centered elliptic cleaning, and upwind constrained transport with and without elliptic cleaning. The red dashed line shows the surface of the star. The field is well maintained in all cases except that there are some distortions in the vicinity of the star’s surface.
Paper: An Extension of Gmunu: General-relativistic Resistive Magnetohydrodynamics Based on Staggered-meshed Constrained Transport with Elliptic Cleaning
Authors: Patrick Chi-Kit Cheong, 志杰 張, David Yat Tung Pong, Anson Ka Long Yip, Tjonnie Guang Feng Li
Figure caption: The evolution of the normalized energy of the toroidal field ﹩{{ \mathcal E }}_{\mathrm{tor}}(t)/{{ \mathcal E }}_{\mathrm{tor}}(t=0)﹩ of a magnetized neutron star with a purely toroidal initial field with different values of conductivity σ c. Since the ohmic decay timescale of magnetic fields scales linearly with 1/σ c, the magnetic energy decreases exponentially with time, which is approximately proportional to ﹩\exp \left(-2t/{\sigma }_{{\rm{c}}}\right)﹩. The magnetic energy decreases exponentially with time (solid lines) and the decay rates agree with the expected decay rates (dashed lines). Note that this evolution process is valid only when axial symmetry is assumed.
Paper: An Extension of Gmunu: General-relativistic Resistive Magnetohydrodynamics Based on Staggered-meshed Constrained Transport with Elliptic Cleaning
Authors: Patrick Chi-Kit Cheong, 志杰 張, David Yat Tung Pong, Anson Ka Long Yip, Tjonnie Guang Feng Li
Figure caption: An empirical functional form for the conductivity proposed in Dionysopoulou et al. (2013): ﹩{\sigma }_{{\rm{c}}}={\sigma }_{0}{\left(max\left[\left(1-{D}_{{\rm{atmo}}}/D\right),0\right]\right)}^{2}﹩, where D is the conserved density, and the conductivity at the center of the star is set as σ 0 = 108, which is roughly 2.03 × 1013 s−1 in cgs units.
Paper: An Extension of Gmunu: General-relativistic Resistive Magnetohydrodynamics Based on Staggered-meshed Constrained Transport with Elliptic Cleaning
Authors: Patrick Chi-Kit Cheong, 志杰 張, David Yat Tung Pong, Anson Ka Long Yip, Tjonnie Guang Feng Li
Figure caption: The relative variation of the rest mass M  b  (upper panel), maximum density ﹩{\rho }_{\max }﹩ (middle panel), and minimum lapse function ﹩{\alpha }_{\min }﹩ (lower panel) in time. All evolutions of the fluid are almost identical with all divergence-free handling methods.
Paper: An Extension of Gmunu: General-relativistic Resistive Magnetohydrodynamics Based on Staggered-meshed Constrained Transport with Elliptic Cleaning
Authors: Patrick Chi-Kit Cheong, 志杰 張, David Yat Tung Pong, Anson Ka Long Yip, Tjonnie Guang Feng Li
Figure caption: Upper panel: relative variation of the magnetic energy of the poloidal field ﹩{{ \mathcal E }}_{\mathrm{pol}}﹩ in time. Lower panel: relative variation of the volume-averaged magnetic field 〈B〉 in time. Upwind constrained transport performs slightly better at preserving these quantities.
Paper: Evolution of the Heliotail Lobes over a Solar Cycle as Measured by IBEX
Authors: M. A. Dayeh, E. J. Zirnstein, S. A. Fuselier, H. O. Funsten, D. J. McComas
Figure caption: A schematic summary of the observations in this study. (a) Sunspot variations indicating the solar cycle phase. (b) SW progenitor conditions mapped to the studied ENA observations, based on estimates from Zirnstein et al. (2020). (c) Summary of the heliotail lobes’ motion during a solar cycle. Color coded symbols indicate the centers of the different lobes during different SW conditions. Superposed lines mark the ecliptic, heliographic meridian, and solar equatorial planes (gray), along with the ribbon trace (violet). Green arrows illustrate the motion of the centers with time and red points mark the nonweighted averages of the lobe centers (Table 1). The downwind direction is also marked with a black star.
