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.

本仓库包含支撑论文《最小基泰耶链的单次奇偶校验读出》(Single-shot parity readout of a minimal Kitaev chain)的数据集与代码。其涵盖原始测量数据、经分析的结果、理论模拟脚本，以及用于生成论文手稿中所有图表的Python代码。有关数据采集、数据集组织方式以及如何运行Jupyter Notebook的详细说明，请参阅<code>README.txt</code>文件。本仓库还提供了精简数据集（<code>datasets_figures.zip</code>），无需下载全部原始数据即可复现所有图表。<br>本研究的分析与绘图工作均通过Jupyter Notebook完成，配套的精简Conda环境配置文件为<code>env.yml</code>。若要运行这些Jupyter Notebook，请按以下步骤操作：<br>1. 下载Anaconda<br>2. 在存放<code>env.yml</code>的文件夹中打开终端窗口，执行命令：<em>conda env create -f env.yml</em><br>3. 激活新建的环境：<em>conda activate pmm_readout</em><br>4. 启动Jupyter Lab：<em>jupyter lab</em><br>可通过运行<code>pmm_readout_figures.ipynb</code>生成本论文手稿中的所有图表。若要运行该Notebook，请确保将<code>datasets_figures.zip</code>、<code>DataOutput.zip</code>、<code>analysis.py</code>、<code>analysis_msft.py</code>以及<code>analysis_pmmqubit.py</code>下载至同一目录下。同时需将上述压缩包解压至该目录中。配置环境并运行<code>pmm_readout_figures.ipynb</code>通常仅需数分钟即可完成。