

Home Astronomy research Software Infrastructure: MESA FLASH STARLIB My codes White dwarf supernova: Colliding white dwarfs Merging white dwarfs Ignition conditions Metallicity effects Central density effects Detonation density effects Tracer particle burning Subsonic burning fronts Supersonic burning fronts W7 profiles Massive star supernova: Rotating progenitors 3D evolution ^{26}Al & ^{60}Fe ^{44}Ti, ^{60}Co & ^{56}Ni Yields of radionuclides Effects of ^{12}C +^{12}C SN 1987A light curve Constraints on Ni/Fe ratios An rprocess Compact object IMF Stars: PreSN variations MC white dwarfs SAGB Classical novae He shell convection Presolar grains He burn on neutron stars BBFH at 40 years Chemical Evolution: Hypatia catalog Zone models H to Zn Mixing ejecta γrays within 100 Mpc Thermodynamics & Networks Stellar EOS Reaction networks Protonrich NSE MC reaction rates Verification Problems: Validating an astro code SuOlson Cog8 Mader RMTV Sedov Noh Software instruments Presentations Illustrations Videos Bicycle adventures AAS Journals 2017 MESA Summer School ASU+EdX AST111x Teaching materials Education and Public Outreach 2016 NSF SI2 PI Workshop Contact: F.X.Timmes my one page vitae, full vitae, research statement, and teaching statement. 
STARLIB is avaliable at
http://starlib.physics.unc.edu/.
Bayesian Estimation Of Thermonuclear Reaction Rates (2016) The problem of estimating nonresonant astrophysical Sfactors and thermonuclear reaction rates, based on measured nuclear cross sections, is of major interest for nuclear energy generation, neutrino physics, and element synthesis. Many different methods have been applied in the past to this problem, almost all of them based on traditional statistics. Bayesian methods, on the other hand, are now in widespread use in the physical sciences. In astronomy, for example, Bayesian statistics is applied to the observation of extrasolar planets, gravitational waves, and type Ia supernovae. However, nuclear physics, in particular, has been slow to adopt Bayesian methods. In this paper we present astrophysical Sfactors and reaction rates based on Bayesian statistics. We develop a framework that incorporates robust parameter estimation, systematic effects, and nonGaussian uncertainties in a consistent manner. The method is applied to the d(p,γ)^{3}He, ^{3}He(^{3}He,2p)^{4}He, and ^{3}He(α,γ)^{7}Be reactions, important for deuterium burning, solar neutrinos, and big bang nucleosynthesis.
Properties Of CarbonOxygen White Dwarfs From Monte Carlo Stellar Models (2016) We investigate properties of carbonoxygen white dwarfs with respect to the composite uncertainties in the reaction rates using MESA and STARLIB. These are the first Monte Carlo stellar evolution studies that use complete stellar models. Statistical Methods for Thermonuclear Reaction Rates and Nucleosynthesis Simulations (2015) 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 Sfactors, resonance energies and strengths, particle and γray partial widths). In this paper 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 sprocess neutron sources, corecollapse supernovae, classical novae, and big bang nucleosynthesis.
STARLIB: A NextGeneration ReactionRate Library for Nuclear Astrophysics (2013) STARLIB, which is discussed in this paper, is a nextgeneration, allpurpose nuclear reactionrate library. For the first time, this library provides the rate probability density at all temperature grid points for convenient implementation in models of stellar phenomena. The recommended rate and its associated uncertainties are also included. Currently, uncertainties are absent from all other rate libraries, and, although estimates have been attempted in previous evaluations and compilations, these are generally not based on rigorous statistical definitions. A common standard for deriving uncertainties is clearly warranted. STARLIB represents a first step in addressing this deficiency by providing a tabular, uptodate database that supplies not only the rate and its uncertainty but also its distribution. Because a majority of rates are lognormally distributed, this allows the construction of rate probability densities from the columns of STARLIB. This structure is based on a recently suggested Monte Carlo method to calculate reaction rates, where uncertainties are rigorously defined. In STARLIB, experimental rates are supplemented with: (i) theoretical TALYS rates for reactions for which no experimental input is available, and (ii) laboratory and theoretical weak rates. STARLIB includes all types of reactions of astrophysical interest to Z=83, such as (p,γ), (p,α), (α,n), and corresponding reverse rates. Strong rates account for thermal target excitations. Here, we summarize our Monte Carlo formalism, introduce the library, compare methods of correcting rates for stellar environments, and discuss how to implement our library in Monte Carlo nucleosynthesis studies.




