![]() |
|
||||||
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. |
The Impact of Nuclear Reaction Rate Uncertainties On The Evolution of Core-Collapse Supernova Progenitors (2018)
In this article we explore properties of core-collapse supernova progenitors with respect to the composite uncertainties in the thermonuclear reaction rates by coupling the reaction rate probability density functions provided by the STARLIB reaction rate library with MESA stellar models. We evolve 1000 15 M$_{\odot}$ models from the pre main-sequence to core O-depletion at solar and subsolar metallicities for a total of 2000 Monte Carlo stellar models. For each stellar model, we independently and simultaneously sample 665 thermonuclear reaction rates and use them in a MESA in situ reaction network that follows 127 isotopes from $^{1}$H to $^{64}$Zn. With this framework we survey the core mass, burning lifetime, composition, and structural properties at five different evolutionary epochs. At each epoch we measure the probability distribution function of the variations of each property and calculate Spearman Rank-Order Correlation coefficients for each sampled reaction rate to identify which reaction rate has the largest impact on the variations on each property. We find that uncertainties in $^{14}$N$(p,\gamma)^{15}$O, triple-$\alpha$, $^{12}$C$(\alpha,\gamma)^{16}$O, $^{12}$C($^{12}$C,p)$^{23}$Na, $^{12}$C($^{16}$O,p)$^{27}$Al, $^{16}$O($^{16}$O,n)$^{31}$S, $^{16}$O($^{16}$O,p)$^{31}$P, and $^{16}$O($^{16}$O,$\alpha$)$^{28}$Si reaction rates dominate the variations of the properties surveyed. We find that variations induced by uncertainties in nuclear reaction rates grow with each passing phase of evolution, and at core H-, He-depletion are of comparable magnitude to the variations induced by choices of mass resolution and network resolution. However, at core C-, Ne-, and O-depletion, the reaction rate uncertainties can dominate the variation causing uncertainty in various properties of the stellar model in the evolution towards iron core-collapse.
|
||||||
|
---|