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arXiv 2109.02551hep-ex
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AtlFast3:ATLAS中下一代快速模拟

AtlFast3: the next generation of fast simulation in ATLAS

ATLAS Collaboration

AI总结:

本文介绍ATLAS下一代快速模拟框架AtlFast3,它结合参数化方法与机器学习技术替代量能器簇射模拟,在保持高精度的同时显著改善喷注子结构建模,从而高效模拟大规模物理事件。

摘要:

大型强子对撞机上的ATLAS实验拥有广泛的物理研究计划,涵盖从精确测量到直接寻找新粒子和新相互作用,这需要规模越来越大且精度越来越高的模拟蒙特卡洛事件数据集。基于Geant4的探测器模拟虽然精确,但需要大量CPU资源。在过去十年中,ATLAS开发并使用了多种工具,用更快的模拟方法取代模拟中最消耗CPU的部分——量能器簇射模拟。本文介绍了AtlFast3,即ATLAS中下一代高精度快速模拟。AtlFast3将参数化方法与机器学习技术相结合,用于应对ATLAS实验当前和未来的计算挑战及模拟需求。凭借高精度的性能以及对喷注内部子结构建模的显著改进,AtlFast3能够为广泛的物理过程模拟大量事件。

英文摘要:

The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with \textsc{Geant4} is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation -- the calorimeter shower simulation -- with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.

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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