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Comparing Experimental Results with Numerical Simulations of Ultra-High-Intensity Laser-Plasma Interactions

This article discusses the comparison of experimental results with fully-relativistic, three-dimensional numerical simulations of ultra-high-intensity laser-plasma interactions. It explores the characteristics of peak laser intensity and the generation of radiation across the spectrum, as well as applications such as non-destructive testing, radiography, lithography, micro-machining, ultrafast reactions, and metrology. The article also examines the collimation of the laser beam and electrons, the acceleration of electrons with laser wakefield plasma waves, and the prediction of monoenergetic electrons. It concludes by discussing the computing power required for modeling these interactions and the technological convergence of laser and computer power.

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Comparing Experimental Results with Numerical Simulations of Ultra-High-Intensity Laser-Plasma Interactions

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  1. Ultra-High-Intensity Laser-Plasma Interactions: Comparing Experimental Results with Three-Dimensional,Fully-Relativistic, Numerical Simultations Donald Umstadter Scott Sepke

  2. “Moore’s Law” for Peak Laser Intensity

  3. Characteristics Femtosecond Tunable Collimated Synchronized Bench-top Bright Micron source Type THz Infrared X-rays Electrons Positrons Protons Neutrons Intense optical laser light can generate radiation across the entire spectrum • Applications • Non-destructive testing • Radiography • Lithography • Micro-machining • Ultrafast reactions • Metrology

  4. Relativistic self-channeling leads to collimation of the laser beam, which leads to collimation of the electrons. tlaser= 30 fs D ~ 0.25o tlaser= 400 fs D = 1° Beam divergence found to be reduced with increasing laser intensity Plaser=30 TW E = 180 MeV r= 1010 e- LANEX

  5. Laser wakefield plasma waves can accelerate electons to energy 100 MeV in a single millimeter F~I Emaxatt~p/p tl

  6. “Monoenergetic” electrons with energy exceeding 150 MeV experimental result PIC code prediction • J. Faure et al., Nature 431, 541 (2004) • C.G. R. Geddes et al., Nature 431, 538 (2004) • S.P.D Mangles et al., Nature 431, 535 (2004)

  7. Maxwell’s Equations E,B Fields (r, J) Equation of Motion Particle-in-Cell Laser-Plasma Simulations • An exact field and particle motion solver. • LSP is a hybrid fluid/particle-in-cell code: • Models include plasmas, lasers, ionization, particle beams, QMD equations of state, TE and TM modes… • Allows migration between fluid and kinetic solvers. • Uses explicit and stable implicit particle and field solvers.

  8. PrairieFire Beowulf Cluster 256 2.2 GHz Opteron (64-bit) processors 128 nodes each containing 4 GB of RAM Plasma wave Plasma “bubble” 30fs laser pulse Self-injected electrons LSP Particle-in-Cell Simulations • Fully relativistic 1,2,3D Cartesian and cylindrical geometry • Self-consistent laser-plasma interactions Longitudinal Electric Field Average Velocity

  9. UNL soon to have a laser with peak power-rate of 1 PW-Hz, highest of any in the US 1 Peak Power Rate (PW-Hz) 30-fs pulse duration 3-J energy per pulse 100-TW peak power 10-Hz repetition rate

  10. Diffraction limited laser focusing requires exact-field solutions • Electron deflection experiment/simulations show that accurate laser fields are essential. • We have derived exact solutions for arbitrary, focused Gaussian and super-Gaussian laser profiles. • These models are complex and must be solved numerically.

  11. Concluding Remarks • High-intensity laser-plasma interactions (including laser accelerators) is one of few physical systems in plasma physics (which is a many-many-body problem) that can be numerically modeled with reasonable accuracy. • The computing power required for 3-D modeling was reached only in the last decade. • The availability of greater computing power will enable simulations with larger domains and longer durations, which can more accurately model larger interaction regions and higher plasma densities. • The simultaneous rapid increases in laser and computer power are good example of technological convergence.

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