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State-dependent running costs #38
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In principle, it's possible both with Krotov's method and GRAPE, but I haven't gotten around to implementing it in either package (since I haven't needed it, personally). GRAPE is going to be easier, so I can probably implement that soonish.
See JuliaQuantumControl/GRAPE.jl#53 and JuliaQuantumControl/Krotov.jl#34 for the details of GRAPE and Krotov, respectively.
In any case, it would be helpful to have a specific example so that I have something to test the implementation against. Can you create a Jupyter notebook (or script) in the style of the examples that sets up the problem you're trying to solve and upload that somewhere, like in a Gist?
I just want to clarify that nothing is going to happen on this issue without an example
Hey, I wanted to jump in since I recently had the chance to try out your package. A typical example where a running cost on the states would be very useful is precisely in cases where one wants to avoid certain subspaces during the evolution, as mentioned in your paper.
As a simple working example, I’ve put together a notebook largely inspired by yours. It demonstrates a transmon qubit on which I want to implement a fast X gate while avoiding population of states |3⟩, |4⟩, … during the evolution.
Would this still be on your todo?
Reacted by Michael Goerz
In the article published on Quantum state-dependent running costs are taken into account. How can this be done using this (collection of) package?