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PySiPMGUI: A Universal Python-Based Software for Photodetector I-V Quality Assurance: From Underground Dark Matter Searches to Astroparticle Cherenkov Cameras

Tanay Dey, Suraj Shaw, Ritabrata Banerjee, Pratik Majumdar, Satyaki Bhattacharya

Abstract

Silicon photomultipliers (SiPMs) are currently the most prevalent photon detection technology in modern experiments in high-energy physics, astroparticle physics, neutrino physics, and dark matter searches. The high detection efficiency for photons, excellent timing resolution, small size, and magnetic field independence make them ideal for precision measurements in low-light conditions. However, key parameters like breakdown voltage, gain, and dark count rate show a strong dependence on the bias voltage and temperature, requiring a systematic characterization. In this work, we present an open-source graphical user interface (GUI) for automated SiPM characterization, leveraging PyVISA-controlled instruments. The tool provides a free, open, and platform-independent solution for detector R&D and large-scale SiPM characterization.

PySiPMGUI: A Universal Python-Based Software for Photodetector I-V Quality Assurance: From Underground Dark Matter Searches to Astroparticle Cherenkov Cameras

Abstract

Silicon photomultipliers (SiPMs) are currently the most prevalent photon detection technology in modern experiments in high-energy physics, astroparticle physics, neutrino physics, and dark matter searches. The high detection efficiency for photons, excellent timing resolution, small size, and magnetic field independence make them ideal for precision measurements in low-light conditions. However, key parameters like breakdown voltage, gain, and dark count rate show a strong dependence on the bias voltage and temperature, requiring a systematic characterization. In this work, we present an open-source graphical user interface (GUI) for automated SiPM characterization, leveraging PyVISA-controlled instruments. The tool provides a free, open, and platform-independent solution for detector R&D and large-scale SiPM characterization.

Paper Structure

This paper contains 21 sections, 14 equations, 8 figures, 1 table.

Table of Contents

  1. Introduction
  2. Software Architecture
  3. Safe Control Framework and Environmental Monitoring
  4. Voltage Control and Safe Ramping Algorithm
  5. Safe Ramp-Down Protocol
  6. Safety Interlocks and Compliance Handling
  7. Temperature and Humidity Monitoring
  8. Automated I-V Characterization Logic
  9. Theoretical Modeling of SiPM I-V Characteristics
  10. Pre-Breakdown Leakage Current ($I_{leak}$)
  11. Post-Breakdown Avalanche Current ($I_{aval}$)
  12. Temperature Dependent SiPM Dark Current
  13. Experimental Methodology
  14. Detector Description
  15. Biasing and Readout Circuitry
  16. ...and 6 more sections

Figures (8)

  • Figure 1: Flow chart illustrating the workflow of the GUI.
  • Figure 2: The Python-based GUI during an I-V characterization run. The left sidebar contains configuration controls for voltage range, step size ($V_{step}$), and compliance limits. The central monitoring strip displays real-time scalar values for voltage, leakage current, and environmental data (temperature/humidity).
  • Figure 3: (a) SiPM device and experimental setup used for characterization; (b) Biasing Circuit Design for MicroFC-60035-SMTonsemi_AND9809_2018.
  • Figure 4: Schematic diagram of experimental setup.
  • Figure 5: (a) Pannel to enable breakdown voltage and dark count rate (DCR) analysis. (b) Snapshot of pannel for post-processing.
  • ...and 3 more figures