5 papers
Classical shadows with arbitrary group representations
Maxwell West, Frederic Sauvage, Aniruddha Sen +6
Classical shadows (CS) has recently emerged as an important framework to efficiently predict properties of an unknown quantum state. A common strategy in CS protocols is to paramet…
Hunting for "Oddballs" with Machine Learning: Detecting Anomalous Exoplanets Using a Deep-Learned Low-Dimensional Representation of Transit Spectra with Autoencoders
Alexander Roman, Emilie Panek, Roy T. Forestano +3
This study explores the application of autoencoder-based machine learning techniques for anomaly detection to identify exoplanet atmospheres with unconventional chemical signatures…
Supervised Machine Learning Methods with Uncertainty Quantification for Exoplanet Atmospheric Retrievals from Transmission Spectroscopy
Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva +1
Standard Bayesian retrievals for exoplanet atmospheric parameters from transmission spectroscopy, while well understood and widely used, are generally computationally expensive. In…
Recursive Cartan decompositions for unitary synthesis
David Wierichs, Maxwell West, Roy T. Forestano +2
Recursive Cartan decompositions (CDs) provide a way to exactly factorize quantum circuits into smaller components, making them a central tool for unitary synthesis. Here we present…
Lie-Equivariant Quantum Graph Neural Networks
Jogi Suda Neto, Roy T. Forestano, Sergei Gleyzer +3
Discovering new phenomena at the Large Hadron Collider (LHC) involves the identification of rare signals over conventional backgrounds. Thus binary classification tasks are ubiquit…