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Upgrade of the Trigger and Data Acquisition System for Continuous Imaging and Multi-Camera Operation in CYGNO

F. D. Amaro, R. Antonietti, E. Baracchini, L. Benussi, C. Capoccia, M. Caponero, L. G. M. de Carvalho, G. Cavoto, I. A. Costa, A. Croce, M. D'Astolfo, G. D'Imperio, G. Dho, E. Di Marco, J. M. F. dos Santos, D. Fiorina, F. Iacoangeli, Z. Islam, E. Kemp, H. P. Lima, G. Maccarrone, R. D. P. Mano, D. J. G. Marques, G. Mazzitelli, P. Meloni, A. Messina, V. Monno, C. M. B. Monteiro, R. A. Nobrega, G. M. Oppedisano, I. F. Pains, E. Paoletti, F. Petrucci, S. Piacentini, D. Pierluigi, D. Pinci, F. Renga, A. Russo, G. Saviano, P. A. O. C. Silva, N. J. Spooner, R. Tesauro, S. Tomassini, D. Tozzi

Abstract

The CYGNO experiment employs an optical readout to image particle interactions in a gaseous Time Projection Chamber (TPC), combining cameras and photomultiplier tubes (PMTs) to achieve high spatial resolution and timing information. This approach enables detailed track reconstruction but poses significant challenges for data acquisition, particularly in view of the next experimental phase, CYGNO-04, which will operate multiple cameras simultaneously. In this paper, we present an upgrade of the CYGNO Trigger and Data Acquisition (T-DAQ) system, developed starting from the LIME configuration and validated on the MANGO prototype. The upgrade introduces a continuous imaging acquisition mode, substantially reducing the camera dead time, together with an extended trigger time-tagging scheme that provides a robust global time reference for PMT signals. A synchronous multi-camera DAQ architecture is also implemented and tested, enabling coordinated operation of multiple optical sensors without a master camera. The performance of the upgraded system is validated through dedicated tests, demonstrating stable continuous acquisition, reliable time-tagging, and consistent synchronization across multiple cameras. These results establish a solid and scalable foundation for the CYGNO-04 DAQ and represent a key step toward efficient data acquisition in future large-scale optical TPC detectors.

Upgrade of the Trigger and Data Acquisition System for Continuous Imaging and Multi-Camera Operation in CYGNO

Abstract

The CYGNO experiment employs an optical readout to image particle interactions in a gaseous Time Projection Chamber (TPC), combining cameras and photomultiplier tubes (PMTs) to achieve high spatial resolution and timing information. This approach enables detailed track reconstruction but poses significant challenges for data acquisition, particularly in view of the next experimental phase, CYGNO-04, which will operate multiple cameras simultaneously. In this paper, we present an upgrade of the CYGNO Trigger and Data Acquisition (T-DAQ) system, developed starting from the LIME configuration and validated on the MANGO prototype. The upgrade introduces a continuous imaging acquisition mode, substantially reducing the camera dead time, together with an extended trigger time-tagging scheme that provides a robust global time reference for PMT signals. A synchronous multi-camera DAQ architecture is also implemented and tested, enabling coordinated operation of multiple optical sensors without a master camera. The performance of the upgraded system is validated through dedicated tests, demonstrating stable continuous acquisition, reliable time-tagging, and consistent synchronization across multiple cameras. These results establish a solid and scalable foundation for the CYGNO-04 DAQ and represent a key step toward efficient data acquisition in future large-scale optical TPC detectors.
Paper Structure (16 sections, 4 equations, 6 figures)

This paper contains 16 sections, 4 equations, 6 figures.

Table of Contents

  1. Introduction
  2. The CYGNO LIME-Based T-DAQ System
  3. LIME DAQ architecture and trigger logic
  4. Limitations of the frame-based acquisition scheme
  5. Continuous Imaging T-DAQ Upgrade
  6. Design Requirements and Concept
  7. Continuous Imaging Implementation
  8. Extended Group Trigger Time Tag
  9. Performance Validation
  10. Multi-Camera Synchronous DAQ Architecture
  11. Synchronization Strategy
  12. Hardware Logic and Timing Distribution
  13. Performance Validation
  14. Synchronization between camera and PMT time coordinates
  15. Discussion and Implications for CYGNO-04
  16. ...and 1 more sections

Figures (6)

  • Figure 1: Complete scheme of the LIME DAQ employing NIM and VME modules. The delivered trigger is shown in green, while the coincidence signals producing it are shown in red.
  • Figure 2: Timing diagram of the LIME camera acquisition. The software trigger starts the exposure of the CMOS rows, during which the global exposure (GE) occurs when all rows are simultaneously active. The corresponding CAMEXP and GE NIM logic signals are shown in the lower traces. The diagram also reports the PMT coincidence signal. In the second frame shown, no PMT coincidence occurs within the camera-sensitive interval and the camera image is therefore not acquired.
  • Figure 3: Timing diagram of the camera operated in continuous acquisition mode. The camera is started by a single software trigger at the beginning of the run and subsequently acquires frames continuously. The exposure proceeds without interruptions on a frame-by-frame basis, resulting in a negligible dead-time fraction.
  • Figure 4: Scheme of the MANGO multi-camera DAQ architecture employing NIM and VME modules. The configuration is illustrated with two cameras for clarity, although the design is modular and scalable to a larger number of devices. The PMT readout chain is omitted, as it follows the same logic adopted in the LIME DAQ. The signals contributing to the generation of the SYNC-IN reference for the digitizer are highlighted in blue.
  • Figure 5: Timing diagram of the cameras operated in synchronous readout trigger mode. The first trigger pulse starts the exposure of the initial frame, while subsequent frames are advanced after a predefined number of input pulses. This scheme ensures that all cameras share a common exposure cadence and aligned frame boundaries.
  • ...and 1 more figures