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arXiv 2603.05545nucl-thhep-phnucl-ex
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VarP-GP：基于可变统计精度的低成本贝叶斯模拟用于夸克-胶子等离子体建模

Cost-efficient Bayesian emulation of quark-gluon plasma modeling with variable statistical precision

Lawrence Berkeley National Laboratory（劳伦斯伯克利国家实验室）；University of California, Berkeley（加州大学伯克利分校）；Duke University（杜克大学）；JMP Statistical Discovery LLC（JMP统计发现有限责任公司）

R. Ehlers, Y. Ji, P. M. Jacobs, S. Mak

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AI总结：

VarP-GP通过低成本贝叶斯模拟提升夸克-胶子等离子体建模的精度与效率

摘要：

我们提出了VarP-GP，一种新的低成本贝叶斯模拟器，用于处理具有可变统计精度的昂贵计算模型。我们关注通过与数值模型的比较来解释高能核碰撞中产生的夸克-胶子等离子体（QGP）的测量结果，使用贝叶斯推断。此类推断计算计算成本高，需要替代模型模拟，通常通过基于机器学习（ML）的高斯过程（GPs）实现。模拟器训练数据由蒙特卡洛模拟生成，其数值精度取决于所用的计算资源；精度提高意味着计算成本更高。本研究利用JETSCAPE模拟了RHIC和LHC核碰撞中包涵的强子和喷注测量。VarP-GP模拟器结合了多个不同精度的模拟运行信息，在模型参数空间中利用QCD驱动过程的平滑性。与传统模拟器方法的比较显示，在固定计算成本下，模拟器不确定性显著降低，表明对参数设计空间整体轮廓的了解比在有限数量设计点上的详细信息更重要。作为VarP-GP的初步应用，报告了计算成本高昂的喷注淬灭数据模型参数敏感性研究。VarP-GP模拟器使新的多模型和多观测量校准成为可能，这在现有计算资源下是无法实现的。

英文摘要：

We present VarP-GP, a new cost-efficient Bayesian emulator for expensive computational models with variable statistical precision. We focus on the interpretation of measurements of the quark-gluon plasma (QGP) generated in high-energy nuclear collisions, through comparison to numerical models using Bayesian Inference. Such inference calculations are computationally expensive and require surrogate model emulation, which is commonly implemented using Machine Learning (ML) based Gaussian processes (GPs). Emulator training data are generated by Monte Carlo simulations whose numerical precision depends on the computational resources utilized; improved precision entails greater computational cost. This study utilizes JETSCAPE simulations of inclusive hadron and jet measurements in nuclear collisions at RHIC and the LHC. The VarP-GP emulator combines information from multiple simulation runs with varying precision across the model parameter space, taking advantage of the smoothness in that space of QCD-driven processes. Comparison to a traditional emulator approach shows a marked reduction in emulator uncertainty at fixed computational cost, indicating that knowledge of the overall contours of the parameter design space is more important for precise emulation than detailed information at a more limited number of design points. As an initial application of VarP-GP, a computationally-expensive model parameter sensitivity study of jet quenching data is reported. The VarP-GP emulator enables new multi-model and many-observable calibrations of QGP data and modeling, which would otherwise not be possible with achievable computing resources.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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