Linear response strength functions with iterative Arnoldi diagonalization

TL;DR

This paper introduces an iterative Arnoldi diagonalization method for calculating RPA strength functions that avoids explicit RPA matrix storage, improving scalability and stability for large model spaces.

Contribution

It presents a novel approach to compute RPA strength functions using iterative Arnoldi diagonalization, enhancing efficiency and numerical stability over traditional methods.

Findings

Accurately reproduces RPA strength functions for 132Sn

Demonstrates improved scalability with larger model spaces

Shows stable numerical performance in benchmark tests

Abstract

We report on an implementation of a new method to calculate RPA strength functions with iterative non-hermitian Arnoldi diagonalization method, which does not explicitly calculate and store the RPA matrix. We discuss the treatment of spurious modes, numerical stability, and how the method scales as the used model space is enlarged. We perform the particle-hole RPA benchmark calculations for double magic nucleus 132Sn and compare the resulting electromagnetic strength functions against those obtained within the standard RPA.