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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.