The Computational Quantum Science Lab researches, develops, and promotes a broad range of advanced computational techniques to study quantum phenomena. Under the direction of Giuseppe Carleo, the methods developed at CQSL include innovative machine learning techniques to study Condensed Matter, Ultracold Atoms, Electronic Structure, as well as to characterize Quantum Devices. In addition to numerical approaches based on classical computers, novel algorithms to simulate quantum processes and suitable for near-term quantum devices are also being developed.
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.
'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.
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).