Introduction

Importance of Machine Learning (ML) in high-energy physics field increases rapidly in order to go beyond ordinary cut-based data-analyses performance. The big international experiments are producing a huge amount of complex data, and the data volume will continue to grow. In this era of "Big-Data", the recent development of Deep Learning (DL) is becoming a driving force to incorporate ML in data-analyses. Studies of ML and DL as a tool to enhance the achievement of physics have being pursued in our center.

Development for practical use of Quantum Computing (QC) is progressing rapidly. Quantum annealing machine with O(1000) qubits is available in a market, and O(10) qubit machines for the gate-type QC are also becoming available for research. Our center has started studies of the application for such QC machines in high-energy physics experiments.

Members

Yutaro Iiyama, Tomoe Kishimoto, Masahiro Morinaga, Masahiko Saito, Ryu Sawada, Junichi Tanaka, Koji Terashi (in A-Z order)