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This dataset accompanies the publication "GenASiS: General Astrophysical Simulation System. II. Self-gravitating Baryonic Matter." This dataset contains simulation outputs from GenASiS for the test problems described in that publication.
This dataset accompanies the publication "GenASiS: General Astrophysical Simulation System. II. Self-gravitating Baryonic Matter." This dataset contains simulation outputs from GenASiS described in the Appendix of that publication.
GenASiS (General Astrophysical Simulation System) is a code being developed initially and primarily, though not exclusively, for the simulation of core-collapse supernovae on the world's leading capability supercomputers. This paper---the second in a series---documents capabilities for Newtonian self-gravitating fluid dynamics, including tabulated microphysical equations of state treating nuclei and nuclear matter (`baryonic matter'). Computation of the gravitational potential of a spheroid, and simulation of the gravitational collapse of dust and of an ideal fluid, provide tests of self-gravitation against known solutions. In multidimensional computations of the adiabatic collapse, bounce, and explosion of spherically symmetric pre-supernova progenitors---which we propose become a standard benchmark for code comparisons---we find that the explosions are prompt and remain spherically symmetric (as expected), with an average shock expansion speed and total kinetic energy that are inversely correlated with the progenitor mass at the onset of collapse and the compactness parameter.
We add an ensemble of nuclei to the equation of state for homogeneous nucleonic matter to generate a new set of models suitable for astrophysical simulations of core-collapse supernovae and neutron star mergers. We implement empirical constraints from (i) nuclear mass measurements, (ii) proton-proton scattering phase shifts, and (iii) neutron star observations. Our model is also guided by microscopic many-body theory calculations based on realistic nuclear forces, including the zero-temperature neutron matter equation of state from quantum Monte Carlo simulations and thermal contributions to the free energy from finite-temperature many-body perturbation theory. We ensure that the parameters of our model can be varied while preserving thermodynamic consistency and the connection to experimental or observational data, thus providing a probability distribution of the astrophysical hot and dense matter equation of state. Furthermore, we compare our results with those obtained from other available equations of state. While our probability distributions indeed represent a large number of possible equations of state, we cannot yet claim to have fully explored all of the uncertainties, especially with regard to the structure of nuclei in the hot and dense medium.
We present efforts at improving the performance of FLASH, a multi-scale, multi-physics simulation code principally for astrophysical applications, by using huge pages on Ookami, an HPE Apollo 80 A64FX platform. FLASH is written principally in modern Fortran and makes use of the PARAMESH library to manage a block-structured adaptive mesh. We explored options for enabling the use of huge pages with several compilers, but we were only able to successfully use huge pages when compiling with the Fujitsu compiler. As a result, the use of huge pages substantially reduced the number of translation lookaside buffer misses, but overall performance gains were marginal.
Abstract We present an extension of the massively parallel, GPU native, astrophysical hydrodynamics code Cholla to magnetohydrodynamics (MHD). Cholla solves the ideal MHD equations in their Eulerian form on a static Cartesian mesh utilizing the Van Leer + constrained transport integrator, the HLLD Riemann solver, and reconstruction methods at second and third order. Cholla’s MHD module can perform ≈260 million cell updates per GPU-second on an NVIDIA A100 while using the HLLD Riemann solver and second order reconstruction. The inherently parallel nature of GPUs combined with increased memory in new hardware allows Cholla’s MHD module to perform simulations with resolutions ∼500 3 cells on a single high-end GPU (e.g., an NVIDIA A100 with 80 GB of memory). We employ GPU direct Message Passing Interface to attain excellent weak scaling on the exascale supercomputer Frontier, while using 74,088 GPUs and simulating a total grid size of over 7.2 trillion cells. A suite of test problems highlights the accuracy of Cholla’s MHD module and demonstrates that zero magnetic divergence in solutions is maintained to round off error. We also present new testing and CI tools using GoogleTest, GitHub Actions, and Jenkins that have made development more robust and accurate and ensure reliability in the future.
In the Concurrent Computing Laboratory in the Department of Physics and Astronomy at Louisiana State University we have constructed a heterogeneous computing environment that permits us to routinely simulate complicated three-dimensional fluid flows and to readily visualize the results of each simulation via three-dimensional animation sequences. An 8192-node MasPar MP-1 computer with 0.5 GBytes of RAM provides 250 MFlops of execution speed for our fluid flow simulations. Utilizing the parallel virtual machine (PVM) language, at periodic intervals data is automatically transferred from the MP-1 to a cluster of workstations where individual three-dimensional images are rendered for inclusion in a single animation sequence. Work is underway to replace executions on the MP-1 with simulations performed on the 512-node CM-5 at NCSA and to simultaneously gain access to more potent volume rendering workstations.
