11 citations · 22 across the 12 of their papers we have counts for
5 papers · 1 filter
Quantum Annealing: Optimisation, Sampling, and Many-Body Dynamics
Steven Abel, Andrei Constantin, Luca A. Nutricati
Quantum annealing is a computational paradigm in which optimisation problems are mapped onto the energy landscape of an interacting quantum system and explored through its dynamica…
Quantum Annealing Feature Selection on Light-weight Medical Image Datasets
Merlin A. Nau, Luca A. Nutricati, Bruno Camino +2
We investigate the use of quantum computing algorithms on real quantum hardware to tackle the computationally intensive task of feature selection for light-weight medical image dat…
Enhancing the Energy Gap of Random Graph Problems via XX-catalysts in Quantum Annealing
Luca A. Nutricati, Roopayan Ghosh, Natasha Feinstein +2
One of the bottlenecks in solving combinatorial optimisation problems using quantum annealers is the emergence of exponentially-closing energy gaps between the ground state and the…
Enhancement of quantum annealing via n-local catalysts
Roopayan Ghosh, Luca A. Nutricati, Natasha Feinstein +2
The potential quantum speedup in solving optimization problems via adiabatic quantum annealing is often hindered by the closing of the energy gap during the anneal, especially when…
A Genetic Quantum Annealing Algorithm
Steven Abel, Luca A. Nutricati, Michael Spannowsky
A genetic algorithm (GA) is a search-based optimization technique based on the principles of Genetics and Natural Selection. We present an algorithm which enhances the classical GA…