Git Product home page Git Product logo

Hi there 👋 My name is Sophia!

I am an astronomer based in the US. My scientific research focuses on understanding the nebulae in galaxies both nearby and (sometimes very) far away using spectroscopy of light emitted in the UV, visible, and infrared. I also spend a lot of time developing code for various modeling and statistical analyses for my research. For more about me, check out my website.

Below are several repositories of code I've released publicly for various scientific applications. They include statistics ( FeldCous, KaplanMeier, histogram, kendall, LinRegConf ), modeling (OutLines, redneb), and combinations of the two (LyCsurv).

Highlighted Repository: OutLines

cartoon depicting observation of an outflow This code calculates model emission and absorption line profiles based on the physics of stellar winds and galactic outflows. The basic premise is illustrated with this (highly simplistic) cartoon where the yellow gas emits light and the orange gas emits _and_ absorbs light. All the gas is moving with some momentum based on how far away that gas is from the source of its momentum. The motion of the gas causes a _Doppler shift_ in the light absorbed or emitted by the gas, indicated by the color of the arrows (purple = blue-shifted, red = red-shifted, green = not shifted). As a result, the motion of the gas and the amount of gas at each Doppler shift produce a unique signature in the light we ultimately observe.

O VI profile

An example of the light we might see is the the O VI P Cygni feature in the far ultraviolet, as shown here, where the dips correspond to the absorbing gas (the orange region) and the spikes correspond to the emitting gas (yellow and orange regions). We see the spikes and dips together, which makes them combine to "cancel out" in some places but not others. My code models both the spikes and the dips in order to predict the total profile. Examples are included in the repository readme.





Quick Facts

  • 🔭 I am currently working on
    • multivariate and survival stats analysis (R and python)
    • statistical approaches to computer game event outcomes (C# and python)
  • 🌱 I am currently learning
    • database dev and management (and some SQL)
    • CSS, Javascript, and HTML for website dev
  • 💬 Ask me about: astronomy, statistics, galaxies, game dev
  • 😄 Pronouns: she/her
  • ⚡ Fun things I enjoy: 🎲 tabletop games, 🐈 cats, 📖 reading, 🎹 music, 🥖 baking bread

Sophia Flury's Projects

histogram icon histogram

Calculates histograms accounting for uncertainties using Poisson binomial statistics

kaplanmeier icon kaplanmeier

statistical assessments with the Kaplan-Meier survival function (lower/upper limits)

kendall icon kendall

Calculate non-parametric correlation coefficient Kendall's tau, accounting for censoring (upper/lower limits).

linregconf icon linregconf

Perform linear least squares regression, accounting for uncertainty, using linear algebra methods

lycsurv icon lycsurv

Predict LyC escape fraction from given predictors using the LzLCS to train Cox proportional hazards models

outlines icon outlines

Computes spectral line profiles arising from galactic outflows

redneb icon redneb

Calculate nebular extinction from hydrogen Balmer series emission lines, accounting for temperature and density of the gas.

vygrboi icon vygrboi

custom color palette for data science visualization

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.