Spatial Regionalization: A Hybrid Quantum Computing Approach
- URL: http://arxiv.org/abs/2506.18799v1
- Date: Mon, 23 Jun 2025 16:04:05 GMT
- Title: Spatial Regionalization: A Hybrid Quantum Computing Approach
- Authors: Yunhan Chang, Amr Magdy, Federico M. Spedalieri, Ibrahim Sabek,
- Abstract summary: We introduce the first hybrid quantum-classical method to spatial regionalization by decomposing the problem into manageable subproblems.<n>Our initial results show a promising quantum performance advantage for a broad range of spatial regionalization problems and their variants.
- Score: 4.484833918455159
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Quantum computing has shown significant potential to address complex optimization problems; however, its application remains confined to specific problems at limited scales. Spatial regionalization remains largely unexplored in quantum computing due to its complexity and large number of variables. In this paper, we introduce the first hybrid quantum-classical method to spatial regionalization by decomposing the problem into manageable subproblems, leveraging the strengths of both classical and quantum computation. This study establishes a foundational framework for effectively integrating quantum computing methods into realistic and complex spatial optimization tasks. Our initial results show a promising quantum performance advantage for a broad range of spatial regionalization problems and their variants.
Related papers
- Parallel Quantum Local Search via Evolutionary Mechanism [0.9208007322096533]
We propose an innovative Parallel Quantum Local Search (PQLS) methodology that leverages the capabilities of small-scale quantum computers.
Our approach transcends this constraint by simultaneously executing multiple QLS pathways and aggregating their most effective outcomes at certain intervals to establish a generation''
Our findings demonstrate the profound impact of parallel quantum computing in enhancing the resolution of Ising problems.
arXiv Detail & Related papers (2024-06-10T16:35:52Z) - Bias-field digitized counterdiabatic quantum optimization [39.58317527488534]
We call this protocol bias-field digitizeddiabatic quantum optimization (BF-DCQO)
Our purely quantum approach eliminates the dependency on classical variational quantum algorithms.
It achieves scaling improvements in ground state success probabilities, increasing by up to two orders of magnitude.
arXiv Detail & Related papers (2024-05-22T18:11:42Z) - State-Averaged Orbital-Optimized VQE: A quantum algorithm for the
democratic description of ground and excited electronic states [0.0]
The SA-OO-VQE package aims to answer both problems with its hybrid quantum-classical conception based on a typical Variational Quantum Eigensolver approach.
The SA-OO-VQE has the ability to treat degenerate (or quasi-degenerate) states on the same footing, thus avoiding known numerical optimization problems around avoided crossings or conical intersections.
arXiv Detail & Related papers (2024-01-22T12:16:37Z) - Quantum Complexity vs Classical Complexity: A Survey [2.4302813010040714]
Adapting problem-solving strategies is crucial to harness the full potential of quantum computing.
This paper concentrates on aggregating prior research efforts dedicated to solving intricate classical computational problems through quantum computing.
arXiv Detail & Related papers (2023-12-16T16:02:21Z) - Exploring the topological sector optimization on quantum computers [5.458469081464264]
topological sector optimization (TSO) problem attracts particular interests in the quantum many-body physics community.
We demonstrate that the optimization difficulties of TSO problem are not restricted to the gaplessness, but are also due to the topological nature.
To solve TSO problems, we utilize quantum imaginary time evolution (QITE) with a possible realization on quantum computers.
arXiv Detail & Related papers (2023-10-06T14:51:07Z) - Quantum algorithms: A survey of applications and end-to-end complexities [90.05272647148196]
The anticipated applications of quantum computers span across science and industry.
We present a survey of several potential application areas of quantum algorithms.
We outline the challenges and opportunities in each area in an "end-to-end" fashion.
arXiv Detail & Related papers (2023-10-04T17:53:55Z) - Near-Term Distributed Quantum Computation using Mean-Field Corrections
and Auxiliary Qubits [77.04894470683776]
We propose near-term distributed quantum computing that involve limited information transfer and conservative entanglement production.
We build upon these concepts to produce an approximate circuit-cutting technique for the fragmented pre-training of variational quantum algorithms.
arXiv Detail & Related papers (2023-09-11T18:00:00Z) - Formulation of the Electric Vehicle Charging and Routing Problem for a
Hybrid Quantum-Classical Search Space Reduction Heuristic [0.0]
We show how to exploit multilevel carriers of quantum information -- qudits -- for the construction of constrained quantum optimization algorithms.
We propose a hybrid classical quantum strategy that allows us to sample constrained solutions while greatly reducing the search space of the problem.
arXiv Detail & Related papers (2023-06-07T13:16:15Z) - Quantum Annealing for Single Image Super-Resolution [86.69338893753886]
We propose a quantum computing-based algorithm to solve the single image super-resolution (SISR) problem.
The proposed AQC-based algorithm is demonstrated to achieve improved speed-up over a classical analog while maintaining comparable SISR accuracy.
arXiv Detail & Related papers (2023-04-18T11:57:15Z) - Variational Quantum Algorithms for Computational Fluid Dynamics [0.0]
Variational quantum algorithms are particularly promising since they are comparatively noise tolerant.
We show how variational quantum algorithms can be utilized in computational fluid dynamics.
We argue that a quantum advantage over classical computing methods could be achieved by the end of this decade.
arXiv Detail & Related papers (2022-09-11T18:49:22Z) - Synergy Between Quantum Circuits and Tensor Networks: Short-cutting the
Race to Practical Quantum Advantage [43.3054117987806]
We introduce a scalable procedure for harnessing classical computing resources to provide pre-optimized initializations for quantum circuits.
We show this method significantly improves the trainability and performance of PQCs on a variety of problems.
By demonstrating a means of boosting limited quantum resources using classical computers, our approach illustrates the promise of this synergy between quantum and quantum-inspired models in quantum computing.
arXiv Detail & Related papers (2022-08-29T15:24:03Z) - Quantum communication complexity beyond Bell nonlocality [87.70068711362255]
Efficient distributed computing offers a scalable strategy for solving resource-demanding tasks.
Quantum resources are well-suited to this task, offering clear strategies that can outperform classical counterparts.
We prove that a new class of communication complexity tasks can be associated to Bell-like inequalities.
arXiv Detail & Related papers (2021-06-11T18:00:09Z) - Quantum Entropic Causal Inference [30.939150842529052]
We put forth a new theoretical framework for merging quantum information science and causal inference by exploiting entropic principles.
We apply our proposed framework to an experimentally relevant scenario of identifying message senders on quantum noisy links.
arXiv Detail & Related papers (2021-02-23T15:51:34Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.