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This paper revisits the error analysis of the Stochastic Lanczos Quadrature (SLQ) method for approximating the trace of matrix functions, with a specific focus on asymmetric Lanczos quadrature rules. We reexplain an existing theoretical…

Numerical Analysis · Mathematics 2026-05-14 Wenhao Li , Yixuan Huang , Shengxin Zhu

Two analysis techniques, the generalized eigenvalue method (GEM) or Prony's (or related) method (PM), are commonly used to analyze statistical estimates of correlation functions produced in lattice quantum field theory calculations. GEM…

High Energy Physics - Lattice · Physics 2023-09-12 George T. Fleming

The quantum many-body problem lies at the center of the most important open challenges in condensed matter, quantum chemistry, atomic, nuclear, and high-energy physics. While quantum Monte Carlo, when applicable, remains the most powerful…

Strongly Correlated Electrons · Physics 2022-06-30 Hongwei Chen , Douglas Hendry , Phillip Weinberg , Adrian E. Feiguin

In numerical approaches to solving differential equations on a lattice, a representation of the derivative operator that correctly matches the continuum behaviour of functions of momentum up to the band limit must be non-local. We present…

We propose the Lanczos network (LanczosNet), which uses the Lanczos algorithm to construct low rank approximations of the graph Laplacian for graph convolution. Relying on the tridiagonal decomposition of the Lanczos algorithm, we not only…

Machine Learning · Computer Science 2019-10-24 Renjie Liao , Zhizhen Zhao , Raquel Urtasun , Richard S. Zemel

Computing eigenvalues is a computationally intensive task central to numerous applications in the natural sciences. Toward this end, we investigate the quantum block Krylov subspace projector (QBKSP) algorithm - a multireference quantum…

Quantum Physics · Physics 2025-11-26 Maria Gabriela Jordão Oliveira , Nina Glaser

The classical formalism of the Moment Problem has been combined with a cumulant approach and applied to the extensive many-body problem. This has yielded many new exact results for many-body systems in the thermodynamic limit - for the…

Statistical Mechanics · Physics 2007-05-23 N. S. Witte

In this paper, we present a new approach for model reduction of large scale first and second order dynamical systems with multiple inputs and multiple outputs (MIMO). This approach is based on the projection of the initial problem onto…

Numerical Analysis · Computer Science 2019-03-19 Yassine Kaouane , Khalide Jbilou

We describe a number of recently developed techniques for improving the performance of large-scale nuclear configuration interaction calculations on high performance parallel computers. We show the benefit of using a preconditioned block…

Numerical Analysis · Computer Science 2017-12-29 Meiyue Shao , Hasan Metin Aktulga , Chao Yang , Esmond G. Ng , Pieter Maris , James P. Vary

The Lanczos algorithm is evaluated for solving the time-independent as well as the time-dependent Dirac equation with arbitrary electromagnetic fields. We demonstrate that the Lanczos algorithm can yield very precise eigenenergies and…

Computational Physics · Physics 2015-01-05 Randolf Beerwerth , Heiko Bauke

We study the Lanczos algorithm where the initial vector is sampled uniformly from $\mathbb{S}^{n-1}$. Let $A$ be an $n \times n$ Hermitian matrix. We show that when run for few iterations, the output of Lanczos on $A$ is almost…

Numerical Analysis · Mathematics 2020-09-15 Jorge Garza-Vargas , Archit Kulkarni

We describe a further development of the stochastic state selection method, a new Monte Carlo method we have proposed recently to make numerical calculations in large quantum spin systems. Making recursive use of the stochastic state…

Strongly Correlated Electrons · Physics 2009-11-11 Tomo Munehisa , Yasuko Munehisa

With rapid progress being made in the development of platforms for quantum computation, there has been considerable interest in whether present-day and near-term devices can be used to solve problems of relevance. A commonly cited…

The Lanczos process constructs a sequence of orthonormal vectors v_m spanning a nested sequence of Krylov subspaces generated by a hermitian matrix A and some starting vector b. In this paper we show how to cheaply recover a secondary…

High Energy Physics - Lattice · Physics 2015-04-22 A. Frommer , K. Kahl , Th. Lippert , H. Rittich

In this paper we propose a new class of coupling methods for the sensitivity analysis of high dimensional stochastic systems and in particular for lattice Kinetic Monte Carlo. Sensitivity analysis for stochastic systems is typically based…

Numerical Analysis · Mathematics 2015-06-18 Georgios Arampatzis , Markos Katsoulakis

Lattice quantum chromodynamics (LQCD) has the promise of constraining low-energy constants (LECs) of nuclear effective field theories (EFTs) from first-principles calculations that incorporate the dynamics of quarks and gluons. Given the…

High Energy Physics - Lattice · Physics 2022-05-25 Zohreh Davoudi , Saurabh V. Kadam

We present randUBV, a randomized algorithm for matrix sketching based on the block Lanzcos bidiagonalization process. Given a matrix $\bf{A}$, it produces a low-rank approximation of the form ${\bf UBV}^T$, where $\bf{U}$ and $\bf{V}$ have…

Numerical Analysis · Mathematics 2021-02-09 Eric Hallman

The Adiabatic Gauge Potential (AGP) is the generator of adiabatic deformations between quantum eigenstates. There are many ways to construct the AGP operator and evaluate the AGP norm. Recently, it was proposed that a Gram-Schmidt-type…

Quantum Physics · Physics 2023-02-21 Budhaditya Bhattacharjee

There is a class of statistical problems that arises in several contexts, the Lattice QCD problem of particle physics being one that has attracted the most attention. In essence, the problem boils down to the estimation of an infinite…

Methodology · Statistics 2012-01-06 Joshua Landon , Frank X. Lee , Nozer D. Singpurwalla

Recent years have witnessed intense development of randomized methods for low-rank approximation. These methods target principal component analysis (PCA) and the calculation of truncated singular value decompositions (SVD). The present…

Computation · Statistics 2017-01-02 Arthur Szlam , Yuval Kluger , Mark Tygert
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