Machine Learning Self-Calibrated FPGA Time-to-Digital Converter

This episode explores an FPGA-based time-to-digital converter that combines careful delay-line layout with machine-learning-based calibration to achieve very fine timing measurements on real hardware. It explains how tapped-delay-line TDCs work, why real FPGA implementations suffer from nonuniform time bins and bubble errors, and why those imperfections matter for applications like LiDAR, medical imaging, particle physics, and high-speed communications. The discussion compares the new approach against earlier FPGA TDC work, arguing that the real contribution is not flashy AI but a practical learned decoder that maps a 940-bit raw hardware output into a more accurate time estimate after physical design has reduced as much noise as possible. Listeners would find it interesting because it gets specific about where machine learning genuinely helps in instrumentation: not replacing physics, but reducing calibration effort while preserving picosecond-level precision. Sources: 1. Machine Learning Self-Calibrated FPGA Time-to-Digital Converter https://podcast.do-not-panic.com/uploaded-pdfs/2026-05-08T03-07-35-153Z-1-s2.0-S2667305326000190-main.pdf 2. A 19.6 ps, FPGA-Based TDC With Multiple Channels for Open Source Applications — Matthew W. Fishburn, L. Harmen Menninga, Claudio Favi, Edoardo Charbon, 2013 https://scholar.google.com/scholar?q=A+19.6+ps%2C+FPGA-Based+TDC+With+Multiple+Channels+for+Open+Source+Applications 3. A low nonlinearity, missing-code free time-to-digital converter based on 28nm FPGAs with embedded bin-width calibrations — Haochang Chen, Yongliang Zhang, David Day-Uei Li, 2017 https://scholar.google.com/scholar?q=A+low+nonlinearity%2C+missing-code+free+time-to-digital+converter+based+on+28nm+FPGAs+with+embedded+bin-width+calibrations 4. A 19 ps Precision and 170 M Samples/s Time-to-Digital Converter Implemented in FPGA with Online Calibration — Mengdi Zhang, Ye Zhao, Zhengsheng Han, Fazhan Zhao, 2022 https://scholar.google.com/scholar?q=A+19+ps+Precision+and+170+M+Samples%2Fs+Time-to-Digital+Converter+Implemented+in+FPGA+with+Online+Calibration 5. Low-Resource Time-to-Digital Converters for Field Programmable Gate Arrays: A Review — Diego Real, David Calvo, 2024 https://scholar.google.com/scholar?q=Low-Resource+Time-to-Digital+Converters+for+Field+Programmable+Gate+Arrays%3A+A+Review 6. Calibration Methods for Time-to-Digital Converters — Wassim Khaddour, Wilfried Uhring, Foudil Dadouche, Norbert Dumas, Morgan Madec, 2023 https://scholar.google.com/scholar?q=Calibration+Methods+for+Time-to-Digital+Converters 7. Time Resolution Improvement Using Dual Delay Lines for Field-Programmable-Gate-Array-Based Time-to-Digital Converters with Real-Time Calibration — Yuan-Ho Chen, 2019 https://scholar.google.com/scholar?q=Time+Resolution+Improvement+Using+Dual+Delay+Lines+for+Field-Programmable-Gate-Array-Based+Time-to-Digital+Converters+with+Real-Time+Calibration 8. Novel machine learning-driven optimizing decoding solutions for FPGA-based time-to-digital converters — Fabio Garzetti, Nicola Lusardi, Enrico Ronconi, Andrea Costa, Angelo Geraci, 2024 https://scholar.google.com/scholar?q=Novel+machine+learning-driven+optimizing+decoding+solutions+for+FPGA-based+time-to-digital+converters 9. A novel FPGA-based time-to-digital converter featuring machine learning-aided self-calibration — Arash Amini Bardpareh, Eleonora Vacca, Davide Nicolini, Corrado De Sio, Sarah Azimi, Luca Sterpone, Elisa Fiorina, Emanuele Maria Data, Felix Mas Milian, 2026 https://scholar.google.com/scholar?q=A+novel+FPGA-based+time-to-digital+converter+featuring+machine+learning-aided+self-calibration 10. Multiple-tapped-delay-line hardware-linearisation technique based on wire load regulation — Dariusz Chaberski, Robert Frankowski, Marek Zielinski, Lukasz Zaworski, 2016 https://scholar.google.com/scholar?q=Multiple-tapped-delay-line+hardware-linearisation+technique+based+on+wire+load+regulation 11. 