Data and code underlying the publication "Single-shot parity readout of a minimal Kitaev chain"
DOI: 10.4121/227fd419-fded-4a96-ab62-421a0cd57fa5
Datacite citation style
Dataset
Licence CC BY 4.0
Interoperability
This repository contains the datasets and code supporting the article "Single-shot parity readout of a minimal Kitaev chain". 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 README.txt file. A minimal dataset (datasets_figures.zip) is provided to reproduce all plots without downloading the full raw data.
Analysis and plotting was performed using Jupyter notebooks. A minimal conda environment is provided in env.yml. To run the Jupyter notebooks:
1) Download Anaconda
2) Open a terminal window in the folder where you downloaded env.yml and run:
conda env create -f env.yml
3) Activate the newly created environment environment
conda activate pmm_readout
4) Start Jupyter Lab
jupyter lab
The plots in the manuscript can be generated running pmm_readout_figures.ipynb. To run the notebook, make sure that you download datasets_figures.zip , DataOutput.zip , and analysis.py in the same directory. The zip files should also be unzipped in the same directory. Installing the environment and running pmm_readout_figures.ipynb typically takes a few minutes.
History
- 2025-07-02 first online
- 2025-07-03 published, posted
Publisher
4TU.ResearchDataFormat
scripts/.py, notebooks/.ipynb, datasets/.nc, figures/.pdfOrganizations
QuTech, Delft University of TechnologyKavli Institute of Nanoscience, Delft University of Technology
DATA
Files (11)
- 5,629 bytesMD5:
13039ed5b44b06889b5cb44a9fd114b6README.txt - 60,596 bytesMD5:
c27a7f815e11689747392c46e8b27dc1analysis.py - 16,480,735,812 bytesMD5:
bd5494b44ae378a1deea8a31f9852f9aanalyzed_timetraces.zip - 3,309,616 bytesMD5:
35534b3f3d007b47ab7caca89dd08132DataOutput.zip - 101,628,214 bytesMD5:
433a1b9c66b02878826fb4896e89237fdatasets_figures.zip - 361 bytesMD5:
bb467579fc5bf3af54da462d815349ceenv.yml - 1,798,321 bytesMD5:
64f0981233151178bef5caa2e4632c69output_figures.zip - 199,947 bytesMD5:
3326a775ed1b7f1b19a875a7c5afb9e8pmm_readout_figures.ipynb - 140,961,828,251 bytesMD5:
2524f8412e555d6ff87e89090c77b407raw_data.zip - 23,702 bytesMD5:
39b90fc5ff5bdeee0a44885cc7fcb055theory.ipynb - 40,715 bytesMD5:
3805eedf0778a13a3d415424234a6bfctimetraces_analysis.ipynb -
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