Comparing optimising and benchmarking quantum control algorithms in a unifying programming framework

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 ampli...

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Vydáno v:Physical review. A, Atomic, molecular, and optical physics Ročník 84; číslo 2
Hlavní autoři: Machnes, S., Sander, U., Glaser, S. J., de Fouquières, P., Gruslys, A., Schirmer, S., Schulte-Herbrüggen, T.
Médium: Journal Article
Jazyk:angličtina
Vydáno: United States 03.08.2011
Témata:
ACCURACY
ALGORITHMS
CALCULATION METHODS
CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS
COMPUTERIZED SIMULATION
INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY
OPTIMAL CONTROL
OPTIMIZATION
PROGRAMMING
QUANTUM COMPUTERS
RECOMMENDATIONS
ISSN:1050-2947, 1094-1622
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Popis
Shrnutí: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.
ISSN:1050-2947
1094-1622
DOI:10.1103/PhysRevA.84.022305