Quantum Computing Solutions for High-Energy Physics
The key goal of project QuantHEP – Quantum Computing Solutions for High-Energy Physics is to develop quantum algorithms as a solution to the increasingly challenging, and soon intractable, problem of analysing and simulating events from large particle-physics experiments.
The acronym QuantHEP comes from the merging of the names of the sections of the arXiv used by the two communities involved in this project: Quantum Physics (quant-ph), and High-Energy Physics (hep-ex, hep-lat, hep-ph, hep-th). QuantHEP will develop quantum algorithms for event selection and event reconstruction, and will use them to perform proof-of-principle analysis of real data from CERN, exploiting a combination of classical and freely-available quantum processors, and benchmarking the potential advantage of this novel quantum-enhanced processing.
Furthermore, we will develop software libraries to simulate particle physics’ objects (elementary particles, composite particles, jets), and will use them as building blocks to develop the quantum simulation of scattering processes. A proof-of-principle scattering quantum simulation will be performed combining classical and freely-available quantum processors, and will be benchmarked against CERN classical simulations to characterize a quantum advantage threshold for HEP processes.
To tackle these challenges, project QuantHEP brings together an interdisciplinary and experienced team whose expertise spans quantum information theory, quantum algorithms, quantum computational complexity, quantum analog and digital computing, quantum simulation, theoretical high-energy physics, experimental (data analysis) high-energy physics, inclduing the corresponding state-of-the-art classical algorithms and neural network methods. Project QuantHEP has also a foundational character, putting forward an original comprehensive approach to investigate and measure the potential of quantum computation for experimental particle physics challenges.
- Coordinator: Yasser Omar (Instituto de Telecomunicações, PT)
- Simone Montangero (INFN, IT)
- Andris Ambainis (Latvijas Universitāte, LV)