Speaker
Description
LANRS (Exploration of Lattice Dynamics of Nanostructures and Active Site Structures in Iron Proteins and Batteries with Nuclear Resonance) is a ministry-funded project aimed at enabling next-generation Nuclear Resonance Scattering (NRS) experiments. These require a large detection area, ultra-high temporal resolution of a few nanoseconds, and the ability to handle high event rates immediately after beam interactions. We present a novel detector concept addressing these needs, based on multiple Timepix3 front-end chips coupled with a high-resolution, ultra-fast sensor that leverages trench-isolated Low Gain Avalanche Diode (LGAD) technology.
Summary (500 words)
In this contribution, we present a novel large-area detector system developed for LANRS experiments, based on Timepix3 front-end ASICs bump-bonded to trench-isolated LGAD (TI-LGAD) sensors fabricated by FBK. The detector architecture addresses several critical challenges related to timing precision, high-rate capability, and continuous long-duration acquisition.
A key focus of the contribution is the full system design, encompassing sensor technology, bonding processes, data acquisition (DAQ) hardware, and control software. The bump-bonding process was developed in-house at KIT, ensuring precise alignment and reliable interconnects between the TI-LGAD sensor and the Timepix3 chip. The front-end is supported by a robust and scalable DAQ system built around the Zynq UltraScale+ (ZYNQ US+) programmable platform. This hardware enables real-time data handling and control with high flexibility and performance.
The system is optimized for continuous-mode operation, capable of sustaining long acquisition periods (several hours) without introducing dead time. Acquired data are transmitted via high-speed optical links using standard Ethernet protocols, supporting data rates up to 40 Gb/s. This ensures reliable and efficient transfer of large data volumes for downstream processing. The overall architecture is modular and scalable, designed to meet the stringent performance requirements of LANRS experiments while allowing future expansion and adaptation.
On the software side, a dedicated Python-based framework has been developed to manage chip control, data acquisition, and performance characterization. Hosted on the embedded ARM processor of the Zynq platform, this software supports full configuration of the Timepix3 chip, including both global settings and pixel-level registers. All measurement modes are supported: combined timing and energy acquisition, timing-only, energy-only, and integration mode. The software also includes advanced features for system calibration and performance optimization. Automated routines allow for comprehensive noise characterization—with and without the sensor attached—enabling precise identification of electronic noise sources. Moreover, threshold equalization at the pixel level ensures uniform response across the matrix, a critical requirement for accurate energy measurements and spatial resolution.
This software framework is a key component of the detector system, supporting both laboratory development and experimental deployment. It enables calibration, monitoring, and data quality assessment, ensuring reliable detector operation under demanding conditions. Overall, the presented detector system combines cutting-edge sensor and electronics technology with a robust DAQ and software infrastructure, offering a powerful and flexible platform for time-resolved studies in advanced Nuclear Resonance Scattering experiments.
