Research on electronic devices and materials is currently driven by both the slowing down
of transistor scaling and the exponential growth of computing needs, which make present …

Abstract The Quantum Approximate Optimization Algorithm (QAOA) is a highly promising
variational quantum algorithm that aims to solve combinatorial optimization problems that …

For the first time in history, we are seeing a branching point in computing paradigms with the
emergence of quantum processing units (QPUs). Extracting the full potential of computation …

Gate-model quantum computers promise to solve currently intractable computational
problems if they can be operated at scale with long coherence times and high-fidelity logic …

A universal fault-tolerant quantum computer that can efficiently solve problems such as
integer factorization and unstructured database search requires millions of qubits with low …

Nowadays, quantum computing has reached the engineering phase, with fully-functional
quantum processors integrating hundreds of noisy qubits. Yet–to fully unveil the potential of …

Applications such as simulating complicated quantum systems or solving large-scale linear
algebra problems are very challenging for classical computers, owing to the extremely high …

Quantum computers have demonstrable ability to solve problems at a scale beyond brute-
force classical simulation. Interest in quantum algorithms has developed in many areas …

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 …

Recently, several quantum machine learning algorithms have been proposed that may offer
quantum speed-ups over their classical counterparts. Most of these algorithms are either …