English
Related papers

Related papers: Dynamic renormalization-group approach to diffusiv…

200 papers

Diffusion models have emerged as potential tools to tackle the challenge of sparse-view CT reconstruction, displaying superior performance compared to conventional methods. Nevertheless, these prevailing diffusion models predominantly focus…

Image and Video Processing · Electrical Eng. & Systems 2023-09-06 Kai Xu , Shiyu Lu , Bin Huang , Weiwen Wu , Qiegen Liu

We study the renormalization group flow of higher derivative gravity, utilizing the functional renormalization group equation for the average action. Employing a recently proposed algorithm, termed the universal renormalization group…

High Energy Physics - Theory · Physics 2012-02-29 F. Saueressig , K. Groh , S. Rechenberger , O. Zanusso

Radiative transfer plays a key role in the star formation process. Due to a high computational cost, radiation-hydrodynamics simulations performed up to now have mainly been carried out in the grey approximation. In recent years,…

Instrumentation and Methods for Astrophysics · Physics 2015-05-27 Matthias González , Neil Vaytet , Benoît Commerçon , Jacques Masson

Methods to solve the relativistic hydrodynamic equations are a key computational kernel in a large number of astrophysics simulations and are crucial to understanding the electromagnetic signals that originate from the merger of…

Instrumentation and Methods for Astrophysics · Physics 2015-12-02 Jackson DeBuhr , Bo Zhang , Matthew Anderson , David Neilsen , Eric W. Hirschmann

Stable and accurate finite element methods are presented for Darcy flow in heterogeneous porous media with an interface of discontinuity of the hydraulic conductivity tensor. Accurate velocity fields are computed through global or local…

Numerical Analysis · Mathematics 2025-05-26 Maicon R. Correa , Abimael F. D. Loula

A new numerical method for the solution of the Dynamical Mean Field Theory's self-consistent equations is introduced. The method uses the Density Matrix Renormalization Group technique to solve the associated impurity problem. The new…

Strongly Correlated Electrons · Physics 2016-08-31 Daniel J. Garcia , Karen Hallberg , Marcelo J. Rozenberg

The recursion relations of hierarchical models are studied and contrasted with functional renormalisation group equations in corresponding approximations. The formalisms are compared quantitatively for the Ising universality class, where…

High Energy Physics - Theory · Physics 2008-11-26 Daniel F. Litim

This paper addresses the problem of generating dynamically admissible trajectories for control tasks using diffusion models, particularly in scenarios where the environment is complex and system dynamics are crucial for practical…

Robotics · Computer Science 2025-10-15 Darshan Gadginmath , Fabio Pasqualetti

We study the slightly compressible Darcy-Forchheimer equations modeling gas flow in porous media, particularly in applications related to combustion processes. The equations are discretized in time using the backward Euler method and in…

Numerical Analysis · Mathematics 2026-04-16 Laura Portero , Andrés Arrarás , Francisco J. Gaspar , Florin A. Radu

A new algorithm, "HiER-leap", is derived which improves on the computational properties of the ER-leap algorithm for exact accelerated simulation of stochastic chemical kinetics. Unlike ER-leap, HiER-leap utilizes a hierarchical or…

Molecular Networks · Quantitative Biology 2012-12-18 David Orendorff , Eric Mjolsness

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a…

Computational Physics · Physics 2017-12-06 Horacio V. Guzman , Christoph Junghans , Kurt Kremer , Torsten Stuehn

Adapting pretrained diffusion models to downstream objectives such as inverse problems often requires expensive test-time guidance or optimization. We propose a principled framework for generating high-quality reward-aligned samples at…

Machine Learning · Computer Science 2026-05-22 Kushagra Pandey , Farrin Marouf Sofian , Jan Niklas Groeneveld , Felix Draxler , Stephan Mandt

Many applications of computational fluid dynamics require multiple simulations of a flow under different input conditions. In this paper, a numerical algorithm is developed to efficiently determine a set of such simulations in which the…

Numerical Analysis · Mathematics 2017-05-29 Max Gunzburger , Nan Jiang , Zhu Wang

We propose a density matrix renormalization group approach to tackle a two-state system coupled to a bosonic bath with continuous spectrum. In this approach, the optimized phonon scheme is applied to several hundred phonon modes which are…

Strongly Correlated Electrons · Physics 2008-05-31 Hang Wong , Zhi-De Chen

This paper is concerned with probabilistic techniques for forecasting dynamical systems described by partial differential equations (such as, for example, the Navier-Stokes equations). In particular, it is investigating and comparing…

Machine Learning · Computer Science 2025-11-07 Hans Harder , Abhijeet Vishwasrao , Luca Guastoni , Ricardo Vinuesa , Sebastian Peitz

We present simulations of coherent structures in compressible flows near the transition to turbulence using the Dissipative Particle Dynamics (DPD) method. The structures we find are remarkably consistent with experimental observations and…

The renormalization-group method is used to analyze the low-temperature behaviour of a two-dimentional, spin-$s$ quantum Heisenberg ferromagnet. A set of recursion equations is derived in an one-loop approximation. The low-temperature…

Condensed Matter · Physics 2009-10-28 Naoum Karchev

The high-pressure transportation process of pipeline necessitates an accurate hydraulic transient simulation tool to prevent slack line flow and over-pressure, which can endanger pipeline operations. However, current numerical solution…

Computational Engineering, Finance, and Science · Computer Science 2024-09-18 Jian Du , Haochong Li , Qi Liao , Jun Shen , Jianqin Zheng , Yongtu Liang

This paper describes a hierarchical learning strategy for generating sparse representations of multivariate datasets. The hierarchy arises from approximation spaces considered at successively finer scales. A detailed analysis of stability,…

Machine Learning · Statistics 2019-10-23 Prashant Shekhar , Abani Patra

A wealth of cosmological and astrophysical information is expected from many ongoing and upcoming large-scale surveys. It is crucial to prepare for these surveys now and develop tools that can efficiently extract most information. We…

‹ Prev 1 8 9 10 Next ›