Julian Schuhmacher, Laura Boggia, et al.
Machine Learning: Science and Tech.
We investigate supervised and unsupervised quantum machine learning algorithms in the context of typical data analyses at the LHC. To accommodate the constraints on the problem size, dictated by limitations on the quantum hardware, we concatenate the quantum algorithms to the encoder of a classical convolutional autoencoder, used for dimensionality reduction. We present results for a quantum classifier and a quantum anomaly detection algorithm, comparing performance to corresponding classical algorithms.