Browsing by Keyword "Quantum Annealer"
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Item Analyzing the behaviour of D'WAVE quantum annealer: Fine-tuning parameterization and tests with restrictive Hamiltonian formulations(Institute of Electrical and Electronics Engineers Inc., 2022) Villar-Rodriguez, Esther; Osaba, Eneko; Oregi, Izaskun; Ishibuchi, Hisao; Kwoh, Chee-Keong; Tan, Ah-Hwee; Srinivasan, Dipti; Miao, Chunyan; Trivedi, Anupam; Crockett, Keeley; QuantumDespite being considered as the next frontier in computation, Quantum Computing is still in an early stage of development. Indeed, current commercial quantum computers suffer from some critical restraints, such as noisy processes and a limited amount of qubits, among others, that affect the performance of quantum algorithms. Despite these limitations, researchers have devoted much effort to propose different frameworks for efficiently using these Noisy Intermediate-Scale Quantum (NISQ) devices. One of these procedures is D'WAVE Systems' quantum-annealer, which can be used to solve optimization problems by translating them into an energy minimization problem. In this context, this work is focused on providing useful insights and information into the behaviour of the quantum-annealer when addressing real-world combinatorial optimization problems. Our main motivation with this study is to open some quantum computing frontiers to non-expert stakeholders. To this end, we perform an extensive experimentation, in the form of a parameter sensitive analysis. This experimentation has been conducted using the Traveling Salesman Problem as benchmarking problem, and adopting two QUBOs: state-of-the-art and a heuristically generated. Our analysis has been performed on a single 7-noded instance, and it is based on more than 200 different parameter configurations, comprising more than 3700 unitary runs and 7 million of quantum reads. Thanks to this study, findings related to the energy distribution and most appropriate parameter settings have been obtained. Finally, an additional study has been performed, aiming to determine the efficiency of the heuristically built QUBO in further TSP instances.Item Optimization of Image Acquisition for Earth Observation Satellites via Quantum Computing(Springer Science and Business Media Deutschland GmbH, 2023) Makarov, Antón; Taddei, Márcio M.; Osaba, Eneko; Franceschetto, Giacomo; Villar-Rodríguez, Esther; Oregi, Izaskun; Quaresma, Paulo; Gonçalves, Teresa; Camacho, David; Yin, Hujun; Julian, Vicente; Tallón-Ballesteros, Antonio J.; QuantumSatellite image acquisition scheduling is a problem that is omnipresent in the earth observation field; its goal is to find the optimal subset of images to be taken during a given orbit pass under a set of constraints. This problem, which can be modeled via combinatorial optimization, has been dealt with many times by the artificial intelligence and operations research communities. However, despite its inherent interest, it has been scarcely studied through the quantum computing paradigm. Taking this situation as motivation, we present in this paper two QUBO formulations for the problem, using different approaches to handle the non-trivial constraints. We compare the formulations experimentally over 20 problem instances using three quantum annealers currently available from D-Wave, as well as one of its hybrid solvers. Fourteen of the tested instances have been obtained from the well-known SPOT5 benchmark, while the remaining six have been generated ad-hoc for this study. Our results show that the formulation and the ancilla handling technique is crucial to solve the problem successfully. Finally, we also provide practical guidelines on the size limits of problem instances that can be realistically solved on current quantum computers.