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This paper presents a method for expressing the determinant of an N {\times} N complex block matrix in terms of its constituent blocks. The result allows one to reduce the determinant of a matrix with N^2 blocks to the product of the…

Rings and Algebras · Mathematics 2011-12-22 Philip D. Powell

The computation of a matrix function $f(A)$ is an important task in scientific computing appearing in machine learning, network analysis and the solution of partial differential equations. In this work, we use only matrix-vector products…

Numerical Analysis · Mathematics 2026-03-03 Taejun Park , Yuji Nakatsukasa

The matrix elements of the spin operator for the periodic Ising model in a basis of eigenvectors for the transfer matrix are calculated in the massive scaling limit.

Exactly Solvable and Integrable Systems · Physics 2015-05-19 John Palmer , Grethe Hystad

Quantum computers are believed to have the ability to process huge data sizes which can be seen in machine learning applications. In these applications, the data in general is classical. Therefore, to process them on a quantum computer,…

Quantum Physics · Physics 2023-03-02 Ammar Daskin , Rishabh Gupta , Sabre Kais

We represent low dimensional quantum mechanical Hamiltonians by moderately sized finite matrices that reproduce the lowest O(10) boundstate energies and wave functions to machine precision. The method extends also to Hamiltonians that are…

Quantum Physics · Physics 2015-06-03 Johann Foerster , Alejandro Saenz , Ulli Wolff

In this paper we present a method for matrix inversion based on Cholesky decomposition with reduced number of operations by avoiding computation of intermediate results; further, we use fixed point simulations to compare the numerical…

Mathematical Software · Computer Science 2013-10-21 Aravindh Krishnamoorthy , Deepak Menon

We derive an integral-free thermodynamic perturbation series expansion for quantum partition functions which enables an analytical term-by-term calculation of the series. The expansion is carried out around the partition function of the…

Statistical Mechanics · Physics 2018-05-23 Itay Hen

Tuning scientific and probabilistic machine learning models $-$ for example, partial differential equations, Gaussian processes, or Bayesian neural networks $-$ often relies on evaluating functions of matrices whose size grows with the data…

Machine Learning · Computer Science 2024-10-28 Nicholas Krämer , Pablo Moreno-Muñoz , Hrittik Roy , Søren Hauberg

In addition to recent developments in computing speed and memory, methodological advances have contributed to significant gains in the performance of stochastic simulation. In this paper, we focus on variance reduction for matrix…

Machine Learning · Statistics 2023-03-28 Anant Mathur , Sarat Moka , Zdravko Botev

Inverse design of large-area metasurfaces can potentially exploit the full parameter space that such devices offer and achieve highly efficient multifunctional flat optical elements. However, since practically useful flat optics elements…

We consider evaluation of matrix elements with the coupled-cluster method. Such calculations formally involve infinite number of terms and we devise a method of partial summation (dressing) of the resulting series. Our formalism is built…

Atomic Physics · Physics 2009-11-10 Andrei Derevianko , Sergey Porsev

We present quadrature schemes to calculate matrices, where the so-called modified Hilbert transformation is involved. These matrices occur as temporal parts of Galerkin finite element discretizations of parabolic or hyperbolic problems when…

Numerical Analysis · Mathematics 2022-07-26 Marco Zank

In the papers dealing with derivation and applications of operational matrices of Bernstein polynomials, a basis transformation, commonly a transformation to power basis, is used. The main disadvantage of this method is that the…

Numerical Analysis · Mathematics 2016-11-02 M. Jani , E. Babolian , S. Javadi , D. Bhatta

Transfer matrix method is a well-known and extensively used tool to compute the reflection and transmission coefficients of electromagnetic waves when interacting with a system of layers parallel to each other. We present here a modified…

Optics · Physics 2017-03-14 Srinivas Ganganagunta

Matrix factor model is drawing growing attention for simultaneous two-way dimension reduction of well-structured matrix-valued observations. This paper focuses on robust statistical inference for matrix factor model in the ``diverging…

Methodology · Statistics 2023-06-07 Yong He , Xin-Bing Kong , Dong Liu , Ran Zhao

Fast Fourier transform algorithms are an arsenal of effective tools for solving various problems of analysis and high-speed processing of signals of various natures. Almost all of these algorithms are designed to process sequences of…

Data Structures and Algorithms · Computer Science 2025-04-11 Aleksandr Cariow

We explain how masses and matrix elements can be computed in lattice QCD using Schr"odinger functional boundary conditions. Numerical results in the quenched approximation demonstrate that good precision can be achieved. For a statistical…

High Energy Physics - Lattice · Physics 2015-06-25 Marco Guagnelli , Jochen Heitger , Rainer Sommer , Hartmut Wittig

We investigate scalar matrix elements of the nucleon using $N_f=2+1+1$ flavors of maximally twisted mass fermions at a fixed value of the lattice spacing of $a\approx 0.078{\rm fm}$. We compute disconnected contributions to the relevant…

High Energy Physics - Lattice · Physics 2012-02-17 S. Dinter , V. Drach , K. Jansen

This is a short review of some recent results obtained by the author. These results are related the problem of obtaining polynomial identities (computational formulas) for some matrix functions by means of the known polarization theorem,…

Combinatorics · Mathematics 2018-05-01 Georgy P. Egorychev

We present a new method for computing the impedance matrix elements in the method of moments for geometries described by bilinear quadrilaterals (BQ) and for higher-order basis functions (HOBF). Our method is restricted to the Magnetic…

Computational Physics · Physics 2017-03-08 John S. Asvestas