Autoencoders for anomaly detection at LHCb

In the following work, a Machine Learning tool that differentiates typical Standard Model events from Beyond Standard Model was developed. The algorithm, called Autoencoder, was able to successfully separate a specific low mass model of dark shower topology (soft bomb events) from Standard Model, showing its potentiality to be implemented in the LHCb trigger so as to be able to find new high energy physics scenarios.