@inproceedings{059236bf8e8e45eb8857546c5cba967e,
title = "FPGA based time-to-digital converters",
abstract = "Time-to-digital converters are a key component in many photonics systems, ranging from LiDAR, quantum key distribution, quantum optics experiments and time correlated single photon counting applications. A novel efficient timeto- digital converter non-linearity calibration technique has been developed and demonstrated on a Spartan 6 LX150 field programmable gate array (FPGA). Most FPGA based time-to-digital converters either use post processing or have calibration techniques which do not focus on minimizing resource utilization. With the move towards imaging with arrays of single photon detectors, scalable timing instrumentation is required. The calibration system demonstrated minimizes block memory utilization, using the same memory for probability density function measurement and cumulative distribution function generation, creating a look up table which can be used to calibrate the sub-clock timing module of the time-to-digital converter. The system developed contains 16 time-to-digital converters and demonstrates an average accuracy of 21ps RMS (14.85ps single channel) with a resolution of 1.86ps.",
keywords = "Photon counting, Time correlated single photon counting, Time-to-digital converters",
author = "Nock, {Richard W.} and Xiao Ai and Yang Lu and Naim Dahnoun and Rarity, {John G.}",
note = "Copyright 2020 SPIE. One print or electronic copy may be made for personal use only. Systematic reproduction, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. ; Quantum Technologies 2020 ; Conference date: 06-04-2020 Through 10-04-2020",
year = "2020",
month = mar,
day = "30",
doi = "10.1117/12.2555997",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Eleni Diamanti and Sara Ducci and Nicolas Treps and Shannon Whitlock",
booktitle = "Quantum Technologies 2020",
address = "United States",
}