![]() |
|
||||||||||||||
Home Astronomy research Software Infrastructure: MESA FLASH STARLIB MESA-Web starkiller-astro My instruments White dwarf supernova: Remnant metallicities 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 26Al & 60Fe 44Ti, 60Co & 56Ni Yields of radionuclides Effects of 12C +12C SN 1987A light curve Constraints on Ni/Fe ratios An r-process Neutron Stars and Black Holes: Black Hole Mass Gap Compact object IMF Stars: Neutrino HR diagram Pulsating white dwarfs Pop III with JWST Monte Carlo massive stars Neutrinos from pre-SN Pre-SN variations Monte Carlo white dwarfs SAGB stars Classical novae He shell convection Presolar grains He burn on neutron stars BBFH at 40 years Chemical Evolution: Iron Pseudocarbynes Radionuclides in the 2020s Hypatia catalog Zone models H to Zn Mixing ejecta γ-rays within 100 Mpc Thermodynamics & Networks Stellar EOS 12C(α,γ)16O Rate Proton-rich NSE Reaction networks Bayesian reaction rates Verification Problems: Validating an astro code Su-Olson Cog8 Mader RMTV Sedov Noh Software instruments Presentations Illustrations cococubed YouTube Bicycle adventures Public Outreach Education materials 2022 ASU Solar Systems Astronomy 2022 ASU Energy in Everyday Life AAS Journals AAS YouTube 2022 Earendel, A Highly Magnified Star 2022 TV Columbae, Micronova 2022 White Dwarfs and 12C(α,γ)16O 2022 MESA in Don't Look Up 2022 MESA Marketplace 2022 MESA Summer School 2022 MESA Classroom 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/Rate-Library/
The Impact of Nuclear Reaction Rate Uncertainties On The Evolution of Core-Collapse 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 Carbon-Oxygen White Dwarfs From Monte Carlo Stellar Models (2016) We investigate properties of carbon-oxygen 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 non-resonant astrophysical S-factors 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 extra-solar 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 S-factors and reaction rates based on Bayesian statistics. We develop a framework that incorporates robust parameter estimation, systematic effects, and non-Gaussian uncertainties in a consistent manner. The method is applied to the d(p,γ)3He, 3He(3He,2p)4He, and 3He(α,γ)7Be 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 S-factors, resonance energies and strengths, particle and γ-ray 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 s-process neutron sources, core-collapse supernovae, classical novae, and big bang nucleosynthesis.
STARLIB: A Next-Generation Reaction-Rate Library for Nuclear Astrophysics (2013) STARLIB, discussed in this article, is a next-generation, all-purpose nuclear reaction-rate 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, up-to-date 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.
|
||||||||||||||
|
|
---|