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.

Publication DOI: https://doi.org/10.1117/12.2555997
Divisions: Aston University (General)
Funding Information: The authors would like to thank QUANTIC for the partnership resource funding which made the development of the new 16-channel hardware possible.
Additional Information: 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.
Event Title: Quantum Technologies 2020
Event Type: Other
Event Dates: 2020-04-06 - 2020-04-10
Uncontrolled Keywords: Photon counting,Time correlated single photon counting,Time-to-digital converters,Electronic, Optical and Magnetic Materials,Condensed Matter Physics,Computer Science Applications,Applied Mathematics,Electrical and Electronic Engineering
ISBN: 9781510634664
Last Modified: 01 Nov 2024 08:45
Date Deposited: 09 Jun 2020 09:02
Full Text Link:
Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
https://www.spi ... 997.short?SSO=1 (Publisher URL)
PURE Output Type: Conference contribution
Published Date: 2020-03-30
Accepted Date: 2020-01-01
Authors: Nock, Richard W. (ORCID Profile 0000-0001-8384-9621)
Ai, Xiao
Lu, Yang
Dahnoun, Naim
Rarity, John G.

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