4 papers
Learning minimal representations of stochastic processes with variational autoencoders
Gabriel Fernández-Fernández, Carlo Manzo, Maciej Lewenstein +2
Stochastic processes have found numerous applications in science, as they are broadly used to model a variety of natural phenomena. Due to their intrinsic randomness and uncertaint…
Superresolving collective quantum measurements
J. O. de Almeida, M. Lewenstein, M. Skotiniotis
We demonstrate a method for super-resolving signals encoded as finite mixtures of bosonic modes using collective measurements that exploit permutation symmetry. Specifically, we us…
Modern applications of machine learning in quantum sciences
Anna Dawid, Julian Arnold, Borja Requena +26
In this book, we provide a comprehensive introduction to the most recent advances in the application of machine learning methods in quantum sciences. We cover the use of deep learn…
Nonlinear optics using intense optical coherent state superpositions
Theocharis Lamprou, Javier Rivera-Dean, Philipp Stammer +2
Superpositions of coherent light states, are vital for quantum technologies. However, restrictions in existing state preparation and characterization schemes, in combination with d…