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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Data and code for "Robust poor man's Majorana zero modes using Yu-Shiba-Rusinov states"

Authors: Zatelli, Francesco;

Data and code for "Robust poor man's Majorana zero modes using Yu-Shiba-Rusinov states"

Abstract

This folder contains the raw data and code used to generate the plots for the paper Robust poor man's Majorana zero modes using Yu-Shiba-Rusinov states. To run the Jupyter notebook, install Anaconda and execute: conda env create -f env.yml followed by: conda activate robust-pmm Finally, jupyter lab to launch the notebook. Raw data are stored in netCDF (.nc) format. The experimental datasets are exported by the data acquisition package QCoDeS and can be read as an xarray Dataset. Both the experimental and the numerical datasets were saved as netCDF files using xarray built-in function.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average