The nonequilibrium physics of many-body quantum systems harbors various unconventional
phenomena. In this Letter, we experimentally investigate one of the most puzzling of these …

Estimating expectation values is a key subroutine in quantum algorithms. Near-term
implementations face two major challenges: a limited number of samples required to learn a …

We propose a new viewpoint on the study of localization transitions in disordered quantum
systems, showing how critical properties can be seen also as a geometric transition in the …

We present a learning algorithm for discovering conservation laws given as sums of
geometrically local observables in quantum dynamics. This includes conserved quantities …

We present a technique for enhancing the estimation of quantum state properties by
incorporating approximate prior knowledge about the quantum state. This consists in …

Estimating global properties of many-body quantum systems such as entropy or bipartite
entanglement is a notoriously difficult task, typically requiring a number of measurements or …

Expectation values of observables are routinely estimated using so-called classical
shadows $\unicode {x2014} $ the outcomes of randomized bases measurements on a …

We present a robust shadow estimation protocol for wide classes of shallow measurement
circuits that mitigates noise as long as the effective measurement map is locally unitarily …

Efficiently learning expectation values of a quantum state using classical shadow
tomography has become a fundamental task in quantum information theory. In a classical …

Classical shadows are a versatile tool to probe many-body quantum systems, consisting of a
combination of randomised measurements and classical post-processing computations. In a …