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Trapped Ion Quantum Computing
QICS: Quantum Information Conic Solver
arXiv
Authors: Kerry He, James Saunderson, Hamza Fawzi
Year
2024
Paper ID
37761
Status
Preprint
Abstract Read
~2 min
Abstract Words
133
Citations
N/A
Abstract
We introduce QICS (Quantum Information Conic Solver), an open-source primal-dual interior point solver fully implemented in Python, which is focused on solving optimization problems arising in quantum information theory. QICS has the ability to solve optimization problems involving the quantum relative entropy, noncommutative perspectives of operator convex functions, and related functions. It also includes an efficient semidefinite programming solver which exploits sparsity, as well as support for Hermitian matrices. QICS is also currently supported by the Python optimization modelling software PICOS. This paper aims to document the implementation details of the algorithm and cone oracles used in QICS, and serve as a reference guide for the software. Additionally, we showcase extensive numerical experiments which demonstrate that QICS outperforms state-of-the-art quantum relative entropy programming solvers, and has comparable performance to state-of-the-art semidefinite programming solvers.
Why This Paper Matters
- This paper contributes to the Trapped-Ion Quantum Computing research area in the Quantum Articles archive.
- It adds a 2024 reference point for readers tracking recent quantum research.
- We introduce QICS (Quantum Information Conic Solver), an open-source primal-dual interior point solver fully implemented in Python, which is focused on solving optimization...
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