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Testing a Neural Network for Anomaly Detection in the CMS Global Trigger Test Crate during Run 3
Journal of Instrumentation ( IF 1.3 ) Pub Date : 2024-03-12 , DOI: 10.1088/1748-0221/19/03/c03029
Noah Zipper ,

We present the deployment and testing of an autoencoder trained for unbiased detection of new physics signatures in the CMS Level-1 Global Trigger (GT) test crate during LHC Run 3. The GT test crate is a copy of the main GT system, receiving the same input data, but whose output is not used to trigger the readout of CMS, providing a platform for thorough testing of new trigger algorithms on live data, but without interrupting data taking. We describe the integration of the Neural Network into the GT test crate, and the monitoring, testing, and validation of the algorithm during proton collisions.

中文翻译:

在运行 3 期间测试 CMS 全局触发器测试箱中的神经网络异常检测

我们展示了在 LHC 运行 3 期间,在 CMS 1 级全局触发 (GT) 测试箱中部署和测试的自动编码器,该自动编码器经过训练,可以无偏差地检测新的物理特征。GT 测试箱是主 GT 系统的副本,接收相同的输入数据,但其输出不用于触发 CMS 的读出,为对实时数据的新触发算法进行彻底测试提供了一个平台,但不会中断数据获取。我们描述了神经网络与 GT 测试箱的集成,以及质子碰撞期间算法的监控、测试和验证。
更新日期:2024-03-12
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