Thermodynamic systems typically conserve quantities (known as charges) such as energy
and particle number. The charges are often assumed implicitly to commute with each other …

Quantum machine learning, which involves running machine learning algorithms on
quantum devices, has garnered significant attention in both academic and business circles …

Parametrized quantum circuits serve as ansatze for solving variational problems and
provide a flexible paradigm for the programming of near-term quantum computers. Ideally …

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

Parameterized quantum circuits (PQCs) play an essential role in the performance of many
variational quantum algorithms. One challenge in implementing such algorithms is choosing …

Many experimental proposals for noisy intermediate scale quantum devices involve training
a parameterized quantum circuit with a classical optimization loop. Such hybrid quantum …

We present a theory of the entanglement transition tuned by measurement strength in qudit
chains evolved by random unitary circuits and subject to either weak or random projective …

The Haar measure plays a vital role in quantum information, but its study often requires a
deep understanding of representation theory, posing a challenge for beginners. This tutorial …

A bstract Krylov complexity measures the spread of the wavefunction in the Krylov basis,
which is constructed using the Hamiltonian and an initial state. We investigate the evolution …

We analyze the dynamics of entanglement entropy in a generic quantum many-body open
system from the perspective of quantum information and error corrections. We introduce a …