Speaker
Kinga Anna Wozniak
(University of Vienna (AT))
Description
We investigate supervised and unsupervised quantum machine learning algorithms in the context of typical data analyses at the LHC. To deal with constraints on the problem size, dictated by limitations on the quantum hardware, we concatenate the quantum algorithms to the encoder of a classic autoencoder, used for dimensional reduction. We show results for a quantum classifier and a quantum anomaly detection algorithm, comparing performance to corresponding classic algorithms.
| Speaker time zone | Compatible with Europe |
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Primary authors
Kinga Anna Wozniak
(University of Vienna (AT))
Maurizio Pierini
(CERN)
Panagiotis Barkoutsos
Sofia Vallecorsa
(CERN)
Vasileios Belis
(ETH Zurich (CH))
