Bulletin of the American Physical Society
2023 APS March Meeting
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session M62: Machine Learning for Quantum Matter III
8:00 AM–10:36 AM,
Wednesday, March 8, 2023
Room: Room 417
Sponsoring
Unit:
DCOMP
Chair: George Booth, King's College London
Abstract: M62.00011 : Efficient and scalable modeling of strongly correlated electronic systems with NQS in continuous space*
10:24 AM–10:36 AM
Presenter:
Gabriel M Pescia
(Ecole Polytechnique Federale de Lausanne)
Author:
Gabriel M Pescia
(Ecole Polytechnique Federale de Lausanne)
In this presentation, we will introduce a novel fermionic NQS architecture that -- together with an advanced and scalable optimization scheme -- dramatically reduces the number of variational parameters needed to achieve state-of-the-art results on prototypical fermionic bulk systems. We apply our model to the homogeneous electron gas at system sizes that have not been accessible to NQS previously.
1G. Pescia, J. Han, A. Lovato, J. Lu and G. Carleo, Neural-network quantum states for periodic systems in continuous space, Phys. Rev. Research 4, 023138 (2022), doi:10.1103/PhysRevResearch.4.023138.
*The research is supported by the Swiss National Science Foundation under Grant No. 200021\_200336
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