Authors of pre-print: Nam Nguyen, Richard Thompson (2024)
Pre-print: https://arxiv.org/abs/2402.14156
Notebook by: Óscar Amaro (2024-2025)
Obs: While attempting to reproduce some results from this pre-print, I believe there may be some typos, which do not impact its results or conclusions. However, I cannot guarantee this with certainty, nor that my alternative implementation is the correct one. Use this code and the accompanying notes at your own discretion.
Abstract: Maxwells equations are fundamental to our understanding of electromagnetic fields, but their solution can be computationally demanding, even for high-performance computing clusters. Quantum computers offer a promising alternative for solving these equations, as they can simulate larger and more complex systems more efficiently both in time and resources. In this paper we investigate the potential of using the variational quantum imaginary time evolution (VarQITE) algorithm on near-term quantum hardware to solve for the Maxwells equations. Our objective is to analyze the trade-off between the accuracy of the simulated fields and the depth of the quantum circuit required to implement the VarQITE algorithm. We demonstrate that VarQITE can efficiently approximate the solution of these equations with high accuracy, and show that its performance can be enhanced by optimizing the quantum circuit depth. Our findings suggest that VarQITE on near-term quantum devices could provide a powerful tool for solving PDEs in electromagnetics and other fields.