Statistical methods for thermonuclear reaction rates and nucleosynthesis simulations

Christian Iliadis, Richard Longland, Alain Coc, Francis Timmes, Art E. Champagne

Research output: Contribution to journalArticlepeer-review

31 Scopus citations


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.

Original languageEnglish (US)
Article number034007
JournalJournal of Physics G: Nuclear and Particle Physics
Issue number3
StatePublished - Mar 1 2015


  • Monte Carlo
  • nucleosynthesis
  • statistical methods
  • stellar models
  • thermonuclear reaction rates

ASJC Scopus subject areas

  • Nuclear and High Energy Physics


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