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We study the problem of estimating the diagonal of an implicitly given matrix $\Ab$. For such a matrix we have access to an oracle that allows us to evaluate the matrix quadratic form $ \ub^\top \Ab \ub$. Based on this query oracle, we…

Numerical Analysis · Mathematics 2025-06-19 Haishan Ye , Xiangyu Chang

We develop a symmetry-aware toolkit for finite mixtures whose components are only identifiable up to a finite \emph{folding} group action. The correct estimand is the multiset of parameter orbits in the quotient space, not an ordered list…

Methodology · Statistics 2025-11-11 Koustav Mallik

The $k$-step Lanczos bidiagonalization reduces a matrix $A\in\mathbb{R}^{m\times n}$ into a bidiagonal form $B_k\in\mathbb{R}^{(k+1)\times k}$ while generates two orthonormal matrices $U_{k+1}\in\mathbb{R}^{m\times (k+1)}$ and…

Numerical Analysis · Mathematics 2022-10-20 Haibo Li , Guangming Tan , Tong Zhao

This paper presents an adaptation of recently developed algorithms for quadratic forms over number fields in arXiv:1304.0708 to global function fields of odd characteristics. First, we present algorithm for checking if a given…

Number Theory · Mathematics 2021-04-22 Mawunyo Kofi Darkey-Mensah

We investigate quadrature rules for measures supported on real algebraic and rational curves, focusing on the {odd-degree} case \(2s-1\). Adopting an optimization viewpoint, we minimize suitable penalty functions over the space of…

Algebraic Geometry · Mathematics 2025-10-07 Cordian Riener , Ettore Teixeira Turatti

Successive quadratic approximations, or second-order proximal methods, are useful for minimizing functions that are a sum of a smooth part and a convex, possibly nonsmooth part that promotes regularization. Most analyses of iteration…

Optimization and Control · Mathematics 2019-01-25 Ching-pei Lee , Stephen J. Wright

We develop numerical algorithms for the efficient evaluation of quantities associated with generalized matrix functions [J. B. Hawkins and A. Ben-Israel, Linear and Multilinear Algebra 1(2), 1973, pp. 163-171]. Our algorithms are based on…

Numerical Analysis · Mathematics 2015-12-10 Francesca Arrigo , Michele Benzi , Caterina Fenu

We establish the global gradient bounds for weak solutions to the elliptic variational inequality with two-sided obstructions, associated with a $p(x)$-Laplacian type operator involving degenerate or singular matrix weights. Under the…

Analysis of PDEs · Mathematics 2026-01-05 Minh-Phuong Tran , Duc-Quang Bui , Thanh-Nhan Nguyen

This work introduces a method for determining the energy spectrum of lattice quantum chromodynamics (LQCD) by applying the Lanczos algorithm to the transfer matrix and using a bootstrap generalization of the Cullum-Willoughby method to…

High Energy Physics - Lattice · Physics 2025-05-09 Michael L. Wagman

We consider three mathematically equivalent variants of the conjugate gradient (CG) algorithm and how they perform in finite precision arithmetic. It was shown in [{\em Behavior of slightly perturbed Lanczos and conjugate-gradient…

Numerical Analysis · Computer Science 2021-07-19 Anne Greenbaum , Hexuan Liu , Tyler Chen

The spectral decomposition of a real skew-symmetric matrix $A$ can be mathematically transformed into a specific structured singular value decomposition (SVD) of $A$. Based on such equivalence, a skew-symmetric Lanczos bidiagonalization…

Numerical Analysis · Mathematics 2024-08-20 Jinzhi Huang , Zhongxiao Jia

A new robust algorithm for the numerical computation of biarcs, i.e. $G^1$ curves composed of two arcs of circle, is presented. Many algorithms exist but are based on geometric constructions, which must consider many geometrical…

Numerical Analysis · Mathematics 2017-11-06 Enrico Bertolazzi , Marco Frego

Symmetry in mathematical programming may lead to a multiplicity of solutions. In nonconvex optimisation, it can negatively affect the performance of the branch-and-bound algorithm. Symmetry may induce large search trees with multiple…

Optimization and Control · Mathematics 2019-01-23 Georgia Kouyialis , Ruth Misener

A short intrinsic proof is given for the Bourgain-Brezis-Mironescu theorem with an extension for higher-order gradient forms. This argument illustrates the role of functional geometry and Fourier analysis for obtaining embedding estimates.…

Analysis of PDEs · Mathematics 2012-08-02 William Beckner

A sequential quadratic optimization algorithm for minimizing an objective function defined by an expectation subject to nonlinear inequality and equality constraints is proposed, analyzed, and tested. The context of interest is when it is…

Optimization and Control · Mathematics 2023-03-01 Frank E. Curtis , Daniel P. Robinson , Baoyu Zhou

We show that a recently discovered fourth order symplectic algorithm, which requires one evaluation of force gradient in addition to three evaluations of the force, when iterated to higher order, yielded algorithms that are far superior to…

Computational Physics · Physics 2009-11-06 Siu A. Chin , Donald W. Kidwell

Quadratic systems of equations appear in several applications. The results in this paper are motivated by quadratic systems of equations that describe equilibrium behavior of physical infrastructure networks like the power and gas grids.…

Optimization and Control · Mathematics 2017-03-28 Krishnamurthy Dvijotham , Hung Nguyen , Konstantin Turitsyn

Using methods from symplectic geometry, the second and fifth authors have provided theoretical groundwork and tools aimed at analyzing periodic orbits, their stability and their bifurcations in families, for the purpose of space mission…

Symplectic Geometry · Mathematics 2024-01-26 Cengiz Aydin , Urs Frauenfelder , Otto van Koert , Dayung Koh , Agustin Moreno

In this paper, we consider the Forward--Backward proximal splitting algorithm to minimize the sum of two proper convex functions, one of which having a Lipschitz continuous gradient and the other being partly smooth relative to an active…

Optimization and Control · Mathematics 2015-03-11 Jingwei Liang , Jalal Fadili , Gabriel Peyré

The spectral transformation Lanczos method for the sparse symmetric definite generalized eigenvalue problem for matrices $A$ and $B$ is an iterative method that addresses the case of semidefinite or ill conditioned $B$ using a shifted and…

Numerical Analysis · Mathematics 2024-11-07 Michael Stewart