Quantum random sampling is the leading proposal for demonstrating a computational
advantage of quantum computers over classical computers. Recently the first large-scale …

In recent years, significant advances have been made in the design and evaluation of
balanced (hyper) graph partitioning algorithms. We survey trends of the past decade in …

To ensure a long-term quantum computational advantage, the quantum hardware should be
upgraded to withstand the competition of continuously improved classical algorithms and …

Interactions in quantum systems can spread initially localized quantum information into the
exponentially many degrees of freedom of the entire system. Understanding this process …

This chapter sketches the foundations of the subject, discussing salient features of quantum
information, formulates a mathematical model of quantum computation and highlights some …

A recent quantum simulation of observables of the kicked Ising model on 127 qubits
implemented circuits that exceed the capabilities of exact classical simulation. We show that …

We propose a tensor network approach to compute amplitudes and probabilities for a large
number of correlated bitstrings in the final state of a quantum circuit. As an application, we …

We study the problem of generating independent samples from the output distribution of
Google's Sycamore quantum circuits with a target fidelity, which is believed to be beyond the …

Today's experimental noisy quantum processors can compete with and surpass all known
algorithms on state-of-the-art supercomputers for the computational benchmark task of …

We give a polynomial time classical algorithm for sampling from the output distribution of a
noisy random quantum circuit in the regime of anti-concentration to within inverse …