1. Attenuation measurement with all 4 frozen-in SPATS strings Justin Vandenbroucke Freija Descamps IceCube Collaboration Meeting, Utrecht, Netherlands September 15, 2008

2. Outline Motivation and background Data set Method Amplitude vs. distance Best fit and confidence regions Attenuation length lower limit Systematics Justin Vandenbroucke Utrecht, Netherlands September 15, 2008

3. Motivation Two types of attenuation analyses – Inter-string: frozen-in sensors & transmitters – Pinger: frozen-in sensors & retrievable pinger in water Last year’s 3-string inter-string analyses inconclusive Last year’s pinger analyses inconclusive Improve with 4-string inter-string? Now enough strings for single-transmitter analysis, to reduce systematics Justin Vandenbroucke Utrecht, Netherlands September 15, 2008 Is attenuation length at least a few hundred meters? Background

4. Significantly improved inter-string data set taken 4 strings (D with improved transmitters and sensors) Each sensor records 200 seconds @ 200 kHz 40 Hz transmitter repetition: 8,000 pulses per T-S combination! cf. 726 pulses previously Optimized parameters – Sampling frequency – RAM disk size – Transmitter repetition rate – Steering amplitude Justin Vandenbroucke Utrecht, Netherlands September 15, 2008

5. Geometry: D transmitter to ABC sensors, all at 320 m depth Justin Vandenbroucke Utrecht, Netherlands September 15, 2008

6. Data subset for this analysis Single depth (320 m) transmitters & sensors, to reduce systematics One transmitter only, to reduce systematics All 3 ABC string sensors recording All 3 channels per module recording Select only the first 10 s: for longer duration we need more precision in clock drift determination Justin Vandenbroucke Utrecht, Netherlands September 15, 2008

7. Pulse averaging algorithm Justin Vandenbroucke Utrecht, Netherlands September 15, 2008 (1)Stretch times according to clock drift (2)Wrap and re-sort by time (3)Re-bin at chosen sampling frequency - all samples wrapped and sorted - average pulse after binning at 200 kHz

8. Azimuthal variation of transmitter? Justin Vandenbroucke Utrecht, Netherlands September 15, 2008 transmitter sensor 19° 29° We use a small range of azimuths:

9. Analysis method Frozen-in transmitter removes many systematics plaguing the pinger analyses Single level to minimize systematics String D transmitter (good quality) Use amplitudes directly (no ratios assuming negligible angular variation) Determine clock drift by scanning over assumed drift values, maximize V pp, check V max and V min peak at same drift value Apply full confidence level treatment Justin Vandenbroucke Utrecht, Netherlands September 15, 2008

10. Peak to peak amplitude vs. distance (linear scale) Justin Vandenbroucke Utrecht, Netherlands September 15, 2008

11. Ln(amplitude * distance) vs. distance Justin Vandenbroucke Utrecht, Netherlands September 15, 2008 “statistical” errors: std. dev. of avg. pulse V pp pulse to pulse signal variation pulse to pulse noise variation residual clock drift

12. Attenuation coefficient confidence region Justin Vandenbroucke Utrecht, Netherlands September 15, 2008 Best fit and sigma of each parameter from analytical method Ellipses from numerical method best fit - best fit +/- 1 sigma - delta-chi-square = 1 (tangents contain 68.3% of either parameter alone) - delta-chi-square = 2.3 (contains 68.3% of parameter space jointly)

13. Attenuation length confidence region Justin Vandenbroucke Utrecht, Netherlands September 15, 2008 Best fit: 1055 m

14. Attenuation coefficient PDF (Gaussian) Justin Vandenbroucke Utrecht, Netherlands September 15, 2008

15. Attenuation length: probability distribution function Justin Vandenbroucke Utrecht, Netherlands September 15, 2008

16. Attenuation length cumulative PDF and lower limit Justin Vandenbroucke Utrecht, Netherlands September 15, 2008 Attenuation length > 363 m @ 68.3 % CL statistical errors only without constraining lambda positive

17. Adding 100% systematic error to the statistical error Justin Vandenbroucke Utrecht, Netherlands September 15, 2008

18. Lower limit with 100% systematic error and lambda constrained positive Justin Vandenbroucke Utrecht, Netherlands September 15, 2008 68.3% CL:attenuation length > 269 m 90% CL:attenuation length > 168 m

19. Systematic effects Justin Vandenbroucke Utrecht, Netherlands September 15, 2008 EffectPresent?Comment S chan. to chan. variationAccounte d Dominant systematic error: ~100% ? IceCube cable shadowingYesEffectively changes S sens. or T. azim. Hole ice qualityYesWould appear as chan. to chan. S variation Clock driftSmallRemoved, but sufficiently? T azimuth responseSmallAll S in roughly same direction Background noiseNoAutomatically in statistical uncertainty T zenith responseNoSingle depth S zenith responseNoSingle depth S azimuth responseNoEach sensor channel used once T module to module variation NoSingle transmitter Reflections interferenceNoFrozen hole column Transmission coef. with angleNoFrozen hole column: no transmission coef. Shear wavesNoNo variation in fraction going to S waves SaturationNoNone of these runs saturated Variation in waveform shapeNoNo pinger motion T = transmitter S = sensor

20. Conclusions We now have high quality optimized 4-string inter-string data set First analysis complete Confidence interval and lower limit in addition to best fit “Direct” method, complementary to “ratio” method Claim: this analysis is least affected by systematics, of all (inter-string or pinger) attenuation analyses to date Is it good enough? No. We need improved pinger runs (see Delia’s talk) and more inter-string analysis To do – Verify amplitude determination (clock drift correction algorithm) – Verify systematic error estimate – New data for few combinations with sufficient online drift determination – Repeat with transmitters at other depths on D (also ABC?) – Frequency domain analysis? Justin Vandenbroucke Utrecht, Netherlands September 15, 2008

21. Cross check: Two independent amplitude determinations Justin Vandenbroucke Utrecht, Netherlands September 15, 2008 JustinFreija

22. Ratio analysis: in progress Justin Vandenbroucke Utrecht, Netherlands September 15, 2008

23. Pulse averaging improves signal to noise Justin Vandenbroucke Utrecht, Netherlands September 15, 2008 - single raw pulse - average pulse

24. Pulse averaging: Effect of chosen re-binning sampling frequency on average pulse Justin Vandenbroucke Utrecht, Netherlands September 15, 2008 - 200 kHz - 6 MHz after stretching times, wrapping, and re-sorting BT6 to AS5-0; 3000 pulses