Comparing, optimizing, and benchmarking quantum-control algorithms in a unifying programming framework
- Quantum Group, Department of Physics, Tel-Aviv University, Tel Aviv 69978 (Israel)
- Department of Chemistry, Technical University of Munich (TUM), D-85747 Garching (Germany)
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, CB3 0WA (United Kingdom)
For paving the way to novel applications in quantum simulation, computation, and technology, increasingly large quantum systems have to be steered with high precision. It is a typical task amenable to numerical optimal control to turn the time course of pulses, i.e., piecewise constant control amplitudes, iteratively into an optimized shape. Here, we present a comparative study of optimal-control algorithms for a wide range of finite-dimensional applications. We focus on the most commonly used algorithms: GRAPE methods which update all controls concurrently, and Krotov-type methods which do so sequentially. Guidelines for their use are given and open research questions are pointed out. Moreover, we introduce a unifying algorithmic framework, DYNAMO (dynamic optimization platform), designed to provide the quantum-technology community with a convenient matlab-based tool set for optimal control. In addition, it gives researchers in optimal-control techniques a framework for benchmarking and comparing newly proposed algorithms with the state of the art. It allows a mix-and-match approach with various types of gradients, update and step-size methods as well as subspace choices. Open-source code including examples is made available at http://qlib.info.
- OSTI ID:
- 22068498
- Journal Information:
- Physical Review. A, Vol. 84, Issue 2; Other Information: (c) 2011 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA); ISSN 1050-2947
- Country of Publication:
- United States
- Language:
- English
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