A nonuniform fast Hankel transform

IDeAS
Jan 13, 2025
11 am - 12 pm
224 Fine Hall

Abstract: 

We describe a fast algorithm for computing discrete Hankel transforms of moderate orders from n nonuniform points to m nonuniform frequencies in O((m+n)logmin(n,m)) time. Our approach combines local and asymptotic Bessel function expansions with nonuniform fast Fourier transforms. The order of each expansion is adjusted automatically according to error analysis to obtain any desired precision. Several numerical examples are provided which demonstrate the speed and accuracy of the algorithm and its applications in spatial statistics.

Paul Beckman - Bio

 

 

Paul Beckman

Paul Beckman

Paul Beckman is a PhD candidate at The Courant Institute at New York University advised by Professor Michael O’Neil. Prior to his doctoral work, he was a math and statistics researcher at Argonne National Laboratory with Professors Mihai Anitescu and Michael Stein. His research focuses on using tools from classical and modern numerical analysis to develop fast algorithms for problems in spatial statistics and data science.