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

Quantum annealing is a quantum computing approach widely used for optimization and
probabilistic sampling problems. It is an alternative approach designed due to the limitations …

Optimization is one of the research areas where quantum computing could bring significant
benefits. In this scenario, a hybrid quantum–classical variational algorithm, the Quantum …

Abstract The Quantum Approximate Optimization Algorithm (QAOA) is a variational quantum
algorithm for Near-term Intermediate-Scale Quantum computers (NISQ) providing …

We study large-scale applications using a GPU-accelerated version of the massively parallel
Jülich universal quantum computer simulator (JUQCS–G). First, we benchmark JUWELS …

Compiling quantum circuits on target quantum hardware architectures is one of the key
issues in the development of quantum algorithms, and the related problem is known as the …

Mobile edge computing is a promising paradigm that provides edge users with dependable
computing services. However, due to the dynamic nature of mobile users and the limited …

The Quantum Approximate Optimization Algorithm (QAOA) is one of the most promising
Noisy Intermediate Quantum Algorithms (NISQ) in solving combinatorial optimizations and …

Feature selection plays a significant role in computer science; nevertheless, this task is
intractable since its search space scales exponentially with the number of dimensions …

Today's Noisy Intermediate-Scale Quantum (NISQ) computers support only limited sets of
available quantum gates and restricted connectivity. Therefore, quantum algorithms must be …