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Computation of vorticity in conjunction with the strain rate tensor, plays an important role in fluid mechanics in vortical structure identification and in the modeling of various complex fluids. For the simulation of flows accompanied by…

Fluid Dynamics · Physics 2019-08-20 Farzaneh Hajabdollahi , Kannan N. Premnath

Two-level stochastic optimization formulations have become instrumental in a number of machine learning contexts such as continual learning, neural architecture search, adversarial learning, and hyperparameter tuning. Practical stochastic…

Optimization and Control · Mathematics 2023-11-08 Tommaso Giovannelli , Griffin Dean Kent , Luis Nunes Vicente

The Bethe-Salpeter equation (BSE) is currently the state of the art in the description of neutral electron excitations in both solids and large finite systems. It is capable of accurately treating charge-transfer excitations that present…

In this paper, a new progressive mesh algorithm is introduced in order to perform fast physical simulations by the use of a lattice Boltzmann method (LBM) on a single-node multi-GPU architecture. This algorithm is able to mesh automatically…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-10-14 Julien Duchateau , François Rousselle , Nicolas Maquignon , Gilles Roussel , Christophe Renaud

Iterative methods based on tensors have emerged as powerful tools for solving tensor equations, and have significantly advanced across multiple disciplines. In this study, we propose two-step tensor-based iterative methods to solve the…

Numerical Analysis · Mathematics 2025-02-07 Ratikanta Behera , Saroja Kumar Panda , Jajati Keshari Sahoo

In this work, we present a method for minimizing the time required for a redundant dual-arm robot to follow a desired relative Cartesian path at constant path speed by optimizing its joint trajectories, subject to position, velocity, and…

Robotics · Computer Science 2025-06-05 Jonathan Fried , Santiago Paternain

We present the Multilevel Bregman Proximal Gradient Descent (ML BPGD) method, a novel multilevel optimization framework tailored to constrained convex problems with relative Lipschitz smoothness. Our approach extends the classical…

Optimization and Control · Mathematics 2026-05-06 Yara Elshiaty , Stefania Petra

Traditional Monte Carlo methods for particle transport utilize source iteration to express the solution, the flux density, of the transport equation as a Neumann series. Our contribution is to show that the particle paths simulated within…

Probability · Mathematics 2024-07-03 J. Darby Smith , Rich Lehoucq , Brian Franke

In this work, we propose a family of single-node second-order boundary schemes for the lattice Boltzmann method with general collision terms. The construction of the schemes is quite universal and simple, it does not involve concrete…

Computational Physics · Physics 2017-12-27 Weifeng Zhao , Wen-An Yong

A method is presented for calculating solutions to differential equations analytically for a variety of problems in physics. An iteration procedure based on the recently proposed BLUES (Beyond Linear Use of Equation Superposition) function…

Pattern Formation and Solitons · Physics 2020-12-09 Jonas Berx , Joseph O. Indekeu

The analysis of second-order optimization methods based either on sub-sampling, randomization or sketching has two serious shortcomings compared to the conventional Newton method. The first shortcoming is that the analysis of the iterates…

Optimization and Control · Mathematics 2024-04-05 Nick Tsipinakis , Panos Parpas

Multitask learning (MTL) can utilize the relatedness between multiple tasks for performance improvement. The advent of multimodal data allows tasks to be referenced by multiple indices. High-order tensors are capable of providing efficient…

Machine Learning · Computer Science 2023-08-23 Jiani Liu , Qinghua Tao , Ce Zhu , Yipeng Liu , Johan A. K. Suykens

Seismic traveltime tomography represents a popular and useful tool for unravelling the structure of the subsurface across the scales. In this work we address the case where the forward model is represented by the eikonal equation and derive…

Geophysics · Physics 2025-08-21 Andrea Zunino , Scott Keating , Andreas Fichtner

An update of the ODEtools Maple package, for the analytical solving of 1st and 2nd order ODEs using Lie group symmetry methods, is presented. The set of routines includes an ODE-solver and user-level commands realizing most of the relevant…

General Relativity and Quantum Cosmology · Physics 2009-10-30 E. S. Cheb-Terrab , L. G. S. Duarte , L. A. C. P. da Mota

In this paper we consider multi-stages traffic assignment with several demand layers, user types and network types. We consider two stages: demand matrix calculation (Entropy Wilson's model) and traffic assignment models (Beckmann or…

In this paper, we study a spline collocation method for a numerical solution to the optimal transport problem We mainly solve the \MAE with the second boundary condition numerically by proposing a center matching algorithm. We prove a…

Numerical Analysis · Mathematics 2023-10-27 Ming-Jun Lai , Jinsil Lee

Partial differential equations (PDE) often involve parameters, such as viscosity or density. An analysis of the PDE may involve considering a large range of parameter values, as occurs in uncertainty quantification, control and…

Numerical Analysis · Mathematics 2017-09-28 Max Gunzburger , Nan Jiang , Michael Schneier

In transport theory, physical phenomena are well described using the Boltzmann equation, which is efficiently simulated and discretized with the lattice Boltzmann method. The collision step defines the microscopic molecules behavior, and…

A collision-based hybrid algorithm for the discrete ordinates approximation of the neutron transport equation is extended to the multigroup setting. The algorithm uses discrete energy and angle grids at two different resolutions and…

Computational Physics · Physics 2022-12-05 Ben Whewell , Ryan G. McClarren , Cory D. Hauck , Minwoo Shin

In this paper, we explore a specific optimization problem that combines a differentiable nonconvex function with a nondifferentiable function for multi-block variables, which is particularly relevant to tackle the multilinear…

Optimization and Control · Mathematics 2025-01-10 Zehui Liu , Qingsong Wang , Chunfeng Cui
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