Paper: Evolution of the Heliotail Lobes over a Solar Cycle as Measured by IBEX
Authors: M. A. Dayeh, E. J. Zirnstein, S. A. Fuselier, H. O. Funsten, D. J. McComas
Figure caption: (a) Combined IBEX-Hi ENA maps over five periods, as follows: [2009–2011], [2012–2013], [2014–2015], [2016–2017], and [2018–2019]. The layout is similar to that of Figure 2. (b) Statistically smoothed maps of Figure 3(a). A smoothing window of 9° is applied (see text for details).
Paper: Evolution of the Heliotail Lobes over a Solar Cycle as Measured by IBEX
Authors: M. A. Dayeh, E. J. Zirnstein, S. A. Fuselier, H. O. Funsten, D. J. McComas
Figure caption: Structure of the five-lobed heliotail as it appears at ∼1.1 and ∼4.3 keV in the 11 yr (2009–2019) combined smoothed maps. The black trace corresponds to the ribbon location in the sky. The characteristic heliotail lobes are indicated: (a) central ENA enhancement at ∼1.1 keV and (b) northern and southern ENA enhancements, in addition to port and starboard ENA depressions. The black line here indicates the energy-averaged ribbon path (Dayeh et al. 2019).
Paper: Evolution of the Heliotail Lobes over a Solar Cycle as Measured by IBEX
Authors: M. A. Dayeh, E. J. Zirnstein, S. A. Fuselier, H. O. Funsten, D. J. McComas
Figure caption: Lobe contours on a Mollweide projection during the five studied time periods, color coded by time. Each contour represents the average boundaries with 10% variability around the flux threshold (see text for details). Missing contours for some periods indicate that the contour limit is too small or too large extending to the polar regions. The uncertainties of the contour regions are of the order shown in Figure 4.
Paper: Evolution of the Heliotail Lobes over a Solar Cycle as Measured by IBEX
Authors: M. A. Dayeh, E. J. Zirnstein, S. A. Fuselier, H. O. Funsten, D. J. McComas
Figure caption: (a) Latitudinal variations of averaged ENA fluxes at all energies along an 18° swath in the downwind direction, highlighted in the inset map. Vertical lines indicate the downwind and S-lobe centers, representing the slow and fast SW regions, respectively. (b) RJ  (Equation (5)) as a function of energy for all time periods. This illustrates the derivation of the heliotail transition energy as further discussed in the text.
Paper: Evolution of the Heliotail Lobes over a Solar Cycle as Measured by IBEX
Authors: M. A. Dayeh, E. J. Zirnstein, S. A. Fuselier, H. O. Funsten, D. J. McComas
Figure caption: Mollweide projections of IBEX-Hi annual (ram-direction) ENA sky maps, centered on the downwind direction. Columns represent the five different energy passbands and rows show maps of the 11 sequential years from 2009 to 2019. Black swaths are regions with no data.
Paper: Evolution of the Heliotail Lobes over a Solar Cycle as Measured by IBEX
Authors: M. A. Dayeh, E. J. Zirnstein, S. A. Fuselier, H. O. Funsten, D. J. McComas
Figure caption: Demonstration of how lobe boundaries are determined. (a) A large solid angle is drawn around the lobe of interest and the weighted-average flux is determined. (b) A threshold below (this case) or above the averaged flux constrains the lobe contour. The three contours shown mark the 10% variability around the threshold value. See text for details.
Paper: Evolution of the Heliotail Lobes over a Solar Cycle as Measured by IBEX
Authors: M. A. Dayeh, E. J. Zirnstein, S. A. Fuselier, H. O. Funsten, D. J. McComas
Figure caption: Variations of the heliotail lobes’ properties over a solar cycle. Top to bottom in each plot: Variation of the mean ENA flux, area in the sky, and longitude and latitude of the respective weighted lobe center. Missing points indicate that the algorithm used does not converge to a meaningful value. As expected, the N-lobe has the least inferred information due to the ribbon’s passage through it.
