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相关论文: Simulating Cosmological Evolution with Enzo

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We investigate the observational tests of generalized mass-to-horizon entropic cosmology by incorporating large-scale structure growth data in addition to purely geometric probes. The theoretical framework is constructed from a generalized…

广义相对论与量子宇宙学 · 物理学 2026-03-09 Tomasz Denkiewicz , Hussain Gohar

I present a large set of high resolution simulations, called CosmicGrowth Simulations, which were generated with either 8.6 billion or 29 billion particles. As the nominal cosmological model that can match nearly all observations on…

宇宙学与河外天体物理 · 物理学 2018-08-28 Y. P. Jing

Despite advances in climate modeling, simulating the El Ni\~no-Southern Oscillation (ENSO) remains challenging due to its spatiotemporal diversity and complexity. To address this, we build upon existing model hierarchies to develop a new…

大气与海洋物理 · 物理学 2025-03-27 Jinyu Wang , Xianghui Fang , Nan Chen , Bo Qin , Mu Mu , Chaopeng Ji

Cloud computing offers an opportunity to run compute-resource intensive climate models at scale by parallelising model runs such that datasets useful to the exoplanet community can be produced efficiently. To better understand the…

Modern sky surveys are returning precision measurements of cosmological statistics such as weak lensing shear correlations, the distribution of galaxies, and cluster abundance. To fully exploit these observations, theorists must provide…

宇宙学与河外天体物理 · 物理学 2015-06-15 Katrin Heitmann , Earl Lawrence , Juliana Kwan , Salman Habib , David Higdon

We study multidimensional cosmological models with a higher-dimensional product manifold, that consists of spherical and flat spaces, in the presence of a minimal free scalar field. Dynamical behaviour of the model is analyzed both in…

广义相对论与量子宇宙学 · 物理学 2007-05-23 Baukh Victor

Simulations of frames from existing and upcoming high-resolution spectrographs, targeted for high accuracy radial velocity measurements, are computationally demanding (both in time and space). We present in this paper an innovative approach…

天体物理仪器与方法 · 物理学 2020-08-14 M. Genoni , M. Landoni , G. Pariani , M. Riva , A. Bianco , G. Li Causi , T. Marquart , F. A. Pepe , A. Marconi , E. Oliva

Cosmological N-Body simulations have become an essential tool for studying formation of large scale structure. These simulations are computationally challenging even though the available computing power gets better every year. A number of…

天体物理学 · 物理学 2007-05-23 J. S. Bagla

Obtaining the set of cosmological parameters consistent with observational data is an important exercise in current cosmological research. It involves finding the global maximum of the likelihood function in the multi-dimensional parameter…

宇宙学与河外天体物理 · 物理学 2012-07-03 Jayanti Prasad , Tarun Souradeep

In this paper, we have investigated some accelerating cosmological models at the backdrop of an anisotropic metric in an extended gravity theory. Two viable cosmological models one with a little rip behaviour and the other with a hyperbolic…

广义相对论与量子宇宙学 · 物理学 2020-09-23 B. Mishra , S. K. Tripathy

We introduce the public version of the cosmological magnetohydrodynamical moving-mesh simulation code Arepo. This version contains a finite-volume magnetohydrodynamics algorithm on an unstructured, dynamic Voronoi tessellation coupled to a…

天体物理仪器与方法 · 物理学 2020-06-17 Rainer Weinberger , Volker Springel , Rüdiger Pakmor

We present results from seven cosmological simulations that have been extended beyond the present era as far as redshift $z=-0.995$ or $t\approx96\,{\rm Gyr}$, using the Enzo simulation code. We adopt the calibrated star formation and…

星系天体物理 · 物理学 2021-10-27 Boon Kiat Oh , John A. Peacock , Sadegh Khochfar , Britton D. Smith

We present cosmo_learn, an open-source python-based software package designed to simulate cosmological data and perform data-driven inference using a range of modern statistical and machine learning techniques. Motivated by the growing…

We compare two cosmological hydrodynamic simulation codes in the context of hierarchical galaxy formation: The SPH code GADGET, and the Eulerian AMR code ENZO. Both codes represent dark matter with the N-body method, but use different…

天体物理学 · 物理学 2009-11-10 Brian W. O'Shea , Kentaro Nagamine , Volker Springel , Lars Hernquist , Michael L. Norman

We describe an extension of the cosmological hydrodynamics code ENZO to include the self-consistent transport of ionizing radiation modeled in the flux-limited diffusion approximation. A novel feature of our algorithm is a coupled implicit…

天体物理仪器与方法 · 物理学 2015-05-13 Michael L. Norman , Daniel R. Reynolds , Geoffrey C. So

Cosmological simulations are the key tool for investigating the different processes involved in the formation of the universe from small initial density perturbations to galaxies and clusters of galaxies observed today. The identification…

宇宙学与河外天体物理 · 物理学 2015-05-13 Steffen R. Knollmann , Alexander Knebe

This paper describes the architecture and demonstrates the capabilities of a newly developed, physically-based imaging simulator environment called SISPO, developed for small solar system body fly-by and terrestrial planet surface mission…

Inspired by recent advances in observational astrophysics and continued explorations in the field of analog gravity, we discuss the prospect of simulating models of cosmology within the context of synthetic mechanical lattice experiments.…

介观与纳米尺度物理 · 物理学 2025-04-22 Brendan Rhyno , Ivan Velkovsky , Peter Adshead , Bryce Gadway , Smitha Vishveshwara

I survey the use and impact of adaptive mesh refinement (AMR) simulations in numerical astrophysics and cosmology. Two basic techniques are in use to extend the dynamic range of Eulerian grid simulations in multi-dimensions: cell…

天体物理学 · 物理学 2007-05-23 Michael L. Norman

Modern cosmological observations allow us to study in great detail the evolution and history of the large scale structure hierarchy. The fundamental problem of accurate constraints on the cosmological parameters, within a given cosmological…

天体物理学 · 物理学 2009-11-13 K. Dolag , S. Borgani , S. Schindler , A. Diaferio , A. M. Bykov