arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2203.16355physics.ins-detcs.LG
收藏

生成对抗网络用于快速模拟MPD探测器的时间投影室响应

Generative Adversarial Networks for the fast simulation of the Time Projection Chamber responses at the MPD detector

HSE University(高等经济大学);Yandex School of Data Analysis(Yandex数据分析学院);Joint Institute for Nuclear Research(联合核研究所);Petersburg Nuclear Physics Institute(彼得堡核物理研究所)

A. Maevskiy, F. Ratnikov, A. Zinchenko, V. Riabov, A. Sukhorosov, D. Evdokimov

摘要:

详细的探测器仿真模型对于现代高能物理实验的成功运行至关重要。在大多数情况下,这种详细的模型需要大量的计算资源来运行。通常可能无法提供这种服务,因此需要资源密集程度较低的办法。在这项工作中,我们证明了生成对抗网络(GAN)的适用性,这种快速仿真模型的基础上的情况下的时间投影室(TPC)在MPD检测器在NICA加速器复杂。与详细模拟相比,我们基于GAN的TPC原型模型的工作速度快了一个数量级以上,而生成数据的高级重建特性的质量没有任何明显下降。比较了直接和间接质量度量优化方法。

英文摘要:

The detailed detector simulation models are vital for the successful operation of modern high-energy physics experiments. In most cases, such detailed models require a significant amount of computing resources to run. Often this may not be afforded and less resource-intensive approaches are desired. In this work, we demonstrate the applicability of Generative Adversarial Networks (GAN) as the basis for such fast-simulation models for the case of the Time Projection Chamber (TPC) at the MPD detector at the NICA accelerator complex. Our prototype GAN-based model of TPC works more than an order of magnitude faster compared to the detailed simulation without any noticeable drop in the quality of the high-level reconstruction characteristics for the generated data. Approaches with direct and indirect quality metrics optimization are compared.

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。

↑