145 citations · 501 across the 21 of their papers we have counts for
5 papers · 1 filter
Demonstration of machine-learning-enhanced Bayesian quantum state estimation
Sanjaya Lohani, Joseph M. Lukens, Atiyya A. Davis +6
Machine learning (ML) has found broad applicability in quantum information science in topics as diverse as experimental design, state classification, and even studies on quantum fo…
Deep learning for enhanced free-space optical communications
Manon P. Bart, Nicholas J. Savino, Paras Regmi +8
Atmospheric effects, such as turbulence and background thermal noise, inhibit the propagation of coherent light used in ON-OFF keying free-space optical communication. Here we pres…
Dimension-adaptive machine-learning-based quantum state reconstruction
Sanjaya Lohani, Sangita Regmi, Joseph M. Lukens +3
We introduce an approach for performing quantum state reconstruction on systems of qubits using a machine-learning-based reconstruction system trained exclusively on qubits…
Classical Optical Analogue of Quantum Discord
Jacob M. Leamer, Wenlei Zhang, Nicholas J. Savino +4
Quantum discord has been shown to be a resource for quantum advantage in addition to quantum entanglement. While many experiments have demonstrated classical analogies of entanglem…
Data-Centric Machine Learning in Quantum Information Science
Sanjaya Lohani, Joseph M. Lukens, Ryan T. Glasser +2
We propose a series of data-centric heuristics for improving the performance of machine learning systems when applied to problems in quantum information science. In particular, we…