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

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 The Quantum Approximate Optimization Algorithm (QAOA) is a general-purpose
algorithm for combinatorial optimization problems whose performance can only improve with …

Classical simulation of quantum computers will continue to play an essential role in the
progress of quantum information science, both for numerical studies of quantum algorithms …

We use Pontryagin's minimum principle to optimize variational quantum algorithms. We
show that for a fixed computation time, the optimal evolution has a bang-bang (square …

Integer factorization has been one of the cornerstone applications of the field of quantum
computing since the discovery of an efficient algorithm for factoring by Peter Shor …

Intelligent transportation systems (ITS) are a critical component of Industry 4.0 and 5.0,
particularly having applications in logistic management. One of their crucial utilization is in …

We consider the power of local algorithms for approximately solving Max $ k $ XOR, a
generalization of two constraint satisfaction problems previously studied with classical and …

We introduce a novel open-source software package QForte, a comprehensive development
tool for new quantum simulation algorithms. QForte incorporates functionality for handling …

The minimum vertex cover problem belongs to a NP-complete problem, which is difficult to
obtain the near-optimal solution in the polynomial time range using classical algorithms. In …