Quantum-Assisted Learning of Time-Dependent Parabolic PDEs
Quantum Physics
2025-08-26 v1
Abstract
We present a hybrid quantum-classical framework for solving general time-dependent parabolic partial differential equations (PDEs) using quantum variational circuits. Building on the QPINN approach, this method applies broadly to parabolic PDEs. To demonstrate its effectiveness, we focus on the 1D and 2D heat equations as representative examples and analyze its performance under constrained quantum resources. Our results show that the framework can accurately capture spatiotemporal dynamics, offering a promising direction for quantum-assisted scientific computing.
Keywords
Cite
@article{arxiv.2508.17553,
title = {Quantum-Assisted Learning of Time-Dependent Parabolic PDEs},
author = {Nahid Binandeh Dehaghani and Ban Tran and A. Pedro Aguiar and Rafal Wisniewski and Susan Mengel},
journal= {arXiv preprint arXiv:2508.17553},
year = {2025}
}
Comments
2 pages, 5 figures