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Related papers: Optimal mixing enhancement

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We propose a distributed algorithm based on Alternating Direction Method of Multipliers (ADMM) to minimize the sum of locally known convex functions using communication over a network. This optimization problem emerges in many applications…

Optimization and Control · Mathematics 2016-01-05 Ali Makhdoumi , Asuman Ozdaglar

In this paper we provide an algorithm which given any $m$-edge $n$-vertex directed graph with integer capacities at most $U$ computes a maximum $s$-$t$ flow for any vertices $s$ and $t$ in $m^{11/8+o(1)}U^{1/4}$ time with high probability.…

Data Structures and Algorithms · Computer Science 2019-11-01 Yang P. Liu , Aaron Sidford

Mainstream flow matching methods typically focus on learning the local velocity field, which inherently requires multiple integration steps during generation. In contrast, Mean Velocity Flow models establish a relationship between the local…

Machine Learning · Computer Science 2026-03-18 Chenrui Ma

For general connections, the problem of finding network codes and optimizing resources for those codes is intrinsically difficult and little is known about its complexity. Most of the existing solutions rely on very restricted classes of…

Information Theory · Computer Science 2015-03-02 Ying Cui , Muriel Médard , Edmund Yeh , Douglas Leith , Ken Duffy

We use numerical simulations to examine two-dimensional particle mixtures that strongly phase separate in equilibrium. When the system is externally driven in the presence of quenched disorder, plastic flow occurs in the form of meandering…

Statistical Mechanics · Physics 2009-11-13 A. Libal , C. Reichhardt , C. J. Olson Reichhardt

One-step generative modeling has emerged as a leading approach to amortize the inference cost of diffusion and flow-matching models. Among distillation-free methods, MeanFlow training is notoriously unstable, with non-decreasing loss and…

Machine Learning · Computer Science 2026-05-12 Juanwu Lu , Ziran Wang

Numerical simulation of multi-component flow systems characterized by the simultaneous presence of pressure-velocity coupling and pressure-density coupling dominated regions remains a significant challenge in computational fluid dynamics.…

Fluid Dynamics · Physics 2025-10-17 Xi Deng , Bin Xie , Omar K. Matar , Pierre Boivin

While flow optimization has been extensively studied in the continuum regime, its extension to rarefied gas flows remains less explored. Here, based on the Boltzmann model equation, an adjoint topology optimization method is employed to…

Fluid Dynamics · Physics 2025-10-17 Ruifeng Yuan , Lei Wu

We formulate a finite-particle method of mass transport that accounts for general mixed boundary conditions. The particle method couples a geometrically-exact treatment of advection; Wasserstein gradient-flow dynamics; and a…

Numerical Analysis · Mathematics 2025-03-05 Anna Pandolfi , Ignacio Romero , Michael Ortiz

We investigate a family of approximate multi-step proximal point methods, accelerated by implicit linear discretizations of gradient flow. The resulting methods are multi-step proximal point methods, with similar computational cost in each…

Optimization and Control · Mathematics 2023-10-23 Yushen Huang , Yifan Sun

Recent work has shown that leveraging learned predictions can improve the running time of algorithms for bipartite matching and similar combinatorial problems. In this work, we build on this idea to improve the performance of the widely…

Data Structures and Algorithms · Computer Science 2023-03-03 Sami Davies , Benjamin Moseley , Sergei Vassilvitskii , Yuyan Wang

Microfluidic devices are gaining attention for their small size and ability to handle tiny fluid volumes. Mixing fluids efficiently at this scale, known as micromixing, is crucial. This article builds upon previous research by introducing a…

Most of numerical methods for deterministic simulations of rarefied gas flows use the discrete velocity (or discrete ordinate) approximation. In this approach, the kinetic equation is approximated with a global velocity grid. The grid must…

Numerical Analysis · Mathematics 2014-03-19 Stéphane Brull , Luc Mieussens

We consider a class of optimal control problems for measure-valued nonlinear transport equations describing traffic flow problems on networks. The objective isto minimise/maximise macroscopic quantities, such as traffic volume or average…

Optimization and Control · Mathematics 2019-11-11 Simone Cacace , Fabio Camilli , Raul De Maio , Andrea Tosin

This paper proposes a convex optimization based distributed algorithm to solve multi-period optimal gas-power flow (OGPF) in coupled energy distribution systems. At the gas distribution system side, the non-convex Weymouth gas flow…

Optimization and Control · Mathematics 2016-10-18 Cheng Wang , Wei Wei , Jianhui Wang , Linquan Bai , Yile Liang

In this paper, we consider the complex flows when all three regimes pre-Darcy, Darcy and post-Darcy may be present in different portions of a same domain. We unify all three flow regimes under mathematics formulation. We describe the flow…

Numerical Analysis · Mathematics 2021-06-24 John Cummings , Matthew Hamilton , Thinh Kieu

A model for the development of turbulent shear flows, created by non-uniform parallel flows in a confining channel, is used to identify the diffuser shape that maximises pressure recovery when the inflow is non-uniform. Wide diffuser angles…

Fluid Dynamics · Physics 2018-04-09 GP Benham , IJ Hewitt , CP Please , P Bird

The mixing in three-dimensional enclosures is investigated numerically using flow in cubical cavity as a geometrically simple model of various natural and engineering flows. The mixing rate is evaluated for up to the value of Reynolds…

Fluid Dynamics · Physics 2023-01-23 Alex Povitsky

In this paper we provide an algorithm which given any $m$-edge $n$-vertex directed graph with integer capacities at most $U$ computes a maximum $s$-$t$ flow for any vertices $s$ and $t$ in $m^{4/3+o(1)}U^{1/3}$ time. This improves upon the…

Data Structures and Algorithms · Computer Science 2020-04-16 Yang P. Liu , Aaron Sidford

Ensemble calculations are essential for systems with uncertain data but require substantial increase in computational resources. This increase severely limits ensemble size. To reach beyond current limits, we present a first-order…

Numerical Analysis · Mathematics 2017-12-19 Joseph A. Fiordilino , Michael McLaughlin
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