86 citations · 400 across the 24 of their papers we have counts for
8 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…
Complete characterization of quantum correlations by randomized measurements
Nikolai Wyderka, Andreas Ketterer, Satoya Imai +5
The fact that quantum mechanics predicts stronger correlations than classical physics is an essential cornerstone of quantum information processing. Indeed, these quantum correlati…
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…
Coexistent quantum channel characterization using spectrally resolved Bayesian quantum process tomography
Joseph C. Chapman, Joseph M. Lukens, Muneer Alshowkan +3
The coexistence of quantum and classical signals over the same optical fiber with minimal degradation of the transmitted quantum information is critical for operating large-scale q…
Broadband polarization-entangled source for C+L-band flex-grid quantum networks
Muneer Alshowkan, Joseph M. Lukens, Hsuan-Hao Lu +4
The rising demand for transmission capacity in optical networks has motivated steady interest in expansion beyond the standard C-band (1530-1565 nm) into the adjacent L-band (1565-…
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…
Generation of polarization entanglement via the quantum Zeno effect
Ian C. Nodurft, Harry C. Shaw, Ryan T. Glasser +2
The quantum Zeno effect reveals that the continuous observation of a quantum system can result in significant alterations to its evolution. Here, we present a method for establishi…
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…