Cluster 2: Computation and Machine Learning: Physics, Big Data, and Our Understanding of the Universe

  

Instructors:

Dr. Albert Siryaporn, Physics and Astronomy, UCI

Dr. Luis Jauregui, Physics and Astronomy, UCI

Prerequisites: N/A

Course Description:

Students will embark on a captivating journey through the cutting-edge realm of modern physics. In recent years, the convergence of computing power, machine learning algorithms, and advanced measurement devices has sparked a revolutionary shift in our understanding of the universe. This course is designed to unravel the mysteries behind these breakthroughs and explore how recent technological developments have reshaped our perception of the cosmos and the fundamental nature of matter.

Students will dive into a dynamic curriculum that spans the fascinating domains of condensed matter physics, particle physics, biological physics, astronomy, and plasma physics. From the intricacies of quantum computing to the exploration of quantum materials, elementary neutrino particles, and the promising frontier of fusion energy, our course offers an immersive exploration of the interdisciplinary intersections between physics, chemistry, and biology.

Through stimulating classroom discussions and hands-on lab work, students will construct cutting-edge devices, collect real-world data, and analyze it using computation, machine learning, and the Python programming language. Analytical skills and a deep understanding of the scientific method will be developed as students evaluate the validity of their studies using statistical methods and critical thinking. The course is a gateway to valuable skill sets that will empower students in any STEM career path. Through this transformative course, students will be equipped with the knowledge and expertise to contribute meaningfully to the ever-evolving landscape of scientific discovery.

Projects: 

Students will build the fundamental components of a quantum computer, an ion thruster, a high-temperature superconductor, and a neutrino detector. Students will then take measurements using their devices, develop computational algorithms to analyze their data, and present their results. Students who are curious about physics but have not had significant exposure to the subject are encouraged to apply. Students with little programming experience or strong preparation in physics are welcome.