The Latin American Giant Observatory (LAGO) is an extensive cosmic ray observatory network comprising Water Cherenkov Detectors (WCDs) distributed across various sites in Latin America. These detectors play a crucial role in studying high-energy astroparticles and understanding cosmic phenomena. One of LAGO's primary objectives is to design and implement high-performance, cost-effective data acquisition systems (DAS) for particle detection, making advanced scientific research more accessible.
In collaboration with Red Pitaya, a company known for its versatile and open-source test and measurement platforms, the LAGO team has developed a comprehensive testing environment.
This environment bridges both hardware and software innovations, aiming to advance particle detector technology while keeping costs low and performance high.
Innovative Testing Environment
The testing environment developed by the team consists of two custom-designed Printed Circuit Boards (PCBs) and a suite of software tools. These components are designed to interface seamlessly with the Red Pitaya STEMlab platform, providing a flexible and powerful foundation for data acquisition and processing.
1. PMT Interface Board
The Photomultiplier Tube (PMT) Interface Board is a critical component that connects the Red Pitaya platform to a PMT and various environmental sensors. PMTs are highly sensitive light detectors commonly used in high-energy particle detection due to their ability to amplify weak light signals generated by cosmic particles interacting with the WCDs.
Key Features:
- Bias Voltage Generation: The board uses two DC-DC converters to produce the multiple voltage levels (+3.3V, +5V, -3.3V) required for PMT operation and sensor interfacing. This ensures that all connected devices receive stable and accurate power supplies.
- High Voltage Control: A conditioning circuit amplifies the Red Pitaya's Pulse Width Modulation (PWM) signal from 0-1.8V to 0-2.5V. This amplified signal controls a Hamamatsu high-voltage power supply, which can generate up to 2000V to operate a PMT. The actual high voltage applied to the PMT is monitored through a feedback mechanism, ensuring precise control and safety.
- Sensor Connectivity: The board includes I2C and UART connectors, allowing for the integration of various environmental sensors, such as those of temperature, pressure, and humidity. These sensors provide valuable contextual data that can affect particle detection and are crucial for accurate measurements.
Figure 2: PMT's circuit block diagram
2. SiPM Biasing Board
The Silicon Photomultiplier (SiPM) Biasing Board is designed to interface a Red Pitaya board with SiPMs, which are solid-state alternatives to PMTs. SiPMs offer advantages such as lower operating voltages, compact size, and immunity to magnetic fields, making them suitable for various detection scenarios.
Key Features:
- Modular Design: The board supports up to eight SiPMs with independent biasing, allowing for scalable detector arrays. Multiple boards can be connected in a daisy-chain configuration, enabling the setup of extensive detection systems with minimal complexity.
- High Voltage Generation: The DC-DC converter provides up to 45V of bias voltage, adjustable to accommodate different SiPM models. Voltage is limited for safety and compatibility reasons, ensuring that sensitive components are not damaged.
- Signal Amplification and Filtering: The board includes filters to eliminate noise and interference, as well as an amplifier configured as a non-inverting amplifier. This setup enhances the SiPM signals, ensuring they are within the input range of the Red Pitaya's analog inputs (+/- 1V) for accurate detection.
Figure 3: SIPM’s circuit block diagram
Software Development
To complement the hardware, the team developed some versatile data acquisition software using LabVIEW and MATLAB. This software emulates the functionality of the Red Pitaya and provides a user-friendly interface for researchers to configure and control the data acquisition process.
Designed to work seamlessly with Keysight oscilloscopes (20xx, 30xx, 40xx series) and easily adaptable to other models, the software ensures that researchers can use existing equipment without significant additional investment. Users can configure acquisition parameters such as channel settings, time scales, trigger levels, and data saving options through an intuitive graphical interface.
The software offers real-time visualization by providing an oscilloscope-like display within the application. This feature allows immediate monitoring of pulses, enabling quick adjustments and troubleshooting during experiments.
