Winners of Pasqal’s Quantum Hackathon on Energy Transition Announced

Start-up Pasqal’s quantum hackathon ended on November 28, after two months of competition. Three winners were rewarded in Clermont-Ferrand, following a conference entitled “The meaning of tech, artificial and quantum intelligence”. A windfall of 50,000 euros was shared with them, and the GENCI computing center, which was a partner of the event, will offer them computing hours. Pasqal has also installed machines there.

A quantum hackathon on the theme of energy transition

Launched at the beginning of October by the French quantum champion, this hackathon had the theme of energy transition. A logical choice for Georges-Olivier Reymond, CEO of Pasqal, because one of the strengths of quantum computing is its low energy consumption. “Our machine consumes the equivalent of five hair dryers”, he wants to point out. It was also organized in honor of Blaise Pascal, one of the great French thinkers of the 17th century, inventor of a “calculating machine”, and from whom the start-up takes its name. According to the company, it attracted more than 700 participants, divided into around a hundred projects. A first selection took place at the end of October.


The first prize was awarded to the project “Neutral Atom Renewable Energy Forecasting: Improving Renewable Energy Forecasting with Neutral Atom Reservoir Computing”, led by Naomi Mona Chmielewski, Leo Monbroussou and Ulysse Remond. This is a project to optimize the electricity network to make the most of renewable energy sources. Modeling this type of use typically requires large computing and data capacities. Quantum computing makes it possible to do this much more cost-effectively.

Optimization of the electricity network, the challenge of tomorrow

The authors describe it thus: “An interesting machine learning paradigm for modeling physically complex systems is known as reservoir computing. A reservoir is a physical system that exhibits complex behavior. Its dynamics are used to reproduce the behavior of underlying time series. Linear regression is the only learning step, and it is performed after all the data has been successively fed into the reservoir, resulting in a very low learning cost. A free arrangement of neutral atoms makes reservoir computing particularly well suited to analog frameworks such as Pasqal machines.”

The second awarded project is “Neutrogen: Unlocking data driven applications: Optimally embedding neutral atoms for any data-driven application”, by Maria Demidik, Cenk Tuysuk, Manuel Rudlph, Giorgio Fecelli and Ravi Kumar. It concerns the optimization of the layout of a wind farm so that it is as efficient as possible. The third is called “Molecular Docking with Neutral Atoms: Enhancing drug discovery pipelines to find a sustainable alternative to Paclitaxel” and comes from Victor Onofre, Noe Bosc-Haddad and Mathieu Garrigues. It focuses on the identification of new molecules for medical treatments using a molecular docking technique.


The energy sector is one of Pasqal’s priority areas of application today, along with finance and health. In particular, work has already been undertaken with EDF to optimize the charging management of electric vehicles. Smart grid themes are particularly suited to this. On the performance side, the next step for Pasqal is the launch of its 1000-qubit machine, scheduled for January 2024. This will be followed by the demonstration of a quantum advantage on an industrial case.

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