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Quantum Optimization
Analysis and Experimental Demonstration of Amplitude Amplification for Combinatorial Optimization
arXiv
Authors: Daniel Koch, Brian Pardo, Kip Nieman
Year
2026
Paper ID
3753
Status
Preprint
Abstract Read
~2 min
Abstract Words
141
Citations
N/A
Abstract
Quantum Amplitude Amplification (QAA), the generalization of Grover's algorithm, is capable of yielding optimal solutions to combinatorial optimization problems with high probabilities. In this work we extend the conventional 2-dimensional representation of Grover's (orthogonal collective states) to oracles which encode cost functions such as QUBO, and show that linear cost functions are a special case whereby an exact formula exists for determining optimal oracle parameter settings. Using simulations of problem sizes up to 40 qubits we demonstrate QAA's algorithmic performance across all possible solutions, with an emphasis on the closeness in Grover-like performance for solutions near the global optimum. We conclude with experimental demonstrations of generalized QAA on both IBMQ (superconducting) and IonQ (trapped ion) qubits, showing that the observed probabilities of each basis state match our equations as a function of varying the free parameters in the oracle and diffusion operators.
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- This paper contributes to the Quantum Optimization research area in the Quantum Articles archive.
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- Quantum Amplitude Amplification (QAA), the generalization of Grover's algorithm, is capable of yielding optimal solutions to combinatorial optimization problems with high...
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