We present shadow spectroscopy as a simulator-agnostic quantum algorithm for estimating
energy gaps using very few circuit repetitions (shots) and no extra resources (ancilla qubits) …

Matrix product states (MPSs) and matrix product operators (MPOs) have been proven to be a
powerful tool to study quantum many-body systems but are restricted to moderately …

Dynamic quantum simulation is a leading application for achieving quantum advantage.
However, high circuit depths remain a limiting factor on near-term quantum hardware. We …

Simulating time evolution is one of the most natural applications of quantum computers and
is thus one of the most promising prospects for achieving practical quantum advantage …

The many-body problem is central to many fields, such as condensed-matter physics and
chemistry, but also to combinatorial optimization, which is nothing but a classical many-body …

We present a hardware-reconfigurable ansatz on $ N_q $-qubits for the variational
preparation of many-body states of the Anderson impurity model (AIM) with $ N_ {\text …

Traditional machine learning algorithms are facing significant challenges as the world enters
the era of big data, with a dramatic expansion in volume and range of applications and an …