TY - JOUR

T1 - Statistical methods for thermonuclear reaction rates and nucleosynthesis simulations

AU - Iliadis, Christian

AU - Longland, Richard

AU - Coc, Alain

AU - Timmes, Francis

AU - Champagne, Art E.

PY - 2015/3/1

Y1 - 2015/3/1

N2 - Rigorous statistical methods for estimating thermonuclear reaction rates and nucleosynthesis are becoming increasingly established in nuclear astrophysics. The main challenge being faced is that experimental reaction rates are highly complex quantities derived from a multitude of different measured nuclear parameters (e.g., astrophysical S-factors, resonance energies and strengths, particle and γ-ray partial widths). We discuss the application of the Monte Carlo method to two distinct, but related, questions. First, given a set of measured nuclear parameters, how can one best estimate the resulting thermonuclear reaction rates and associated uncertainties? Second, given a set of appropriate reaction rates, how can one best estimate the abundances from nucleosynthesis (i.e., reaction network) calculations? The techniques described here provide probability density functions that can be used to derive statistically meaningful reaction rates and final abundances for any desired coverage probability. Examples are given for applications to s-process neutron sources, core-collapse supernovae, classical novae, and Big Bang nucleosynthesis.

AB - Rigorous statistical methods for estimating thermonuclear reaction rates and nucleosynthesis are becoming increasingly established in nuclear astrophysics. The main challenge being faced is that experimental reaction rates are highly complex quantities derived from a multitude of different measured nuclear parameters (e.g., astrophysical S-factors, resonance energies and strengths, particle and γ-ray partial widths). We discuss the application of the Monte Carlo method to two distinct, but related, questions. First, given a set of measured nuclear parameters, how can one best estimate the resulting thermonuclear reaction rates and associated uncertainties? Second, given a set of appropriate reaction rates, how can one best estimate the abundances from nucleosynthesis (i.e., reaction network) calculations? The techniques described here provide probability density functions that can be used to derive statistically meaningful reaction rates and final abundances for any desired coverage probability. Examples are given for applications to s-process neutron sources, core-collapse supernovae, classical novae, and Big Bang nucleosynthesis.

KW - Monte Carlo

KW - nucleosynthesis

KW - statistical methods

KW - stellar models

KW - thermonuclear reaction rates

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U2 - 10.1088/0954-3899/42/3/034007

DO - 10.1088/0954-3899/42/3/034007

M3 - Article

AN - SCOPUS:84924366038

VL - 42

JO - Journal of Physics G: Nuclear and Particle Physics

JF - Journal of Physics G: Nuclear and Particle Physics

SN - 0954-3899

IS - 3

M1 - 034007

ER -