Search Results for author: Günther Dissertori

Found 3 papers, 2 papers with code

Guided Quantum Compression for Higgs Identification

1 code implementation14 Feb 2024 Vasilis Belis, Patrick Odagiu, Michele Grossi, Florentin Reiter, Günther Dissertori, Sofia Vallecorsa

To ameliorate this issue, we design an architecture that unifies the preprocessing and quantum classification algorithms into a single trainable model: the guided quantum compression model.

Classification Dimensionality Reduction +1

Quantum anomaly detection in the latent space of proton collision events at the LHC

1 code implementation25 Jan 2023 Kinga Anna Woźniak, Vasilis Belis, Ema Puljak, Panagiotis Barkoutsos, Günther Dissertori, Michele Grossi, Maurizio Pierini, Florentin Reiter, Ivano Tavernelli, Sofia Vallecorsa

The designed quantum anomaly detection models, namely an unsupervised kernel machine and two clustering algorithms, are trained to find new-physics events in the latent representation of LHC data produced by the autoencoder.

Anomaly Detection Quantum Machine Learning

Higgs analysis with quantum classifiers

no code implementations15 Apr 2021 Vasileios Belis, Samuel González-Castillo, Christina Reissel, Sofia Vallecorsa, Elías F. Combarro, Günther Dissertori, Florentin Reiter

We have developed two quantum classifier models for the $t\bar{t}H(b\bar{b})$ classification problem, both of which fall into the category of hybrid quantum-classical algorithms for Noisy Intermediate Scale Quantum devices (NISQ).

BIG-bench Machine Learning Quantum Machine Learning

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