Quantum Computing @ UM

Quantum & high-performance computing for physics

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.

Department of Advanced Computing Sciences
Gravitational Waves & Fundamental Physics

Faculty of Science and Engineering

Highlights

Maastricht University to enter quantum computing collaboration with IBM

CERN’s LHCb experiment embraces graphics cards to sift through massive amounts of data

Challenges

The Einstein Telescope

Artist Impression of ET by Marco Kraan

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.

LHCb detector at the High-Luminosity Large Hadron Collider (HL-LHC)

Image: LHCb/CERN

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.

News

Poster prize at CERN's International Conference on Quantum Technologies for High-Energy Physics
Friday, November 4, 2022

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'.

Read more
Quantum Machine Learning enters the fray in CERN’s LHCb experiment
Wednesday, August 3, 2022

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.

Read more
SURF joins Maastricht University and partners in efforts in the field of quantum computing
Tuesday, April 5, 2022

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.

Read more

Maastricht University to enter quantum computing collaboration with IBM
Monday, October 5, 2020
Maastricht University will become the first Dutch university to enter the IBM Q Network. The goal of the collaboration is to develop the high-performance computation power required for two next-generation advanced physics detectors.
Read more
CERN’s LHCb experiment embraces graphics cards to sift through massive amounts of data
Tuesday, June 16, 2020
Hundreds of graphics cards will power the LHCb detector’s initial data filter, which is tasked with selecting which particle collision events will be saved and studied at the Large Hadron Collider’s LHCb experiment. One of the driving forces behind the innovation is Dr. Daniel Cámpora.
Read more