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What is QAOA for Multi-Constrained Optimization about?

This paper introduces an efficient architecture for the Quantum Approximate Optimization Ansatz (QAOA) aimed at solving Multi-Constrained Optimization Problems by integrating specific constraint encoding methods. It presents a workflow that utilizes XY-mixers for one-hot constraints and oracle-based Indicator Functions for inequality constraints, demonstrating improved solution quality and faster time-to-solution compared to traditional QUBO formulations. The proposed method is validated through simulations

Author

Anurag Kumar

Language

EN