Variational quantum algorithm (VQA), which is comprised of a classical optimizer and a
parameterized quantum circuit, emerges as one of the most promising approaches for …

Variational quantum algorithms (VQAs) can potentially solve practical problems using
contemporary Noisy Intermediate Scale Quantum (NISQ) computers. VQAs find near-optimal …

Quantum multi-programming is a method utilizing contemporary noisy intermediate-scale
quantum computers by executing multiple quantum circuits concurrently. Despite early …

NISQ devices have several physical limitations and unavoidable noisy quantum operations,
and only small circuits can be executed on a quantum machine to get reliable results. This …

Qubit map** for NISQ superconducting quantum computers is essential to fidelity and
resource utilization. The existing qubit map** schemes meet challenges, eg, crosstalk …

Quantum computing has gained considerable attention, especially after the arrival of the
Noisy Intermediate-Scale Quantum (NISQ) era. Quantum processors and cloud services …

We introduce the Quantum Operating System (QOS), a unified system stack for managing
quantum resources while mitigating their inherent limitations, namely their limited and noisy …

Quantum Machine Learning (QML) is an accelerating field of study that leverages the
principles of quantum computing to enhance and innovate within machine learning …

Quantum computers face challenges due to limited resources, particularly in cloud
environments. Despite these ob-stacles, Variational Quantum Algorithms (VQAs) are …

Common Pool Resources (CPRs) pose a challenge to find balance between individual self-
interest and collective cooperation. The current state of art tries to solve the problem using …