7 papers
Learning Reduced Representations for Quantum Classifiers
Patrick Odagiu, Vasilis Belis, Lennart Schulze +6
Data sets that are specified by a large number of features are currently outside the area of applicability for quantum machine learning algorithms. An immediate solution to this im…
Performance of the front-end electronics of the CMS electromagnetic calorimeter barrel for the High-Luminosity LHC
The CMS Electromagnetic Calorimeter Group
The performance of the CMS electromagnetic calorimeter upgraded readout electronics, developed for the High-Luminosity phase of the LHC, is discussed. Data collected in two beam te…
PETNet -- Coincident Particle Event Detection using Spiking Neural Networks
Jan Debus, Charlotte Debus, Günther Dissertori +1
Spiking neural networks (SNN) hold the promise of being a more biologically plausible, low-energy alternative to conventional artificial neural networks. Their time-variant nature…
Radiation Testing of New Readout Electronics for the CMS ECAL Barrel
Nico Härringer, Günther Dissertori, Tomasz Gadek +7
In preparation of the operation of the CMS electromagnetic calorimeter (ECAL) barrel at the High Luminosity Large Hadron Collider (HL-LHC) the entire on-detector electronics will b…
Guided Quantum Compression for High Dimensional Data Classification
Vasilis Belis, Patrick Odagiu, Michele Grossi +3
Quantum machine learning provides a fundamentally different approach to analyzing data. However, many interesting datasets are too complex for currently available quantum computers…
Quantum anomaly detection in the latent space of proton collision events at the LHC
Vasilis Belis, Kinga Anna Woźniak, Ema Puljak +7
The ongoing quest to discover new phenomena at the LHC necessitates the continuous development of algorithms and technologies. Established approaches like machine learning, along w…