Paper: Evolution of the Heliotail Lobes over a Solar Cycle as Measured by IBEX
Authors: M. A. Dayeh, E. J. Zirnstein, S. A. Fuselier, H. O. Funsten, D. J. McComas
Figure caption: Energy at which the tail splits from a C-lobe (most visible at ∼1.1 keV) into an N-lobe and S-lobe (most visible at ∼4.3 keV). As shown, the split energy during solar minimum conditions is stable and varies with increasing solar activity, as the slow and fast SW content in the IHS gets modified.
Paper: Entropy-conserving Scheme for Modeling Nonthermal Energies in Fluid Dynamics Simulations
Authors: Vadim A. Semenov, Andrey V. Kravtsov, Benedikt Diemer
Figure caption: Dependence of the nonthermal entropy error produced by the energy-based scheme in the postshock region on the compression ratio of the shock, r s = ρ 1/ρ 0, for different values of the adiabatic index of the nonthermal component: γ nt = 4/3 (blue squares) and γ nt = 5/3 (green circles). The entropy error increases monotonically with r s until ΔS nt/S nt becomes ∼1, at which point the error diverges. For a larger γ nt, this divergence occurs at a smaller r s. For this test, the nonthermal energy is dynamically decoupled from the hydrodynamics by making its initial value arbitrary small and removing its contribution from the total pressure. The color intensity corresponds to different ways of varying r s. Lighter colors correspond to variations in γ th, keeping the shock Mach number high so that r s ≈ (γ th + 1)/(γ th − 1), with γ th spanning a range from γ th = 5 (leftmost points) to γ th = 1.16 and 1.36 (rightmost points for γ nt = 4/3 and γ nt = 5/3, respectively). Darker colors show the variation in the shock Mach number at fixed γ th = 5/3 (from left to right, M ≈ 1.3, 1.5, 1.9, 3.0, 9.0), with the vertical gray line showing the high-Mach-number limit of r s = 4.
Paper: Entropy-conserving Scheme for Modeling Nonthermal Energies in Fluid Dynamics Simulations
Authors: Vadim A. Semenov, Andrey V. Kravtsov, Benedikt Diemer
Figure caption: Hydrodynamic Zel’dovich pancake test with 70% of internal energy in the nonthermal form with γ nt = γ th = 5/3. The results are shown before and after the wave crossing (left and right sets of panels, respectively) and for the energy-based and entropy-conserving methods (left and right columns in each set). The connected points show simulation results, while the thick lines show the analytic solution: orange lines show gas density, velocity, and total temperature, while red and blue lines show thermal and nonthermal components. Note that the analytic solution is valid only outside the shocked regions. Thin red lines in the top panels show the grid refinement level, with the zeroth level corresponding to 32 cells per box size. The bottom panels in the left set show the relative entropy error, while in the right set, they show the absolute value of entropy normalized to the initial total entropy. The energy-based scheme conserves nonthermal entropy relatively well during the adiabatic stage (with a relative error of <1%). After the wave crossing, however, the nonthermal entropy suffers from strong numerical heating at the shocks. The entropy-conserving scheme, in contrast, conserves nonthermal entropy throughout the duration of the run, with the nonthermal “temperature” increasing only due to adiabatic compression.
Paper: Entropy-conserving Scheme for Modeling Nonthermal Energies in Fluid Dynamics Simulations
Authors: Vadim A. Semenov, Andrey V. Kravtsov, Benedikt Diemer
Figure caption: Shock tube test with an extra nonthermal energy representing cosmic rays (γ nt = 4/3) using the energy-based (left column) and entropy-conserving (right column) schemes for modeling thermal energy and cosmic rays. The initial conditions are taken from Pfrommer et al. (2017): (ρ, u, P th, P nt) = (1, 0, 17.172, 34.344) and (0.125, 0, 0.05, 0.05) for the left and right initial states, respectively. Thick lines show the analytic solution from Pfrommer et al. (2017, Appendix C2), with orange lines showing the solutions for the density, velocity, and total pressure, and red and blue lines showing the solutions for the thermal and cosmic ray components, respectively. The results are compared at t = 0.5. As the bottom panel shows, the energy-based scheme leads to a spurious production of nonthermal entropy at the shock, while the entropy-conserving scheme ensures nonthermal entropy conservation across the shock.
