Machine learning (ML) has emerged as a formidable force for identifying hidden but
pertinent patterns within a given data set with the objective of subsequent generation of …

Quantum metrology is one of the most promising applications of quantum technologies. The
aim of this research field is the estimation of unknown parameters exploiting quantum …

Quantum computers solve ever more complex tasks using steadily growing system sizes.
Characterizing these quantum systems is vital, yet becoming increasingly challenging. The …

Bayesian inference is a powerful paradigm for quantum state tomography, treating
uncertainty in meaningful and informative ways. Yet the numerical challenges associated …

Full quantum tomography of high-dimensional quantum systems is experimentally infeasible
due to the exponential scaling of the number of required measurements on the number of …

Consider the task of verifying that a given quantum device, designed to produce a particular
entangled state, does indeed produce that state. One natural approach would be to …

Adaptive techniques have great potential for wide application in enhancing the precision of
quantum parameter estimation. We present an adaptive quantum state tomography protocol …

Quantum metrology promises unprecedented measurement precision but suffers in practice
from the limited availability of resources such as the number of probes, their coherence time …

In recent years, Bayesian methods have been proposed as a solution to a wide range of
issues in quantum state and process tomography. State-of-the-art Bayesian tomography …

Current algorithms for quantum state tomography (QST) are costly both on the experimental
front, requiring measurement of many copies of the state, and on the classical computational …