TY  - JOUR
AU  - Chai, Yahui
AU  - Jansen, Karl
AU  - Kühn, Stefan
AU  - Schwägerl, Tim
AU  - Stollenwerk, Tobias
TI  - Warm Start of Variational Quantum Algorithms for Quadratic Unconstrained Binary Optimization Problems
JO  - EPJ Quantum Technology
VL  - 13
IS  - 1
SN  - 2196-0763
CY  - Heidelberg ˜[u.a.]œ
PB  - SpringerOpen
M1  - PUBDB-2025-05521
M1  - arXiv:2407.02569
SP  - 9
PY  - 2026
AB  - 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.
KW  - Warm start (autogen)
KW  - Variational quantum algorithm (autogen)
KW  - Combinatorial optimization (autogen)
LB  - PUB:(DE-HGF)16
DO  - DOI:10.1140/epjqt/s40507-025-00452-0
UR  - https://bib-pubdb1.desy.de/record/642366
ER  -