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

Quantum alternating operator ansatz (QAOA) has a strong connection to the adiabatic
algorithm, which it can approximate with sufficient depth. However, it is unclear to what …

The adiabatic theorem provides sufficient conditions for the time needed to prepare a target
ground state. While it is possible to prepare a target state much faster with more general …

We propose and analyze the use of Bayesian optimization techniques to design quantum
annealing schedules with minimal user and resource requirements. We showcase our …

Solving optimization problems using variational algorithms stands out as a crucial
application for noisy intermediate-scale devices. Instead of constructing gate-based …

We present a hybrid classical-quantum computing paradigm where the quantum part strictly
runs within the coherence time of a quantum annealer, a method we call variational …

Aquaculture is a vital contributor to global food security, yet maintaining optimal water quality
remains a persistent challenge, particularly in resource-limited rural settings. This study …

Dynamical quantum phase transition is a critical phenomenon involving out-of-equilibrium
states and broken symmetries without classical analogy. However, when finite-sized …

Abstract Variational Quantum-Classical Algorithm (VQCA) is a potential tool for machine
learning (ML) prediction tasks, but its efficacy, adaptability to big datasets, and optimization …

It is becoming more obvious that quantum computing might have ground-breaking
implications in a variety of different industries as the globe continues to explore further into …