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QHDOPT: A Software for Nonlinear Optimization with Quantum Hamiltonian Descent

Authors :
Kushnir, Samuel
Leng, Jiaqi
Peng, Yuxiang
Fan, Lei
Wu, Xiaodi
Publication Year :
2024

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.<br />Comment: 23 pages, 7 figures. The full repository is available at https://github.com/jiaqileng/QHDOPT

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2409.03121
Document Type :
Working Paper