Monte Carlo variations as a tool to assess nuclear physics uncertainties in nucleosynthesis studies

被引:1
|
作者
Rauscher, Thomas [1 ]
机构
[1] Univ Basel, Dept Phys, Klingelbergstr 82, CH-4056 Basel, Switzerland
基金
欧盟第七框架计划;
关键词
S-PROCESS NUCLEOSYNTHESIS; CROSS-SECTIONS; RATES;
D O I
10.1088/1742-6596/1643/1/012062
中图分类号
P1 [天文学];
学科分类号
0704 ;
摘要
The propagation of uncertainties in reaction cross sections and rates of neutron-, proton-, and alpha-induced reactions into the final isotopic abundances obtained in nucleosynthesis models is an important issue in studies of nucleosynthesis and Galactic Chemical Evolution. We developed a Monte Carlo method to allow large-scale postprocessing studies of the impact of nuclear uncertainties on nucleosynthesis. Temperature-dependent rate uncertainties combining realistic experimental and theoretical uncertainties are used. From detailed statistical analyses uncertainties in the final abundances are derived as probability density distributions. Furthermore, based on rate and abundance correlations an automated procedure identifies the most important reactions in complex flow patterns from superposition of many zones or tracers. The method already has been applied to a number of nucleosynthesis processes.
引用
收藏
页数:6
相关论文
共 50 条
  • [41] Assessment and propagation of the 237Np nuclear data uncertainties in integral calculations by Monte Carlo techniques
    Noguere, Gilles
    Bernard, David
    Saint Jean, Cyrille De
    Iooss, Bertrand
    Gunsing, Frank
    Kobayashi, Katsuhei
    Mughabghab, Said F.
    Siegler, Peter
    NUCLEAR SCIENCE AND ENGINEERING, 2008, 160 (01) : 108 - 122
  • [42] SPECIFIC PURPOSE MONTE-CARLO MODELING OF NUCLEAR WELL LOGGING TOOL RESPONSES
    GARDNER, RP
    VERGHESE, K
    CHOI, HK
    MICKAEL, M
    IEEE TRANSACTIONS ON NUCLEAR SCIENCE, 1988, 35 (01) : 882 - 885
  • [43] MCHP (Monte Carlo plus Human Phantom): Platform to facilitate teaching nuclear radiation physics
    Beni, Mehrdad Shahmohammadi
    Watabe, Hiroshi
    Krstic, Dragana
    Nikezic, Dragoslav
    Yu, Kwan Ngok
    PLOS ONE, 2021, 16 (09):
  • [44] Phenomenology and formal studies on small-x physics by using Monte Carlo techniques
    Chachamis, G.
    Sabio Vera, A.
    NUCLEAR AND PARTICLE PHYSICS PROCEEDINGS, 2016, 273 : 2767 - 2769
  • [45] A software tool to assess uncertainty in transient-storage model parameters using Monte Carlo simulations
    Ward, Adam S.
    Kelleher, Christa A.
    Mason, Seth J. K.
    Wagener, Thorsten
    McIntyre, Neil
    McGlynn, Brian
    Runkel, Robert L.
    Payn, Robert A.
    FRESHWATER SCIENCE, 2017, 36 (01) : 195 - 217
  • [46] Monte Carlo event generators in atomic physics: A new tool to tackle the few-body dynamics
    Ciappina, M. F.
    Schulz, M.
    Kirchner, T.
    XXVII INTERNATIONAL CONFERENCE ON PHOTONIC, ELECTRONIC AND ATOMIC COLLISIONS (ICPEAC 2011), PTS 1-15, 2012, 388
  • [47] Estimating cost uncertainties in nuclear power plant construction through Monte Carlo sampled correlated random variables
    Maronati, G.
    Petrovic, B.
    PROGRESS IN NUCLEAR ENERGY, 2019, 111 : 211 - 222
  • [48] Using Hamiltonian Monte-Carlo to design longitudinal count studies accounting for parameter and model uncertainties
    Loingeville, Florence
    Thu Thuy Nguyen
    Riviere, Marie-Karelle
    Mentre, France
    JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS, 2017, 44 : S32 - S32
  • [49] SPECIFIC MONTE-CARLO CODE DEVELOPMENT FOR NUCLEAR WELL-LOGGING TOOL RESPONSES
    MICKAEL, M
    CHOI, HK
    GARDNER, RP
    VERGHESE, K
    NUCLEAR GEOPHYSICS, 1989, 3 (04): : 339 - 350
  • [50] Exploring Stochastic Sampling in Nuclear Data Uncertainties Assessment for Reactor Physics Applications and Validation Studies
    Vasiliev, Alexander
    Rochman, Dimitri
    Pecchia, Marco
    Ferroukhi, Hakim
    ENERGIES, 2016, 9 (12):