https://doi.org/10.1140/epjqt/s40507-025-00452-0
Research
Warm start of variational quantum algorithms for quadratic unconstrained binary optimization problems
1
Deutsches Elektronen-Synchrotron DESY, Platanenallee 6, 15738, Zeuthen, Germany
2
Computation-Based Science and Technology Research Center, The Cyprus Institute, 20 Kavafi Street, 2121, Nicosia, Cyprus
3
Institut für Physik, Humboldt-Universität zu Berlin, Newtonstr. 15, 12489, Berlin, Germany
4
Institute for Quantum Computing Analytics (PGI-12) Jülich Research Center, Wilhelm-Johnen-Str., 52428, Jülich, Germany
a
This email address is being protected from spambots. You need JavaScript enabled to view it.
Received:
7
September
2025
Accepted:
3
December
2025
Published online:
12
December
2025
Variational Quantum Eigensolver (VQE) is widely used in near-term hardware. However, their performances remain limited by the poor trainability and are dependent on random parameter initialization. In this work, we propose a warm start method inspired by imaginary time evolution, allowing for determining initial parameters that prioritize lower energy states in a resource-efficient way. Using classical simulations, we demonstrate that this warm start method significantly improves the success rate and reduces the number of iterations required for the convergence of VQE. The numerical results also indicate that the warm start approach effectively mitigates statistical errors arising from a finite number of measurements, and to a certain extent alleviates the effect of barren plateaus.
Key words: Warm start / Variational quantum algorithm / Combinatorial optimization
© The Author(s) 2025
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
