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Particle smoothing methods are used for inference of stochastic processes based on noisy observations. Typically, the estimation of the marginal posterior distribution given all observations is cumbersome and computational intensive. In…

机器学习 · 计算机科学 2017-05-24 H. -Ch. Ruiz , H. J. Kappen

We formulate a general method for perturbative evaluations of statistics of smoothed cosmic fields, and provide useful formulas in application of the perturbation theory to various statistics. This formalism is an extensive generalization…

天体物理学 · 物理学 2007-05-23 Takahiko Matsubara

The gravitational evolution of the genus and other statistics of isodensity contours of the density field is derived analytically in a weakly nonlinear regime using second-order perturbation theory. The effect of final smoothing in…

天体物理学 · 物理学 2016-08-30 Takahiko Matsubara

Snow density estimates as a function of depth are used for understanding climate processes, evaluating water accumulation trends in polar regions, and estimating glacier mass balances. The common and interpretable physically-derived…

统计方法学 · 统计学 2021-06-22 Philip White , Durban Keeler , Daniel Sheanshang , Summer Rupper

Using a perturbation technique, we derive a new approximate filtering and smoothing methodology generalizing along different directions several existing approaches to robust filtering based on the score and the Hessian matrix of the…

统计方法学 · 统计学 2023-06-06 Giuseppe Buccheri , Giacomo Bormetti , Fulvio Corsi , Fabrizio Lillo

Smoothed Particle Hydrodynamics (SPH) is a Lagrangian method for solving the fluid equations that is commonplace in astrophysics, prized for its natural adaptivity and stability. The choice of variable to smooth in SPH has been the topic of…

星系天体物理 · 物理学 2021-05-26 Josh Borrow , Matthieu Schaller , Richard G. Bower

Modulating the number of particles in a region is key to accurately capturing the nuances in compressible flows with Smoothed Particle Hydrodynamics (SPH). This paper presents a volume-based adaptive refinement and derefinement procedure,…

流体动力学 · 物理学 2025-08-08 Navaneet Villodi , Prabhu Ramachandran

This paper discusses a general framework for smoothing parameter estimation for models with regular likelihoods constructed in terms of unknown smooth functions of covariates. Gaussian random effects and parametric terms may also be…

统计方法学 · 统计学 2016-05-10 Simon N. Wood , Natalya Pya , Benjamin Säfken

The numerical accuracy of particle-based approximations in Smoothed Particle Hydrodynamics (SPH) is significantly affected by the spatial uniformity of particle distributions, especially for second-order derivatives. This study aims to…

数值分析 · 数学 2026-01-29 Zhonghua Qiao , Yifan Wei

Weak gravitational lensing surveys are rapidly becoming important tools to probe directly the mass density fluctuations in the universe and its background dynamics. Earlier studies have shown that it is possible to model the statistics of…

天体物理学 · 物理学 2009-11-07 Patrick Valageas , Andrew J. Barber , Dipak Munshi

The smoothing spline is one of the most popular curve-fitting methods, partly because of empirical evidence supporting its effectiveness and partly because of its elegant mathematical formulation. However, there are two obstacles that…

统计理论 · 数学 2012-09-11 Yu Ryan Yue , Daniel Simpson , Finn Lindgren , Håvard Rue

The weakly compressible Smoothed Particle Hydrodynamics (SPH) is known to suffer from the pressure oscillation, which would undermine the simulation stability and accuracy. To address this issue, we propose a generalized density dissipation…

流体动力学 · 物理学 2023-08-30 Bo Xue Zheng , Zhi Wen Cai , Pei Dong Zhao , Xiao Yang Xu , Tak Shing Chan , Peng Yu

The smoothed particle hydrodynamics (SPH) method has been increasingly used to study fluid problems in recent years; but its computational cost can be high if high resolution is required. In this study, an adaptive resolution method based…

计算物理 · 物理学 2019-01-23 Xiufeng Yang , Song-Charng Kong

A new consistent, spatially adaptive, smoothed particle hydrodynamics (SPH) method for Fluid-Structure Interactions (FSI) is presented. The method combines several attributes that have not been simultaneously satisfied by other SPH methods.…

流体动力学 · 物理学 2019-02-20 Wei Hu , Guannan Guo , Xiaozhe Hu , Dan Negrut , Zhijie Xu , Wenxiao Pan

Smoothed particle hydrodynamics is a particle-based, fully Lagrangian, method for fluid-flow simulations. In this work, fundamental concepts of the method are first briefly recalled. Then, we present a thorough comparison of three different…

流体动力学 · 物理学 2012-08-22 Kamil Szewc , Jacek Pozorski , Jean-Pierre Minier

The smoothed particle hydrodynamics (SPH) method is a useful numerical tool for the study of a variety of astrophysical and planetlogical problems. However, it turned out that the standard SPH algorithm has problems in dealing with…

天体物理仪器与方法 · 物理学 2015-06-16 Natsuki Hosono , Takayuki R. Saitoh , Junichiro Makino

The smoothed particle hydrodynamics (SPH) method has been widely used to simulate incompressible and slightly compressible fluid flows. Adaptive refinement strategies to dynamically increase the resolution of the particles to capture sharp…

流体动力学 · 物理学 2024-07-31 Abhinav Muta , Pawan Negi , Prabhu Ramachandran

Smoothed particle hydrodynamics (SPH) has been extensively studied in computer graphics to animate fluids with versatile effects. However, SPH still suffers from two numerical difficulties: the particle deficiency problem, which will…

图形学 · 计算机科学 2020-01-29 Xiaowei He , Huamin Wang , Guoping Wang , Hongan Wang , Enhua Wu

It has been shown that the large--scale correlation functions of the density field (and velocity divergence field) follow a specific hierarchy in the quasilinear regime and for Gaussian initial conditions (Bernardeau 1992). The exact…

天体物理学 · 物理学 2007-05-23 F. Bernardeau

In this paper we present solutions to three short comings of Smoothed Particles Hydrodynamics (SPH) encountered in previous work when applying it to Giant Impacts. First we introduce a novel method to obtain accurate SPH representations of…

地球与行星天体物理 · 物理学 2017-03-29 Christian Reinhardt , Joachim Stadel
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