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

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 …

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 …

Abstract Variational Quantum Algorithms (VQAs) may be a path to quantum advantage on
Noisy Intermediate-Scale Quantum (NISQ) computers. A natural question is whether noise …

The quantum approximate optimization algorithm (QAOA) is a leading candidate algorithm
for solving optimization problems on quantum computers. However, the potential of QAOA to …

Faster algorithms for combinatorial optimization could prove transformative for diverse areas
such as logistics, finance and machine learning. Accordingly, the possibility of quantum …

The quantum approximate optimization algorithm (QAOA) is a hybrid quantum-classical
variational algorithm designed to tackle combinatorial optimization problems. Despite its …

Many experimental proposals for noisy intermediate scale quantum devices involve training
a parameterized quantum circuit with a classical optimization loop. Such hybrid quantum …

Previously proposed quantum algorithms for solving linear systems of equations cannot be
implemented in the near term due to the required circuit depth. Here, we propose a hybrid …

The next few years will be exciting as prototype universal quantum processors emerge,
enabling the implementation of a wider variety of algorithms. Of particular interest are …