Timo Griesel IceCube Collaboration Meeting 04/28-05/02/2009 Madison, USA

1. ArtificialdeadtimeOptimizationfortheIceCube – SN - system 3.0 Timo Griesel IceCubeCollaboration Meeting 04/28-05/02/2009 Madison, USA

2. Reminder Time betweentwohits DOM 754dad1d3800 (Str49-1) Ideal poissoniannoise Correlatednoise, Afterpulses Shown fit: Page 1/

3. Data – Str83, Str36 All data : 900s Omicron ATWD hit data read out by J. Jacobsen, T.Griesel and the help of K.Hanson. 1st data sample : Str49, Str39 (02/06/2008) 2nd data sample : Str83, Str36 (02/12/2009) • Difference between 1st and 2nd data sample : • Str83 (-L) first DC Str with high efficiency R7081MOD PMT • Str83, Str36 not fully frozen • Str36 with „golden“ DOMs • 36-43, 36-46, 36-51 Page 2/

4. Rates – 1st Look • Rate is to low compared to the other Strings Page 3/

5. Rates – 1st Look • Rate better than ideal poissonian • Rate lower than on a „normal“ String …somthing must be wrong Page 4/

6. Data Correction maximal gap • reason for increased rates are large gaps between following hits • large gaps need to be cleaned •  total time information between DOMs is lost – no LC analysis possible Page 5/

7. Data Correction Large gap cleaning applies DOM:83-30: ==================================== Maximum gap between hits allowed [s]: 0.5 Total Time of Measurement [s]: 900.329 Total Sum of delta t values [s]: 900.329 Real Time of Measurement [s]: 576.215 Detector deadtime fraction [s]: 0.6400049 ==================================== No. of events: 384444 No. of large gaps: 187 No. of events after cleaning: 384257 No. of cleaned entries: 384257 Fraction of bad events [%]: 0.0004864 ==================================== • Data Cleaning for a maximum gap of 0.5s between following hits Page 6/ ~ 36% of the data is lost !!!!

8. Rates – 2nd Look • Str36 is 62 days in ice at the time of measurement  not fully frozen • Comparison to the rates of Str39 and Str49: Page 7/

9. Rates – 2nd Look Str83 • Odd DOM spacing is a Deep Core feature • Str83 is 29 days in ice at the time of measurement  not fully frozen • Expected Rate for R7081MOD DOMs should be ~30% higher Page 8/

10. Temperaturedependance Linear Fit Non Thermal Fit Richardson Law Mayer arXiv:0805.0771v1 • Additional Information about the OMICRON *.moni files is needed ! Page 9/

11. The optimizationmethod Generating SN Signal NSN Superpose NSN with measured background NB Apply artificial deadtime  to the sample NSN+B Apply artificial deadtime  to the sample NB Significance Increase artificial deadtime  Page 10/

12. Rates – 1st Look Page 2/

13. Rates – 1st Look Page 2/

14. Detectabilityof SN Typ Ia Neutrino signals in IceCube

15. Supernova Type Ia‘s ESO press photo 31b/07 • Neutrino emission (burst) due to electron capture on free protons and nuclei • Little Neutrino emission due to beta decay and positron induced capture Page 5/

16. Input variables • All simulation input is based on Kunugise et al.(Publications of the Astronomical Society of Japan, Vol.59, No.6, pp.L57--L61) • Neutrino Luminosity is three orders of magnitude smaller compared to CC-SN Page 5/

17. Input variables • Total Neutrino burst duration ~1.7s • The average Neutrino energy is a factor of three smaller as in a CC-SN  expected IceCube Neutrino signal 27000 less than CC-SN signal Page 5/

18. Input variables • Since the burst time is so small we use just the average energy for the signal simulation Page 5/

19. Detectionsignificance Alpha Centauri @ 1.33pc • CNS3 (Gliese Catalog of Nearby Stars): 3803 in 25pc radius •  30424 within 50pc • 50 % of all stars are in a binary system Page 5/ ~7500 candidates for IceCube…