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This work aims to minimize a continuously differentiable convex function with Lipschitz continuous gradient under linear equality constraints. The proposed inertial algorithm results from the discretization of the second-order primal-dual…

Optimization and Control · Mathematics 2022-08-03 Radu Ioan Bot , Ernö Robert Csetnek , Dang-Khoa Nguyen

The lattice Boltzmann method (LBM) is a numerical approach to tackle problems described by a Boltzmann type-equation, where time, space, and velocities are discretized to describe scattering and advection. Even though the LBM executes…

Computational Physics · Physics 2020-09-10 René Hammer , Verena Fritz , Natalia Bedoya-Martínez

This article presents an innovative methodology for locating injection points in injection-molded parts using intelligent models with geometric algorithms for discrete topologies. The first algorithm calculates the center of mass of the…

Graphics · Computer Science 2025-07-29 J. Mercado Colmenero , A. Torres Alba , C. Martin Donate

We consider the task of decentralized minimization of the sum of smooth strongly convex functions stored across the nodes of a network. For this problem, lower bounds on the number of gradient computations and the number of communication…

Optimization and Control · Mathematics 2020-11-16 Dmitry Kovalev , Adil Salim , Peter Richtárik

The possibilities of exploiting the special structure of d.c. programs, which consist of optimizing the difference of convex functions, are currently more or less limited to variants of the DCA proposed by Pham Dinh Tao and Le Thi Hoai An…

Optimization and Control · Mathematics 2016-10-21 Sebastian Banert , Radu Ioan Bot

We propose a doubly stochastic primal-dual coordinate optimization algorithm for empirical risk minimization, which can be formulated as a bilinear saddle-point problem. In each iteration, our method randomly samples a block of coordinates…

Machine Learning · Computer Science 2017-04-13 Adams Wei Yu , Qihang Lin , Tianbao Yang

Worm algorithms have been very successful with the simulation of sigma models with fixed length spins which result from scalar field theories in the limit of infinite quartic coupling lambda. Here we investigate closer their algorithmic…

High Energy Physics - Lattice · Physics 2015-05-27 Tomasz Korzec , Ingmar Vierhaus , Ulli Wolff

We propose an unconstrained optimization method based on the well-known primal-dual hybrid gradient (PDHG) algorithm. We first formulate the optimality condition of the unconstrained optimization problem as a saddle point problem. We then…

Optimization and Control · Mathematics 2024-08-29 X. Zuo , S. Osher , W. Li

We analyze a random lozenge tiling model of a large regular hexagon, whose underlying weight structure is periodic of period $2$ in both the horizontal and vertical directions. This is a determinantal point process whose correlation kernel…

Mathematical Physics · Physics 2020-10-02 Christophe Charlier

We characterize equilibrium properties and relaxation dynamics of a two-dimensional lattice containing, at each site, two particles connected by a double-well potential (dumbbell). Dumbbells are oriented in the orthogonal direction with…

Statistical Mechanics · Physics 2021-01-27 Quentin Novinger , Antonio Suma , Daniel Sigg , Giuseppe Gonnella , Vincenzo Carnevale

We present a near linear time algorithm for constructing hierarchical nets in finite metric spaces with constant doubling dimension. This data-structure is then applied to obtain improved algorithms for the following problems: Approximate…

Data Structures and Algorithms · Computer Science 2007-05-23 Sariel Har-Peled , Manor Mendel

We study and simulate N=2 supersymmetric Wess-Zumino models in one and two dimensions. For any choice of the lattice derivative, the theories can be made manifestly supersymmetric by adding appropriate improvement terms corresponding to…

High Energy Physics - Lattice · Physics 2008-11-26 Tobias Kaestner , Georg Bergner , Sebastian Uhlmann , Andreas Wipf , Christian Wozar

High-dimensional PDEs have been a longstanding computational challenge. We propose to solve high-dimensional PDEs by approximating the solution with a deep neural network which is trained to satisfy the differential operator, initial…

Mathematical Finance · Quantitative Finance 2018-10-17 Justin Sirignano , Konstantinos Spiliopoulos

A fast algorithm (linear in the degrees of freedom) for the solution of linear variable-coefficient rational-order fractional integral and differential equations is described. The approach is related to the ultraspherical method for…

Numerical Analysis · Mathematics 2017-12-04 Nicholas Hale , Sheehan Olver

Approximating multivariate periodic functions in weighted Korobov spaces via rank-1 lattices is fundamentally limited by frequency aliasing. Existing optimal-rate methods rely on randomized constructions or large pre-computations. We…

Numerical Analysis · Mathematics 2026-04-06 Jiarui Du , Josef Dick

We are able to perform the duality transformation of the spin system which was found before as a lattice realization of the string with linear action. In four and higher dimensions this spin system can be described in terms of a…

High Energy Physics - Theory · Physics 2009-10-28 G. K. Savvidy , K. G. Savvidy , F. J. Wegner

Using a combinatorial method, the partition functions for two-dimensional nearest neighbour Ising models have been derived for a square lattice of 16 sites in the presence of the magnetic field. A novel hierarchical method of enumeration of…

Statistical Mechanics · Physics 2022-05-24 Anshu Priya , M V Sangaranarayanan

We formulate a new geometrical string on the euclidean lattice. It is possible to find such spin systems with local interaction which reproduce the same surface dynamics.In the three-dimensional case this spin system is a usual Ising…

High Energy Physics - Theory · Physics 2009-10-22 G. K. Savvidy , F. J. Wegner

Duality relations for the 2D nonhomogeneous Ising model on the finite square lattice wrapped on the torus are obtained. The partition function of the model on the dual lattice with arbitrary combinations of the periodical and antiperiodical…

High Energy Physics - Theory · Physics 2007-05-23 Anatolij I. Bugrij , Vitalij N. Shadura

We propose a geometric algorithm for topic learning and inference that is built on the convex geometry of topics arising from the Latent Dirichlet Allocation (LDA) model and its nonparametric extensions. To this end we study the…

Machine Learning · Statistics 2016-10-31 Mikhail Yurochkin , XuanLong Nguyen