activity
20192026
collaborators

8 papers

math.NA2026

A recursive butterfly factorization with optimality guarantees

David Persson, Paul G. Beckman, Tyler Chen +2

We formalize a recursive format for representing a butterfly matrix. This new format naturally leads to a simple recursive algorithm for computing a quasi-optimal butterfly approxi…

math.NA2026

A Butterfly-Accelerated Manifold Harmonic Transform

Paul G. Beckman, Samuel F. Potter, Michael O'Neil

The eigenfunctions of the Laplacian are a natural basis of functions for many tasks in computational mathematics. On the circle and sphere, the eigenfunctions are given by complex…

math.NA2026

Linear Systems and Eigenvalue Problems: Open Questions from a Simons Workshop

Noah Amsel, Yves Baumann, Paul Beckman +33

This document presents a series of open questions arising in matrix computations, i.e., the numerical solution of linear algebra problems. It is a result of working groups at the w…

stat.ME2025

Fast nonparametric spectral density estimation from irregularly sampled data

Christopher J. Geoga, Paul G. Beckman

We introduce a nonparametric spectral density estimator for continuous-time and continuous-space processes measured at fully irregular locations. Our estimator is constructed using…

math.NA2024

A Nonuniform Fast Hankel Transform

Paul G. Beckman, Michael O'Neil

We describe a fast algorithm for computing discrete Hankel transforms of moderate orders from nonuniform points to nonuniform frequencies in operati…

stat.CO2024

Fast Adaptive Fourier Integration for Spectral Densities of Gaussian Processes

Paul G. Beckman, Christopher J. Geoga

The specification of a covariance function is of paramount importance when employing Gaussian process models, but the requirement of positive definiteness severely limits those use…

stat.CO2022

Scalable Computations for Nonstationary Gaussian Processes

Paul G. Beckman, Christopher J. Geoga, Michael L. Stein +1

Nonstationary Gaussian process models can capture complex spatially varying dependence structures in spatial datasets. However, the large number of observations in modern datasets…

math.NA2019

A Shift Selection Strategy for Parallel Shift-Invert Spectrum Slicing in Symmetric Self-Consistent Eigenvalue Computation

David B. Williams-Young, Paul G. Beckman, Chao Yang

The central importance of large scale eigenvalue problems in scientific computation necessitates the development of massively parallel algorithms for their solution. Recent advance…