1 / 29

A. Tsirigotis Hellenic Open University

A. Tsirigotis Hellenic Open University. N eutrino E xtended S ubmarine T elescope with O ceanographic R esearch Reconstruction, Background Rejection Tools and Methods. Background Sources. Bioluminescence Activity. PMT Rates vs Time : Up-Looking PMTs. Background Sources.

dorcas
Télécharger la présentation

A. Tsirigotis Hellenic Open University

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. A. Tsirigotis Hellenic Open University Neutrino Extended Submarine Telescope with Oceanographic Research Reconstruction, Background Rejection Tools and Methods

  2. Background Sources Bioluminescence Activity PMT Rates vs Time : Up-Looking PMTs

  3. Background Sources Bioluminescence Activity PMT Rates vs Time : Down-Looking PMTs

  4. Background Sources Bioluminescence Activity • Light Bursts with duration 1-10sec • Site depended • Decreases exponentially with depth • Seasonal variations • Correlated with water currents • Contributes to detector dead time

  5. Background Sources Bioluminescence Activity Emitted light at the single photoelectron level Number of Collected P.E.s During Bioluminescence Activity Bioluminescence Activity Excluded Trigger:≥ 4fold Coincidence

  6. Background Sources Bioluminescence Activity Bioluminescence Contribution to the Total Trigger Rates Bioluminescence Occurs for the 1.1% ± 0.1% of the Active Experimental Time Total Trigger Rates Bioluminescence Contribution to the Total Trigger Rates Experimental Trigger Rates from Periods Without Bioluminescence

  7. Background Sources K40 beta decay Increasing Thresholds does not affect seriously the detection efficiency Data Collected with 4fold Majority Coincidence Trigger

  8. Background Sources K40 K40 radioactivity can be used for calibration purposes in deep sea Data from a depth of 4000 m: PMT Pulse Height Distribution Calibration single p.e. LED Run single p.e. pulse height distribution two p.e.s pulse height distribution dark current pulse height distribution sum of the above

  9. Background Sources Atmospheric muon angular distribution Okada parameterization Cosmic ray muon background Depth intensity curve

  10. Background Sources Cosmic ray muon background Down coming atmospheric muons can be misreconstructed as upcoming neutrino induced muons (mirror tracks) By using the accumulated charge on each PMT we can reduce the mirror track background (the reduction depends on the available degrees of freedom)

  11. Signal processing Amplitude Frequency (MHz) Fourier Transform-Comparison Phase (rad) Frequency (MHz) Detector Preparation Attenuation Correction Reference waveform Electronic delay lines and amplifier Coaxial cable

  12. Signal processing Event by Event Sampling Interval Variation (Constant Temperature) RMS=0.006 ns 40 MHz Clock Waveform Capture ADC Counts Sample Software to Hardware Trigger Time Difference (arbitrary time offset) σ=0.7ns Time (ns)

  13. Signal processing Amplitude Frequency (MHz) Phase (rad) Frequency (MHz) raw data Offset (ADC counts) ATWD counts ATWD sample number Sample baseline subtraction Voltage (mV) Time (ns) attenuation correction Voltage (mV) Time (ns)

  14. Signal processing Voltage (mV) Before the F.F.T and the attenuation corrections After the F.F.T and the attenuation corrections Time (ns) Voltage (mV) Rise Time 16 ns 9 ns Voltage (mV) Time (ns) Time (ns) Correction for overflow Double pulse disentangling

  15. Signal processing Voltage (mV) Arrival time definition… Time (ns) Arrival time

  16. Data from a depth of 4000 m Calibration Run <Δt>: 0.6 ± 0.1 ns σ : 3.3 ± 0.1 ns Number of Events Time Difference (ns) Number of Events <Δt>: 0.2 ± 0.1 ns σ : 3.3 ± 0.1 ns Time Difference (ns) LED Calibration Data Gain Monitors

  17. Data from a depth of 4000 m: Calibration Run

  18. Reconstructed Waveforms Input to the Fitter

  19. Track Reconstruction. . .

  20. Run: 81_127 Event: 1789 Input to the Fitter

  21. Run: 81_127 Event: 1789 Best fit Fit Results

  22. Run: 81_127 Event: 1789 Pictorial Representation

  23. Preliminary Preliminary Data σ=0.94±0.2 M.C. Prediction (atmospheric muons) Data Points

  24. M.C. Prediction (atmospheric muons) Data Points Preliminary Total number of p.e.s per Track

  25. M.C. Prediction (atmospheric muons) Data Points Preliminary Zenith Angular Distribution • χ2probability > 0.1 • track selection according to the charge-likelihood • more than 4.5 p.e.s per hit per track

  26. Extension to many floors One Tower • Each floor runs independently (floor sub-event) • An event is a collection of several floor sub-events when certain requirements (e.g. timing) are fullfilled • Online event-building • Offline track reconstruction Many Towers • Track segment fit: using the PMT’s of each Tower • Global fit: using matched track segments. • Second iteration to collect more points Trivially the best strategy is to use all the PMT’s independent of tower This is depended on the trigger, data transmission (e.g. optoelectronics) and DAQ architecture

  27. Event 2213 – Run 78 – BFile 70

  28. Event 2213 – Run 78 – BFile 70 Best Fit

  29. Event 2213 – Run 78 – BFile 70

More Related