Paper: Entropy-conserving Scheme for Modeling Nonthermal Energies in Fluid Dynamics Simulations
Authors: Vadim A. Semenov, Andrey V. Kravtsov, Benedikt Diemer
Figure caption: Joint distribution of gas density and total subgrid velocity dispersion, which includes both subgrid turbulence and thermal sound speed, ﹩{\sigma }_{\mathrm{tot}}=\sqrt{{\sigma }_{\mathrm{turb}}^{2}+{c}_{{\rm{s}}}^{2}}﹩. The contours show 68%, 95%, and 99% of the gas mass and the color indicates the average galactocentric radius of cells within a pixel. The thick dotted line shows the star formation threshold, α vir,sf = 10, while the thin lines show the values of α vir = 1 and 100 for reference. To reduce noise, the distributions are averaged over 21 snapshots spaced 10 Myr apart. Switching to the entropy-conserving scheme reduces σ tot ≈ σ turb in dense gas (n > 10 cm−3) by a factor of ∼1.5 and completely removes the horizontal feature at σ turb > 30 km s−1 and n > 100 cm−3 that corresponds to the central region of the disk.
Paper: Entropy-conserving Scheme for Modeling Nonthermal Energies in Fluid Dynamics Simulations
Authors: Vadim A. Semenov, Andrey V. Kravtsov, Benedikt Diemer
Figure caption: Shock tube test with 20% of dissipated energy injected in the nonthermal component using the entropy-conserving scheme and the energy partitioning method outlined in Section 2.3. The initial conditions are the same as in Figure 1. The left and right columns show the results for different adiabatic indices of the nonthermal component: γ nt = 4/3 and 5/3, respectively. The nonthermal energy injected at the shock is tracked separately and shown with green color in the bottom two panels. The analytic solution for all quantities is computed following Pfrommer et al. (2017, Appendix C2) and is shown with the thick lines. When γ nt differs from γ th = 5/3, the injected energy in the postshock region is underestimated by ∼20%, while for γ nt = γ th = 5/3 the result is in perfect agreement with the analytical solution.
Paper: Entropy-conserving Scheme for Modeling Nonthermal Energies in Fluid Dynamics Simulations
Authors: Vadim A. Semenov, Andrey V. Kravtsov, Benedikt Diemer
Figure caption: Results of the isolated galaxy simulation with the full subgrid turbulence model and star formation prescription coupled with the predicted turbulent velocities. The columns show the mid-plane slices of density, n, and subgrid turbulent velocity, σ turb, and the surface density of SFR, ﹩{\dot{{\rm{\Sigma }}}}_{\star }﹩, computed using particles younger than 30 Myr. Different rows show simulations where thermal energy and subgrid turbulence are modeled by using either the energy-based or entropy-conserving scheme. To guide the eye, black contours in the n and σ turb maps show n = 10 cm−3 density isocontours. The ﹩{\dot{{\rm{\Sigma }}}}_{\star }﹩ maps show the most apparent difference between the two schemes: the SFR in the run with the energy-based scheme is more clumpy and strongly suppressed near the galaxy center.
Paper: Entropy-conserving Scheme for Modeling Nonthermal Energies in Fluid Dynamics Simulations
Authors: Vadim A. Semenov, Andrey V. Kravtsov, Benedikt Diemer
Figure caption: Results of the entropy-conserving scheme in the regime where the energy-based scheme is highly unstable. The initial conditions are the same as in Figure 1, but the adiabatic indices of the thermal and nonthermal components are set to γ th = 1.1 and γ nt = 5/3 to make the shock highly compressible, with a compression ratio of r s ≈ 13.2. Such r s is significantly higher than the value at which the entropy error of the energy-based scheme diverges (r s ∼ 6.5 for γ nt = 5/3, see Figure 2). The entropy-conserving scheme still performs well.
