

Home Astronomy research Software Infrastructure: MESA FLASHX STARLIB MESAWeb starkillerastro My instruments White dwarf pulsations: Probe of ^{12}C(α,γ)^{16}O Impact of ^{22}Ne Impact of ν cooling Variable white dwarfs MC reaction rates Micronovae Novae White dwarf supernova: Stable nickel production Remnant metallicities Colliding white dwarfs Merging white dwarfs Ignition conditions Metallicity effects Central density effects Detonation density Tracer particle burning Subsonic burning fronts Supersonic fronts W7 profiles Massive stars: Pop III with HST/JWST Rotating progenitors 3D evolution to collapse MC reaction rates PreSN variations Massive star supernova: Yields of radionuclides ^{26}Al & ^{60}Fe ^{44}Ti, ^{60}Co & ^{56}Ni SN 1987A light curve Constraints on Ni/Fe An rprocess Effects of ^{12}C +^{12}C Neutron Stars and Black Holes: Black Hole spectrum Mass Gap with LVK Compact object IMF He burn neutron stars Neutrino Emission: Identifying the PreSN Neutrino HR diagram PreSN Beta Processes PreSN neutrinos Stars: Hypatia catalog SAGB stars Nugrid Yields I He shell convection BBFH at 40 years γrays within 100 Mpc Iron Pseudocarbynes PreSolar Grains: Crich presolar grains SiC Type U/C grains Grains from massive stars Placing the Sun SiC Presolar grains Chemical Evolution: Radionuclides in 2020s Zone models H to Zn Mixing ejecta Thermodynamics & Networks Skye EOS Helm EOS Five EOSs Equations of State 12C(α,γ)16O Rate Protonrich NSE Reaction networks Bayesian reaction rates Verification Problems: Validating an astro code SuOlson Cog8 Mader RMTV Sedov Noh Software instruments Presentations Illustrations cococubed YouTube Bicycle adventures Public Outreach Education materials 2023 ASU Solar Systems Astronomy 2023 ASU Energy in Everyday Life AAS Journals AAS YouTube 2023 MESA VI 2023 MESA Marketplace 2023 MESA Classroom 2022 Earendel, A Highly Magnified Star 2022 White Dwarfs & ^{12}C(α,γ)^{16}O 2022 Black Hole Mass Spectrum 2022 MESA in Don't Look Up 2021 Bill Paxton, Tinsley Prize Contact: F.X.Timmes my one page vitae, full vitae, research statement, and teaching statement. 
STARLIB is avaliable at
https://starlib.github.io/RateLibrary/
The Impact of Nuclear Reaction Rate Uncertainties On The Evolution of CoreCollapse Supernova Progenitors (2018) We investigate properties of massive stars with respect to the composite uncertainties in the reaction rates using MESA and STARLIB. This is the first Monte Carlo massive star evolution study that use complete stellar models. 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. This is the first Monte Carlo stellar evolution study that use complete stellar models. Bayesian Estimation Of Thermonuclear Reaction Rates (2016) 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 article 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.
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 article 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, discussed in this article, is a nextgeneration, allpurpose nuclear reactionrate library. For the first time, a 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.