Data processing is enhanced through MATLAB algorithms employed to filter noise, detect peaks, and count pulses. A smooth filter cleans the acquired data, and a peak detection algorithm identifies significant events, which is essential for determining the detectors' working points.
With minimal modifications, the software can acquire data from multiple channels simultaneously. This capability is crucial for experiments requiring coincidence detection, where simultaneous events across different detectors are of interest.
Setting the working point
Finding the optimal operating conditions, known as the working point, for both PMTs and SiPMs is crucial for consistent and reliable particle detection. The working point ensures that the detector operates within a range where signal pulses can be effectively discriminated from background noise or "dark pulses."
Process for PMTs:
- High Voltage (HV) Sweeping: The team set a low discriminator threshold (approximately 30mV) and varied the HV control values from 40% to 70% of the total control voltage. By plotting the counts per minute against HV control values, they identified a plateau region where the count rate remained stable. This plateau indicates the optimal HV setting.
- Trigger Level Adjustment: With the optimal HV identified, the trigger level was swept to find a threshold that maximizes signal detection while minimizing noise.
- Working Point Determination: Combining the HV and trigger level plots, the optimal working point for the PMT was determined to be at an HV of 1400V and a trigger level of 500mV.
- Pulse Height Distribution (PHD): A histogram of pulse heights at the working point was generated to verify the clear separation between signal pulses and noise.
Process for SiPMs:
- Bias Voltage Sweeping: The SiPMs were tested within their operational voltage range (25V to 30V), sweeping the bias voltage while keeping the trigger level low (around 10mV).
- Optimal Bias Voltage: Similar to the PMT process, the counts per minute were plotted against bias voltage to find a stable plateau, indicating the optimal operating voltage.
- Trigger Level Optimization: The trigger level was adjusted to fine-tune the detection capability, resulting in an optimal trigger level of 50mV for the SiPM.
- Working Point Determination: The optimal working point for the SiPM was found to be at a bias voltage of 27.3V and a trigger level of 50mV.
Results and Applications
The hardware components, including the PMT interface board and the SiPM biasing board, underwent thorough testing following a comprehensive protocol. All voltage levels, control mechanisms, and interfacing capabilities met or exceeded design expectations, confirming the robustness of the hardware design.
The integrated system successfully captured pulses from both PMTs and SiPMs. The software's real-time visualization and data processing capabilities allowed for immediate verification and analysis of the signals. The ability to handle multiple channels enables the detection of coincidences between different detectors, which is vital for advanced particle physics experiments and enhances the system's versatility.
The modularity and compatibility of the boards facilitate the development of hybrid detectors. By combining WCDs with scintillator detectors using SiPMs, researchers can create sophisticated detection systems that leverage the strengths of both technologies. Additionally, the system's capability to be powered by various means—including batteries, solar panels, or wind turbines—makes it suitable for remote installations where conventional power sources are unavailable, expanding the potential deployment sites for cosmic ray observation.
Conclusion
The collaboration between the LAGO team and Red Pitaya has resulted in a cost-effective, high-performance data acquisition system that significantly advances the capabilities of particle detection. By utilizing the flexible and powerful Red Pitaya platform, combined with custom hardware and software, the team has created a solution that is both accessible and scalable. This achievement not only benefits the LAGO project but also sets a precedent for accessible and scalable particle detection systems within the broader scientific community.
Looking ahead, the next step involves fully integrating the data acquisition and processing algorithms into the Red Pitaya's FPGA. This integration is expected to enhance performance and reduce reliance on external equipment like oscilloscopes, streamlining the setup and making it more portable.
Incorporating additional environmental sensors and improving data contextualization will lead to more accurate and insightful observations. By understanding the environmental factors that affect particle detection, researchers can refine their measurements and interpretations.
Sharing designs and software with the broader scientific community encourages collaboration and innovation. Open-source dissemination of this technology can lead to new discoveries and technological advancements, fostering a collaborative environment that benefits all involved in high-energy physics research, with Red Pitaya at the heart of this.
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October 30, 2024
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