BicepMC Overview
An undergraduate research project focused on integrating observational data from the BICEP telescope with CosmoMC, a Fortran-based cosmological parameter estimation tool, and developing a custom implementation for analyzing cosmic microwave background (CMB) data.
Working under Professor Brian Keating at UCSD, this project involved deep diving into CosmoMC's Fortran codebase to enable integration with BICEP telescope data. The work included both utilizing the San Diego Supercomputer Center for large-scale simulations and developing a smaller custom implementation combining various CMB data sources.
Technical Implementation
Primary Components
- CosmoMC Integration: Modified Fortran codebase to accept BICEP telescope data formats
- Automation: Python scripts for batch processing and simulation management
- Custom Analysis: Mathematica implementation combining CAMB results with multiple data sources
Data Sources
- BICEP2 CMB measurements
- POLARBEAR telescope data
- Publicly available supernova data
- CAMB simulation results
Key Challenges
The project involved several technical challenges:
- Understanding and modifying complex Fortran codebase in CosmoMC
- Configuring and running large-scale simulations on the San Diego Supercomputer
- Processing and analyzing Markov Chain Monte Carlo (MCMC) data for cosmological parameter estimation
- Developing a simplified custom implementation that could integrate multiple data sources
Learning Outcomes
This undergraduate research experience provided valuable insights into:
- Advanced computational physics and cosmological parameter estimation
- High-performance computing and large-scale data analysis
- Integration of multiple data sources for scientific computing
- Working with legacy scientific codebases
Educational Impact
This project provided hands-on experience with real-world cosmological data analysis and high-performance computing applications in physics research.