Comparative study of variations in quantum approximate optimization
algorithms for the Traveling Salesman Problem
- URL: http://arxiv.org/abs/2307.07243v1
- Date: Fri, 14 Jul 2023 09:35:58 GMT
- Title: Comparative study of variations in quantum approximate optimization
algorithms for the Traveling Salesman Problem
- Authors: Wenyang Qian, Robert A. M. Basili, Mary Eshaghian-Wilner, Ashfaq
Khokhar, Glenn Luecke, James P. Vary
- Abstract summary: We tackle the Traveling Salesman Problem (TSP) using the quantum approximate optimization algorithm (QAOA) approach.
We present numerical results obtained from the gate-based digital quantum simulator.
We find a well-balanced QAOA mixer design exhibits more promising potential for gate-based simulators and realistic quantum devices in the long run.
- Score: 0.06524460254566902
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: The Traveling Salesman Problem (TSP) is one of the most often-used NP-Hard
problems in computer science to study the effectiveness of computing models and
hardware platforms. In this regard, it is also heavily used as a vehicle to
study the feasibility of the quantum computing paradigm for this class of
problems. In this paper, we tackle the TSP using the quantum approximate
optimization algorithm (QAOA) approach by formulating it as an optimization
problem. By adopting an improved qubit encoding strategy and a layerwise
learning optimization protocol, we present numerical results obtained from the
gate-based digital quantum simulator, specifically targeting TSP instances with
3, 4, and 5 cities. We focus on the evaluations of three distinctive QAOA mixer
designs, considering their performances in terms of numerical accuracy and
optimization cost. Notably, we find a well-balanced QAOA mixer design exhibits
more promising potential for gate-based simulators and realistic quantum
devices in the long run, an observation further supported by our noise model
simulations. Furthermore, we investigate the sensitivity of the simulations to
the TSP graph. Overall, our simulation results show the digital quantum
simulation of problem-inspired ansatz is a successful candidate for finding
optimal TSP solutions.
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