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© 2023 Springer Nature

Quantum chemistry with neural-network wave functions

— A recent review article in Nature Reviews Chemistry presents a comprehensive analysis of the integration of neural-network wave functions within quantum chemistry. Titled "Ab initio quantum chemistry with neural-network wave functions," this review offers insights into the potential and challenges of using machine learning techniques to solve the fundamental equations of quantum mechanics.

© 2023 APS

CQSL at the APS March Meeting in Las Vegas

— CQSL is presenting several of its works at the APS March Meeting in Las Vegas, between March 6th and Friday 10th

© 2022 EPFL

The expressive power of neural networks in quantum physics

— A collaboration between the CQSL lab at EPFL and the Hebrew University of Jerusalem in Israel has studied the expressive power of neural network representation of quantum states. By means of an efficient mapping of tensor contractions to deep neural networks, the work establishes for the first time the efficient representability of one-dimensional gapped ground states by means of neural quantum states. Other connections to tensor-network states are also discussed. 

© 2022 Simons Foundation/Javier Robledo Moreno

'Ghost' electrons used to reconstruct behaviour of quantum systems

— Physicists at EPFL and the Flatiron Institute’s Center for Computational Quantum Physics have created a new way to simulate quantum entanglement between interacting particles. Their approach involves adding extra, fictitious particles controlled by an artificial intelligence technique called a neural network.

Yimon Aye, Jean-Philippe Brantut, Raffaella Buonsanti, and Giuseppe Carleo. Credit: EPFL

Four SB researchers awarded ERC Consolidator Grants

— Four professors at EPFL’s School of Basic Sciences have been awarded Consolidator Grants from the European Research Council (ERC). As Switzerland currently has a non-association status to Horizon Europe, their projects will be financed by Switzerland’s State Secretariat for Education, Research and Innovation (SERI).

© 2022 American Physical Society

CQSL research featured at the APS "March Meeting" in Chicago

— The incoming March meeting of the American Physical Society will feature several presentations of the research performed at EPFL's Computational Quantum Science Lab (CQSL) and in collaboration with other institutions worldwide. CQSL work will be presented in about 8 oral presentations, including 2 invited talks. 

© 2022 EPFL

Machine-Learning Augmented Sampling for the Molecular Sciences

— CQSL is a proud sponsor of the forthcoming CECAM workshop entitled "Machine Learning Augmented Sampling for the Molecular Sciences".

Rob Lavinsky, iRocks.com – CC-BY-SA-3.0, CC BY-SA 3.0 <https://creativecommons.org/licenses/by-sa/3.0>, via Wikimedia Commons

Quantum Magnetism on the Pyrochlore Lattice

— A collaboration between CQSL and the University of Zurich has studied the elusive properties of quantum magnets on the Pyrochlore Lattice. The work, now published in Physical Review X, is based on extensive numerical simulations relying on novel ways to represent complex quantum wave functions, including deep convolutional neural networks.

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Running quantum software on a classical computer

— Two physicists, from EPFL and Columbia University, have introduced an approach for simulating the quantum approximate optimization algorithm using a traditional computer. Instead of running the algorithm on advanced quantum processors, the new approach uses a classical machine-learning algorithm that closely mimics the behavior of near-term quantum computers.

© 2021 American Physical Society

Neural-Network Quantum States for Nuclear Matter

— The first application of neural-network quantum states to nuclear matter has been published in Physical Review Letters, in a collaboration between CQSL and Argonne National Laboratory, in Chicago. 

© 2021 Giuseppe Carleo and Matija Medvidović

Simulating quantum computing with classical machine learning

— A recent CQSL work published in NPJ Quantum Information shows how machine learning techniques can be used to simulate the inner workings of near-term quantum computers.

© 2021 American Physical Society

CQSL at the APS March Meeting 2021

— The Computational Quantum Science Lab will be present at the virtual edition of the 2021 APS March Meeting, with about 8 contributed talks and 2 invited seminars. 

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