Programmable quantum simulators and quantum computers are opening unprecedented
opportunities for exploring and exploiting the properties of highly entangled complex …

Classical machine learning (ML) provides a potentially powerful approach to solving
challenging quantum many-body problems in physics and chemistry. However, the …

Learning a many-body Hamiltonian from its dynamics is a fundamental problem in physics.
In this Letter, we propose the first algorithm to achieve the Heisenberg limit for learning an …

We study the problem of observing quantum collective phenomena emerging from large
numbers of measurements. These phenomena are difficult to observe in conventional …

We report universal statistical properties displayed by ensembles of pure states that
naturally emerge in quantum many-body systems. Specifically, two classes of state …

We prove that random quantum circuits on any geometry, including a 1D line, can form
approximate unitary designs over $ n $ qubits in $\log n $ depth. In a similar manner, we …

Monitored quantum dynamics—unitary evolution interspersed with measurements—has
recently emerged as a rich domain for phase structure in quantum many-body systems away …

Producing quantum states at random has become increasingly important in modern
quantum science, with applications being both theoretical and practical. In particular …

The spectral form factor (SFF), characterizing statistics of energy eigenvalues, is a key
diagnostic of many-body quantum chaos. In addition, partial spectral form factors (PSFFs) …

We present exact results on a novel kind of emergent random matrix universality that
quantum many-body systems at infinite temperature can exhibit. Specifically, we consider an …