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    24 repositories

    • computing

      Public
      Documentation for using KIPAC's computing and storage allocations at SLAC and Stanford
      5•4•0•0•Updated Mar 6, 2026Mar 6, 2026

    • Physics79L

      Public
      Jupyter Notebook
      •
      GNU General Public License v3.0
      •18•3•0•0•Updated Mar 6, 2026Mar 6, 2026

    • c2i2o

      Public
      Cosmologies to Intermediates to Obserables and Back Again
      Python
      •
      MIT License
      •0•0•0•0•Updated Jan 23, 2026Jan 23, 2026

    • CDFVI

      Public
      Comoving Distance Fitting, Visualization and Inference
      Python
      •
      MIT License
      •0•0•0•0•Updated Nov 2, 2025Nov 2, 2025

    • HPMCM

      Public
      Hierarchical Pixel-based Multi-Catalog Matcher
      Python
      •
      MIT License
      •0•1•0•0•Updated Nov 1, 2025Nov 1, 2025

    • MACSS

      Public
      Materials for Mexican Astro Cosmo Statisitics School
      Jupyter Notebook
      •
      MIT License
      •0•2•0•0•Updated Oct 3, 2025Oct 3, 2025

    • NWayMatch

      Public
      Jupyter Notebook
      •
      BSD 3-Clause "New" or "Revised" License
      •0•1•0•0•Updated Sep 12, 2025Sep 12, 2025

    • RubinDXDay

      Public
      Repository for notebooks KIPAC members produced to explore Rubin data.
      Jupyter Notebook
      •3•0•0•1•Updated Jul 11, 2025Jul 11, 2025

    • Rubin

      Public
      Materials for people working on Rubin observatory and Rubin-related science projects at KIPAC
      CSS
      •
      MIT License
      •0•1•0•0•Updated Jul 11, 2025Jul 11, 2025

    • ObservationalAstro

      Public
      Course materials and schedule for Physics 100: Introduction to Observational Astrophysics
      Jupyter Notebook
      •0•1•0•0•Updated May 27, 2025May 27, 2025

    • 360

      Public
      Jupyter Notebook
      •
      BSD 2-Clause "Simplified" License
      •0•0•0•0•Updated Feb 9, 2025Feb 9, 2025

    • StatisticalMethods

      Public
      Course notes and resources for Stanford University graduate course PHYS366: Statistical Methods in Astrophysics
      astrophysicsstatistical-methodologies
      astrophysicsstatistical-methodologies
      Jupyter Notebook
      •
      Other
      •83•123•0•0•Updated Nov 16, 2024Nov 16, 2024

    • NBToPackage

      Public
      Resources for an active learning session about converting a notebook to a software package.
      Jupyter Notebook
      •
      GNU General Public License v3.0
      •0•3•0•0•Updated Aug 2, 2022Aug 2, 2022

    • bolo-calc

      Public
      Python
      •
      BSD 3-Clause "New" or "Revised" License
      •2•4•8•0•Updated May 26, 2022May 26, 2022

    • BootCamp

      Public
      Annual computing Boot Camp for new (and other) KIPAC members
      Jupyter Notebook
      •
      Other
      •34•18•8•0•Updated Jul 7, 2021Jul 7, 2021

    • physics367_spring2021

      Public
      Course repository for Physics 367: Special Topics in Astrophysics, Structure Formation and Galaxy Formation
      GNU General Public License v3.0
      •0•0•0•0•Updated Mar 30, 2021Mar 30, 2021

    • cfgmdl

      Public
      Configuration parsing and model build tools
      Python
      •
      BSD 3-Clause "New" or "Revised" License
      •1•0•0•0•Updated Mar 3, 2021Mar 3, 2021

    • kipac_package_template

      Public template
      Python
      •
      BSD 3-Clause "New" or "Revised" License
      •0•0•0•0•Updated Feb 16, 2021Feb 16, 2021

    • StatisticsCookbook

      Public
      Short introductory lessons on statistical data analysis
      Jupyter Notebook
      •
      Other
      •3•3•0•0•Updated Jan 24, 2021Jan 24, 2021

    • nuXgal

      Public
      Analysis code for studying cross corellations between neturino events and galaxy samples.
      Python
      •
      GNU General Public License v2.0
      •3•1•0•0•Updated Feb 15, 2020Feb 15, 2020

    • CMBLensing

      Public
      Website and other materials for the KIPAC CMB Lensing Workshop
      CSS
      •
      Other
      •0•1•0•0•Updated Jan 17, 2018Jan 17, 2018

    • Blinding

      Public
      Do cosmological inferences need to be done blindly, in order to avoid unconscious concordance bias? And if so, how are we going to achieve this?
      0•1•0•0•Updated Apr 11, 2017Apr 11, 2017

    • Answers

      Public
      Responses to questions asked by members of the public, for pasting into the KIPAC blog.
      HTML
      •
      MIT License
      •0•0•7•1•Updated Oct 25, 2016Oct 25, 2016

    • PublicationList

      Public
      Python and LaTeX code for preparing KIPAC's annual publication list
      Jupyter Notebook
      •
      MIT License
      •1•0•0•0•Updated Sep 17, 2016Sep 17, 2016
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