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Rigorous statistical methods for estimating thermonuclear reaction rates andnucleosynthesis are becoming increasingly established in nuclear astrophysics.The main challenge being faced is that experimental reaction rates are highlycomplex quantities derived from a multitude of different measured nuclearparameters (e.g., astrophysical S-factors, resonance energies and strengths,particle and gamma-ray partial widths). We discuss the application of the MonteCarlo method to two distinct, but related, questions. First, given a set ofmeasured nuclear parameters, how can one best estimate the resultingthermonuclear reaction rates and associated uncertainties? Second, given a setof appropriate reaction rates, how can one best estimate the abundances fromnucleosynthesis (i.e., reaction network) calculations? The techniques describedhere provide probability density functions that can be used to derivestatistically meaningful reaction rates and final abundances for any desiredcoverage probability. Examples are given for applications to s-process neutronsources, core-collapse supernovae, classical novae, and big bangnucleosynthesis.

Statistical Methods for Thermonuclear Reaction Rates and Nucleosynthesis Simulations