Quantum Computing at Maastricht University (QC@UM) is a collaboration between the Department of Advanced Computing Sciences, specialized in Data Sciences and Artificial Intelligence, and Gravitational Waves & Fundamental Physics, specialized in research in gravitational waves and elementary particles.
The aim of the project is to explore the potential of the novel field of Quantum Computers for High-Performance Computing and high-throughput smart data processing that will be required for the future state-of-the-art physics detectors.
Upon its completion in 2035, the Einstein Telescope (ET) will be the most sensitive gravitational wave detector in the world. The Einstein Telescope is set to become 10x more sensitive than its current-generation counterparts, LIGO and Virgo, which should result in an expected 100,000 to 1 million gravitational wave detections of black hole mergers alone, as compared to the current frequency of ~1 per week. In addition, novel exotic types of signals are expected to be found as well.
One of the current standard methods for detecting gravitational waves is a method called ‘matched filtering’, which uses computer-generated templates to compare whether incoming signals match the predicted shape of a gravitational wave. Matched filtering and parameter estimation of the sources will no longer be feasible due to ET's superior sensitivity, necessitating the development of new data analysis techniques.
The Large Hadron Collider at CERN in Geneva, Switzerland, is scheduled to be upgraded for superior performance from 2027 and onwards. Its luminosity will increase tenfold, proportionally increasing the number of particle collisions and allowing physicists to study them in greater detail.
The LHCb detector filters out traces of beauty particles by reconstructing the particles' tracks as they pass through the detector. Relevant tracks are filtered out of the data and saved in real-time, requiring us to rethink computing infrastructure as the number of particle collisions quickly becomes too much to handle.
Together with INFN-colleague Davide Zuliani, Davide Nicotra and Miriam Lucio Martinez (both UM/Nikhef) won the poster prize with their poster 'Quantum Computing applications at LHCb'.
In a recent article in the Journal of High Energy Physics (JHEP), the LHCb collaboration reports the application of Quantum Machine Learning for identifying properties of so-called jets: streams of particles that result from particle collisions.
Maastricht University, Nikhef, CERN and SURF will address some specific challenges for the LHCb experiment in order to determine which elements of the data analysis chains are best suited for a quantum computing approach.
Dr. Pietro Bonizzi
Assistant Professor
Department of Advanced Computing Sciences
Dr. Daniel Cámpora
Assistant Professor
Department of Advanced Computing Sciences
CERN, LHCb group
Nikhef
Dr. Menica Dibenedetto
Assistant Professor Physics
Faculty of Science and Engineering
Dr. Kurt Driessens
Associate Professor
Department of Advanced Computing Sciences
Dr. Jérémie Gobeil
Postdoc
Grativational Waves & Fundamental Physics
Prof. Dr. Stefan Hild
Full Professor
Gravitational Waves & Fundamental Physics
Einstein Telescope, ETpathfinder
Nikhef
Dr. Gideon Koekoek
Assistant Professor
Gravitational Waves & Fundamental Physics
Einstein Telescope, ETpathfinder
Nikhef
Dr. Miriam Lucio Martinez
Postdoc
Gravitational Waves & Fundamental Physics
Prof. Dr. Marcel Merk
Full Professor
Graviational Waves & Fundamental Physics
CERN, LHCb group
Nikhef
Dr. Rico Möckel
Associate professor
Department of Advanced Computing Sciences
Davide Nicotra
PhD student
Gravitational Waves & Fundamental Physics
Dr. Georgios Stamoulis
Assistant professor
Department of Advanced Computing Sciences
Dr. Jacco de Vries
Assistant Professor
Gravitational Waves & Fundamental Physics
CERN, LHCb group
Nikhef
Dr. Ronald Westra
Associate Professor
Department of Advanced Computing Sciences
CERN, LHCb group
Nikhef
Dr. Cor van der Struijf
Quantum Ambassador
For questions regarding QC@UM, please send an e-mail to Dr. Ronald Westra via westra[at]maastrichtuniversity[dot]nl.