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High-order Godunov methods for gas dynamics have become a standard tool for simulating different classes of astrophysical flows. Their accuracy is mostly determined by the spatial interpolant used to reconstruct the pair of Riemann states at cell interfaces and by the Riemann solver that computes the interface fluxes. In most Godunov-type methods, these two steps can be treated independently, so that many different schemes can in principle be built from the same numerical framework. Because astrophysical simulations often test out the limits of what is feasible with the computational resources available, it is essential to find the scheme that produces the numerical solution with the desired accuracy at the lowest computational cost. However, establishing the best combination of numerical options in a Godunov-type method to be used for simulating a complex hydrodynamic problem is a nontrivial task. In fact, formally more accurate schemes do not always outperform simpler and more diffusive methods, especially if sharp gradients are present in the flow. For this work, we used our fully compressible Seven-League Hydro (SLH) code to test the accuracy of six reconstruction methods and three approximate Riemann solvers on two- and three-dimensional (2D and 3D) problems involving subsonic flows only. We considered Mach numbers in the range from 10 −3 to 10 −1 , which are characteristic of many stellar and geophysical flows. In particular, we considered a well-posed, 2D, Kelvin–Helmholtz instability problem and a 3D turbulent convection zone that excites internal gravity waves in an overlying stable layer. Although the different combinations of numerical methods converge to the same solution with increasing grid resolution for most of the quantities analyzed here, we find that (i) there is a spread of almost four orders of magnitude in computational cost per fixed accuracy between the methods tested in this study, with the most performant method being a combination of a low-dissipation Riemann solver and a sextic reconstruction scheme; (ii) the low-dissipation solver always outperforms conventional Riemann solvers on a fixed grid when the reconstruction scheme is kept the same; (iii) in simulations of turbulent flows, increasing the order of spatial reconstruction reduces the characteristic dissipation length scale achieved on a given grid even if the overall scheme is only second order accurate; (iv) reconstruction methods based on slope-limiting techniques tend to generate artificial, high-frequency acoustic waves during the evolution of the flow; and (v) unlimited reconstruction methods introduce oscillations in the thermal stratification near the convective boundary, where the entropy gradient is steep.
Turbulence is a key process in many fields of astrophysics. Advances in numerical simulations of fluids over the last several decades have revolutionized our understanding of turbulence and related processes such as star formation and cosmic ray propagation. However, data from numerical simulations of astrophysical turbulence are often not made public. We introduce a new simulation-oriented database for the astronomical community: the Catalogue for Astrophysical Turbulence Simulations (CATS), located at www.mhdturbulence.com. CATS includes magnetohydrodynamic (MHD) turbulent box simulation data products generated by the public codes athena++, arepo, enzo, and flash. CATS also includes several synthetic observational data sets, such as turbulent HI data cubes. We also include measured power spectra and three-point correlation functions from some of these data. We discuss the importance of open-source statistical and visualization tools for the analysis of turbulence simulations such as those found in CATS.
The role of sophisticated numerical models and simulations in the field of plasma astrophysics is discussed. The need for an iteration between microphysics and macrophysics in order for astrophysical plasma physics to produce quantitative results that can be related to astronomical data is stressed. A discussion on computational requirements for simulations of astrophysical plasmas contrasts microscopic plasma simulations with macroscopic system models. An overview of particle-in-cell simulations (PICS) is given and two examples of PICS of astrophysical plasma are discussed including particle acceleration by collisionless shocks in relativistic plasmas and magnetic field reconnection in astrophysical plasmas.
Modern astrophysical simulation codes employ a variety of numerical algorithms capable of achieving higher-order accuracy in both space and time. Albeit they succeed in achieving an effective higher spatial resolution and in suppressing the numerical damping of waves, to our knowledge, all current astrophysical simulations invoking self-gravity are limited to second-order accuracy in space. If we can devise an algorithm to evaluate self-gravity with a higher-order spatial accuracy, we can better the evaluation of the gravitational acceleration and gravitational energy release which dictate the evolution of many astrophysical systems. Herein, we present a numerical algorithm for self-gravitating hydrodynamics capable of achieving fourth-order accuracy for a given density distribution on a Cartesian uniform grid. First, we derive the cell-averaged gravitational potential at fourth-order accuracy from the cell-averaged density by solving the Poisson equation. Next, we obtain the cell average of the product of the density and gravitational acceleration, which differs from the cell-averaged density multiplied by the cell-averaged gravitational acceleration. We then show the verification of the algorithm by applying it to critical test problems: (1) maintaining equilibria of self-gravitating slabs, even upon advection, (2) evolving a polytropic sphere with a massive power-law envelope, and (3) conservation of specific entropy during the propagation of a sound wave.
