Preparation for the Deep Underground Neutrino Experiment and Measurement of Pion-Argon Cross-sections

该项目将包括在美国长基线中微子设施LBNF进行的深地下中微子实验DUNE的准备研究。中微子由美国费米实验室的1.2兆瓦质子束产生，并传播800公里到达桑福德地下研究设施。光束上装有两个近、远探测器。远距探测器以40k吨液态氩气为基础，作为时间投影室TPC。为了减少远探测器在20年的实验寿命中产生的数据量，数据采集系统包括一个数据选择系统，或“触发器”。该项目将包括触发器算法的开发，以及用蒙特卡罗模拟对其性能的估计。触发算法也将在ProtoDUNE探测器上部署和表征，ProtoDUNE探测器是未来DUNE远探测器的800吨原型，目前在CERN运行。最后，利用ProtoDUNE在2024年第2次运行期间收集的数据，将进行介子-氩气截面的测量。这将侧重于电荷交换过程，并将研究使用机器学习算法来识别液态氩气TPC中的中性介子。

The project will comprise preparatory studies for the Deep Underground Neutrino Experiment DUNE, at the Long-Baseline Neutrino Facility LBNF, USA. Neutrinos are generated from a 1.2 MW proton beam at Fermilab, USA, and travel 800km to the Sanford Underground Research Facility. The beam is instrumented with two near and far detectors. The Far Detector is based around an active volume of 40k-tonne of liquid Argon, instrumented as a time projection chamber TPC. In order to reduce the data volume produced by the Far Detector over the 20 year lifespan of the experiment, the data acquisition system includes a data-selection system, or "trigger". This project will include development of trigger algorithms, and estimation of their performance with Monte-Carlo simulation. Trigger algorithms will also be deployed and characterised at the ProtoDUNE detector, an 800 tonne prototype of the future DUNE Far Detector, currently in operation at CERN. Finally, using data collected during Run 2 of ProtoDUNE in 2024, a measurement of pion-Argon cross-sections will be performed. This will focus on the charge-exchange process and will investigate use of machine learning algorithms to identify neutral pions in the liquid Argon TPC.