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

Due to low numbers of qubits and their error-proneness, Noisy Intermediate-Scale Quantum
(NISQ) computers impose constraints on the size of quantum algorithms they can …

Quantum processing units (QPUs) are currently exclusively available from cloud vendors.
However, with recent advancements, hosting QPUs will soon be possible everywhere …

As quantum computers evolve, so does the complexity of the software that they can run. To
make this software efficient, maintainable, reusable, and cost-effective, quality attributes that …

Quantum computers (QCs) aim to disrupt the status-quo of computing–replacing traditional
systems and platforms that are driven by digital circuits and modular software–with hardware …

Quantum algorithms have the potential to outperform classical algorithms for certain
problems. However, implementing quantum algorithms in a reusable manner and …

The capabilities of current quantum computers are limited by their high error rates. Thus,
reducing the impact of these errors is one of the crucial challenges for the successful …

Today's quantum computers are limited in their capabilities, eg, the size of executable
quantum circuits. The Quantum Approximate Optimization Algorithm (QAOA) addresses …

Continuously evolving quantum service offerings vary in development and deployment
requirements they impose on quantum application developers. Further, since quantum …

With quantum computers now available as cloud services, there is a global quest for
applications where a quantum advantage can be shown. Naturally, data management is a …