DOAJ Open Access 2024

A Comparative Study on Solving Optimization Problems With Exponentially Fewer Qubits

David Winderl Nicola Franco Jeanette Miriam Lorenz

Abstrak

Variational quantum optimization algorithms, such as the variational quantum eigensolver (VQE) or the quantum approximate optimization algorithm (QAOA), are among the most studied quantum algorithms. In our work, we evaluate and improve an algorithm based on the VQE, which uses exponentially fewer qubits compared to the QAOA. We highlight the numerical instabilities generated by encoding the problem into the variational ansatz and propose a classical optimization procedure to find the ground state of the ansatz in fewer iterations with a better or similar objective. In addition, we propose a method to embed the linear interpolation of the MaxCut problem on a quantum device. Furthermore, we compare classical optimizers for this variational ansatz on quadratic unconstrained binary optimization and graph partitioning problems.

Topik & Kata Kunci

Atomic physics. Constitution and properties of matter Materials of engineering and construction. Mechanics of materials

Penulis (3)

David Winderl

Nicola Franco

Jeanette Miriam Lorenz

Format Sitasi

APA MLA BibTeX

Winderl, D., Franco, N., Lorenz, J.M. (2024). A Comparative Study on Solving Optimization Problems With Exponentially Fewer Qubits. https://doi.org/10.1109/TQE.2024.3392834

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Informasi Jurnal

Tahun Terbit: 2024
Sumber Database: DOAJ
DOI: 10.1109/TQE.2024.3392834
Akses: Open Access ✓