This article presents a hybrid metaheuristic optimization algorithm that combines particle
filter (PF) and particle swarm optimization (PSO) algorithms. The new PF–PSO algorithm …

The selection mechanism of genetic algorithms can play a key role in leading the
optimization process towards suitable solutions of a given problem, as their application can …

Finding the exact counterdiabatic potential is, in principle, particularly demanding. Following
recent progress about variational strategies to approximate the counterdiabatic operator, in …

The study of optimal control of quantum annealing by modulating the pace of evolution and
by introducing a counterdiabatic potential has gained significant attention in recent times. In …

In reverse quantum annealing, the initial state is an eigenstate of the final problem
Hamiltonian and the transverse field is cycled rather than strictly decreased as in standard …

We present counterdiabatic reverse annealing, a quantum annealing protocol that extends
the range of application of reverse annealing to the previously inaccessible short-time …

A crucial step in the race towards quantum advantage is optimizing quantum annealing
using ad-hoc annealing schedules. Motivated by recent progress in the field, we propose to …

Quantum computing is an emerging research area which promises to offer a revolution in
the computing performance. The world's first commercially available quantum computer has …

Noisy Intermediate Scale Quantum (NISQ) devices are expected to demonstrate the real
potential of quantum computing in solving hard problems. However, quantum noise that …

Accurate models of real quantum systems are important for investigating their behaviour, yet
are difficult to distil empirically. Here, we report an algorithm—the quantum model learning …