News

Running quantum software on a classical computer

Published:03.08.21 — 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.

Neural-Network Quantum States for Nuclear Matter

Published:07.07.21 — 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. 

Simulating quantum computing with classical machine learning

Published:05.07.21 — 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.

Quantum computing: cold chips can control qubits

Published:17.05.21 — A cryogenic controller chip opens the door to solving the ‘wiring bottleneck’ and subsequently to realize a fully integrated, scalable quantum computer. A research from QuTech in the Netherlands, from Intel Corp and from EPFL professor Edoardo Charbon.

Light meets superconducting circuits

Published:12.05.21 — EPFL researchers have developed a light-based approach to read out superconducting circuits, overcoming the scaling-up limitations of quantum computing systems.

New tech builds ultralow-loss integrated photonic circuits

Published:22.04.21 — EPFL scientists have developed ultralow-loss silicon nitride integrated circuits that are central for many photonic devices, such as chip-scale frequency combs, narrow-linewidth lasers, coherent LiDAR, and neuromorphic computing.