Browsing by Subject "CODE"
Now showing items 1-6 of 6
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(2021)We present a new, updated version of the EuclidEmulator (called EuclidEmulator2), a fast and accurate predictor for the nonlinear correction of the matter power spectrum. 2 per cent level accurate emulation is now supported in the eight-dimensional parameter space of w(0)w(a)CDM+Sigma m(nu) models between redshift z = 0 and z = 3 for spatial scales within the range . In order to achieve this level of accuracy, we have had to improve the quality of the underlying N-body simulations used as training data: (i) we use self-consistent linear evolution of non-dark matter species such as massive neutrinos, photons, dark energy, and the metric field, (ii) we perform the simulations in the so-called N-body gauge, which allows one to interpret the results in the framework of general relativity, (iii) we run over 250 high-resolution simulations with 3000(3) particles in boxes of 1(h(-1)Gpc)(3) volumes based on paired-and-fixed initial conditions, and (iv) we provide a resolution correction that can be applied to emulated results as a post-processing step in order to drastically reduce systematic biases on small scales due to residual resolution effects in the simulations. We find that the inclusion of the dynamical dark energy parameter w(a) significantly increases the complexity and expense of creating the emulator. The high fidelity of EuclidEmulator2 is tested in various comparisons against N-body simulations as well as alternative fast predictors such as HALOFIT, HMCode, and CosmicEmu. A blind test is successfully performed against the Euclid Flagship v2.0 simulation. Nonlinear correction factors emulated with EuclidEmulator2 are accurate at the level of or better for and z
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(2017)We focus on implementing and optimizing a sixth-order finite-difference solver for simulating compressible fluids on a GPU using third-order Runge-Kutta integration. Since graphics processing units perform well in data-parallel tasks, this makes them an attractive platform for fluid simulation. However, high-order stencil computation is memory-intensive with respect to both main memory and the caches of the GPU. We present two approaches for simulating compressible fluids using 55-point and 19-point stencils. We seek to reduce the requirements for memory bandwidth and cache size in our methods by using cache blocking and decomposing a latency-bound kernel into several bandwidth-bound kernels. Our fastest implementation is bandwidth-bound and integrates 343 million grid points per second on a Tesla K40t GPU, achieving a 3.6x speedup over a comparable hydrodynamics solver benchmarked on two Intel Xeon E5-2690v3 processors. Our alternative GPU implementation is latency-bound and achieves the rate of 168 million updates per second. (C) 2017 Elsevier B.V. All rights reserved.
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(2020)We present the novel algorithmically regularized integration method MSTAR for high-accuracy (vertical bar Delta E/E vertical bar greater than or similar to 10(-14)) integrations of N-body systems using minimum spanning tree coordinates. The twofold parallelization of the O(N-part(2)) force loops and the substep divisions of the extrapolation method allow for a parallel scaling up to N-CPU = 0.2 x N-part. The efficient parallel scaling of MSTAR makes the accurate integration of much larger particle numbers possible compared to the traditional algorithmic regularization chain (AR-CHAIN) methods, e.g. N-part = 5000 particles on 400 CPUs for 1 Gyr in a few weeks of wall-clock time. We present applications of MSTAR on few particle systems, studying the Kozai mechanism and N-body systems like star clusters with up to N-part = 10(4) particles. Combined with a tree or fast multipole-based integrator, the high performance of MSTAR removes a major computational bottleneck in simulations with regularized subsystems. It will enable the next-generation galactic-scale simulations with up to 109 stellar particles (e.g. m(star) = 100 M-circle dot) for an M-star = 10(11) M-circle dot galaxy), including accurate collisional dynamics in the vicinity of nuclear supermassive black holes.
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(2021)Generating pre-initial conditions (or particle loads) is the very first step to set up a cosmological N-body simulation. In this work, we revisit the numerical convergence of pre-initial conditions on dark matter halo properties using a set of simulations which only differs in initial particle loads, i.e. grid, glass, and the newly introduced capacity constrained Voronoi tessellation (CCVT). We find that the median halo properties agree fairly well (i.e. within a convergence level of a few per cent) among simulations running from different initial loads. We also notice that for some individual haloes cross-matched among different simulations, the relative difference of their properties sometimes can be several tens of per cent. By looking at the evolution history of these poorly converged haloes, we find that they are usually merging haloes or haloes have experienced recent merger events, and their merging processes in different simulations are out-of-sync, making the convergence of halo properties become poor temporarily. We show that, comparing to the simulation starting with an anisotropic grid load, the simulation with an isotropic CCVT load converges slightly better to the simulation with a glass load, which is also isotropic. Among simulations with different pre-initial conditions, haloes in higher density environments tend to have their properties converged slightly better. Our results confirm that CCVT loads behave as well as the widely used grid and glass loads at small scales, and for the first time we quantify the convergence of two independent isotropic particle loads (i.e. glass and CCVT) on halo properties.
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(2018)A theoretical framework for emission originating from rapidly rotating oblate compact objects is described in detail. Using a Hamilton-Jacobi formalism, we show that special relativistic rotational effects such as aberration of angles, Doppler boosting, and time dilatation naturally emerge from the general relativistic treatment of rotating compact objects. We use the Butterworth-Ipser metric expanded up to the second order in rotation and hence include effects of light bending, frame-dragging, and quadrupole deviations on our geodesic calculations. We also give detailed descriptions of the numerical algorithms used and provide an open-source implementation of the numerical framework called BENDER. As an application, we study spectral line profiles (i.e., smearing kernels) from rapidly rotating oblate neutron stars. We find that in this metric description, the second-order quadrupole effects are not strong enough to produce narrow observable features in the spectral energy distribution for almost any physically realistic parameter combination, and hence, actually detecting them is unlikely. The full width at tenth-maximum and full width at half-maximum of the rotation smearing kernels are also reported for all viewing angles. These can then be used to quantitatively estimate the effects of rotational smearing on the observed spectra. We also calculate accurate pulse profiles and observer skymaps of emission from hot spots on rapidly rotating accreting millisecond pulsars. These allow us to quantify the strength of the pulse fractions one expects to observe from typical fast-spinning millisecond pulsars.
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(2017)Ion beam processing of surfaces is well known to lead to sputtering, which conventionally is associated only with erosion of atoms from the material. We show here, by combination of experiments and a newly developed Monte Carlo algorithm, that in the case of nanoparticles in a regular two-dimensional array on surfaces, the redeposition of sputtered atoms may play a significant role on the system development. The simulations are directly compared to in situ experiments obtained using a dual focused Ga+ ion beam system and high resolution scanning electron microscopy, and explain the size evolution by a combination of sputtering and redeposition of sputtered material on neighboring particles. The effect is found to be dependent on the size of the nanoparticles: if the nanoparticle size is comparable to the ion range, the reposition is negligible. For larger nanoparticles the redeposition becomes significant and is able to compensate up to 20% of the sputtered material, effectively reducing the process of sputtering. The redeposition may even lead to significant growth: this was seen for the nanoparticles with the sizes much smaller than the ion range. Furthermore, the algorithm shows that significant redeposition is possible when the large size neighboring nanoparticles are present.
