IEEE Electron Devices Technology & Manufacturing Conference (EDTM)

Performance Comparison for Quantum Approximate Optimization Algorithm (QAOA) across Noiseless Simulation, Experimentally Benchmarked Noisy Simulation, and Experimental Hardware Platforms

Sanyam Singhal, Vandit Srivastava, P Rohith, Prateek Jain, Debanjan Bhowmik

Published Mar 3, 2024• 3 citations

Abstract

We implement Quantum Approximate Optimization Algorithm (QAOA) on NP-Hard problem MaxCut (for 3-chain and 4-node chain graphs, and 4-node and 6node Mobius Ladder graphs) on a quantum simulator without noise, a simulator with experimentally bench-marked noise (fake back-end), and 5-qubit and 7-qubit processors. We use the following modes of operation: QAOA parameters updated through forward pass on the quantum circuit, modelled by the noiseless simulator as well as fake back-end, and the quantum circuit for final run with updated parameters implemented on the noiseless simulator, fake back-end, and real quantum processors. While QAOA yields higher approximation ratio compared to random guess for almost all graph instances, we also conclude that given the noise in existing quantum hardware, a quantum circuit with more than two stages is not suitable for experimental implementation of QAOA currently.

DOI: 10.1109/edtm58488.2024.10512142

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