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Recent work found that an analysis formalism based on the Lanczos algorithm allows energy levels to be extracted from Euclidean correlation functions with faster ground-state convergence than effective masses, convergent estimators for…

High Energy Physics - Lattice · Physics 2025-09-12 Daniel C. Hackett , Michael L. Wagman

We compute the one-loop lattice renormalization of the two-quark operators $\bar{\psi} \Gamma \psi$, where $\Gamma$ denotes the generic Dirac matrix, for the lattice formulation of QCD using the overlap-Dirac operator. We also study the…

High Energy Physics - Lattice · Physics 2008-11-26 C. Alexandrou , E. Follana , H. Panagopoulos , E. Vicari

The overlap Dirac operator, which satisfies the Ginsparg-Wilson relation, realizes exact chiral symmetry on the lattice without any unphysical doubler modes. To perform the path integrals, one should, however, note that the overlap fermion…

High Energy Physics - Lattice · Physics 2007-05-23 Hidenori Fukaya

We introduce a performance-optimized method to simulate localization problems on bipartite tight-binding lattices. It combines an exact renormalization group step to reduce the sparseness of the original problem with the recursive Green's…

Disordered Systems and Neural Networks · Physics 2021-06-08 Martin Puschmann , Thomas Vojta

In this paper, we present a method for the computation of the low-lying real eigenvalues of the Wilson-Dirac operator based on the Arnoldi algorithm. These eigenvalues contain information about several observables. We used them to calculate…

High Energy Physics - Lattice · Physics 2015-05-27 G. Bergner , J. Wuilloud

Lattice QCD calculations of disconnected quark loop operators are extremely computer time-consuming to evaluate. To compute these diagrams using lattice techniques, one generally uses stochastic noise methods. These employ a randomly…

High Energy Physics - Lattice · Physics 2019-06-26 Suman Baral , Travis Whyte , Walter Wilcox , Ronald B. Morgan

Inverse scattering has a broad applicability in quantum mechanics, remote sensing, geophysical, and medical imaging. This paper presents a robust direct reduced order model (ROM) method for solving inverse scattering problems based on an…

Numerical Analysis · Mathematics 2023-11-29 Justin Baker , Elena Cherkaev , Vladimir Druskin , Shari Moskow , Mikhail Zaslavsky

While there is no lack of efficient Krylov subspace solvers for Hermitian systems, there are few for complex symmetric, skew symmetric, or skew Hermitian systems, which are increasingly important in modern applications including quantum…

Mathematical Software · Computer Science 2014-01-14 Sou-Cheng , Choi

This work is concerned with the computation of the action of a matrix function f(A), such as the matrix exponential or the matrix square root, on a vector b. For a general matrix A, this can be done by computing the compression of A onto a…

Numerical Analysis · Mathematics 2023-06-06 Alice Cortinovis , Daniel Kressner , Yuji Nakatsukasa

We consider the approximation of $B^T (A+sI)^{-1} B$ for large s.p.d. $A\in\mathbb{R}^{n\times n}$ with dense spectrum and $B\in\mathbb{R}^{n\times p}$, $p\ll n$. We target the computations of Multiple-Input Multiple-Output (MIMO) transfer…

Numerical Analysis · Mathematics 2025-04-18 Vladimir Druskin , Jörn Zimmerling

We discuss the computational problems when analyzing general, non-hermitian matrices and in particular the un-modified Wilson lattice Dirac operator. We report on our experiences with the Implicitly Restarted Arnoldi Method. The eigenstates…

High Energy Physics - Lattice · Physics 2009-10-31 Christof Gattringer , Ivan Hip

Solving symmetric positive definite linear problems is a fundamental computational task in machine learning. The exact solution, famously, is cubicly expensive in the size of the matrix. To alleviate this problem, several linear-time…

Machine Learning · Computer Science 2017-06-02 Filip de Roos , Philipp Hennig

Many optimization problems require hyperparameters, i.e., parameters that must be pre-specified in advance, such as regularization parameters and parametric regularizers in variational regularization methods for inverse problems, and…

Optimization and Control · Mathematics 2025-10-09 Matthias J. Ehrhardt , Silvia Gazzola , Sebastian J. Scott

This work presents a new Krylov-subspace-recycling method for efficiently solving sequences of linear systems of equations characterized by varying right-hand sides and symmetric-positive-definite matrices. As opposed to typical truncation…

Numerical Analysis · Mathematics 2016-01-22 Kevin Carlberg , Virginia Forstall , Ray Tuminaro

In this text I present a couple of new principles and thereon based iterative methods for numerical solution of sequences of systems of linear equations with fixed system matrix and changing right-hand-sides. The use of the new methods is…

Numerical Analysis · Mathematics 2015-12-17 Martin Neuenhofen

In these lectures, we discuss different types of renormalization problems in QCD and their non-perturbative solution in the framework of the lattice formulation. In particular the recursive finite size methods to compute the…

High Energy Physics - Phenomenology · Physics 2009-10-30 Rainer Sommer

We show that it is possible to improve the chiral behaviour and the approach to the continuum limit of correlation functions in lattice QCD with Wilson fermions by taking arithmetic averages of correlators computed in theories regularized…

High Energy Physics - Lattice · Physics 2009-11-10 R. Frezzotti , G. C. Rossi

In a system where chiral symmetry is spontaneously broken, the low energy eigenmodes of the continuum Dirac operator are extended. On the lattice, due to discretization effects, the Dirac operator can have localized eigenmodes that affect…

High Energy Physics - Lattice · Physics 2008-11-26 Anna Hasenfratz , Roland Hoffmann , Stefan Schaefer

In this paper, we investigate the use of multilinear algebra for reducing the order of multidimensional linear time-invariant (MLTI) systems. Our main tools are tensor rational Krylov subspace methods, which enable us to approximate the…

Numerical Analysis · Mathematics 2024-11-28 Houda Barkouki , Khalide Jbilou

We present a novel Krylov subspace method for approximating $L_f(A, E) \vc{b}$, the matrix-vector product of the Fr\'echet derivative $L_f(A, E)$ of a large-scale matrix function $f(A)$ in direction $E$, a task that arises naturally in the…

Numerical Analysis · Mathematics 2026-01-30 Daniel Kressner , Peter Oehme
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