The IBEX Bayesian Inverse Problem

Code solving the Bayesian inverse problem for satellite data collected by the Interstellar Boundary Explorer (IBEX) and output from a computer model attempting to represent the rate at which energetic neutral atoms (ENA) are generated throughout the heliosphere. The goal is to estimate the posterior distributions of the input parameter to the computer simulation, given observed data from the IBEX satellite.

Descriptions of directories and files contained in the top-level directory are below.

Directories

• data: contains IBEX satellite data, computer model simulation output, and synthetic satellite data for testing purposes provided in this dataset
• papers: includes any content necessary to compile the manuscript along with R scripts for toy examples and figure generation
• presentations: code used to produce figures and documents for conference presentations
• tests: various bash, Python, and R scripts conducting tests to evaluate the performance and functionality of our proposed Poisson Bayesian inverse problem framework

Files

• pois_bayes_inv.R: contains the function that implements the proposed Poisson Bayesian inverse problem framework. Requires computer model input/output and field observations
• mcmc.R: support functions for our Markov chain Monte Carlo (MCMC), including proposals and likelihood evaluations
• helper.R: contains functions that aid in the processing of IBEX satellite and simulator data, particulary in preparation for running our Bayesian inverse problem method
• check.R: input validation functions
• vecchia_scaled.R: original implementation of the Scaled Vecchia GP approximation for use as a surrogate model of the IBEX simulator. Original code found here: https://github.com/katzfuss-group/scaledVecchia

Dependencies

• Code relies on the following R packages: R.utils, Tmvtnorm, GPvecchia, GpGp, laGP, deepgp, ggplot2, lhs, plgp, MASS, coda, ks, mvtnorm, gridExtra, dplyr, doParallel, parallel, scoringRules
• All packages are available to install via CRAN
• To install all packages in one shot, run Rscript dependencies.R

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Copyright 2023 for O4646

This program is Open-Source under the BSD-3 License.

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