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Flasher reconstruction at LBNL

Flasher reconstruction at LBNL. Dima Chirkin. Photon detection. muon track:. flasher/cascade:. t=t 0 +|z-z 0 |/c. Residual time description. Pandel log likelihood. Pandel log likelihood. Convoluted Pandel. Scattering. Absorption. ice. bubbles. dust. dust. Ice description.

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Flasher reconstruction at LBNL

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  1. Flasher reconstruction at LBNL Dima Chirkin

  2. Photon detection

  3. muon track: flasher/cascade: t=t0+|z-z0|/c Residual time description

  4. Pandel log likelihood

  5. Pandel log likelihood

  6. Convoluted Pandel

  7. Scattering Absorption ice bubbles dust dust Ice description

  8. Ice description

  9. Ice description

  10. Reconstruction in fat-reader • fat-reader contains a plug-in reconstruction module, which: • uses convoluted pandel description • uses multi-media propagation coefficients • relies on the Kurt’s 6-parameter ice model • has Klaus’s stability of the solution • parameterization is possible for bulk ice • reconstructs both tracks and showers/flashers • calculates an energy estimate • also reconstructs IceTop showers

  11. Flasher analysis of April 9 data

  12. Flasher analysis of April 9 data

  13. Flasher analysis of July 12 data

  14. Energy reconstruction

  15. Flasher energy reconstruction

  16. Flasher intensity variations (in progress)

  17. Flasher energy estimate Quantum efficiency = 0.24 PMT area = 492.10 cm2 Energy = 5.08 TeV Cascade: 1.37 105 photons/GeV

  18. Conclusions • In-ice track and cascade position and energy reconstruction algorithms have been implemented in a module of the fat-reader. • Flasher position reconstruction works very well • Despite a very early state of the energy reconstruction, results are encouraging. Outlook • only rough optimization of the llh parameters was performed, need to refine. Kurt’s ice model has been extended to all IceCube depths, will need to rerun reconstruction with new tables • detailed measurement of scattering coefficients with the string • IceTray implementation and further improvements, e.g., multiple coincident event reconstruction (by Jon Aytac)

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