UTILIZING FPGA TECHNOLOGY FOR REAL-TIME SPECTROSCOPIC ANALYSIS IN CAVITY RING-DOWN COMB SPECTROSCOPY WITH MACHINE LEARNING-ASSISTED COMB LINE ALIGNMENT

Huang, Yi-Jan

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https://hdl.handle.net/2142/122715 Copy

Description

Title

UTILIZING FPGA TECHNOLOGY FOR REAL-TIME SPECTROSCOPIC ANALYSIS IN CAVITY RING-DOWN COMB SPECTROSCOPY WITH MACHINE LEARNING-ASSISTED COMB LINE ALIGNMENT

Author(s)

Huang, Yi-Jan

Contributor(s)

• Chen, Tzu-Ling
• Okumura, Mitchio
• Bagheri, Mahmood
• Meyer, Jerry R
• Frez, Clifford
• Vurgaftman, Igor
• Canedy, Chadwick L
• Ober, Douglas
• Sterczewski, Lukasz A.
• Markus, Charles R.

Issue Date

2023-06-21

Keyword(s)

Instrument/Technique Demonstration

Abstract

In this work, we propose a novel approach for spectroscopic analysis in Cavity Ring-Down Comb Vernier Spectroscopy (CRDCVS) by exploiting FPGA architecture and an Arm-based embedded Linux system. This approach takes advantage of the high-speed data processing and acquisition capabilities of FPGA. In the Vernier configuration, a mode-resolved comb spectrum should align non-equidistant comb peaks in different scans and fitting the ring down time for each comb line. Especially a significant challenge in spectroscopic analysis is presented when the sample accumulation is required for improved sensitivity or temporal resolution. To address this challenge, we developed a machine-learning framework to predict comb line appearance in the operating platform. This enables ring-down-time accumulation for different comb peaks in CRDCVS. We demonstrated the proof-of-principle performance of the developed system with CRDCS measurements of toluene using a 3.3um chip-scale Interband Cascade Laser (ICL) comb. We will discuss the overall performance and the potential to advance the field of CRDCVS by improving measurement accuracy and reliability.

Publisher

International Symposium on Molecular Spectroscopy

Type of Resource

Text

Language

eng

Handle URL

https://hdl.handle.net/2142/122715

DOI

https://doi.org/10.15278/isms.2023.7343

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