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Physics > Instrumentation and Detectors

arXiv:2509.14649 (physics)
[Submitted on 18 Sep 2025 ]

Title: Intensified optical camera with Timepix4 readout

Title: 带有Timepix4读出的增强型光学相机

Authors:Erik Hogenbirk, Andrei Nomerotski, Bram Bouwens, Gabriel Diaz, Shazia Farooq, Erik Maddox, Ondrej Matousek, Peter Svihra, Henrique Zanoli
Abstract: We report the first characterization results of an optical time-stamping camera based on the Timepix4 chip coupled to a fully depleted optical silicon sensor and fast image intensifier, enabling sub-nanosecond scale, time-resolved imaging for single photons. The system achieves an RMS time resolution of 0.27 ns in direct detection mode without the intensifier and from 0.55 to 1.4 ns in the single-photon regime with intensifier for different amplitude-based signal selections. This shows that Timepix4 provides a significant improvement over previous Timepix3-based cameras in terms of timing precision, pixel count, and data throughput. We analyze key factors that affect performance, including sensor bias and time-walk, and demonstrate effective correction methods to recover high temporal accuracy. The camera temporal resolution, event-driven readout and high rate capability make it a scalable platform for a wide range of applications, including quantum optics, ultrafast imaging, and time-correlated photon counting experiments.
Abstract: 我们报告了基于与完全耗尽的光学硅传感器和快速图像增强器耦合的Timepix4芯片的光学时间标记相机的首次表征结果,该相机能够实现亚纳秒级的时间分辨单光子成像。 系统在直接检测模式下(不使用增强器)实现了0.27 ns的均方根时间分辨率,在不同基于幅度的信号选择下,使用增强器时在单光子模式下的时间分辨率从0.55 ns到1.4 ns不等。 这表明,与之前的基于Timepix3的相机相比,Timepix4在时间精度、像素数量和数据吞吐量方面都有显著提升。 我们分析了影响性能的关键因素,包括传感器偏置和时间走动,并展示了有效的校正方法以恢复高时间精度。 该相机的时间分辨率、事件驱动读出和高率能力使其成为一个可扩展的平台,适用于量子光学、超快成像和时间相关光子计数实验等多种应用。
Subjects: Instrumentation and Detectors (physics.ins-det) ; Optics (physics.optics)
Cite as: arXiv:2509.14649 [physics.ins-det]
  (or arXiv:2509.14649v1 [physics.ins-det] for this version)
  https://doi.org/10.48550/arXiv.2509.14649
arXiv-issued DOI via DataCite

Submission history

From: Andrei Nomerotski [view email]
[v1] Thu, 18 Sep 2025 06:09:03 UTC (3,449 KB)
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