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Autoregressive Neural Networks based on dense or convolutional layers have recently been shown to be a viable strategy for generating classical spin systems. Unlike these methods, sampling with transformers is commonly considered to be…

Disordered Systems and Neural Networks · Physics 2026-05-01 Piotr Białas , Piotr Korcyl , Tomasz Stebel , Adam Stefański , Dawid Zapolski

This paper has solved the inverse eigenvalue problem for "fixed-free" mass-chain systems with inerters. It is well known that for a spring-mass system wherein the adjacent masses are linked through a spring, the natural frequency assignment…

Optimization and Control · Mathematics 2019-12-24 Zhaobo Liu , Qida Xie , Chanying Li

We considered the Ising 1D chain in an external magnetic field taking into account the nearest and next-nearest neighbor interactions. By the method of Kramers--Wannier transfer-matrix, the rigorous analytical expression for…

Statistical Mechanics · Physics 2022-06-22 A. V. Zarubin , F. A. Kassan-Ogly , A. I. Proshkin

We present a renormalization group (RG) procedure which works naturally on a wide class of interacting one-dimension models based on perturbed (possibly strongly) continuum conformal and integrable models. This procedure integrates Kenneth…

Strongly Correlated Electrons · Physics 2016-07-05 Robert M. Konik , Yury Adamov

In this paper, using the linearization technique we write the Helmholtz transmission eigenvalue problem as an equivalent nonselfadjoint linear eigenvalue problem whose left-hand side term is a selfadjoint, continuous and coercive…

Numerical Analysis · Mathematics 2016-03-03 Yidu Yang , Jiayu Han , Hai Bi

In the present work, eigenvalue distributions defined by a random rectangular matrix whose components are neither independently nor identically distributed are analyzed using replica analysis and belief propagation. In particular, we…

Portfolio Management · Quantitative Finance 2016-05-24 Takashi Shinzato

Recently, we used the Sinc collocation method with the double exponential transformation to compute eigenvalues for singular Sturm-Liouville problems. In this work, we show that the computation complexity of the eigenvalues of such a…

Numerical Analysis · Mathematics 2016-03-23 Philippe Gaudreau , Hassan Safouhi

It has been argued that despite remarkable success, existing random matrix theories are not adequate to describe disordered conductors in the metallic regime, due to the presence of certain two-body interactions in the effective Hamiltonian…

Condensed Matter · Physics 2007-05-23 K. A. Muttalib

A class of quasi two and three dimensional quantum lattice spin models with nearest and next nearest neighbour interactions is proposed. The basic idea of construction is to introduce interactions in an array of XXZ spin chains through…

Condensed Matter · Physics 2016-08-31 Anjan Kundu

We consider the Ising model on the square lattice with biaxially correlated random ferromagnetic couplings, the critical point of which is fixed by self-duality. The disorder represents a relevant perturbation according to the extended…

Statistical Mechanics · Physics 2007-05-23 F. A. Bagamery , L. Turban , F. Igloi

In the Ising model, we consider the problem of estimating the covariance of the spins at two specified vertices. In the ferromagnetic case, it is easy to obtain an additive approximation to this covariance by repeatedly sampling from the…

Data Structures and Algorithms · Computer Science 2021-06-16 Leslie Ann Goldberg , Mark Jerrum

A mixed Ising-Heisenberg spin system consisting of triangular XXZ-Heisenberg spin clusters assembled into a chain by alternating with Ising spins interacting to all three spins in the triangle is considered. The exact solution of the model…

Statistical Mechanics · Physics 2009-11-13 Diana Antonosyan , Stefano Bellucci , Vadim Ohanyan

The Ising model in two dimensions with special toroidal boundary conditions is analyzed. These boundary condition, which we call duality twisted boundary conditions, may be interpreted as inserting a specific defect line ("seam") in the…

Statistical Mechanics · Physics 2017-12-27 Armen Poghosyan , Nickolay Izmailian , Ralph Kenna

The optimal mass transport problem gives a geometric framework for optimal allocation, and has recently gained significant interest in application areas such as signal processing, image processing, and computer vision. Even though it can be…

Optimization and Control · Mathematics 2018-02-07 Johan Karlsson , Axel Ringh

We consider random extended surface perturbations in the transverse field Ising model decaying as a power of the distance from the surface towards a pure bulk system. The decay may be linked either to the evolution of the couplings or to…

Statistical Mechanics · Physics 2007-05-23 L. Turban , D. Karevski , F. Igloi

The study of solving the inverse eigenvalue problem for nonnegative matrices has been around for decades. It is clear that an inverse eigenvalue problem is trivial if the desirable matrix is not restricted to a certain structure. Provided…

Numerical Analysis · Mathematics 2014-08-13 Matthew M. Lin

Using transfer-matrix method a correspondence between $2D$ classical spin systems ($2D$ Ising model and six-vertex model) and $1D$ quantum spin systems is considered. We find the transfer matrix in two limits - in a well-known…

Statistical Mechanics · Physics 2010-06-09 Oles Zaburannyi

We describe a novel algorithm for solving general parametric (nonlinear) eigenvalue problems. Our method has two steps: first, high-accuracy solutions of non-parametric versions of the problem are gathered at some values of the parameters;…

Numerical Analysis · Mathematics 2024-10-14 Davide Pradovera , Alessandro Borghi

The Ising spin glass in two dimensions exhibits rich behavior with subtle differences in the scaling for different coupling distributions. We use recently developed mappings to graph-theoretic problems together with highly efficient…

Disordered Systems and Neural Networks · Physics 2018-03-02 Hamid Khoshbakht , Martin Weigel

Eigenvalue problems have a distinctive forward-inverse structure and are fundamental to characterizing a system's thermal response, stability, and natural modes. Physics-Informed Neural Networks (PINNs) offer a mesh-free alternative for…

Machine Learning · Computer Science 2025-11-04 Akshay Sai Banderwaar , Abhishek Gupta
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