Two-beam Multiparticle Many-body simulations of Inhomogeneous FFI

TL;DR

This paper introduces a tensor-network framework for simulating complex neutrino flavor evolution in dense astrophysical environments, capturing many-body quantum effects beyond mean-field approximations.

Contribution

It provides a unified, scalable simulation method for inhomogeneous, anisotropic neutrino systems, enabling detailed comparison of boundary conditions and initial configurations.

Findings

Many-body systems equilibrate earlier than mean-field models.

Open boundaries can replicate closed-system behavior with initial superimposed beams.

Separated initial configurations develop entanglement more slowly and reach different equilibrium states.

Abstract

Neutrino flavor evolution in dense astrophysical environments is inherently nonlinear and sensitive to many-body (MB) quantum effects beyond the mean-field (MF) approximation. Existing MB studies are constrained by small system sizes, closed boundaries, and highly idealized symmetry assumptions. We present a unified tensor-network framework that enables simulations of inhomogeneous and anisotropic flavor evolution under conditions relevant to core-collapse supernovae and neutron-star mergers. Within this framework, we examine the effects of inhomogeneity, boundary conditions, and convergence with resolution for multiple neutrino distributions, allowing direct comparison of these setups under one consistent formulation. In our simulations, many-body systems equilibrate earlier than their mean-field counterparts while approaching similar final flavor states. Enlarging the interaction region allows open boundaries to reproduce closed-system behavior, but only when the beams begin superimposed and interact continuously. By contrast, initially separated configurations develop entanglement more slowly, interact over longer times, and equilibrate to a flavor content that differs from that obtained from initially superimposed calculations.