Diagrammatic Monte Carlo for Finite Systems at Zero Temperature

TL;DR

This paper introduces a diagrammatic Monte Carlo algorithm tailored for zero-temperature, self-bound finite systems, enabling the inclusion of high-order excitations in nuclear models, bridging the gap between microscopic theory and reactions.

Contribution

The paper presents a novel Monte Carlo method for zero-temperature finite systems, allowing comprehensive diagram sampling to incorporate high-order excitations in nuclear physics models.

Findings

Enables inclusion of high-order excitations in nuclear models.

Demonstrates effectiveness on the Richardson model.

Bridges gap between microscopic understanding and nuclear reactions.

Abstract

High-order virtual excitations play an important role in microscopic models of nuclear reactions at intermediate energies. However, the factorial growth of their complexity has prevented their consistent inclusion in ab initio many-body calculations. For infinite systems at finite temperature, such drawbacks can be overcome using diagrammatic Monte Carlo techniques to resum entire series of Feynman diagrams. We present a diagrammatic Monte Carlo algorithm that can be applied to self-bound systems with discrete energy levels at zero temperature, and demonstrate its potential for the Richardson model of nuclear pairing. We show that sampling the topological space of diagrams allows the inclusion of high-order excitations that are neglected in state-of-the-art approximations used in nuclear physics and quantum chemistry. We propose that sampling the diagrammatic space can overcome the long-standing gap between our microscopic understanding of structure and reactions in nuclear physics.