QHDOPT: A Software for Nonlinear Optimization with Quantum Hamiltonian Descent
Abstract
We develop an open-source, end-to-end software (named QHDOPT), which can solve nonlinear optimization problems using the quantum Hamiltonian descent (QHD) algorithm. QHDOPT offers an accessible interface and automatically maps tasks to various supported quantum backends (i.e., quantum hardware machines). These features enable users, even those without prior knowledge or experience in quantum computing, to utilize the power of existing quantum devices for nonlinear and nonconvex optimization tasks. In its intermediate compilation layer, QHDOPT employs SimuQ, an efficient interface for Hamiltonian-oriented programming, to facilitate multiple algorithmic specifications and ensure compatible cross-hardware deployment. The detailed documentation of QHDOPT is available at https://github.com/jiaqileng/QHDOPT.
Cite
@article{arxiv.2409.03121,
title = {QHDOPT: A Software for Nonlinear Optimization with Quantum Hamiltonian Descent},
author = {Samuel Kushnir and Jiaqi Leng and Yuxiang Peng and Lei Fan and Xiaodi Wu},
journal= {arXiv preprint arXiv:2409.03121},
year = {2024}
}
Comments
23 pages, 7 figures. The full repository is available at https://github.com/jiaqileng/QHDOPT