SUMMARY
This discussion centers on the challenges faced by an undergraduate physics major seeking to undertake a Big Data analytics project related to quantum mechanics or particle physics. The student inquires about the availability of training data, specifically from the Large Hadron Collider (LHC), which is noted for its proprietary nature and massive data volume of approximately 30 petabytes. The conversation highlights the difficulty in accessing public datasets and the need for guidance on how to locate alternative open data sources in the field of physics.
PREREQUISITES
- Understanding of Big Data analytics concepts
- Familiarity with quantum mechanics and particle physics
- Knowledge of data sourcing and management
- Basic skills in data analysis tools such as Python or R
NEXT STEPS
- Research open data repositories in physics, such as CERN Open Data
- Explore data analysis techniques specific to particle physics
- Learn about data visualization tools for scientific data
- Investigate collaborative projects or internships in Big Data within physics
USEFUL FOR
Undergraduate physics majors, data analysts in scientific fields, and anyone interested in applying Big Data techniques to quantum mechanics and particle physics research.