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Small-scale liquid flows on solid surfaces provide convincing details in liquid animation, but they are difficult to be simulated with efficiency and fidelity, mostly due to the complex nature of the surface tension at the contact front…

Graphics · Computer Science 2018-11-07 Rajaditya Mukherjee , Qingyang Li , Zhili Chen , Shicheng Chu , Huamin Wang

Realistic fluid-solid interaction potentials are essential in description of confined fluids especially in the case of geometric heterogeneous surfaces. Correlated random field is considered as a model of random surface with high geometric…

Statistical Mechanics · Physics 2017-05-24 Aleksey Khlyupin , Timur Aslyamov

Existing hybrid Level Set / Front Tracking methods have been developed for structured meshes and successfully used for efficient and accurate simulations of complex multiphase flows. This contribution extends the capability of hybrid Level…

Computational Physics · Physics 2023-11-22 Tobias Tolle , Dieter Bothe , Tomislav Maric

A model, based on Gribov's Reggeon calculus, is proposed and applied to processes of soft diffraction at high energies. It is shown that by accounting for absorptive corrections for all legs of triple-Regge and loop diagrams a good…

High Energy Physics - Phenomenology · Physics 2009-09-29 A. B. Kaidalov , M. G. Poghosyan

Recent neural network sequence models with softmax classifiers have achieved their best language modeling performance only with very large hidden states and large vocabularies. Even then they struggle to predict rare or unseen words even if…

Computation and Language · Computer Science 2016-09-27 Stephen Merity , Caiming Xiong , James Bradbury , Richard Socher

The growing prevalence of nonsmooth optimization problems in machine learning has spurred significant interest in generalized smoothness assumptions. Among these, the (L0, L1)-smoothness assumption has emerged as one of the most prominent.…

Optimization and Control · Mathematics 2026-02-24 Zhirayr Tovmasyan , Grigory Malinovsky , Laurent Condat , Peter Richtárik

Mixture-of-experts models provide a flexible framework for learning complex probabilistic input-output relationships by combining multiple expert models through an input-dependent gating mechanism. These models have become increasingly…

Machine Learning · Statistics 2026-04-23 Nicola Bariletto , Huy Nguyen , Nhat Ho , Alessandro Rinaldo

It is well known that the number of particles should be scaled up to enable industrial scale simulation. The calculations are more computationally intensive when the motion of the surrounding fluid is considered. Besides the advances in…

Computational Physics · Physics 2014-07-28 Hao Zhang , F. Xavier Trias , Assensi Oliva , Dongmin Yang , Yuanqiang Tan , Shi Shu , Yong Sheng

If the dynamics of an evolutionary differential equation system possess a low-dimensional, attracting, slow manifold, there are many advantages to using this manifold to perform computations for long term dynamics, locating features such as…

Computational Physics · Physics 2007-05-23 C. W. Gear , I. G. Kevrekidis

In a supersymmetric (SUSY) theory, the IR-contributions to the Higgs mass are calculable below the mediation scale $\Lambda_{\text{UV}}$ in terms of the IR field content and parameters. However, logarithmic sensitivity to physics at…

High Energy Physics - Phenomenology · Physics 2020-10-14 Timothy Cohen , Nathaniel Craig , Seth Koren , Matthew McCullough , Joseph Tooby-Smith

In this paper, we address the classical problem of maximum-likelihood (ML) detection of data in the presence of random phase noise. We consider a system, where the random phase noise affecting the received signal is first compensated by a…

Information Theory · Computer Science 2016-11-15 Rajet Krishnan , M. Reza Khanzadi , Thomas Eriksson , Tommy Svensson

We propose numerical simulations of viscoelastic fluids based on a hybrid algorithm combining Lattice-Boltzmann models (LBM) and Finite Differences (FD) schemes, the former used to model the macroscopic hydrodynamic equations, and the…

Computational Physics · Physics 2016-07-26 A. Gupta , M. Sbragaglia , A. Scagliarini

I propose a new method to study computationally difficult problems. I consider a new system, larger than the one I want to simulate. The original system is recovered by imposing constraints on the large system. I simulate the large system…

Disordered Systems and Neural Networks · Physics 2009-11-10 Nicolas Sourlas

A key challenge for soft materials design and coarse-graining simulations is determining interaction potentials between components that give rise to desired condensed-phase structures. In theory, the Ornstein-Zernike equation provides an…

Soft Condensed Matter · Physics 2021-02-22 Rhys E. A. Goodall , Alpha A. Lee

We formulate a stochastic process, FiLex, as a mathematical model of lexicon entropy in deep learning-based emergent language systems. Defining a model mathematically allows it to generate clear predictions which can be directly and…

Computation and Language · Computer Science 2023-03-27 Brendon Boldt , David Mortensen

A brief review is presented of the scaling of complex fluids, polymers and polyelectrolytes in solution and in confined geometry, in thermodynamical, structural and rheology properties using equilibrium and nonequilibrium dissipative…

Soft Condensed Matter · Physics 2016-12-06 Armando Gama Goicochea

We extend a heuristic method for automatic dimensionality selection, which maximizes a profile likelihood to identify "elbows" in scree plots. Our extension enables researchers to make automatic choices of multiple hyper-parameters…

Methodology · Statistics 2026-05-20 Gengyang Chen , Mu Zhu

Multi-well potentials are ubiquitous in science, modeling phenomena such as phase transitions, dynamic instabilities, and multimodal behavior across physics, chemistry, and biology. In contrast to non-smooth minimum-of-mixture…

Machine Learning · Statistics 2025-06-24 Reese E. Jones , Adrian Buganza Tepole , Jan N. Fuhg

This paper develops the proximal method of multipliers for a class of nonsmooth convex optimization. The method generates a sequence of minimization problems (subproblems). We show that the sequence of approximations to the solutions of the…

Numerical Analysis · Mathematics 2020-01-14 Tomoya Takeuchi

Polyhedral surfaces are fundamental objects in architectural geometry and industrial design. Whereas closeness of a given mesh to a smooth reference surface and its suitability for numerical simulations were already studied extensively, the…

Metric Geometry · Mathematics 2017-03-17 Felix Günther , Caigui Jiang , Helmut Pottmann