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Electron Heating in Kinetic-Alfvén-Wave Turbulence

Muni Zhou turned to MIT’s Plasma Science and Fusion Center’s dedicated partition on MIT’s Engaging Cluster housed at the MGHPCC to accomplish her highly demanding turbulent plasma computations.

The ability to keep a fusion-temperature plasma well confined is critical to the success of the fusion program. This is often impaired by turbulence and/or macroscopic instabilities.

Today Muni Zhou is a theoretical plasma physicist at Dartmouth University. Formerly, as a PhD student working with Nuno Loureiro in the Nonlinear Plasma Dynamics Group at PSFC at MIT, she turned to MIT’s Plasma Science and Fusion Center’s dedicated partition on MIT’s Engaging Cluster housed at the MGHPCC to accomplish her highly demanding turbulent plasma computations.

The Loreiro Group focuses on addressing these challenges using a powerful code called Viriato, which they developed. Viriato solves complex equations related to plasma behavior. In a recent paper, Zhou, Loureiro, and colleagues used Viriato to explore how electrons gain energy in turbulent environments through interactions with small-scale magnetic waves, known as Kinetic-Alfvén waves.

Muni Zhou
Assistant Professor, Department of Physics and Astronomy, Dartmouth University. Ph.D. Plasma Physics & Nuclear Science and Engineering (2022)

Research projects

The US ATLAS Northeast Tier 2 Center
Yale Budget Lab
Volcanic Eruptions Impact on Stratospheric Chemistry & Ozone
Towards a Whole Brain Cellular Atlas
Tornado Path Detection
The Kempner Institute - Unlocking Intelligence
The Institute for Experiential AI
Taming the Energy Appetite of AI Models
Surface Behavior
Studying Highly Efficient Biological Solar Energy Systems
Software for Unreliable Quantum Computers
Simulating Large Biomolecular Assemblies
Revolutionizing Materials Design with Computational Modeling
Quantum Computing in Renewable Energy Development
Pulling Back the Quantum Curtain on ‘Weyl Fermions’
New Insights on Binary Black Holes
Network Attached FPGAs in the OCT
Monte Carlo eXtreme (MCX) - a Physically-Accurate Photon Simulator
Modeling Hydrogels and Elastomers
Modeling Breast Cancer Spread
Impact of Marine Heatwaves on Coral Diversity
IceCube: Hunting Neutrinos
Global Consequences of Warming-Induced Arctic River Changes
Exact Gravitational Lensing by Rotating Black Holes
Evolution of Viral Infectious Disease
Evaluating Health Benefits of Stricter US Air Quality Standards
Ephemeral Stream Water Contributions to US Drainage Networks
Electron Heating in Kinetic-Alfvén-Wave Turbulence
Discovering Evolution’s Master Switches
Dexterous Robotic Hands
Developing Advanced Materials for a Sustainable Energy Future
Detecting Protein Concentrations in Assays
Denser Environments Cultivate Larger Galaxies
Deciphering Alzheimer's Disease
Dancing Frog Genomes
Asteroid Data Mining
Analyzing the Gut Microbiome
Adaptive Deep Learning Systems Towards Edge Intelligence
Accelerating Rendering Power
Computation + Machine Intelligence | Wu Tsai Institute
Computational Modeling of Biological Systems
Social Capital and Economic Mobility
MIT Brain and Cognitive Sciences
Building for Floods
Better Pathogen Targeting
Tracking Environmental Health Risks
AI for Cancer Diagnosis
Microplastic-Free by Design
Supporting Data-intensive Social Science
Sailing the Symbiosis Seascape
Wrangle Range Modeling
Shining a Light on Dark Matter
Grid Responsive Data Centers
Multifunctional 3D-Printed Materials
AI Pareidolia
Computing Hidden Health Threats from Heat
Staving off the Banana Apocalypse
CRISPR Mice, Smarter Science
Naval and Ocean Renewable Energy Hydrodynamics
AI That Speaks Human About Health
A Safer Way to See Inside Cells
How Monkeys - and Machines - See in 3D
FlowER: AI for Predicting Chemical Reactions
Supercomputers Reveal Ancient Atmospheric Battle
OSN - Open Storage Network
Massachusetts AI Hub
MGHPCC AI Computing Resource (AICR)
YARD: A Curation Workflow Tool
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