We aim to understand the phenomenology of plasma in the laboratory and in the cosmos. We use mathematical models and computer simulations to explain how plasmas move, interact with magnetic fields and boundaries, and evolve on various scales.
Working with collaborators in the U.S. and around the world, we advance fundamental physics concepts that guide experiments and project applications, such as the development of magnetic fusion energy.
This website offers information about our group members, research activities, and publications. We invite you to browse it and to contact us with any questions.
We're pleased that our recent Physical Review E publication on using machine learning to better understand turbulence density and viscosity was featured by UC San Diego News. This piece highlights the collaboration between our research group and the San Diego Supercomputer Center, which provides the immense processing power needed for these machine learning applications.
The Journal of Fluid Mechanics is organizing an interesting webinar series. We hope you'll take a look! (Note: Registration is required for first-time attendees.)
Interested in joining our Zoom seminars? Subscribe to our new email service, UCSD Plasma Physics Seminar Alerts.
Subscribe to Seminar Alerts to receive speaker announcements and Zoom meeting information by email. You can also view a list of recent speakers and recorded seminars.
We invite you to add this SoCal Plasma Zoom Calendar to your personal Google Calendar. (Note: All times shown are Pacific Time.)
A Unified Theory of Zonal Flow Shears and Density Corrugations in Drift Wave Turbulence
Rameswar Singh and P.H. Diamond
Plasma Phys. Control. Fusion 63, 035015, 2021; doi:10.1088/1361-6587/abd618
[download PDF]
Curvature of Radial Electric Field Aggravates Edge Magnetohydrodynamics Mode in Toroidally Confined Plasmas
Zhang, Y., Z.B. Guo and P.H. Diamond
Phys. Rev. Lett. 125(25), 255003, 2020; doi:10.1103/PhysRevLett.125.255003
[download PDF]
Understanding LOC/SOC Phenomenology in Tokamaks
Rice, J.E., J. Citrin, N.M. Cao, P.H. Diamond, M. Greenwald, and B.A. Gierson
Nucl. Fusion 60, 105011, 2020; doi:10.1088/1741-4326/abac4b
[download PDF]
Learning How Structures Form in Drift-Wave Turbulence
Heinonen, R. and P.H. Diamond
Plasma Phys. Control. Fusion 62(10), 105017, 2020; doi:10.1088/1361-6587/abad02
[download PDF]
A Reduced Model for Edge Localized Mode Control by Supersonic Molecular Beam Injection and Pellet Injection
Rhee, T., J.-M. Kwon, and P.H. Diamond
Phys. Plasmas 27, 072503, 2020; doi:10.1063/5.0009583
[download PDF]
Turbulence Model Reduction by Deep Learning
Heinonen, R.A. and P.H. Diamond
Phys. Rev. E, 061201(R), 2020; doi:10.1103/PhysRevE.101.061201
[download PDF]
We develop theory related to plasma and fusion science, including:
Our work is primarily funded by the Office of Fusion Energy Sciences of the U.S. Department of Energy (Grant No. DE-FG02-04ER54738).