Advances in quantum technology require scalable techniques to efficiently extract
information from a quantum system. Traditional tomography is limited to a handful of qubits …

Optimization with constraints is a typical problem in quantum physics and quantum
information science that becomes especially challenging for high-dimensional systems and …

We introduce a general and systematic theoretical framework for operational dynamic
modeling (ODM) by combining a kinematic description of a model with the evolution of the …

We introduce a fast and accurate heuristic for adaptive tomography that addresses many of
the limitations of prior methods. Previous approaches were either too computationally …

We report an experimental realization of an adaptive quantum state tomography protocol.
Our method takes advantage of a Bayesian approach to statistical inference and is naturally …

Wavefront sensing is a set of techniques providing efficient means to ascertain the shape of
an optical wavefront or its deviation from an ideal reference. Owing to its wide dynamical …

We present an error analysis of various tomographic protocols based on the linear inversion
for the reconstruction of an unknown two-qubit state. We solve the problem of finding a …

Classical machine learning theory and theory of quantum computations are among of the
most rapidly developing scientific areas in our days. In recent years, researchers …

We provide a review of the experimental and theoretical research in the field of quantum
tomography with an emphasis on recently developed adaptive protocols. Several statistical …

The 5 d 5 iridate CaIrO 3 is isostructural with the post-perovskite phase of MgSiO 3, recently
shown to occur under extreme pressure in the lower Earth's mantle. It therefore serves as an …