Giuseppe Carleo
EPFL SB IPHYS CQSL
PH H2 477 (Bâtiment PH)
Station 3
1015 Lausanne
+41 21 693 93 96
Office: PH H2 477
EPFL › SB › IPHYS › CQSL
Site web: https://www.epfl.ch/labs/cqsl/
EPFL SB IPHYS CQSL
PH H2 477 (Bâtiment PH)
Station 3
1015 Lausanne
+41 21 693 93 96
Office: PH H2 477
EPFL › SB › SB-SPH › SPH-ENS
Site web: https://sph.epfl.ch/
EPFL SB IPHYS CQSL
PH H2 477 (Bâtiment PH)
Station 3
1015 Lausanne
+41 21 693 93 96
Office: PH H2 477
EPFL › STI › STI-SSIQ › STI-SSIQ-GE
EPFL SB IPHYS CQSL
PH H2 477 (Bâtiment PH)
Station 3
1015 Lausanne
+41 21 693 93 96
Office: PH H2 477
EPFL › VPA › VPA-AVP-DLE › AVP-DLE-EDOC › EDPY-ENS
EPFL SB IPHYS CQSL
PH H2 477 (Bâtiment PH)
Station 3
1015 Lausanne
+41 21 693 93 96
Office: PH H2 477
EPFL › VPA › VPA-AVP-DLE › AVP-DLE-EDOC › EDPY-GE
Site web: https://go.epfl.ch/phd-edpy
Formation
PhD
| in Theory and Numerical Simulation of the Condensed Matter2007 – 2011 SISSA, International School for Advanced Studies, Trieste, Italy
Master in Physics
|2005 – 2007 Sapienza University, Rome, Italy
Bachelor in Physics
|2002 – 2005 Sapienza University, Rome, Italy
Publications représentatives
Solving the quantum many-body problem with artificial neural networks
Giuseppe Carleo, and Matthias Troyer
Published in Science, 355:602, 2017 in
Neural-network quantum-state tomography
Giacomo Torlai, Guglielmo Mazzola, Juan Carrasquilla, Matthias Troyer, Roger Melko, and Giuseppe Carleo
Published in Nature Physics, 14:447, 2018 in
Machine learning and the physical sciences
Giuseppe Carleo et al.
Published in Reviews of Modern Physics, 91:045002, 2020 in
Localization and Glassy Dynamics Of Many-Body Quantum Systems
Giuseppe Carleo, Federico Becca, Marco Schiró, and Michele Fabrizio
Published in Scientific Reports 2, 243 (2012) in
Neural-Network Approach to Dissipative Quantum Many-Body Dynamics
Michael J. Hartmann, and Giuseppe Carleo
Published in Phys. Rev. Lett. 122, 250502, 2019 in
Quantum Natural Gradient
James Stokes, Josh Izaac, Nathan Killoran, and Giuseppe Carleo
Published in Quantum 4, 269 (2020) in
Doctorant·es actuel·les
David Linteau, Samuele Piccinelli, Linda Mauron, Gian Florin Gentinetta, Gabriel Maria Pescia, Clemens Giuliani, Imelda Romero, Alessandro Sinibaldi, Shao Hen Chiew
A dirigé les thèses EPFL de
Cours
Summer school: Simulating Many-Body 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.
Quantum physics IV
Introduction to the path integral formulation of quantum mechanics. Derivation of the perturbation expansion of Green's functions in terms of Feynman diagrams. Several applications will be presented, including non-perturbative effects, such as tunneling and instantons.
Lecture series on scientific machine learning
This lecture presents ongoing work on how scientific questions can be tackled using machine learning. Machine learning enables extracting knowledge from data computationally and in an automatized way. We will learn on examples how this is influencing the very scientific method.
Introduction to quantum science and technology
Advanced computational physics
The course covers dense/sparse linear algebra, variational methods in quantum mechanics, and Monte Carlo techniques. Students implement algorithms for complex physical problems. Combines theory with coding exercises. Prepares for research in computational physics and related fields.