Jacob Trier Frederiksen, Niels Bohr Institute, Copenhagen, DK

Transcription

1 Jacob Trier Frederiksen, Niels Bohr Institute, Copenhagen, DK

2 Computational Astrophysics group Niels Bohr Institute Computational power History Present state at the Niels Bohr Institute Prospects Plasma Modeling Conventional Particle-in-cell codes New improved PhotonPlasma code Two Examples Gamma-ray bursts: stochastic wakefield processes Test bench: microwave continuum emission from UHECR extensive air shower plasmas Summary and discussion What is the role of computational physics? What is the role of laboratory astrophysics? How can we couple these paradigms is it one-way or two-way?

3 ANDERS LAGERFJÄRD KLAUS GALSGAARD ÅKE NORDLUND BERTIL FABRICIUS DORCH JACOB TRIER FREDERIKSEN LINK

4 Computational capabilities NBI) Tera Peta Moore s Law? Giga Niels Bohr Institute: Tera-scale computing, pushing today Giga-scale computing, 5 years ago

5 Computational capabilities tomorrow Gigabit nationwide scientific networking in Denmark Within 1-2 years we are likely to have 10+ Gbit dedicated bandwidth between centers GRID computing across centers feasible Jump factor 2 to 5 in computational domain size Tera-scale computing is almost standard Peta-scale likely on ~ 10 year horizon

6 Capabilities summary Example: our PIC codes 5 years ago: Grid ~ 10 8 Particles ~ 10 8 Integration time ~ 10 4 ω -1 Today: Grid ~ 10 9 Particles ~ Integration time ~ 10 5 ω -1 Much better physics included at no (low) cost! Tomorrow: Multiply one dimension by factor 10 (2-5 years) Multiply two dimensions by a factor 10 (~10 years)

7 Brute force intractable? -- Still quite far from realistic plasma simulations > 10 orders of magnitude in phase space resolution Avogadro s number plasma simulation in 50 years or so... + Better: at relatively low cost instead Particle numbers are growing fast (automatically) Particle resolution Grid resolution gives flexibility Macro-particles may handle highly refined physics + Multi-core CPUs reconcile some immediate memory issues, but: + Performance increase: further parallelisation (MPI+OMP)

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9 A Conventional PIC code model TSC scheme fullly staggered Optimized algorithms OMP parallelized Improvement; make particles carry continuous weights

10 Frederiksen et al.: Sub-grid <=> detailed N-body collisions

11 T. Haugboelle: Select particles for scattering from physics conditions in cell Split particles according to microphysical cross sections 1 2

12 Examples of conventional PIC code projects GRB Afterglow shocks, magnetic field generation and part. accel. Electromagnetic turbulence in relativistic two-streams Radiation spectral synthesis from PIC plasmas Current sheets in driven PIC plasmas New PhotonPlasma PIC code projects GRB prompt emission stochastic wakefield processes Possible future applications & tests UHECR extensive air shower detection & reconstruction Anything project thinkable...

13 Rapid variation? Slow variation? non-thermal quasi-thermal / hybrid

14 Felix Ryde & M. Battelino KTH, Stockholm

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17 J. T. Frederiksen: Thesis defense, Jacob Trier Frederiksen, April 28 th, 2008

18 Ultra-high Energy Cosmic Rays?!?

19 Gorham et al.:

20 Hawaii

21 Simple atmosphere (multi-species neutral gas) Collisional ionization (detailed balance) Plasma emission effects (PIC + synth spectra) Particle prod., decay, scattering (Monte Carlo) All of these can (will) be included Microwave emission from plasmas (both UHECRs and Lab-tests) simple and direct PIC code validation

22 Synthetic spectra from turbulent plasmas Inexpensive & multiple observers Logarithmic frequency scale => very broadband Pair processes (γ + γ e - + e + ); in progress...

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24 Laboratory astrophysics would lend numerical astrophysics a helping hand by giving us: Scale-transistion experiments!!! sub-debye plasma MHD fluid HD Optically thin collisionless turbulent shocked radiating plasmas Very hot and tenuous plasmas Clean measurements of radiation spectra... but most of this is likely intractable, so we will have to assess the scenery more carefully:

25 C1: Assess relevance of a existing laboratory experiments to astrophysical phenomena. difficult Reversely; devise and build experiments relevant to a given astrophysical phenomenon. expensive C2: Validate of computer models against laboratory experiment. easier Scaling computational plasmas to astrophysical objects / dynamics. hard, but desirable!

26 Improved modeling of plasma phenomena in industrial applications: ITER, space craft charging, nano-scale semiconductor devices, etc. e.g. Space physics could benefit too; DTU/Space is doing PIC-MCC sprites these days (Chanrion & Neubert, 2008)