4 papers
Spectral Bias in Variational Quantum Machine Learning
Callum Duffy, Marcin Jastrzebski
In this work, we investigate the phenomenon of spectral bias in quantum machine learning, where, in classical settings, models tend to fit low-frequency components of a target func…
LArTPC hit-based topology classification with quantum machine learning and symmetry
Callum Duffy, Marcin Jastrzebski, Stefano Vergani +5
We present a new approach to separate track-like and shower-like topologies in liquid argon time projection chamber (LArTPC) experiments for neutrino physics using quantum machine…
To reset, or not to reset -- that is the question
György P. Gehér, Marcin Jastrzebski, Earl T. Campbell +1
Whether to reset qubits, or not, during quantum error correction experiments is a question of both foundational and practical importance for quantum computing. Text-book quantum er…
Unsupervised Beyond-Standard-Model Event Discovery at the LHC with a Novel Quantum Autoencoder
Callum Duffy, Mohammad Hassanshah, Marcin Jastrzebski +1
This study explores the potential of unsupervised anomaly detection for identifying physics beyond the Standard Model that may appear at proton collisions at the Large Hadron Colli…