Berlin 2024 – scientific programme

Parts | Days | Selection | Search | Updates | Downloads | Help

TT: Fachverband Tiefe Temperaturen

TT 2: Focus Session: Artificial Intelligence in Condensed Matter Physics I (joint session TT/DY)

TT 2.4: Invited Talk

Monday, March 18, 2024, 11:15–11:45, H 0104

Neural Quantum States For The Many-Electron Problem — •Giuseppe Carleo — EPFL, Lausanne, Switzerland

This presentation explores recent strides in using neural quantum states [1] to represent many-body fermionic quantum wave functions for the many-electron problem [2]. I will delve into a message-passing-neural-network-based Ansatz designed for simulating strongly interacting electrons in continuous space [3]. This approach achieves unprecedented accuracy in the electron gas problem, pushing the boundaries of system sizes previously inaccessible to neural network states. I will also discuss a Pfaffian-based neural-network quantum state for ultra-cold Fermi gases, outperforming traditional methods and enabling exploration of the BCS-BEC crossover region [4]. Finally, I will provide insight into ongoing work on the entanglement properties of Helium 4 and Helium 3, and discuss open problems in the field [5].

[1] Carleo and Troyer, Science 355, 602 (2017)

[2] Hermann et al., Nature Reviews Chemistry 7, 692 (2023)

[3] Pescia et al., arxiv:2305.07240 (2023)

[4] Kim et al., arxiv:2305.08831 (2023)

[5] Linteau et al., in preparation (2024).

Keywords: Neural Wave Function; Variational Monte Carlo; Electron Gas; Helium 3 and 4; Ultra-cold Fermi gas