Giuseppe Carleo

EPFL SB IPHYS CQSL
PH H2 477 (Bâtiment PH)
Station 3
CH-1015 Lausanne

EPFL SB IPHYS CQSL
PH H2 477 (Bâtiment PH)
Station 3
CH-1015 Lausanne

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Administrative data

Fields of expertise

Machine Learning for Quantum Physics; Numerical methods for strongly-correlated quantum systems; Quantum Computing; Characterization of Quantum Hardware; Dynamics of closed and open quantum systems; Frustrated magnets

Education

PhD

in Theory and Numerical Simulation of the Condensed Matter

SISSA, International School for Advanced Studies, Trieste, Italy

2007 - 2011

Publications

Selected publications

Teaching & PhD

Teaching

Physics

PhD Programs

Doctoral Program in Physics

Doctoral program in computer and communication sciences

Courses

Quantum physics I

Introduction to the concepts, methods and consequences of quantum physics.

Computational quantum physics

The numerical simulation of quantum systems plays a central role in modern physics. This course gives an introduction to key simulation approaches, through lectures and practical programming exercises. Simulation methods based both on classical and quantum computers will be presented.

Lecture series on scientific machine learning

Machine learning is a data analysis and computational tool that in the last two decades brought groundbreaking progress into many modern technologies. What is more, machine learning is becoming an indispensable tool enabling progress in many scientific disciplines where knowledge is deduced from data. This course will present some recent works in this direction. In the first part of the