Modern astrophysical simulation codes employ a variety of numerical algorithms capable of achieving higher-order accuracy in both space and time. Albeit they succeed in achieving an effective higher spatial resolution and in suppressing the numerical damping of waves, to our knowledge, all current astrophysical simulations invoking self-gravity are limited to second-order accuracy in space. If we can devise an algorithm to evaluate self-gravity with a higher-order spatial accuracy, we can better the evaluation of the gravitational acceleration and gravitational energy release which dictate the evolution of many astrophysical systems. Herein, we present a numerical algorithm for self-gravitating hydrodynamics capable of achieving fourth order accuracy for a given density distribution on a Cartesian uniform grid. First, we derive the cell-averaged gravitational potential at fourth-order accuracy from the cell-averaged density by solving the Poisson equation. Next, we obtain the cell average of the product of the density and gravitational acceleration, which differs from the cell-averaged density multiplied by the cell-averaged gravitational acceleration. We then show the verification of the algorithm by applying it to critical test problems: (1) maintaining equilibria of self-gravitating slabs, even upon advection, (2) evolving a polytropic sphere with a massive power-law envelope, and (3) conservation of specific entropy during the propagation of a sound wave.
Phenomena that involve accelerated ions in stellar processes that can be simulated with laboratory accelerators are described. Stellar evolutionary phases, such as the CNO cycle, have been partially explored with accelerators, up to the consumption of He by alpha particle radiative capture reactions. Further experimentation is indicated on reactions featuring N-13(p,gamma)O-14, O-15(alpha, gamma)Ne-19, and O-14(alpha,p)F-17. Accelerated beams interacting with thin foils produce reaction products that permit a determination of possible elemental abundances in stellar objects. Additionally, isotopic ratios observed in chondrites can be duplicated with accelerator beam interactions and thus constraints can be set on the conditions producing the meteorites. Data from isotopic fractionation from sputtering, i.e., blasting surface atoms from a material using a low energy ion beam, leads to possible models for processes occurring in supernova explosions. Finally, molecules can be synthesized with accelerators and compared with spectroscopic observations of stellar winds.
Our research program is designed to carry out state-of-the-art atomic physics calculations crucial to advancing our understanding of fundamental astrophysical problems. We redress the present inadequacies in the atomic data base along two important areas: dielectronic recombination and inner-shell photoionization and multiple electron ejection/Auger fluorescence therefrom. All of these data are disseminated to the astrophysical community in the proper format for implementation in spectral simulation code.
Nyx is a highly parallel, adaptive mesh, finite-volume N-body compressible hydrodynamics solver for cosmological simulations. It has been used to simulate different cosmological scenarios with a recent focus on the intergalactic medium and Lyman alpha forest. Together, Nyx, the compressible astrophysical simulation code, Castro, and the low Mach number code MAESTROeX, make up the AMReX-Astrophysics Suite of open-source, adaptive mesh, performance-portable astrophysical simulation codes. Other examples of cosmological simulation research codes include Enzo, Enzo-P/Cello, RAMSES, ART, FLASH, Cholla, as well as Gadget, Gasoline, Arepo, Gizmo, and SWIFT.
Neutron star mergers are an important source of information for nuclear physics. Except for black holes, neutron stars are the densest macroscopic objects known to exist in the Universe. They provide us with a remarkable laboratory to study the poorly understood high-density states of matter, complementing the study of heavy nuclei performed by nuclear physics experiments on Earth. Collisions of neutron stars are of particular interest. They are among the most energetic events observable in the Universe, powering a broad range of signals across the electromagnetic spectrum as well as gravitational wave signals. These signals contain important information about the properties of extremely dense matter. Colliding neutron stars additionally eject large amounts of neutron-rich material into the surrounding interstellar medium -- material that then undergoes rapid neutron-capture (r-process) nucleosynthesis, the mechanism thought to be responsible for the production of about half of the heavy nuclei. In order to understand current and future observations of neutron star mergers, we need reliable models for the signals that they power. An important component in the construction of such models are numerical simulations of colliding neutron stars. These simulations are costly, running for multiple months on supercomputers, and require the inclusion of complex physics (general relativity, magnetohydrodynamics, neutrino physics, nuclear reactions). In this document, we describe the development of new methods for the treatment of neutrinos in merger simulations, as well as the first simulations capable of evolving the equations of neutrino radiation transport directly and their impact on our understanding of neutron star mergers and more broadly in nuclear astrophysics. We also discuss additional work performed in the study of nucleosynthesis and neutrino physics in neutron star mergers as part of Early Career Award DE-SC0020435.
Understanding the physical chemical processes which affect the structure and composition of astrophysical ices is of central importance to our understanding of the early solar system and early earth. Laboratory experiments on amorphous ice analogues of cometary ices have shown that amorphous ices exhibit a rich and complex morphology. Computer simulation results for ice deposition with the solutes Ne, CH4, and CO are presented. The relative fraction of adsorbed solutes which are subsequently ejected from the growing ice has implications on the composition of comets relative to the composition of the primitive environment in which they formed.