659 citations · 2.9k across the 42 of their papers we have counts for
8 papers · 1 filter
Coarse grained intermolecular interactions on quantum processors
Lewis W. Anderson, Martin Kiffner, Panagiotis Kl. Barkoutsos +3
Variational quantum algorithms (VQAs) are increasingly being applied in simulations of strongly-bound (covalently bonded) systems using full molecular orbital basis representations…
Improving readout in quantum simulations with repetition codes
Jakob M. Günther, Francesco Tacchino, James R. Wootton +2
Near term quantum computers suffer from the presence of different noise sources. In order to mitigate for this effect and acquire results with significantly better accuracy, there…
Simulating a ring-like Hubbard system with a quantum computer
Philippe Suchsland, Panagiotis Kl. Barkoutsos, Ivano Tavernelli +2
We develop a workflow to use current quantum computing hardware for solving quantum many-body problems, using the example of the fermionic Hubbard model. Concretely, we study a fou…
Application of Quantum Machine Learning using the Quantum Kernel Algorithm on High Energy Physics Analysis at the LHC
Sau Lan Wu, Shaojun Sun, Wen Guan +20
Quantum machine learning could possibly become a valuable alternative to classical machine learning for applications in High Energy Physics by offering computational speed-ups. In…
Learning to Measure: Adaptive Informationally Complete Generalized Measurements for Quantum Algorithms
Guillermo García-Pérez, Matteo A. C. Rossi, Boris Sokolov +5
Many prominent quantum computing algorithms with applications in fields such as chemistry and materials science require a large number of measurements, which represents an importan…
Variational learning for quantum artificial neural networks
Francesco Tacchino, Stefano Mangini, Panagiotis Kl. Barkoutsos +4
In the last few years, quantum computing and machine learning fostered rapid developments in their respective areas of application, introducing new perspectives on how information…