标题： 贝叶斯不确定性量化核态密度数据及其对天体物理感兴趣的$(p,γ)$反应的影响 显示英文标题

标题： Bayesian uncertainty quantification on nuclear level density data and their impact on $(p,γ)$ reactions of astrophysical interest

摘要： $p$过程核合成负责从$^{35}$Se 到$^{196}$Hg 的 35 个中子缺乏核素的合成。 影响该过程建模的重要输入是反应网络中涉及核素的相关激发能级的核态密度。 OSLO 方法已被广泛用于测量几个 MeV 激发能级的态密度。 在本工作中，贝叶斯优化被用来估计在 OSLO 数据上优化的两个态密度模型参数的 95% 高密度区间。 然后将这些不确定性传播到$(p,\gamma)$反应的截面中，导致在天体物理相关的能量范围内形成复合核$^{105,106}$Pd 和$^{105,106}$Cd。 在同位素图的这一区域施加约束对于涉及附近$p$核素$^{102}$Pd 和$^{106}$Cd 的网络计算非常重要。 我们讨论了由于态密度数据的不确定性导致的截面范围的减小，与 TALYS 中提供的六种默认态密度模型的范围相比，我们强调了在天体物理相关的能量范围内需要态密度数据。 显示英文摘要

摘要： The $p$ process nucleosynthesis is responsible for the synthesis of 35 neutron-deficient nuclei from $^{35}$Se to $^{196}$Hg. An important input that can affect the modeling of this process is the nuclear level density at the relevant excitation energies of the nuclei involved in the reaction network. The OSLO method has been extensively used for the measurement of level densities in excitation energies of several MeV. In this work, Bayesian optimization has been used in order to estimate the 95% high density intervals for the parameters of two level density models optimized on the OSLO data. These uncertainties are then propagated on the cross sections of $(p,\gamma)$ reactions leading to the compound nuclei $^{105,106}$Pd and $^{105,106}$Cd inside the astrophysically relevant energy range. Imposing constraints in this region of the isotopic chart is important for network calculations involving the nearby $p$ nuclei $^{102}$Pd and $^{106}$Cd. We discuss the reduction of the range of cross sections due to the uncertainties arising from the level density data compared to the range of the six default level density models available in TALYS and we highlight the need for level density data inside the astrophysically relevant energy ranges.