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We study the centraliser of locally compact group extensions of ergodic probability preserving transformations. New methods establishing ergodicity of group extensions are introduced, and new examples of squashable and non-coalescent group…

Dynamical Systems · Mathematics 2007-05-23 Jon. Aaronson , Mariusz Lemanczyk , Dalibor Volny

For Markov chain Monte Carlo methods, one of the greatest discrepancies between theory and system is the scan order - while most theoretical development on the mixing time analysis deals with random updates, real-world systems are…

Machine Learning · Computer Science 2017-10-10 Heng Guo , Kaan Kara , Ce Zhang

We consider the inverse scattering problem for sparse scatterers. An image reconstruction algorithm is proposed that is based on a nonlinear generalization of iterative hard thresholding. The convergence and error of the method was analyzed…

Numerical Analysis · Mathematics 2019-03-27 Anna C. Gilbert , Howard W. Levinson , John C. Schotland

We study the phase transitions of a random copolymer chain with quenched disorder. We apply a replica variational approach based on a Gaussian trial Hamiltonian in terms of the correlation functions of monomer Fourier coordinates. This…

Disordered Systems and Neural Networks · Physics 2009-10-30 A. Moskalenko , Yu. A. Kuznetsov , K. A. Dawson

We use the Litvinov-Maslov correspondence principle to reduce and hybridize networks of biochemical reactions. We apply this method to a cell cycle oscillator model. The reduced and hybridized model can be used as a hybrid model for the…

Molecular Networks · Quantitative Biology 2011-09-21 Vincent Noel , Dima Grigoriev , Sergei Vakulenko , Ovidiu Radulescu

Clustering of proteins is of interest in cancer cell biology. This article proposes a hierarchical Bayesian model for protein (variable) clustering hinging on correlation structure. Starting from a multivariate normal likelihood, we enforce…

Computation · Statistics 2022-02-09 Riddhi Pratim Ghosh , Arnab Kumar Maity , Mohsen Pourahmadi , Bani K. Mallick

Bipartite data is common in data engineering and brings unique challenges, particularly when it comes to clustering tasks that impose on strong structural assumptions. This work presents an unsupervised method for assessing similarity in…

Machine Learning · Computer Science 2017-02-17 Aaron Gerow , Mingyang Zhou , Stan Matwin , Feng Shi

A reciprocal LASSO (rLASSO) regularization employs a decreasing penalty function as opposed to conventional penalization approaches that use increasing penalties on the coefficients, leading to stronger parsimony and superior model…

Methodology · Statistics 2021-09-17 Himel Mallick , Rahim Alhamzawi , Erina Paul , Vladimir Svetnik

We extend the variational cluster approach to deal with strongly correlated lattice bosons in the superfluid phase. To this end, we reformulate the approach within a pseudoparticle formalism, whereby cluster excitations are described by…

Quantum Gases · Physics 2011-04-11 Michael Knap , Enrico Arrigoni , Wolfgang von der Linden

Science and engineering problems frequently require solving a sequence of dual linear systems. Besides having to store only few Lanczos vectors, using the BiConjugate Gradient method (BiCG) to solve dual linear systems has advantages for…

Numerical Analysis · Mathematics 2015-03-17 Kapil Ahuja , Eric de Sturler , Serkan Gugercin , Eun R. Chang

Lattice reduction is a NP-hard problem well known in computer science and cryptography. The Lenstra-Lenstra-Lovasz (LLL) algorithm based on the calculation of orthogonal Gram-Schmidt (GS) bases is efficient and gives a good solution in…

Data Structures and Algorithms · Computer Science 2022-05-10 Cyril Cayron

The influence of static stress and alternating loading direction on the potential energy and mechanical properties of amorphous alloys is investigated using molecular dynamics simulations. The model glass is represented via a binary mixture…

Soft Condensed Matter · Physics 2021-02-09 Nikolai V. Priezjev

We study the general solution of the cyclic Leibniz rule (CLR) which was recently proposed as a new approach to the lattice supersymmetry. Introducing some mathematical preliminaries related to the cyclic symmetry, we find the general…

High Energy Physics - Lattice · Physics 2015-10-28 Daisuke Kadoh , Naoya Ukita

A simple binary model to compute the degree of balancedness in the output sequence of LFSR-combinational generators has been developed. The computational method is based exclusively on the handling of binary strings by means of logic…

Cryptography and Security · Computer Science 2010-05-14 Amparo Fúster-Sabater , Pedro García-Mochales

We study the convergence of iterative linear solvers for discontinuous Galerkin discretizations of systems of hyperbolic conservation laws with polygonal mesh elements compared with that of traditional triangular elements. We solve the…

Numerical Analysis · Mathematics 2019-11-25 Will Pazner , Per-Olof Persson

Many problems in science and engineering fields require the solution of shifted linear systems. To solve such systems efficiently, the recycling BiCG (RBiCG) algorithm in [SIAM J. SCI. COMPUT, 34 (2012) 1925-1949] is extended in this paper.…

Numerical Analysis · Mathematics 2014-06-26 Jing Meng , Pei-yong Zhu , Hou-Biao Li

In this note, first the Recurrent Variational Approach (RVA) is introduced by using as example a non-trivial spin-model, the spin-1/2 antiferromagnetic two-leg-ladder. Then, a first application of this scheme to the electronic structure of…

Condensed Matter · Physics 2007-05-23 S. Pleutin , E. Jeckelmann , M. A. Martin-Delgado , G. Sierra

This paper presents a new Markov chain Monte Carlo method to sample from the posterior distribution of conjugate mixture models. This algorithm relies on a flexible split-merge procedure built using the particle Gibbs sampler. Contrary to…

Computation · Statistics 2017-05-30 Alexandre Bouchard-Côté , Arnaud Doucet , Andrew Roth

Finite elasticity problems commonly include material and geometric nonlinearities and are solved using various numerical methods. However, for highly nonlinear problems, achieving convergence is relatively difficult and requires small load…

Numerical Analysis · Mathematics 2018-05-01 Yue Mei , Daniel E. Hurtado , Sanjay Pant , Ankush Aggarwal

This paper argues that the ideas underlying the renormalization group technique used to characterize phase transitions in condensed matter systems could be useful for distinguishing computational complexity classes. The paper presents a…

Computational Complexity · Computer Science 2007-05-23 S. N. Coppersmith