Theory-driven Quantum Machine Learning for HEP

Seminario di Fenomenologia INFN/DIFI

  • Dipartimento di Fisica - A603 | Zoom
  • Seminario

Relatori

Dr. Jack Araz
IPPP - Durham University

Dettagli

Machine Learning is, in most cases, powerful but a black-box application. In this talk, we will tackle this very problem from a quantum mechanics point of view, arguing that an optimisation problem, such as classification or anomaly detection, can be studied by “rephrasing" the problem as a quantum many-body system or a mixed state. Such an approach allows us to employ the entire arsenal of quantum theory for data analysis techniques while enabling exact representation for a quantum device. Hence this talk will present a small step towards fully theory-driven and interpretable quantum machine learning applications.

Per connettersi a zoom:
Topic: Theory and Pheno seminars
https://infn-it.zoom.us/j/8573185271
Meeting ID: 857 318 5271