%0 Generic %A Wesdorp, Jaap %A Grunhaupt, L. %A Vaartjes, A. %A Pita-vidal, M. %A Bargerbos, Arno %A Splitthoff, L.J. %A Krogstrup, P. %A van Heck, Bernard %A de Lange, G. %D 2022 %T Data repository for: Dynamical polarization of the fermion parity in a nanowire Josephson junction %U https://data.4tu.nl/articles/dataset/Data_repository_for_Dynamical_polarization_of_the_fermion_parity_in_a_nanowire_Josephson_junction/17876240/1 %R 10.4121/17876240.v1 %K Andreev Bound States %K Hybrid nanowires %K Superconducting Circuits %K fermion parity superconductor %X Data repository for Dynamical polarization of the fermion parity in a nanowire Josephson junction.

Josephson junctions in InAs nanowires proximitized with an Al shell can host gate-tunable Andreev bound states. Depending on the bound state occupation, the fermion parity of the junction can be even or odd. Coherent control of Andreev bound states has recently been achieved within each parity sector, but it is impeded by incoherent parity switches due to excess quasiparticles in the superconducting environment. Here, we show that we can polarize the fermion parity dynamically using microwave pulses by embedding the junction in a superconducting LC resonator. We demonstrate polarization up to 94% ± 1% (89% ± 1%) for the even (odd) parity as verified by single shot parity-readout. Finally, we apply this scheme to probe the flux-dependent transition spectrum of the even or odd parity sector selectively, without any post-processing or heralding.




README CONTENTS (also included in the .ZIP)---------------------------------------------------------------------------# Data repository for Dynamical polarization of the fermion parity in a nanowire Josephson junction.
Manuscript located at https://arxiv.org/abs/2112.01936

Authors: J.J. Wesdorp, L. Grunhaupt, A. Vaartjes, M. Pita-Vidal, A. Bargerbos, L.J. Splitthoff, P. Krogstrup, B. van Heck and G. de Lange.


This is a self-contained repository with the code that analyses the raw data (exported to .nc format).
Required packages are:
* matplotlib
* xarray
* h5py
* h5netcdf
* lmfit
* scipy
* numpy
* jupyter-notebook
* cv2 (only for figure S6)
* jupyter_contrib_nbextensions (recommended to see the table of content per notebook)

*An environment.yaml file is provided for conda based installations. The exact versions are denoted there.*


Folder structure:
- data : All data files used to generate the figures in the paper. The data is stored in netcdf format with h5netcdf as engine for loading with xarray.
- data/raw is the unprocessed data extracted from the qcodes measurement databases and converted to xarray file format.
- data/processed is where intermediate analysis results are stored
- figures : All figures used in the manuscript.
- figures/.../img: The raw output (separate panels) of the figure generation code is stored in the img folder
- figure generation : All code to generate the figures in self-contained jupyter notebooks
- figure generation/lib: custom code used for analysis and plotting of the data
%I 4TU.ResearchData