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Simulating the Gamma Ray Sky

Simulating the Gamma Ray Sky. Andrew McLeod SASS August 12, 2009. Astrophysics. Measurable Quantities Particle Flux from a given region of the sky Particle Energies (binned). Astrophysics. EGRET gamma ray sky, > 100 MeV.

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Simulating the Gamma Ray Sky

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  1. Simulating the Gamma Ray Sky Andrew McLeod SASS August 12, 2009

  2. Astrophysics Measurable Quantities • Particle Flux from a given region of the sky • Particle Energies (binned)

  3. Astrophysics EGRET gamma ray sky, > 100 MeV “Modeling of the Galactic diffuse continuum gamma-ray emission”, Igor V. Moskalenko Source: http://galprop.stanford.edu/web_galprop/galprop_manual/manual2.html

  4. GALPROP • Simulates the gamma ray and cosmic ray sky given a set of initial conditions and physical parameters • Allows a priori predictions to be compared to astronomical data

  5. GALPROP Method Generates a field of cosmic rays given a cosmic ray source distribution (SNR, pulsars) by solving the transport equation:

  6. GALPROP Method Computes the interaction of these cosmic rays with the interstellar medium and radiation field • Gas model based on 21-cm (atomic H) and CO (H2) surveys • 3-D or 2-D options; 2-D models have radial symmetry and model gas in 17 concentric rings

  7. “Propagation of cosmic rays: nuclear physics in cosmic ray studies”, Igor V. Moskalenko Source: http://galprop.stanford.edu/web_galprop/galprop_manual/manual2.html GALPROP

  8. GALPROP Method The contribution of these processes (and others) to the gamma ray spectrum are calculated as a function of radial distance

  9. GALPROP Output • Cosmic ray spectra • Bremsstrahlung gamma ray spectrum • Neutral Pion Decay gamma ray spectrum • Inverse-Compton Scattering gamma ray spectrum All output in FITS format, as a function of radius (or gas ring) and energy

  10. GALPROP Predicted gamma ray sky from Bremsstrahlung (gas ring 13)

  11. GALPROP Predicted gamma ray sky from Neutral Pion Decay (gas ring 13)

  12. GALPROP

  13. GaDGET • Optimizes GALPROP models to best-fit observed gamma ray sky (Fermi data) • Fit-weights are computed for each component’s energy bins • Indicates how GALPROP models can be improved

  14. GaDGET Method • Sums over gamma ray contribution of inner, local, and outer galaxy (relative to earth, ~8.5 kpc) • Assigns re-normalizing fit-weights to each region in incremental energy bins

  15. GaDGET For resulting fit-weight adjusted sky-maps • Produces residual sky-maps • Calculates likelihood of model being correct

  16. GaDGET Residual Map, normalized to 1σ

  17. GaDGET

  18. Optimization GALPROP parameters can be varied • Galactic Dimensions • Cosmic Ray Injection Spectra • Source Distribution • Diffusion Coefficient ~ 40 dimensional parameter space

  19. Optimization Propagation processes can be altered • Reacceleration • Convection

  20. Optimization With a full year of Fermi data, models can now be refined with an unprecedented level of precision

  21. Potential Applications • Indirect determination of Milky Way parameters • Better understand the processes by which cosmic rays propagate • Study extragalactic gamma ray spectrum

  22. Works Cited • Moskalenko, Igor. “Modeling of the Galactic diffuse continuum gamma-ray emission” 6th INTEGRAL Workshop, Moscow, Russia. 2006. • Moskalenko, Igor. “Propagation of Cosmic Rays and Diffuse Galactic Gamma Rays” Nuclear Data for Science and Technology, Santa Fe, New Mexico. 2004. • Strong, Andrew. “GALPROP: a Cosmic-ray propagation and Gamma-ray code” Tools for SUSY, Annecy, France. 2006.

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