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Register a new userGLAMER Part I: A Code for Gravitational Lensing Simulations with Adaptive Mesh Refinement
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A computer code is described for the simulation of gravitational lensing data. The code incorporates adaptive mesh refinement in choosing which rays to shoot based on the requirements of the source size, location and surface brightness distribution or to find critical curves/caustics. A variety of source surface brightness models are implemented to represent galaxies and quasar emission regions. The lensing mass can be represented by point masses (stars), smoothed simulation particles, analytic halo models, pixelized mass maps or any combination of these. The deflection and beam distortions (convergence and shear) are calculated by modified tree algorithm when halos, point masses or particles are used and by FFT when mass maps are used. The combination of these methods allow for a very large dynamical range to be represented in a single simulation. Individual images of galaxies can be represented in a simulation that covers many square degrees. For an individual strongly lensed quasar, source sizes from the size of the quasars host galaxy (~ 100 kpc) down to microlensing scales (~ 10^-4 pc) can be probed in a self consistent simulation. Descriptions of various tests of the codes accuracy are given.
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We have developed a simulation code with the techniques which enhance both spatial and time resolution of the PM method for which the spatial resolution is restricted by the spacing of structured mesh. The adaptive mesh refinement (AMR) technique subdivides the cells which satisfy the refinement criterion recursively. The hierarchical meshes are maintained by the special data structure and are modified in accordance with the change of particle distribution. In general, as the resolution of the simulation increases, its time step must be shortened and more computational time is required to complete the simulation. Since the AMR enhances the spatial resolution locally, we reduce the time step locally also, instead of shortening it globally. For this purpose we used a technique of hierarchical time steps (HTS) which changes the time step, from particle to particle, depending on the size of the cell in which particles reside. Some test calculations show that our implementation of AMR and HTS is successful. We have performed cosmological simulation runs based on our code and found that many of halo objects have density profiles which are well fitted to the universal profile proposed by Navarro, Frenk, & White (1996) over the entire range of their radius.
This paper describes the open-source code Enzo, which uses block-structured adaptive mesh refinement to provide high spatial and temporal resolution for modeling astrophysical fluid flows. The code is Cartesian, can be run in 1, 2, and 3 dimensions, and supports a wide variety of physics including hydrodynamics, ideal and non-ideal magnetohydrodynamics, N-body dynamics (and, more broadly, self-gravity of fluids and particles), primordial gas chemistry, optically-thin radiative cooling of primordial and metal-enriched plasmas (as well as some optically-thick cooling models), radiation transport, cosmological expansion, and models for star formation and feedback in a cosmological context. In addition to explaining the algorithms implemented, we present solutions for a wide range of test problems, demonstrate the codes parallel performance, and discuss the Enzo collaborations code development methodology.
We present the newly developed code, GAMER (GPU-accelerated Adaptive MEsh Refinement code), which has adopted a novel approach to improve the performance of adaptive mesh refinement (AMR) astrophysical simulations by a large factor with the use of the graphic processing unit (GPU). The AMR implementation is based on a hierarchy of grid patches with an oct-tree data structure. We adopt a three-dimensional relaxing TVD scheme for the hydrodynamic solver, and a multi-level relaxation scheme for the Poisson solver. Both solvers have been implemented in GPU, by which hundreds of patches can be advanced in parallel. The computational overhead associated with the data transfer between CPU and GPU is carefully reduced by utilizing the capability of asynchronous memory copies in GPU, and the computing time of the ghost-zone values for each patch is made to diminish by overlapping it with the GPU computations. We demonstrate the accuracy of the code by performing several standard test problems in astrophysics. GAMER is a parallel code that can be run in a multi-GPU cluster system. We measure the performance of the code by performing purely-baryonic cosmological simulations in different hardware implementations, in which detailed timing analyses provide comparison between the computations with and without GPU(s) acceleration. Maximum speed-up factors of 12.19 and 10.47 are demonstrated using 1 GPU with 4096^3 effective resolution and 16 GPUs with 8192^3 effective resolution, respectively.
We have explored the evolution of gas distributions from cosmological simulations carried out using the RAMSES adaptive mesh refinement (AMR) code, to explore the effects of resolution on cosmological hydrodynamical simulations. It is vital to understand the effect of both the resolution of initial conditions and the final resolution of the simulation. Lower initial resolution simulations tend to produce smaller numbers of low mass structures. This will strongly affect the assembly history of objects, and has the same effect of simulating different cosmologies. The resolution of initial conditions is an important factor in simulations, even with a fixed maximum spatial resolution. The power spectrum of gas in simulations using AMR diverges strongly from the fixed grid approach - with more power on small scales in the AMR simulations - even at fixed physical resolution and also produces offsets in the star formation at specific epochs. This is because before certain times the upper grid levels are held back to maintain approximately fixed physical resolution, and to mimic the natural evolution of dark matter only simulations. Although the impact of hold back falls with increasing spatial and initial-condition resolutions, the offsets in the star formation remain down to a spatial resolution of 1 kpc. These offsets are of order of 10-20%, which is below the uncertainty in the implemented physics but are expected to affect the detailed properties of galaxies. We have implemented a new grid-hold-back approach to minimize the impact of hold back on the star formation rate.
A new numerical code, called SFUMATO, for solving self-gravitational magnetohydrodynamics (MHD) problems using adaptive mesh refinement (AMR) is presented. A block-structured grid is adopted as the grid of the AMR hierarchy. The total variation diminishing (TVD) cell-centered scheme is adopted as the MHD solver, with hyperbolic cleaning of divergence error of the magnetic field also implemented. The self-gravity is solved by a multigrid method composed of (1) full multigrid (FMG)-cycle on the AMR hierarchical grids, (2) V-cycle on these grids, and (3) FMG-cycle on the base grid. The multigrid method exhibits spatial second-order accuracy, fast convergence, and scalability. The numerical fluxes are conserved by using a refluxing procedure in both the MHD solver and the multigrid method. The several tests are performed indicating that the solutions are consistent with previously published results.
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