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Optimization of artificial deadtime for the - SN- system

Optimization of artificial deadtime for the - SN- system. Timo Griesel IceCube Collaboration Meeting 04/29-05/03/2008 Madison, USA. Correlated Noise. __________________________________________________. __________________________________________________.

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Optimization of artificial deadtime for the - SN- system

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  1. Optimizationofartificialdeadtimeforthe - SN-system Timo Griesel IceCube Collaboration Meeting 04/29-05/03/2008 Madison, USA

  2. Correlated Noise __________________________________________________ __________________________________________________ Time betweentwohits DOM 754dad1d3800 (Str49-1) Ideal poissoniannoise Correlatednoise, Afterpulses Shown fit : Page 1/12

  3. Afterpulse – originofthecorrelatednoise __________________________________________________ __________________________________________________ • Causes: • Afterpulses in the PM • <µs • Scintillations due to radioactive decays in the glas sphere (238U, 232Th )~ms Suppression of afterpulses due to artificial deadtime Hellwig et al. AMANDA-IR/20010301 Hellbing et. al. AMANDA-IR/20030701 O. Franzen Diplomathesis 2003 N. Sido Martin Diplomathesis 2003 Page 2/12

  4. The data __________________________________________________ __________________________________________________ Last Pole season Omicron ATWD hits data was taken (02/06/2008) by John J. and T.Griesel with the help of K.Hanson. I3deadtimeData.root Data: Format: Raw ATWD hits Position: String 39, String 49 – all DOMs Duration: 15min Data Size: ~2GB Contains: GMT Values Str49 Str39 49-60 Processing: Decryption of the OMICRON hits Sorting DOM wise Building a ROOT File with TTree objects 49-1 39-1 StrNo DOMPosition DOMHexName NoOfEntries RawHits Timestamps … … … 49-60 39-60 Page 3/12

  5. Whatwealreadyknewatthe Zeuthen meeting __________________________________________________ __________________________________________________ Paralyzing or Non-paralyzing deadtime  ? non-paralyzed  paralyzed  t t • The artificialdeadtimehastobe a non-paralyzingdeadtime Is there an upper limit for the deadtime ? • The artificial deadtime should not be higher than 400μs Deadtime ? • The optimized artificial deadtime based on „oxygen“ :  = 256μs Page 4/12

  6. First lookatthedata: Rates __________________________________________________ __________________________________________________ • Effects depending on the DOM depth ? Page 5/12

  7. The optimization method 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  __________________________________________________ __________________________________________________ • Is there a maximum in the significance plot ? Page 6/12

  8. The supernova signal __________________________________________________ __________________________________________________ Two different SN signals were used (e.g. @ 10kpc): (1.) Scaled SN1987A signal NKAM = 11ρIce = 917 kg/m³Veff = 51.6m³ * Efth = 0.8mKAM = 2.14 106kgDLMC = 52 kpc DSN = 10 kpc (2.) SN signal based on the „Mainz Simulation“ (A.Piégsa & T.Griesel) Page 7/12

  9. Significance single DOM __________________________________________________ __________________________________________________ Scaled SN1987A signal @ distance 10kpc, DOM 49-11 actual • Is this working out for all DOMs ? Page 8/12

  10. Significance DOMs Str49 __________________________________________________ __________________________________________________ Scaled SN1987A signal @ distance 10kpc, String 49 • What is that ? • Why is that ? Page 9/12

  11. Δt again… __________________________________________________ __________________________________________________ • Effects depending on the DOM depth ? Page 10/12

  12. Afterpulse vs Depth __________________________________________________ __________________________________________________ • Subtracting poissonian noise from background sample • Integration of the „afterpulse“ based correlation • Trend ? Why is that … Page 11/12

  13. Roadmap __________________________________________________ __________________________________________________ • Data for deadtime optimization processed • First look at the rates • First optimization attempt for Str49 was performed • First closer look at the correlated part Next steps… • Investigation of the background after deadtime application still poissonian distributed ? • Depth dependency studies • How is String 39 looking ? … other ideas ? Page 12/12

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