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This article is a direct continuation of [1] where we begun the study of the transfer matrix spectral problem for the cyclic representations of the trigonometric 6-vertex reflection algebra associated to the Bazhanov-Stroganov Lax operator.…

Mathematical Physics · Physics 2018-09-26 J. M. Maillet , G. Niccoli , B. Pezelier

We present a numerically stable re-formulization of the transfer matrix method (TMM). The iteration form of the traditional TMM is transformed into solving a set of linear equations. Our method gains the new ability of calculating accurate…

Computational Physics · Physics 2019-12-30 Liang Chen , Cheng Lv , Xunya Jiang

A transfer matrix scaling technique is developed for randomly diluted systems, and applied to the site-diluted Ising model on a square lattice in two dimensions. For each allowed disorder configuration between two adjacent columns, the…

Condensed Matter · Physics 2009-10-22 S. L. A. de Queiroz , R. B. Stinchcombe

A popular series of style transfer methods apply a style to a content image by controlling mean and covariance of values in early layers of a feature stack. This is insufficient for transferring styles that have strong structure across…

Computer Vision and Pattern Recognition · Computer Science 2018-01-09 Mao-Chuang Yeh , Shuai Tang

In this paper we discuss numerical methods and algorithms for the solution of NLTE stellar atmosphere problems involving expanding atmospheres, e.g., found in novae, supernovae and stellar winds. We show how a scheme of nested iterations…

Astrophysics · Physics 2011-06-02 P. H. Hauschildt , E. Baron

The transfer matrix is a powerful technique that can be applied to statistical mechanics systems as, for example, in the calculus of the entropy of the ice model. One interesting way to study such systems is to map it onto a 3-color…

Statistical Mechanics · Physics 2022-10-24 Roberto da Silva , Silvio R. Dahmen , J. R. Drugowich de Felício

Hybrid numerical-experimental testing is a standard approach for complex dynamical structures that are, on the one hand, not easy to model due to complexity and parameter uncertainty and, on the other hand, too expensive for full-scale…

Dynamical Systems · Mathematics 2020-03-24 Benjamin Unger

In this work we use matrix models to study the problem of strength distributions. This is motivated by noticing near exponential fall offs of strengths in calculated magnetic dipole excitations. We emphasize that the quality of the…

Nuclear Theory · Physics 2021-04-27 Larry Zamick , Arun Kingan

Crafting adversarial examples can be formulated as an optimization problem. While sign-based optimizers such as I-FGSM and MI-FGSM have become the de facto standard for the induced optimization problems, there still exist several unsolved…

Machine Learning · Computer Science 2026-03-03 Wei Tao , Yang Dai , Jincai Huang , Qing Tao

In this paper, we consider the problem of approximating a given matrix with a matrix whose eigenvalues lie in some specific region \Omega, within the complex plane. More precisely, we consider three types of regions and their intersections:…

Optimization and Control · Mathematics 2024-12-20 Neelam Choudhary , Nicolas Gillis , Punit Sharma

We generalize the concepts of D-stability and additive D-stability of matrices. For this, we consider a family of unbounded regions defined in terms of Linear Matrix Inequalities (so-called LMI regions). We study the problem when the…

Spectral Theory · Mathematics 2020-04-24 Olga Y. Kushel , Raffaella Pavani

Nonlinear modal decoupling (NMD) was recently proposed to nonlinearly transform a multi-oscillator system into a number of decoupled oscillators which together behave the same as the original system in an extended neighborhood of the…

Systems and Control · Computer Science 2018-11-12 Bin Wang , Kai Sun , Xin Xu

We consider the Lasserre hierarchy for computing bounds on the stability number of graphs. The semidefinite programs (SDPs) arising from this hierarchy involve large matrix variables and many linear constraints, which makes them difficult…

Optimization and Control · Mathematics 2025-06-11 Lennart Sinjorgo , Renata Sotirov , Juan C. Vera

We report a new analytical method for exact solution of homogeneous linear ordinary differential equations with arbitrary order and variable coefficients. The method is based on the definition of jump transfer matrices and their extension…

Mathematical Physics · Physics 2007-05-23 Sina Khorasani , Ali Adibi

We study statistical model checking of continuous-time stochastic hybrid systems. The challenge in applying statistical model checking to these systems is that one cannot simulate such systems exactly. We employ the multilevel Monte Carlo…

Systems and Control · Computer Science 2017-06-27 Sadegh Esmaeil Zadeh Soudjani , Rupak Majumdar , Tigran Nagapetyan

We mathematically model Smectic-A (SmA) phases with a modified Landau-de Gennes (mLdG) model. The orientational order of the SmA phase is described by a tensor-order parameter $\mathbf{Q}$, and the positional order is described by a real…

Soft Condensed Matter · Physics 2025-09-22 Baoming Shi , Yucen Han , Chengdi Ma , Apala Majumdar , Lei Zhang

The viability of a variant of numerical stochastic perturbation theory, where the Langevin equation is replaced by the SMD algorithm, is examined. In particular, the convergence of the process to a unique stationary state is rigorously…

High Energy Physics - Lattice · Physics 2017-06-02 Mattia Dalla Brida , Martin Lüscher

As the size of engineered systems grows, problems in reliability theory can become computationally challenging, often due to the combinatorial growth in the cut sets. In this paper we demonstrate how Multilevel Monte Carlo (MLMC) - a…

Computation · Statistics 2017-03-14 Louis J. M. Aslett , Tigran Nagapetyan , Sebastian J. Vollmer

Recent progress in style transfer on images has focused on improving the quality of stylized images and speed of methods. However, real-time methods are highly unstable resulting in visible flickering when applied to videos. In this work we…

Computer Vision and Pattern Recognition · Computer Science 2017-05-08 Agrim Gupta , Justin Johnson , Alexandre Alahi , Li Fei-Fei

Multi-Task Learning (MTL) is a growing subject of interest in deep learning, due to its ability to train models more efficiently on multiple tasks compared to using a group of conventional single-task models. However, MTL can be impractical…

Machine Learning · Computer Science 2022-11-24 Anish Lakkapragada , Essam Sleiman , Saimourya Surabhi , Dennis P. Wall