Alexander Velberg - Data-driven discovery of sub-grid models for collisionless magnetic reconnection
Recorded 17 April 2026. Alexander Velberg of the Massachusetts Institute of Technology presents "Data-driven discovery of sub-grid models for collisionless magnetic reconnection" at IPAM's Learning Models from Data for Multi-Fidelity Fusion Plasma Physics Workshop.Abstract: Capturing the global effects of collisionless magnetic reconnection is a key challenge for modeling a variety of multi-scale laboratory and astrophysical plasma systems. In this work, we present a data-driven, machine learning approach to spatial sub-grid closure discovery and apply it to data from simulations of coalescing magnetic islands. The discovered closures capture the effects of collisionless reconnection on the large, magneto-hydrodynamic scale structures supplying the flux, enabling an accurate description of the timescale and rate of reconnection on a coarsened grid. Despite the opaque nature of the neural networks we use here, systematic application of constraints on the information available during training reveals that accurate closures require local gradients of the magnetic fields and flows. Finally, we investigate the relationship between these closures and a simple anomalous resistivity and viscosity, finding that our sub-grid closure for Ohm’s law is accurately represented by an anomalous hyper-resistivity at the reconnection X-point. Away from this point and in the case of viscosity, the additional complexity offered by the machine learned closures leads to significantly better performance.
Learn more online at: https://www.ipam.ucla.edu/programs/workshops/workshop-ii-learning-models-from-data-for-multi-fidelity-fusion-plasma-physics/ Receive SMS online on sms24.me
TubeReader video aggregator is a website that collects and organizes online videos from the YouTube source. Video aggregation is done for different purposes, and TubeReader take different approaches to achieve their purpose.
Our try to collect videos of high quality or interest for visitors to view; the collection may be made by editors or may be based on community votes.
Another method is to base the collection on those videos most viewed, either at the aggregator site or at various popular video hosting sites.
TubeReader site exists to allow users to collect their own sets of videos, for personal use as well as for browsing and viewing by others; TubeReader can develop online communities around video sharing.
Our site allow users to create a personalized video playlist, for personal use as well as for browsing and viewing by others.
@YouTubeReaderBot allows you to subscribe to Youtube channels.
By using @YouTubeReaderBot Bot you agree with YouTube Terms of Service.
Use the @YouTubeReaderBot telegram bot to be the first to be notified when new videos are released on your favorite channels.
Look for new videos or channels and share them with your friends.
You can start using our bot from this video, subscribe now to Alexander Velberg - Data-driven discovery of sub-grid models for collisionless magnetic reconnection
What is YouTube?
YouTube is a free video sharing website that makes it easy to watch online videos. You can even create and upload your own videos to share with others. Originally created in 2005, YouTube is now one of the most popular sites on the Web, with visitors watching around 6 billion hours of video every month.