Paper: Entropy-conserving Scheme for Modeling Nonthermal Energies in Fluid Dynamics Simulations
Authors: Vadim A. Semenov, Andrey V. Kravtsov, Benedikt Diemer
Figure caption: Gas density (left), velocity dispersion of subgrid turbulence (center), and error of the subgrid turbulence entropy (right) in an isolated disk galaxy simulation after ∼300  Myr of evolution. The subgrid turbulence is modeled using the entropy-conserved scheme. In this test, subgrid turbulence is initialized such that its entropy is initially constant, and then the galaxy simulation is evolved with all the source and sink terms of the subgrid turbulence model turned off, except for the PdV term. The right panel illustrates the long-term conservation of the entropy of subgrid turbulence, which remains constant to machine precision (∼10−6 for a single-precision floating point variable) after ∼300  Myr of evolution.
Paper: An Extension of Gmunu: General-relativistic Resistive Magnetohydrodynamics Based on Staggered-meshed Constrained Transport with Elliptic Cleaning
Authors: Patrick Chi-Kit Cheong, 志杰 張, David Yat Tung Pong, Anson Ka Long Yip, Tjonnie Guang Feng Li
Figure caption: The evolution of the y-component of the magnetic field B  y  in the one-dimensional steady dynamo test. The blue dots represent the exponential growth of B  y  when k = 1, which is consistent with the analytical solution with the growth rate 0.385 (green dashed line). In addition, the effects of resistivity and dynamo are canceled by each other when k = 5; the magnetic field is expected to remain unchanged in this case. However, due to numerical errors, the y-component of the magnetic field B  y  with k = 5 (orange dots) remains at the same order of magnitude up to t ∼ 20 and eventually grows with the fastest growing mode at a rate 0.59 (red dashed line).
Paper: An Extension of Gmunu: General-relativistic Resistive Magnetohydrodynamics Based on Staggered-meshed Constrained Transport with Elliptic Cleaning
Authors: Patrick Chi-Kit Cheong, 志杰 張, David Yat Tung Pong, Anson Ka Long Yip, Tjonnie Guang Feng Li
Figure caption: The numerical errors of B  y  vs. resolution (black line) for the self-similar current sheet problem at t = 10. This test uses a second-order accurate strong-stability-preserving IMEX-SSP2(2,2,2) time integrator (Pareschi & Russo 2005) and HLL Riemann solver (Harten et al. 1983) with second-order Montonized central limiter (van Leer 1974). Second-order ideal scaling is given by the dashed blue line while third-order ideal scaling is given by the dashed orange line. The convergence rate is between second-order and third-order in this test.
Paper: An Extension of Gmunu: General-relativistic Resistive Magnetohydrodynamics Based on Staggered-meshed Constrained Transport with Elliptic Cleaning
Authors: Patrick Chi-Kit Cheong, 志杰 張, David Yat Tung Pong, Anson Ka Long Yip, Tjonnie Guang Feng Li
Figure caption: The L 1-norm of the difference between the initial and final values of the z-component of the magnetic field ﹩| | {B}^{z}(T)-{B}_{\mathrm{exact}}^{z}(T)| {| }_{1}﹩ and convergence rates t = T vs. different resolutions N of the two-dimensional relativistic resistive MHD telegraph equation test. This test uses a second-order-accurate strong-stability-preserving IMEX-SSP2(2,2,2) time integrator (Pareschi & Russo 2005) and HLL Riemann solver (Harten et al. 1983) with second-order Montonized central limiter (van Leer 1974). Second-order ideal scaling is given by the dashed black line. Gmunu achieves second-order convergence in this test.
