Journal
PHYSICAL REVIEW A
Volume 84, Issue 2, Pages -Publisher
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevA.84.022305
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Funding
- Tommaso Calarco through EU
- Bavarian Ph.D. Programme of Excellence QCCC
- EU
- QAP
- Q-ESSENCE
- COQUIT
- Deutsche Forschungsgemeinschaft, DFG [SFB 631]
- EPSRC ARF [EP/DO7192X/1]
- EPSRC
- Hitachi [CASE/CNA/07/47]
- Humboldt Foundation
- EPSRC [EP/D07195X/2, EP/D07195X/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/D07195X/2, EP/D07195X/1] Funding Source: researchfish
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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.
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