particle physics, high-performance computing, programming, data analysis, modeling & simulation


Key Points:

  • Quantum Mechanics, Relativity, Standard Model of particle physics

  • Big Data manipulation, analysis and visualization

  • Monte Carlo Simulation tools

  • High Performance Cluster and Grid Computing

  • Quantum Computing​

Detailed Description:

FIRE Quantum Machine Learning introduces undergraduate students to data analysis using high-performance computing open-source data analysis framework . The datasets used are either collected by the detectors in proton-proton collisions at the Large Hadron Collider at CERN in Geneva, or  the particles coming from astrophysical sources such as supernova, gamma ray bursts, and black holes.


  • Data analysis for the Dark Matter searches 

  • Feasibility studies of simulated data to search extra dimensions and exotic particles

  • Quantum Computing circuit design and algorithms

  • Cluster and Grid Computing hardware and software


Key Points:

  • High energy particle physics aims at explaining the makeup of our universe in terms of fundamental forces and particles.

  • The current and future generations of experiments to discover these ​particles and forces require designing and building extremely complex accelerators and detectors. These experiments generate enormous amounts of data and need exceptional computing resources. More often than not, the needs of these experiments drive innovation in all the relevant fields including engineering, electronics, material science, and computing. 

Detailed Description:

Einstein said "The important thing is not to stop questioning. Curiosity has its own reason for existing. One cannot help but be in awe when he contemplates the mysteries of eternity, of life, of the marvelous structure of reality."


Experiments like the Large Hadron Collider at CERN  provide us  opportunity  to satisfy our curiosity about this marvelous nature of reality.  How this curiosity helps the society in general? Electron was discovered in an effort to understand the marvelous nature of reality, but today it is the key word in electronics and electricity. The World Wide Web was originally conceived and developed to meet the demand for information-sharing between scientists working at CERN from the institutes around the world.  The tens of thousands of accelerators around the world are not used for physics research but in the hospitals. 


Key Points:

  • Basic concepts in Quantum Mechanics, Relativity, and interactions of particles at the most fundamental level.

  • Big Data analysis and visualization using high-performance computing and machine learning,  C++, Python, and Shell scripts.

  • Monte Carlo Simulation computational tools to predict random events.

  • Markup and working of Computing Clusters and the World Wide LHC Computing Grid.

  • Combining concepts of Quantum Mechanics and Computing in Quantum-Computing.

  • How to be a part of large scientific collaborations and shine as an individual while being a good team player.

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