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Python implementation of Krotov's method for quantum optimal control

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qucontrol/krotov

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Source code on GithubDocumentationKrotov on the Python Package IndexDocsTestsCodecovBSD LicenseLaunch BinderDOI

Python implementation of Krotov's method for quantum optimal control.

This implementation follows the original implementation in theQDYNFortran library.

Thekrotov package is built on top ofQuTiP.

Development happens onGithub.You can read the full documentationonline.

If you use thekrotov package in your research, pleaseciteit.

Purpose

Optimal control is a cornerstone of quantum technology: relying not juston a passive understanding of quantum mechanics, but on theactiveutilization of the quantum properties of matter. Quantum optimal controlasks how to manipulate the dynamics of a quantum system in some desiredway. This is essential for the realization of quantum computers andrelated technologies such as quantum sensing.

Krotov's method and GRAPE are the two leading gradient-basedoptimization algorithms used in numerical quantum optimal control.Krotov's method distinguishes itself by guaranteeing monotonicconvergence for near-continuous control fields. This makes isparticularly useful for exploring the limits of controllability in aphysical system. While GRAPE is found in various software packages,there has not been an open source implementation of Krotov's method todate. Our package provides that missing implementation.

The Krotov package targets both students wishing to enter the field ofquantum control and researchers in the field. It was designed towardsthe following goals:

  • Leverage theQuTiP library as a platform fornumerically describing quantum systems.
  • Provide a collection of examples inspired by recent publications intheJupyter notebook format, allowing forinteractive exploration of the method.
  • Define a general interface for formulatingany quantum controlproblem, which may extend to other optimization methods in the future.
  • Serve as a reference implementation of Krotov's method, and as afoundation against which to test other implementations.
  • Enable the more widespread use of Krotov's method, for example in thedesign of experiments.

Further Information

For further information, including installation and usage instructions, see thedocumentation athttps://qucontrol.github.io/krotov.


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