Constrained Quantum Optimization for Extractive Summarization on a Trapped-ion Quantum Computer

TL;DR

This paper demonstrates the largest execution of a constraint-preserving quantum optimization algorithm on a trapped-ion quantum computer for extractive summarization, highlighting the importance of encoding constraints directly into quantum circuits.

Contribution

It introduces and experimentally validates the XY-QAOA algorithm with constraint preservation on a large-scale trapped-ion quantum computer for the first time.

Findings

Successfully executed XY-QAOA with 20 qubits and 159 two-qubit gates.

Showed the importance of directly encoding constraints for solution quality.

Compared XY-QAOA with other quantum algorithms, discussing trade-offs.

Abstract

Realizing the potential of near-term quantum computers to solve industry-relevant constrained-optimization problems is a promising path to quantum advantage. In this work, we consider the extractive summarization constrained-optimization problem and demonstrate the largest-to-date execution of a quantum optimization algorithm that natively preserves constraints on quantum hardware. We report results with the Quantum Alternating Operator Ansatz algorithm with a Hamming-weight-preserving XY mixer (XY-QAOA) on trapped-ion quantum computer. We successfully execute XY-QAOA circuits that restrict the quantum evolution to the in-constraint subspace, using up to 20 qubits and a two-qubit gate depth of up to 159. We demonstrate the necessity of directly encoding the constraints into the quantum circuit by showing the trade-off between the in-constraint probability and the quality of the solution that is implicit if unconstrained quantum optimization methods are used. We show that this trade-off makes choosing good parameters difficult in general. We compare XY-QAOA to the Layer Variational Quantum Eigensolver algorithm, which has a highly expressive constant-depth circuit, and the Quantum Approximate Optimization Algorithm. We discuss the respective trade-offs of the algorithms and implications for their execution on near-term quantum hardware.