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Register a new userA Co-Scaling Grid for Athena++
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We present a co-scaling grid formalism and its implementation in the magnetohydrodynamics code Athena++. The formalism relies on flow symmetries in astrophysical problems involving expansion, contraction, and center-of-mass motion. The grid is evolved at the same time order as the fluid variables. The user specifies grid evolution laws, which can be independent of the fluid motion. Applying our implementation to standard hydrodynamic test cases leads to improved results and higher efficiency, compared to the fixed-grid solutions.
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We present modifications to the Athena++ framework to enable use of general equations of state (EOS). Part of our motivation for doing so is to model transient astrophysics phenomena, as these types of events are often not well approximated by an ideal gas. This necessitated changes to the Riemann solvers implemented in Athena++. We discuss the adjustments made to the HLLC, and HLLD solvers and EOS calls required for arbitrary EOS. We demonstrate the reliability of our code in a number of tests which utilize a relatively simple, but non-trivial EOS based on hydrogen ionization, appropriate for the transition from atomic to ionized hydrogen. Additionally, we perform tests using an electron-positron Helmholtz EOS, appropriate for regimes where nuclear statistical equilibrium is a good approximation. These new complex EOS tests overall show that our modifications to Athena++ accurately solve the Riemann problem with linear convergence and linear-wave tests with quadratic convergence. We provide our test solutions as a means to check the accuracy of other hydrodynamic codes. Our tests and additions to Athena++ will enable further research into (magneto)hydrodynamic problems where realistic treatments of the EOS are required.
We report on the latest additions to our open-source, block-grid adaptive framework MPI-AMRVAC, which is a general toolkit for especially hyperbolic/parabolic partial differential equations (PDEs). Applications traditionally focused on shock-dominated, magnetized plasma dynamics described by either Newtonian or special relativistic (magneto)hydrodynamics, but its versatile design easily extends to different PDE systems. Here, we demonstrate applications covering any-dimensional scalar to system PDEs, with e.g. Korteweg-de Vries solutions generalizing early findings on soliton behaviour, shallow water applications in round or square pools, hydrodynamic convergence tests as well as challenging computational fluid and plasma dynamics applications. The recent addition of a parallel multigrid solver opens up new avenues where also elliptic constraints or stiff source terms play a central role. This is illustrated here by solving several multi-dimensional reaction-diffusion-type equations. We document the minimal requirements for adding a new physics module governed by any nonlinear PDE system, such that it can directly benefit from the code flexibility in combining various temporal and spatial discretisation schemes. Distributed through GitHub, MPI-AMRVAC can be used to perform 1D, 1.5D, 2D, 2.5D or 3D simulations in Cartesian, cylindrical or spherical coordinate systems, using parallel domain-decomposition, or exploiting fully dynamic block quadtree-octree grids.
The design and implementation of a new framework for adaptive mesh refinement (AMR) calculations is described. It is intended primarily for applications in astrophysical fluid dynamics, but its flexible and modular design enables its use for a wide variety of physics. The framework works with both uniform and nonuniform grids in Cartesian and curvilinear coordinate systems. It adopts a dynamic execution model based on a simple design called a task list that improves parallel performance by overlapping communication and computation, simplifies the inclusion of a diverse range of physics, and even enables multiphysics models involving different physics in different regions of the calculation. We describe physics modules implemented in this framework for both non-relativistic and relativistic magnetohydrodynamics (MHD). These modules adopt mature and robust algorithms originally developed for the Athena MHD code and incorporate new extensions: support for curvilinear coordinates, higher-order time integrators, more realistic physics such as a general equation of state, and diffusion terms that can be integrated with super-time-stepping algorithms. The modules show excellent performance and scaling, with well over 80% parallel efficiency on over half a million threads. The source code has been made publicly available.
We present a test platform for the Athena X-IFU detection chain, which will serve as the first demonstration of the representative end-to-end detection and readout chain for the X-IFU, using prototypes of the future flight electronics and currently available subsystems. This test bench, housed in a commercial two-stage ADR cryostat, includes a focal plane array placed at the 50 mK cold stage of the ADR with a kilopixel array of transition-edge sensor microcalorimeter spectrometers and associated cold readout electronics. Prototype room temperature electronics for the X-IFU provide the readout, and will evolve over time to become more representative of the X-IFU mission baseline. The test bench yields critical feedback on subsystem designs and interfaces, in particular the warm readout electronics, and will provide an in-house detection system for continued testing and development of the warm readout electronics and for the validation of X-ray calibration sources. In this paper, we describe the test bench subsystems and design, characterization of the cryostat, and current status of the project.
The next generation of High Energy Physics experiments requires a GRID approach to a distributed computing system and the associated data management: the key concept is the Virtual Organisation (VO), a group of geographycally distributed users with a common goal and the will to share their resources. A similar approach is being applied to a group of Hospitals which joined the GPCALMA project (Grid Platform for Computer Assisted Library for MAmmography), which will allow common screening programs for early diagnosis of breast and, in the future, lung cancer. HEP techniques come into play in writing the application code, which makes use of neural networks for the image analysis and shows performances similar to radiologists in the diagnosis. GRID technologies will allow remote image analysis and interactive online diagnosis, with a relevant reduction of the delays presently associated to screening programs.
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