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We describe a Lanczos-based algorithm for approximating the product of a rational matrix function with a vector. This algorithm, which we call the Lanczos method for optimal rational matrix function approximation (Lanczos-OR), returns the…

Numerical Analysis · Mathematics 2023-06-01 Tyler Chen , Anne Greenbaum , Cameron Musco , Christopher Musco

A general framework for oblique projections of nonhermitian matrices onto rational Krylov subspaces is developed. To obtain this framework we revisit the classical rational Krylov subspace algorithm and prove that the projected matrix can…

Numerical Analysis · Mathematics 2019-11-18 Niel Van Buggenhout , Marc Van Barel , Raf Vandebril

In the presence of a non-vanishing chemical potential the eigenvalues of the Dirac operator become complex. We calculate spectral correlation functions of complex eigenvalues using a random matrix model approach. Our results apply to…

High Energy Physics - Theory · Physics 2009-11-07 G. Akemann

We describe an explicit construction of approximate Ginsparg-Wilson fermions for QCD. We use ingredients of perfect action origin, and further elements. The spectrum of the lattice Dirac operator reveals the quality of the approximation. We…

High Energy Physics - Lattice · Physics 2009-10-31 W. Bietenholz , N. Eicker , I. Hip , K. Schilling

Randomized Krylov subspace methods that employ the sketch-and-solve paradigm to substantially reduce orthogonalization cost have recently shown great promise in speeding up computations for many core linear algebra tasks (e.g., solving…

Numerical Analysis · Mathematics 2026-03-13 Emil Krieger , Marcel Schweitzer

Subspace recycling iterative methods and other subspace augmentation schemes are a successful extension to Krylov subspace methods in which a Krylov subspace is augmented with a fixed subspace spanned by vectors deemed to be helpful in…

Numerical Analysis · Mathematics 2022-02-11 Kirk M. Soodhalter

We consider a Krylov subspace approximation method for the symmetric differential Riccati equation $\dot{X} = AX + XA^T + Q - XSX$, $X(0)=X_0$. The method we consider is based on projecting the large scale equation onto a Krylov subspace…

Numerical Analysis · Mathematics 2021-06-24 Antti Koskela , Hermann Mena

We construct new Ginsparg-Wilson fermions for QCD by inserting an approximately chiral Dirac operator - which involves ingredients of a perfect action - into the overlap formula. This accelerates the convergence of the overlap Dirac…

High Energy Physics - Lattice · Physics 2010-04-05 W. Bietenholz

The chiral symmetry at finite lattice spacing of Ginsparg-Wilson fermionic actions constrains the renormalization of the lattice operators; in particular, the topological susceptibility does not require any renormalization, when using a…

High Energy Physics - Lattice · Physics 2009-11-10 Luigi Del Debbio , Claudio Pica

In this work we introduce a memory-efficient method for computing the action of a Hermitian matrix function on a vector. Our method consists of a rational Lanczos algorithm combined with a basis compression procedure based on rational…

Numerical Analysis · Mathematics 2024-03-08 Angelo A. Casulli , Igor Simunec

The resolvent Krylov subspace method builds approximations to operator functions $f(A)$ times a vector $v$. For the semigroup and related operator functions, this method is proved to possess the favorable property that the convergence is…

Numerical Analysis · Mathematics 2019-07-15 Volker Grimm , Tanja Göckler

It was recently proposed by the second author to consider lattice formulations of QCD in which complete actions, including the gauge part, are built explicitly from a given Dirac operator D. In a simple example of such theory, the gauge…

High Energy Physics - Lattice · Physics 2008-11-26 Andrei Alexandru , Ivan Horvath , Keh-Fei Liu

Thus far, sparse representations have been exploited largely in the context of robustly estimating functions in a noisy environment from a few measurements. In this context, the existence of a basis in which the signal class under…

Data Structures and Algorithms · Computer Science 2009-06-26 Mohamed-Ali Belabbas , Patrick J. Wolfe

Randomized orthogonal projection methods (ROPMs) can be used to speed up the computation of Krylov subspace methods in various contexts. Through a theoretical and numerical investigation, we establish that these methods produce…

Numerical Analysis · Mathematics 2023-03-14 Edouard Timsit , Laura Grigori , Oleg Balabanov

Using the overlap-Dirac operator proposed by Neuberger, we have computed in lattice QCD the one-loop renormalization factors of ten operators which measure the lowest two moments of unpolarized and polarized non-singlet quark distributions.…

High Energy Physics - Lattice · Physics 2015-06-25 Stefano Capitani

We present non-perturbative renormalization constants of fermionic bilinears on the lattice in the quenched approximation at beta=6.1 using an overlap fermion action with hypercubic(HYP)-blocked links. We consider the effects of the exact…

High Energy Physics - Lattice · Physics 2009-11-11 Thomas DeGrand , Zhaofeng Liu

Iterative Krylov projection methods have become widely used for solving large-scale linear inverse problems. However, methods based on orthogonality include the computation of inner-products, which become costly when the number of…

Numerical Analysis · Mathematics 2025-02-06 Malena Sabaté Landman , Ariana N. Brown , Julianne Chung , James G. Nagy

The overlap hypercube fermion is a variant of a chirally symmetric lattice fermion, which is endowed with a higher level of locality than the standard overlap fermion. We apply this formulation in quenched QCD simulations with light quarks.…

High Energy Physics - Lattice · Physics 2009-11-11 W. Bietenholz , S. Shcheredin

The low-lying eigenvalues of a (sparse) hermitian matrix can be computed with controlled numerical errors by a conjugate gradient (CG) method. This CG algorithm is accelerated by alternating it with exact diagonalisations in the subspace…

High Energy Physics - Lattice · Physics 2008-11-26 Thomas Kalkreuter , Hubert Simma

We propose a fast algorithm for computing the entire ridge regression regularization path in nearly linear time. Our method constructs a basis on which the solution of ridge regression can be computed instantly for any value of the…

Optimization and Control · Mathematics 2022-10-25 Yifei Wang , Mert Pilanci