Paper: An Extension of Gmunu: General-relativistic Resistive Magnetohydrodynamics Based on Staggered-meshed Constrained Transport with Elliptic Cleaning
Authors: Patrick Chi-Kit Cheong, 志杰 張, David Yat Tung Pong, Anson Ka Long Yip, Tjonnie Guang Feng Li
Figure caption: The L 1-norm of the difference between the exact and final values of the z-component of the magnetic field ﹩\parallel {B}^{z}(t)-{B}_{\mathrm{exact}}^{z}{\parallel }_{1}﹩ and convergence rates of the charged vortex problem at different resolutions N at t = 5 of the two-dimensional stationary charged vortex test. This test uses a second-order-accurate strong-stability-preserving IMEX-SSP2(2,2,2) time integrator (Pareschi & Russo 2005) and HLL Riemann solver (Harten et al. 1983) with second-order Montonized central limiter (van Leer 1974). Second-order ideal scaling is given by the dashed black line. Gmunu achieves second-order convergence in this test.
Paper: An Extension of Gmunu: General-relativistic Resistive Magnetohydrodynamics Based on Staggered-meshed Constrained Transport with Elliptic Cleaning
Authors: Patrick Chi-Kit Cheong, 志杰 張, David Yat Tung Pong, Anson Ka Long Yip, Tjonnie Guang Feng Li
Figure caption: Comparison of the initial and final (t = 200 [code unit] ≈ 1 ms) magnetic fields. The red dashed line shows the surface of the star. Initially, only the toroidal component of magnetic field  B  tor exists and no poloidal parts. However, the toroidal magnetic field is strongly distorted and grows even in the atmosphere. In addition, a poloidal magnetic field develops (the streamlines), and its energy grows significantly during the evolution. These effects are due to the nonphysical choice that requires a nonvanishing resistivity and dynamo terms everywhere.
Paper: An Extension of Gmunu: General-relativistic Resistive Magnetohydrodynamics Based on Staggered-meshed Constrained Transport with Elliptic Cleaning
Authors: Patrick Chi-Kit Cheong, 志杰 張, David Yat Tung Pong, Anson Ka Long Yip, Tjonnie Guang Feng Li
Figure caption: The L 2-norm of ∇ ·  B  vs. time for the advected field loop test with different divergence-control approaches. With the constrained transport scheme, the overall L 2-norm of ∇ ·  B  is significantly low at the order of ﹩{ \mathcal O }\left({10}^{-15}\right)﹩ during the entire simulation. Furthermore, combining the constrained transport scheme with elliptic cleaning, the magnetic monopoles are further suppressed at the order of ﹩{ \mathcal O }\left({10}^{-17}\right)﹩.
Paper: An Extension of Gmunu: General-relativistic Resistive Magnetohydrodynamics Based on Staggered-meshed Constrained Transport with Elliptic Cleaning
Authors: Patrick Chi-Kit Cheong, 志杰 張, David Yat Tung Pong, Anson Ka Long Yip, Tjonnie Guang Feng Li
Figure caption: The evolution of the energy of the poloidal magnetic fields of a magnetized neutron star with a purely poloidal field under a dynamo effect (see Section 5.9). The poloidal magnetic field develops, and its energy grows significantly during the evolution. These effects are due to the nonphysical choice that requires a nonvanishing resistivity and dynamo terms everywhere.
Paper: An Extension of Gmunu: General-relativistic Resistive Magnetohydrodynamics Based on Staggered-meshed Constrained Transport with Elliptic Cleaning
Authors: Patrick Chi-Kit Cheong, 志杰 張, David Yat Tung Pong, Anson Ka Long Yip, Tjonnie Guang Feng Li
Figure caption: The simulated magnetic field B  y  and electric field E  z  (red dashed lines) at t = 10 for the self-similar current sheet test problem with resolution N = 256. The solid black lines are the analytic solutions. The numerical results obtained by Gmunu agree with the analytic solutions.
Paper: An Extension of Gmunu: General-relativistic Resistive Magnetohydrodynamics Based on Staggered-meshed Constrained Transport with Elliptic Cleaning
Authors: Patrick Chi-Kit Cheong, 志杰 張, David Yat Tung Pong, Anson Ka Long Yip, Tjonnie Guang Feng Li
Figure caption: One-dimensional slices along the x-axis (upper panel) and y-axis (lower panel) for the charge density ρ  e  for the stationary charged vortex test at t = 5. The red dots show the numerical results obtained by Gmunu, which agree with the initial condition (black solid lines).