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3 Pith papers cite this work. Polarity classification is still indexing.

3 Pith papers citing it

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citation-polarity summary

years

2026 2 2024 1

verdicts

UNVERDICTED 3

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representative citing papers

Flavomon ray tracing in matter gradients

hep-ph · 2026-04-20 · unverdicted · novelty 7.0

Matter gradients slow but do not suppress neutrino-mass-induced flavor instabilities, so flavomon ray tracing is required instead of local stability analysis alone.

Chaos in Inhomogeneous Neutrino Fast Flavor Instability

astro-ph.HE · 2024-01-03 · unverdicted · novelty 5.0

Small initial flavor perturbations in an inhomogeneous neutrino distribution exhibit chaotic divergence at small scales while domain-averaged density matrices stay stable.

Core Collapse Supernova Modeling: The Next Ten Years

astro-ph.HE · 2026-04-27 · unverdicted · novelty 2.0

Core collapse supernova models have demonstrated the neutrino shock reheating mechanism in three dimensions but require substantially more rigorous treatments of neutrino kinetics, fluid instabilities, magnetic fields, strong gravity, and nuclear physics to achieve quantitative predictive power.

citing papers explorer

Showing 3 of 3 citing papers.

  • Flavomon ray tracing in matter gradients hep-ph · 2026-04-20 · unverdicted · none · ref 12

    Matter gradients slow but do not suppress neutrino-mass-induced flavor instabilities, so flavomon ray tracing is required instead of local stability analysis alone.

  • Chaos in Inhomogeneous Neutrino Fast Flavor Instability astro-ph.HE · 2024-01-03 · unverdicted · none · ref 81

    Small initial flavor perturbations in an inhomogeneous neutrino distribution exhibit chaotic divergence at small scales while domain-averaged density matrices stay stable.

  • Core Collapse Supernova Modeling: The Next Ten Years astro-ph.HE · 2026-04-27 · unverdicted · none · ref 40

    Core collapse supernova models have demonstrated the neutrino shock reheating mechanism in three dimensions but require substantially more rigorous treatments of neutrino kinetics, fluid instabilities, magnetic fields, strong gravity, and nuclear physics to achieve quantitative predictive power.