Detector Stability on short time scales

Transcription

1 Detector Stability on short time scales 1

2 I am going to talk about... Tests used in an offline GRB analysis Cumulative Test Likelihood Test Tests for online burst filter 2

3 Tests used in an offline GRB analysis GRB neutrino expected in coincidence with photons detected by satellites, duration of emission ~ 50 sec Detector stability test without unblinding data: use off-time data for tests 3

4 The Cumulative Test Divide 2 hours in 72 bins (100 sec per bin) -> 8-10 events per bin at Level 3 Expectation: flat distribution for stable detector -> cumulative distribution follows a straight Use χ2 to quantify deviation 4

5 The Cumulative Test Sensitivity depends on position of instability -> shift bins and calculate χ2 for each possible start bin position Use worst χ2 as quality criteria worst χ2 5

6 The Cumulative Test Compare worst χ2 to simulations of stable 2 hour periods Instabilities hard to quantify, therefore: Worst χ2 < % 97.5 % of all stable periods should pass the test. excluded 6

7 Excluded Bursts Missing data due to short runs that have been excluded during the data processing 7

8 The Likelihood Test Again, divide 2 hours in 72 intervals of 100 sec duration Fill histogram with number of events per 100 sec interval Expectation: Poisson distribution for stable detector Fit discrete Poisson function with fixed norm by minimizing ln(likelihood), Lmin Use Lmin as quality criterion 8

9 The Likelihood Test Compare Lmin obtained by the fit to simulations Red line: Lmin obtainded from fit 97.5 % Instabilities hard to quantify, therefore: 97.5 % of all stable periods should pass the test. 9

10 Unstable Bursts Regular gaps appear in 15 minute intervals lasting for 60 sec VLF veto gaps: Known detector effect and not an instability 10

11 Online Burst Filter and Monitor FRAME Line Fit Burst Monitor Coincidence Filter Tests need to run online for every incoming event in addition to run-wise monitoring to be sensitive to instabilities on timescales of seconds Monitoring Module implemented in icetray Paraboloid Fit Coincidence Filter Alert FRAME 11

12 Sky Map Divide sky into several bins with constant solid angle Monitor event rates in each bin (reconstruced with line fit) in 10 s time interval Define a zenith width, e.g. 20 degree zenith width is fixed and azimuth width varies depending on zenith 12

13 Rates Monitor both rates in 10 sec window (corresponds to 1s for 500 Hz) Corsika MC Good run , Level0 ~ 50 Hz (downscaled dataset) generated 50 Hz 13

14 Reference Sky Map Use one of the stable runs or Corsika MC to write a reference (average) sky map for the given bin size Corsika MC Good run , Level0 ~ 50 Hz (downscaled dataset) generated 50 Hz 14

15 Deviation Calculate deviation from reference rate for each bin sigma = nobs nexp /sqrt(nexp) Corsika MC Run , Level0 15

16 Flasher Data Use flasher data to illustrate instability deviation with flasher rate with flasher only flasher Thanks to Dawn Williams!!! 16

17 Rates: on-source off-time off-source on-time Off-source: All other bins On-source: Hit bin and 2 closest neighbours Off-time: excluding a time window right before the event Event On-time: time window right before the event time Off-time window time Event time On-time window time 17

18 Deviation Distributions FRAME Corsika MC good run flasher worst sigma on-source, off-time Corsika MC good run flasher worst sigma off-source, on-time Line Fit Write information to frame Uses information from frame Burst Monitor Coincidence Filter Paraboloid Fit Coincidence Filter FRAME 18

19 Monitoring Module tray.addmodule("burstmonitor", "monitoring")( ("particlekey", "linefit"), ("headername", "I3EventHeader") ("time_window", 10), ("blind_window", 1000), ("zen_width", 20), ("refmapname", "refmap_20deg.dat"), ("write", False) ) 19

20 Summary Online Stability Monitoring Outline of monitoring module Still to do: optimize stability criteria Code review 20