Quantum Circuit Design using Complex valued Neural Network in Stiefel Manifold
Quantum Physics
2025-09-03 v1
Abstract
Quantum algorithms operate on quantum states through unitary transformations in high dimensional complex Hilbert space. In this work, we propose a machine learning approach to create the quantum circuit using a single-layer complex-valued neural network. The input and ouput quantum states are provided to the network, which is trained to approximate the output state of a given quantum algorithm. To ensure that the fundamental property of unitarity is preserved throughout the training process, we employ optimization in Stiefel Manifold.
Cite
@article{arxiv.2509.02374,
title = {Quantum Circuit Design using Complex valued Neural Network in Stiefel Manifold},
author = {Sayan Manna and Mahesh Mohan M R},
journal= {arXiv preprint arXiv:2509.02374},
year = {2025}
}
Comments
6 pages, 4 figures