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September 10, 2025ComputersOpen Access

Spectral Graph Compression in Deploying Recommender Algorithms on Quantum Simulators

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Case study explores graph compression techniques using QAOA for optimized investment recommendations under regulatory constraints.

Efficient graph compression enhances the deployment of quantum algorithms in financial asset management, and highlights the importance of hybrid frameworks.
The introduction of a graph compression pipeline allows for QAOA deployment under quantum hardware constraints, improving scalability in portfolio management.
This work employs quantum simulators, comparing performance against classical methods for solving the Max-Cut problem in investor clustering.
The research emphasizes bridging theoretical quantum advantage to practical applications necessary for regulatory compliance in financial systems.

Liu et al. (2025) studied this question.

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