Data and code underlying the publication "Single-shot parity readout of a minimal Kitaev chain"

This repository contains the datasets and code supporting the article <em>"Single-shot parity readout of a minimal Kitaev chain"</em>. It includes raw measurement data, analyzed results, theory simulations, and the Python code used to generate the figures in the manuscript. Information about data collection, datasets organization, and how to run the notebooks is available in the <code>README.txt</code> file. A minimal dataset (<code>datasets_figures.zip</code>) is provided to reproduce all plots without downloading the full raw data. <br>Analysis and plotting was performed using Jupyter notebooks. A minimal conda environment is provided in <code>env.yml</code>. To run the Jupyter notebooks:<br>1) Download Anaconda<br>2) Open a terminal window in the folder where you downloaded <code>env.yml</code> and run:<em>conda env create -f env.yml</em><br>3) Activate the newly created environment environment <em>conda activate pmm_readout</em><br>4) Start Jupyter Lab<em>jupyter lab</em><br>The plots in the manuscript can be generated running <code>pmm_readout_figures.ipynb</code>. To run the notebook, make sure that you download <code>datasets_figures.zip</code> , <code>DataOutput.zip</code> , <code>analysis.py</code>, <code>analysis_msft.py</code>, and <code>analysis_pmmqubit.py</code> in the same directory. The zip files should also be unzipped in the same directory. Installing the environment and running <code>pmm_readout_figures.ipynb</code> typically takes a few minutes.