1. IceCube: String 21 reconstruction Dmitry Chirkin, LBNL Presented by Spencer Klein LLH reconstruction algorithm Reconstruction of digital waveforms Muon data reconstruction Time calibration verification with muons Combined energy/positional reconstruction PMT saturation / OM sensitivity Flasher/muon energy estimate Timing/geometry verification with flashers

2. 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 depth-dependent 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 feature extracts waveforms using fast Bayesian unfolding corrects the charge due to PMT saturation accounts for the PMT surface acceptance combines energy with positional/track minimization

3. LLH Reconstruction

4. Reconstruction of the simulated data

5. Root-fit waveform pulse reconstruction

6. Bayesian waveform unfolding fast waveform feature extraction: 2-3 ms per every WF (cf. 30 seconds before) why not invert against the tabulated smearing function need to emphasize SPE signal while controlling oscillations of the solution due to noise Bayesian or regularized unfolding does just that

7. Bayesian waveform unfolding If a fitted pulse does not start on the boundary, then it is approximated by a superposition of 2 pulses. The weighted average of these pulses gives the estimate of the leading edge. Simple and complicated waveforms are reconstructed with the same amount of effort

8. Data reconstruction

9. Comparison with the simulated data

10. Muon time calibration verification reconstruct muon tracks without DOM X plot the time residual for DOM X for nearby reconstructed tracks if scattering length is longer than the distance cut (10 m) the most likely residual should be 0, otherwise residual will show delay increasing with the amount of scattering.

11. Energy reconstruction From Gary’s talk: usual hit positional/timing likelihoodenergy density terms From Chrisopher W. reconstruction paper: Therefore, w=1

12. Flasher/cascade energy reconstruction The energy estimate  is constructed according to the Rodin’s Monin formula, with average propagation length obtained from average absorbtion and scattering. These are calculated as during the positional reconstruction, using George/Mathieu prescription based on Kurt’s ice model Similar treatment for muons

13. PMT saturation As measured by Chiba group at 1.17. 10 7 From Bai’s DOM test report Measured between 700 and 1750 V Q corr =Q/(1+Q/Q sat ) Q sat =7500 (gain/10 7 ) -1.24 may require new calibration type?

14. PMT saturation in flasher data DOM 30 flashing at 127 FFF 20 ns DOMs 29 and 28 show approx. 4600 and 3070 PEs After the correction for saturation DOMs 29 and 28 turn out to receive 11700 and 5100 PEs

15. OM angular sensitivity From Ped’s thesis, at the moment as parameterized for an AMANDA OM

16. PMT saturation and OM sensitivity saturation sensitivity

17. Combined positional/energy reconstruction Improves positional reconstruction by constraining the energy observable: Systematic position offset is less than 5 meters in all cases better parameters of Rodin-Monin formula will constrain energy observable even further

18. DOM-to-DOM variation Fixing position according to the geometry file, and performing only the energy reconstruction Large variation is likely due to ice layering, not entirely inconsistent with a constant. For 03F/127 one obtains 10^(7.53) ph. area [m 2 ].

19. PMT effective area PMT area = 492.10 cm 2  81 cm 2 effective area Average quantum efficiency = 0.165 Cascade: 1.37 10 5 photons/GeV  Energy = 61 TeV N ph (03F/127) = 4.2. 10 9 photons (for 6 LEDs) At FFF/127(20ns): 8.4. 10 9 photons Measurement at Chiba Chris Wendt’s estimate: 8. 10 9  20  50% photons (~56 TeV) per flasherboard at FFF/127(20 ns)

20. Muon energy reconstruction Energy density llh term constrains muon-to-string distance, 90% of muons pass within 24 meters of the string. Still, for MC 90% of muons pass within 34 meters. A pull toward the string still exists. A better distance estimate results in better resolution in energy of the muon Based on: Area. N c [m] = 32440 [m -1 ] (1.22+1.36. 10 -3 E/[GeV]). 81 cm 2 Average measured energy vs. surface energy of simulated muons

21. Flasher timing information Flashing DOM X we can measure arrival time of the first photon at DOMs above and below. Those that form sharp distributions can be used for timing jitter measurement (rms of the ditribution) and geometry verification (mean). Nearby or in clear ice follows expectation from geometry verified

22. Conclusions llh algorithm results in estimates position and energy 3 methods of waveform feature extraction are implemented muon and flasher positional reconstruction are satisfactory muon and flasher energy reconstruction work, but need improvement, based on better pdf and OM sensitivity timing and geometry are verified with muon and flasher data an icetray reconstruction module I3llhReco exists (to be released in ~1 week by Jon Aytac) Work is done on multiple muon selection and reconstruction