3 papers
hep-ph2020
Quantum Machine Learning for Particle Physics using a Variational Quantum Classifier
Andrew Blance, Michael Spannowsky
Quantum machine learning aims to release the prowess of quantum computing to improve machine learning methods. By combining quantum computing methods with classical neural network…
hep-ph2019
Novel -decay signatures of light scalars at high energy facilities
Andrew Blance, Mikael Chala, Maria Ramos +1
We study the phenomenology of light scalars of masses and coupling to heavy flavour-violating vector bosons of mass . For few GeV, this scenario…
hep-ph2019
Adversarially-trained autoencoders for robust unsupervised new physics searches
Andrew Blance, Michael Spannowsky, Philip Waite
Machine learning techniques in particle physics are most powerful when they are trained directly on data, to avoid sensitivity to theoretical uncertainties or an underlying bias on…