Explicit Asymptotic Solutions of $\nu_e + e^-$ Neutrino Networks for Large Sets of Partial Differential Equations in Core-Collapse Supernovae
Raghav Chari

TL;DR
This paper introduces FENN, a novel explicit asymptotic method for modeling neutrino networks in core-collapse supernovae, offering improved computational efficiency and stability over traditional implicit methods.
Contribution
The paper presents a new software suite with explicit asymptotic methods for neutrino network modeling, enhancing speed and stability in large-scale astrophysical simulations.
Findings
FENN delivers accurate neutrino network solutions with faster computation.
It extends to scaled networks beyond standard energy groupings.
Demonstrates effective modeling of neutrino-electron scattering interactions.
Abstract
In physics, accurately modeling large-scale phenomena such as core-collapse supernovae, (CCSN), and neutron star mergers are computationally challenging and require solving large sets of partial and ordinary differential equations. Traditional methods used widely in the scientific community are predominantly implicit, which are approximations that often require drastic simplifications and can be computationally inefficient. This thesis presents results on a new software suite titled "Fast Explicit Neutrino Networks" or "FENN", that introduces a suite of algebraically stabilized explicit methods known as explicit asymptotic for modeling Neutrino Electron Scattering, (NES), presenting a novel approach that combines the stability of traditional methods with enhanced computational efficiency. Initial results show that FENN can deliver accurate solutions for neutrino networks at improved…
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Taxonomy
TopicsParticle physics theoretical and experimental studies · Neutrino Physics Research · Cosmology and Gravitation Theories
