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We develop a machine learning method to construct accurate ground-state wave functions of strongly interacting and entangled quantum spin as well as fermionic models on lattices. A restricted Boltzmann machine algorithm in the form of an…

Strongly Correlated Electrons · Physics 2017-11-30 Yusuke Nomura , Andrew S. Darmawan , Youhei Yamaji , Masatoshi Imada

In the fermion loop formulation the contributions to the partition function naturally separate into topological equivalence classes with a definite sign. This separation forms the basis for an efficient fermion simulation algorithm using a…

High Energy Physics - Lattice · Physics 2015-09-14 David Baumgartner , Urs Wenger

A number of many-body problems can be formulated using Hamiltonians that are quadratic in the creation and annihilation operators. Here, we show how such quadratic Hamiltonians can be efficiently estimated indirectly, employing very few…

Quantum Physics · Physics 2011-01-17 Daniel Burgarth , Koji Maruyama , Franco Nori

We discuss the Fermion sign problem and, by examining a very general Hubbard-Stratonovich (HS) transformation, argue that the sign problem cannot be solved with such methods. We propose a different kind of transformation which, while not…

Condensed Matter · Physics 2011-08-11 Ghassan George Batrouni , Philippe de Forcrand

In the paper, we introduce several accelerate iterative algorithms for solving the multiple-set split common fixed-point problem of quasi-nonexpansive operators in real Hilbert space. Based on primal-dual method, we construct several…

Optimization and Control · Mathematics 2023-06-08 Chenzheng Guo , Jing Zhao

To speed up Gaussian process inference, a number of fast kernel matrix-vector multiplication (MVM) approximation algorithms have been proposed over the years. In this paper, we establish an exact fast kernel MVM algorithm based on exact…

Machine Learning · Statistics 2025-08-05 Nicolas Langrené , Xavier Warin , Pierre Gruet

Bayesian inference for exponential family random graph models (ERGMs) is a doubly-intractable problem because of the intractability of both the likelihood and posterior normalizing factor. Auxiliary variable based Markov Chain Monte Carlo…

Computation · Statistics 2020-07-15 Fan Yin , Carter T. Butts

The number of n-gram features grows exponentially in n, making it computationally demanding to compute the most frequent n-grams even for n as small as 3. Motivated by our production machine learning system built on n-gram features, we ask:…

Data Structures and Algorithms · Computer Science 2025-11-20 Ryan R. Curtin , Fred Lu , Edward Raff , Priyanka Ranade

We develop algorithms built around properties of the transfer operator and Koopman operator which 1) test for possible multiscale dynamics in a given dynamical system, 2) estimate the magnitude of the time-scale separation, and finally 3)…

Dynamical Systems · Mathematics 2014-12-24 Gary Froyland , Georg A. Gottwald , Andy Hammerlindl

We introduce an algorithm to solve linear inverse problems regularized with the total (gradient) variation in a gridless manner. Contrary to most existing methods, that produce an approximate solution which is piecewise constant on a fixed…

Signal Processing · Electrical Eng. & Systems 2025-07-08 Yohann de Castro , Vincent Duval , Romain Petit

In this work an iterative algorithm based on unsupervised learning is presented, specifically on a Restricted Boltzmann Machine (RBM) to solve a perfect matching problem on a bipartite weighted graph. Iteratively is calculated the weights…

Optimization and Control · Mathematics 2019-05-03 Francesco Curia

Many boundary element integral equation kernels are based on the Green's functions of the Laplace and Helmholtz equations in three dimensions. These include, for example, the Laplace, Helmholtz, elasticity, Stokes, and Maxwell's equations.…

Computational Physics · Physics 2016-08-24 Ross Adelman , Nail A. Gumerov , Ramani Duraiswami

Sparsity-based representations have recently led to notable results in various visual recognition tasks. In a separate line of research, Riemannian manifolds have been shown useful for dealing with features and models that do not lie in…

Machine Learning · Computer Science 2015-05-21 Mehrtash Harandi , Richard Hartley , Chunhua Shen , Brian Lovell , Conrad Sanderson

Physical systems can often be described via a continuous-time dynamical system. In practice, the true system is often unknown and has to be learned from measurement data. Since data is typically collected in discrete time, e.g. by sensors,…

Machine Learning · Computer Science 2024-01-31 Katharina Ensinger , Nicholas Tagliapietra , Sebastian Ziesche , Sebastian Trimpe

We introduce the tools of intersection theory to the study of Feynman integrals, which allows for a new way of projecting integrals onto a basis. In order to illustrate this technique, we consider the Baikov representation of maximal cuts…

High Energy Physics - Theory · Physics 2019-03-06 Pierpaolo Mastrolia , Sebastian Mizera

Many computer vision and human-computer interaction applications developed in recent years need evaluating complex and continuous mathematical functions as an essential step toward proper operation. However, rigorous evaluation of this kind…

Optimization and Control · Mathematics 2017-11-10 Daniel Berjón , Guillermo Gallego , Carlos Cuevas , Francisco Morán , Narciso García

We discuss a simulation algorithm for dynamical fermions, which combines the multiboson technique with the Hybrid Monte Carlo algorithm. The algorithm turns out to give a substantial gain over standard methods in practical simulations and…

High Energy Physics - Lattice · Physics 2009-10-30 Roberto Frezzotti , Karl Jansen

We find an exact mapping from the generalized Ising models with many-spin interactions to equivalent Boltzmann machines, i.e., the models with only two-spin interactions between physical and auxiliary binary variables accompanied by local…

Statistical Mechanics · Physics 2019-03-13 Nobuyuki Yoshioka , Yutaka Akagi , Hosho Katsura

Graph matching is a challenging problem with very important applications in a wide range of fields, from image and video analysis to biological and biomedical problems. We propose a robust graph matching algorithm inspired in…

Optimization and Control · Mathematics 2013-11-26 Marcelo Fiori , Pablo Sprechmann , Joshua Vogelstein , Pablo Musé , Guillermo Sapiro

We elaborate on the method of differential equations for evaluating Feynman integrals. We focus on systems of equations for master integrals having a linear dependence on the dimensional parameter. For these systems we identify the criteria…

High Energy Physics - Phenomenology · Physics 2015-06-18 Mario Argeri , Stefano Di Vita , Pierpaolo Mastrolia , Edoardo Mirabella , Johannes Schlenk , Ulrich Schubert , Lorenzo Tancredi
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