Speaker
Description
This research offers a stochastic framework for the stellar helium burning network (SHBN), combining Itô stochastic differential equations (SDEs) with multiplicative white noise to approximate turbulence and quantum fluctuations in stellar interiors. We construct a semi-analytical power series solution linked with stochastic correction via the exponential Itô factor, confirming findings against Runge-Kutta integration. Simulations reveal distinct nucleosynthetic regimes: under low noise intensity (σ=0.01–0.04), abundance dispersion emerges without yield suppression, matching observed heterogeneity in quiescent stellar phases (e.g., RGB/AGB stars) while maintaining baryon conservation (< 2% fluctuation); at moderate noise (σ=0.1), efficient nucleosynthesis yields final abundances of (4He=0.0597), (12C=0.0101), (16O=0.0160), and (20Ne=0.0982) while exhibiting stochastic phenomena like burst-like synthesis; however, high noise (σ ≥ 0.5) catastrophically suppresses yields abundances fall below 0.003 at σ=0.5 and collapse to ∼10⁻⁷ at σ=1.0, emulating nucleosynthesis quenching in extreme turbulence (e.g., supernova progenitors). Crucially, the carbon-to-oxygen ratio stays consistent (C/O≈0.634) throughout all σ levels, explaining narrow spectroscopic distributions despite absolute yield fluctuation. These results establish noise as a core physical process essential for reconstructing nucleosynthesis under thermal/turbulent instabilities and for understanding abundance distributions throughout stellar history.
| Stream | Science or Engineering |
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