Neutrino transport with Monte Carlo method: II. Quantum Kinetic Equations

TL;DR

This paper introduces a novel Monte Carlo solver for quantum kinetic equations of neutrinos, enabling self-consistent modeling of flavor conversions, transport, and collisions with improved numerical techniques.

Contribution

It presents an upgraded Monte Carlo neutrino transport solver incorporating flavor degrees of freedom and new collision treatment methods for quantum kinetic equations.

Findings

Validated the new Monte Carlo solver with code tests.

Demonstrated effective suppression of statistical noise.

Showcased potential for new insights into neutrino dynamics.

Abstract

Neutrinos have an unique quantum feature as flavor conversions. Recent studies suggested that collective neutrino oscillations play important roles in high-energy astrophysical phenomena. Quantum kinetic equation (QKE) is capable of describing the neutrino flavor conversion, transport and matter collision self-consistently. However, we have experienced many technical difficulties in their numerical implementation. In this paper, we present a new QKE solver based on Monte Carlo (MC) approach. This is an upgraded version of our classical MC neutrino transport solver; in essence, a flavor degree of freedom including mixing state is added into each MC particle. This extension requires updating numerical treatments of collision terms, in particular for scattering processes. We deal with the technical problem by generating a new MC particle at each scattering event. To reduce statistical noise inherent in MC methods, we develop the effective mean free path method. This suppresses a sudden change of flavor state due to collisions without increasing the number of MC particles. We present a suite of code tests to validate these new modules with comparing to the results reported in previous studies. Our QKE-MC solver is developed with fundamentally different philosophy and design from other deterministic- and mesh methods, suggesting that it will be complementary to others, and potentially provide new insights into physical processes of neutrino dynamics.