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 …

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

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 …

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

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

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 …

A fundamental challenge in quantum information science is certifying that an n-qubit state ρ
prepared in the lab closely matches a target state |ψ⟩. Previous approaches to this problem …

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 …

Quantum thermalization in a many-body system is defined by the approach of local
subsystems toward a universal form, describable as an ensemble of quantum states wherein …