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

It is for the first time that quantum simulation for high-energy physics (HEP) is studied in the
US decadal particle-physics community planning, and in fact until recently, this was not …

The future development of quantum technologies relies on creating and manipulating
quantum systems of increasing complexity, with key applications in computation, simulation …

Computational models are an essential tool for the design, characterization, and discovery
of novel materials. Computationally hard tasks in materials science stretch the limits of …

Quantum computers offer an intriguing path for a paradigmatic change of computing in the
natural sciences and beyond, with the potential for achieving a so-called quantum …

The variational quantum eigensolver (VQE) is an algorithm to compute ground and excited
state energy of quantum many-body systems. A key component of the algorithm and an …

Obtaining the expectation value of an observable on a quantum computer is a crucial step in
the variational quantum algorithms. For complicated observables such as molecular …

Quantum computers solve ever more complex tasks using steadily growing system sizes.
Characterizing these quantum systems is vital, yet becoming increasingly challenging. The …

Quantum neural networks (QNNs) have become an important tool for understanding the
physical world, but their advantages and limitations are not fully understood. Some QNNs …

Informationally complete (IC) positive operator-valued measures (POVMs) are generalized
quantum measurements that offer advantages over the standard computational basis …