The design of new devices and experiments has historically relied on the intuition of human
experts. Now, design inspirations from computers are increasingly augmenting the capability …

Optical communication is an integral part of the modern economy, having all but replaced
electronic communication systems. Future growth in bandwidth appears to be on the horizon …

We apply deep-neural-network-based techniques to quantum state classification and
reconstruction. Our methods demonstrate high classification accuracies and reconstruction …

We revisit the application of neural networks to quantum state tomography. We confirm that
the positivity constraint can be successfully implemented with trained networks that convert …

Classical shadows (CS) have emerged as a powerful way to estimate many properties of
quantum states based on random measurements and classical post-processing. In their …

We introduce the framework of Bayesian relative belief that directly evaluates whether or not
the experimental data at hand support a given hypothesis regarding a quantum system by …

We present a compressive quantum process tomography scheme that fully characterizes
any rank-deficient completely positive process with no spurious a priori information. It uses …

Identifying a reasonably small Hilbert space that completely describes an unknown quantum
state is crucial for efficient quantum information processing. We introduce a general …

Recent quantum technologies utilize complex multidimensional processes that govern the
dynamics of quantum systems. We develop an adaptive diagonal-element-probing …

We train convolutional neural networks to predict whether or not a set of measurements is
informationally complete to uniquely reconstruct any given quantum state with no prior …