Update on HV Tuning Procedure for KM3NeT Group Meeting
Recap and updates on the HV tuning procedure for the KM3NeT group meeting include moving to a procedure based on gain estimates, implementing HV-fitting routines in JFitHV, and addressing issues related to linear behavior, fit ranges, and outliers. Solutions for maximizing the ToT-fits efficiency are also discussed. The presentation details the implementation progress, challenges, and proposed strategies to improve the high-voltage settings for PMTs. Anomalous ToT-fits and their causes are identified and discussed in the context of the ongoing development.
Download Presentation
Please find below an Image/Link to download the presentation.
The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author. Download presentation by click this link. If you encounter any issues during the download, it is possible that the publisher has removed the file from their server.
E N D
Presentation Transcript
HV tuning update Bouke Jung (bjung@nikhef.nl), Alexandre Creusot (creusot@apc.in2p3.fr), Maarten de Jong (mjg@nikhef.nl) Nikhef KM3NeT group meeting 2020/03/13
Recap Move to HV-tuning procedure based on gain-estimates Motivated by theory (see doxygen): Implementation through fit or interpolation of linearized data Extract high-voltage settings from database Extract gain-estimates from JFitToT output Outliers in gain-estimates need to be inspected Database integration via Json 09/14/2024 09:30 KM3NeT collabo - Bouke Jung (bjung@nikhef.nl) 2
HV fit HV-fitting routine is being implemented in JFitHV (updates in Jpp git branch fitToT_full_spectrum) DB-interfacing has been implemented Automatically retrieves (HV,G)-data for all PMTs in user-specified list of data-files Nominal Gain (G = 1.0) Initial results are promising Clear linear behavior on log-log scale for most PMTs A couple of issues Minimum fit-range (G = 0.3) 09/14/2024 09:30 KM3NeT collabo - Bouke Jung (bjung@nikhef.nl) 3
HV fit Maximum fit-range (G = 2.0) HV-fitting routine is being implemented in JFitHV (updates in Jpp git branch fitToT_full_spectrum) DB-interfacing has been implemented Automatically retrieves (HV,G)-data for all PMTs in user-specified list of data-files Nominal Gain (G = 0.9) Initial results are promising Clear linear behavior on log-log scale for most PMTs A couple of issues Deviation from linear behavior at high or low |HV| for some PMTs Fit-range bounds for gain-estimate in JFitToT Minimum fit-range (G = 0.3) 09/14/2024 09:30 KM3NeT collabo - Bouke Jung (bjung@nikhef.nl) 4
ToT-fits for increasing HV N.B: These are animated gif files 09/14/2024 09:30 KM3NeT collabo - Bouke Jung (bjung@nikhef.nl) 5
Solutions Making the ToT-fit work for all possible HV-settings is asking too much For the specific purpose of HV-tuning, set fit-range to region surrounding ToT-distribution peak The datapoints directly surrounding the optimal gain (= 1.0) tell the most about the optimal high voltage setting Switch to linear interpolation/extrapolation 09/14/2024 09:30 KM3NeT collabo - Bouke Jung (bjung@nikhef.nl) 6
Remaining anomalous ToT-fits Thresholdband and PunderAmplified too low to account for large peak at 5ns Extremely high HV Large secondary contribution at 10ns Normalization does not account for large relative fraction of 5ns- and 10ns-peak counts Causes fit to unduly scale down model contribution by increasing its spread 09/14/2024 09:30 KM3NeT collabo - Bouke Jung (bjung@nikhef.nl) 7
Remaining anomalous ToT-fits Thresholdband and PunderAmplified too low to account for large peak at 5ns Extremely low HV Model contribution nearly indistinguishable from 10ns-peak contribution 09/14/2024 09:30 KM3NeT collabo - Bouke Jung (bjung@nikhef.nl) 8
Remaining anomalous ToT-fits Discovered one PMT (808483678.5) with anomaly in first and second bin Output from JCalibrateToT Some artefact in the triggering? 09/14/2024 09:30 KM3NeT collabo - Bouke Jung (bjung@nikhef.nl) 9
Planning 1. Set up a bash script to automatically extract the gain-estimates and find the optimal HVs using a set of user-specified raw data files Prognosis: 2. Implement DB-integration (via JSon) Prognosis: today/tomorrow 3. Document remaining anomalous ToT-fits on ELOG and git Prognosis: today 4. Analyze results with recent (L0-)data using the provided bash script Prognosis: weekend/start of next week 5. Adjust TIME_OVER_THRESHOLD_NS to optimal gain-setting Prognosis: tomorrow/weekend (non-critical) 09/14/2024 09:30 KM3NeT collabo - Bouke Jung (bjung@nikhef.nl) 10
09/14/2024 09:30 KM3NeT collabo - Bouke Jung (bjung@nikhef.nl) 11
