Emilys Galactic Gits

mapping.cpp - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2026-04-02T18:26:31+00:00

Mapping.cpp: Domain Mapping and XAD-enabled Multiphysics Solver mapping.cpp A C++ MFEM-based module implementing a DomainMapper to map reference coordinates to a deformed physical domain, plus a suite of mapped coefficients, nonlinear integrators, and gravity/multiphysics solvers with an EOS via XAD autodiff. It handles domain decomposition (stellar/core/envelope/vacuum), quadrupole moments, gravitational potential, and includes a test harness and CLI-driven entry point.

diffusion.py - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2026-04-02T18:23:31+00:00

FiPy 1D Diffusion Solver for Stellar Species Abundances diffusion.py A Python script using the FiPy finite-volume PDE solver to model one-dimensional diffusion of chemical species on a mass grid. It defines a 1D mesh, initializes abundances for H1 and He4, computes a diffusion coefficient, and solves a diffusion equation with operator splitting, while optionally visualizing the evolving abundances via matplotlib animation. Includes a dummy diffusion function and notes about mass conservation a…

investigatemesabrowndwarfmodel.ipynb - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-05-20T19:52:40+00:00

Analyzing Brown Dwarf Models with MESA Data in Python InvestigateMESABrownDwarfModel.ipynb This file appears to be a Jupyter notebook (.ipynb) focused on analyzing brown dwarf models using data processed through the Modules for Experiments in Stellar Astrophysics (MESA). It includes Python code to import necessary libraries (matplotlib for plotting, numpy for numerical calculations, mesa_reader for reading MESA data, pandas for data manipulation), define a function to parse MESA model files, l…

output_3_1.png - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-05-20T19:52:32+00:00

actionspacedensity.ipynb - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-05-15T15:32:36+00:00

Analyzing Space Density and Cluster Membership in Astrophysical Data ActionSpaceDensity.ipynb This Jupyter notebook contains a comprehensive workflow for analyzing space density and determining cluster membership in astrophysical data, primarily focusing on the properties and movements within galaxies. The notebook starts by importing necessary libraries for data manipulation, statistical analysis, and visualization, including pandas, matplotlib, scipy, and scikit-image. It then defines severa…

output_16_1.png - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-05-15T15:32:27+00:00

output_14_0.png - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-05-15T15:32:26+00:00

output_12_2.png - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-05-15T15:32:25+00:00

output_11_1.png - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-05-15T15:32:25+00:00

output_9_1.png - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-05-15T15:32:24+00:00

fetchlinks.ipynb - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-05-15T15:32:05+00:00

Fetching and Downloading .tar.gz Files in Python fetchLinks.ipynb This Python Notebook ('fetchLinks.ipynb') outlines a process for fetching URLs from a specified website, filtering them to find specific .tar.gz archive links, downloading these archives, and then listing downloaded directories matching a certain pattern. It uses libraries such as BeautifulSoup for parsing

voxel.ipynb - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-03-04T14:29:07+00:00

Voxel Modeling in Python voxel.ipynb This Jupyter Notebook explores voxel-based simulations for physical systems. It discusses optimizing voxel tessellation algorithms, including the considerations for using cubic or truncated octahedral voxel shapes. It also entails practical implementation of these concepts in Python, utilizing numpy and matplotlib for operations like defining 3D kernels for neighbor interactions in voxel grids, computing temperature differences for a modeled sphere, and vis…

rudmodel.ipynb - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-03-04T14:28:44+00:00

Modeling Brown Dwarf Evolution Influenced by Close M-dwarf Companion RudModel.ipynb This Jupyter notebook outlines a model to simulate the evolution of a brown dwarf when influenced by a close M-dwarf companion. The model includes importing necessary libraries such as numpy, scipy, and matplotlib for numerical computations and plotting, along with a specific library for astronomical simulations. It details the initialization of constants like solar luminosity, radius, and mass, alongside brown…

output_28_1.png - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-03-04T14:28:30+00:00

output_25_1.png - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-03-04T14:28:29+00:00

output_22_1.png - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-03-04T14:28:29+00:00

output_19_1.png - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-03-04T14:28:28+00:00

bestfitresultanalysis.ipynb - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-02-23T18:09:24+00:00

Analysis of Best Fit Results in Astronomical Data BestFitResultAnalysis.ipynb This Jupyter notebook titled 'BestFitResultAnalysis.ipynb' is designed for analyzing and visualizing the best fit results obtained from astronomical photometric data. It involves loading photometry data and fit results, performing corrections and interpolations on isochrones, evaluating conditions for best fits, and plotting the corrected isochrones against the photometry data to identify best fitting models of stell…

output_24_0.png - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-02-23T18:09:08+00:00

output_19_0.png - created

tboudreaux (tboudreaux@undisclosed.example.com) — 2024-02-23T18:09:07+00:00