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sflury/README.md

Hi there 👋 My name is Sophia!

I am an astronomer from the US and based in the UK. 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, towrecan, LinRegConf ), modeling ( OutLines, RedNeb, LymanTrans ), 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 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
    • object-oriented user-friendly modeling of spectral lines (python)
    • multivariate and survival stats analysis (R and python)
    • statistical approaches to computer game event outcomes (C# and python)
    • python package design and optimization
  • 🌱 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

Pinned Loading

  1. FeldCous FeldCous Public

    Statistics for low-count signals

    Python

  2. kendall kendall Public

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

    Python 1 1

  3. OutLines OutLines Public

    Computes spectral line profiles arising from astrophysical winds

    Jupyter Notebook 5 1

  4. RedNeb RedNeb Public

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

    Python 1

  5. LyCsurv LyCsurv Public

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

    Python

  6. KaplanMeier KaplanMeier Public

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

    Python