1 / 9

Modeling and Characterization of Soliton Trains in an Electron Beam

Modeling and Characterization of Soliton Trains in an Electron Beam. Jared Ginsberg With Brian Beaudoin.

shay
Télécharger la présentation

Modeling and Characterization of Soliton Trains in an Electron Beam

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Modeling and Characterization of Soliton Trains in an Electron Beam Jared Ginsberg With Brian Beaudoin

  2. “…The mass of water in the channel… accumulated round the prow of the vessel… then suddenly leaving it behind, rolled forward with great velocity, assuming the form of a large solitary elevation… Such, in the month of August 1834, was my first chance interview with that singular and beautiful phenomenon..” - John Scott Russell The earliest observed solitons were found as water waves Video credit goes to youtube user Christophe FINOT

  3. Nonlinear and Dispersive Effects The initial wave steepens due to nonlinearity. The wave also widens and separates due to dispersion. When balanced these two effects can exactly cancel, yielding a soliton. Image courtesy of Yichao Mo

  4. Experimental Setup for Launching Velocity Perturbations Perturbation at beam tail UMER Beam head Perturbations from Induction Cell 30 cm initial perturbation width Beam Velocity = 5.85 x 107m/s (.2c) Machine Circumference = 11.52 m Circulation Time = 197 ns

  5. What’s so great about a model? • Confirm your choice of equation (KdV!) • Direct control over more parameters • Faster and more portable • Red: computer modeled • Blue: experimental data The Math and The Model Kortewegde-Vries (KdV) nonlinearity dispersion • μ dictates the dispersion strength • Determining ε is a major challenge

  6. Agreement Between Model and Experiment Positive Dispersion ε= 5.85 x 107= beam velocity μ = +42 t = 9 x 197 ns Data with minimal current loss Current (amps) Position (meters) Data with considerable current loss Current (amps)

  7. Agreement Between Model and Experiment Negative Dispersion ε= 5.85 x 107= beam velocity μ = - 42 t = 9 x 197 ns Current (amps) Data with minimal current loss A negative dispersion in the model can then be used to model negative perturbations to the beam that are done in the experiment. Position (meters)

  8. Sub-Pulse Spacing (Future Work) Sub-pulse Spacing vs. Dispersive Coefficient Sub-pulse Spacing vs. Dispersive Coefficient Peak-to-peak Space in meters Peak-to-peak Space in meters Dispersive Coefficient Dispersive Coefficient

  9. Acknowledgements • Brian Beaudoin • Kathryn Tracey, Michelle Girvan, Thomas Murphy, SonaliShukla and the rest of TREND • National Science Foundation

More Related