Decomposition-based QAOA with spectral graph cuts and GSR merging solves large satellite MCLP instances with competitive coverage and bounded qubit use where standard QAOA is infeasible.
Ising formulations of many NP problems
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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quant-ph 2years
2026 2representative citing papers
The QuaST Decision Tree is a configurable modular system that automates recommendations for hybrid quantum algorithms, featuring a module for assessing variational algorithm feasibility through scalability analysis.
citing papers explorer
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Decomposition-Based QAOA for Maximum Coverage Location Problem in Satellite Constellation Design
Decomposition-based QAOA with spectral graph cuts and GSR merging solves large satellite MCLP instances with competitive coverage and bounded qubit use where standard QAOA is infeasible.
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The QuaST Decision Tree: Achieving Automation With Data-Based Recommendations
The QuaST Decision Tree is a configurable modular system that automates recommendations for hybrid quantum algorithms, featuring a module for assessing variational algorithm feasibility through scalability analysis.