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quant-ph2026
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…
quant-ph2024
Quantum Circuit Training with Growth-Based Architectures
Callum Duffy, Smit Chaudhary, Gergana V. Velikova
This study introduces growth-based training strategies that incrementally increase parameterized quantum circuit (PQC) depth during training, mitigating overfitting and managing mo…
quant-ph2024
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…