5.7 ps Resolution Time-to-Digital Converter Implementation Using Routing Path Delays — Roza Teklehaimanot Siecha, Getachew Alemu, Jeffrey Prinzie, Paul Leroux, 2023 https://scholar.google.com/scholar?q=5.7+ps+Resolution+Time-to-Digital+Converter+Implementation+Using+Routing+Path+Delays 12. Tapped delay line for compact time-to-digital converter on UltraScale FPGA and its coding method — Min Zhu, Xihan Qi, Tang Cui, Qiang Gao, 2023 https://scholar.google.com/scholar?q=Tapped+delay+line+for+compact+time-to-digital+converter+on+UltraScale+FPGA+and+its+coding+method 13. A High-Resolution (<10 ps RMS) 48-Channel Time-to-Digital Converter (TDC) Implemented in a Field Programmable Gate Array (FPGA) — Eugen Bayer, Michael Traxler, 2011 https://scholar.google.com/scholar?q=A+High-Resolution+%28%3C10+ps+RMS%29+48-Channel+Time-to-Digital+Converter+%28TDC%29+Implemented+in+a+Field+Programmable+Gate+Array+%28FPGA%29 14. A Low Nonlinearity, Missing-Code Free Time-to-Digital Converter Based on 28-nm FPGAs With Embedded Bin-Width Calibrations — Haochang Chen, Yongliang Zhang, David Day-Uei Li, 2017 https://scholar.google.com/scholar?q=A+Low+Nonlinearity%2C+Missing-Code+Free+Time-to-Digital+Converter+Based+on+28-nm+FPGAs+With+Embedded+Bin-Width+Calibrations 15. High-Performance Time-to-Digital Converter IP-Core for Xilinx Ultrascale/Ultrascale+ FPGAs — Nicola Lusardi, Fabio Garzetti, E. Ronconi, Nicola Corna, Andrea Costa, Angelo Geraci, 2022 https://scholar.google.com/scholar?q=High-Performance+Time-to-Digital+Converter+IP-Core+for+Xilinx+Ultrascale%2FUltrascale%2B+FPGAs 16. An FPGA-Based Time-to-Digital Converter With Online Dual-Chain Calibration — authors unclear from snippet, recent; exact year unclear https://scholar.google.com/scholar?q=An+FPGA-Based+Time-to-Digital+Converter+With+Online+Dual-Chain+Calibration 17. A review of advancements and trends in time-to-digital converters based on FPGA — authors unclear from snippet, recent; exact year unclear https://scholar.google.com/scholar?q=A+review+of+advancements+and+trends+in+time-to-digital+converters+based+on+FPGA 18. A study on the effect of temperature variations on FPGA-based multi-channel time-to-digital converters — authors unclear from snippet, recent; exact year unclear https://scholar.google.com/scholar?q=A+study+on+the+effect+of+temperature+variations+on+FPGA-based+multi-channel+time-to-digital+converters 19. Heterogeneous Tapped Delay-Line Time-to-Digital Converter on Artix-7 FPGA — authors unclear from snippet, recent; exact year unclear https://scholar.google.com/scholar?q=Heterogeneous+Tapped+Delay-Line+Time-to-Digital+Converter+on+Artix-7+FPGA 20. A New Implementation of Tapped-Delay-Line Based High-Performance Time-to-Digital Converter on Xilinx Kintex-7 FPGA — authors unclear from snippet, recent; exact year unclear https://scholar.google.com/scholar?q=A+New+Implementation+of+Tapped-Delay-Line+Based+High-Performance+Time-to-Digital+Converter+on+Xilinx+Kintex-7+FPGA 21. NN-Based Encoding Applied to a Time-to-Digital Converter for Time Interval Measurements — authors unclear from snippet, recent; exact year unclear https://scholar.google.com/scholar?q=NN-Based+Encoding+Applied+to+a+Time-to-Digital+Converter+for+Time+Interval+Measurements 22. AI Post Transformers: FPGA Neural Network Accelerators for Space — Hal Turing & Dr. Ada Shannon, 2026 https://podcast.do-not-panic.com/episodes/2026-04-26-fpga-neural-network-accelerators-for-spa-3087ae.mp3 23. AI Post Transformers: Caffeine: A Unified FPGA for CNNs — Hal Turing & Dr. Ada Shannon, 2026 https://podcast.do-not-panic.com/episodes/2026-05-06-caffeine-a-unified-fpga-for-cnns-e8acbe.mp3 Interactive Visualization: Machine Learning Self-Calibrated FPGA Time-to-Digital Converter