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Add new case studies highlighting contributions to recent scientific discoveries

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python

调研方向

首先查看 numpy.org/case-studies/ 上现有的 NumPy 案例研究,以及 issue 中列出的候选研究参考资料。确定研究团队的联系人,并确认 NumPy 在每项发现中的作用,然后为每个选定的案例研究撰写约 7,000 个字符(附支持性引文),并发布扩展后的案例研究。

由索引模型根据 Issue 内容生成。

描述

sustain-2026

It would be great to expand the NumPy case studies with examples showing NumPy's role in some of the major scientific advances of the 2020s.

Potential case studies:
  • JWST – detection of carbon dioxide in an exoplanet atmosphere (WASP-39 b
    NumPy was used in the extraction, reduction, and analysis of JWST observations leading to the detection.
    References: https://www.nature.com/articles/s41586-022-05269-w

  • NANOGrav – evidence for a nanohertz gravitational-wave background
    NumPy is part of the scientific Python stack used to analyze pulsar timing data and search for the gravitational-wave signal.
    References: https://authors.library.caltech.edu/records/mrtaw-spj56)

  • FlyWire – complete adult fruit-fly brain connectome
    NumPy was used in analyses of a connectome containing more than 139,000 neurons and tens of millions of synapses.
    References: https://www.nature.com/articles/s41586-024-07968-y

  • AlphaFold – protein structure prediction
    AlphaFold uses NumPy within its data processing and inference stack. This could illustrate how NumPy supports modern computational biology and AI-driven scientific discovery.
    References: https://github.com/google-deepmind/alphafold/tree/main

  • Event Horizon Telescope – Sagittarius A*
    NumPy is used throughout EHT imaging software involved in reconstructing the first image of the black hole at the center of the Milky Way. This could serve as a follow-up to the existing M87 black-hole case study.
    References: https://github.com/eventhorizontelescope/2022-D02-02

Suggested next steps for each candidate:
  • Identify and connect with members of the research team who could provide quotes about NumPy’s role in the research and/or discovery.
  • Write a case study for numpy.org of ~7,000 characters.
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从这里开始

  1. 先读完整个 Issue,再读项目的贡献指南。
  2. 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
  3. Fork 仓库,在一个分支上完成修改。
  4. 提交 Pull Request,并在描述里引用这个 Issue 编号。

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