AI 中文总结
该研究引入基于手征核子相互作用和PMM构建的混合模拟器用于核物质IMSRG计算，能快速准确预测核状态方程并量化不确定性，为相关计算提供基础，还通过拟合耦合常数及传播不确定性给出应用结果。
AI 中文摘要
我们引入了一种用于核物质介质相似重整化群（IMSRG）计算的混合模拟器，它基于手征核子-核子和三核子相互作用，以及由参数矩阵模型（PMM）构建的隐式缩减基方法模拟器，该模拟器能够通过共形预测严格估计其不确定性。所得的PMM-IMSRG模拟器能够在包括低能耦合、IMSRG流参数、密度和基大小等广泛输入参数范围内，对核状态方程（EOS）进行快速准确的预测，并给出可靠的置信区间。该框架为核EOS的原则性不确定性量化提供了基础，并使诸如使用我们的IMSRG计算进行贝叶斯参数估计等计算要求高的应用成为可能。作为首次应用，我们通过将两个依赖夸克质量的三核子相互作用的耦合常数拟合到经验饱和性质，给出了它们的结果，这些耦合常数最近在基于重整化群分析的手征展开中被确定为次下领先阶贡献。然后，我们在纯中子物质和对称核物质的极限下，将参数和模拟器的不确定性传播到EOS。
英文摘要
We introduce a hybrid emulator for in-medium similarity renormalization group (IMSRG) calculations of nuclear matter, based on chiral nucleon-nucleon and three-nucleon interactions and an implicit-reduced-basis method emulator constructed from parametric matrix models (PMMs) which is capable of rigorously estimating its uncertainties via conformal predictions. The resulting PMM-IMSRG emulator enables fast and accurate predictions with trustworthy confidence intervals of the nuclear equation of state (EOS) across a wide range of input parameters, including low-energy couplings, IMSRG flow parameters, densities, and basis sizes. This framework provides the foundation for principled uncertainty quantification of the nuclear EOS and enables computationally demanding applications such as Bayesian parameter estimation using our IMSRG calculations. As a first application, we present results for the coupling constants of the two quark-mass-dependent three-nucleon interactions, recently identified to contribute at next-to-next-to-leading order in the chiral expansion based on a renormalization-group analysis, by fitting them to empirical saturation properties. We then propagate both parametric and emulator uncertainties to the EOS in the limits of pure neutron matter and symmetric nuclear matter.
