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GPU enabled real-time optical frequency comb spectroscopy and photonic readout

Authors :
Bresler, Sean M.
Long, David A.
Reschovsky, Benjamin J.
Bao, Yiliang.
LeBrun, Thomas W.
Publication Year :
2023

Abstract

We describe a GPU-enabled approach for real-time optical frequency comb spectroscopy in which data is recorded, Fourier transformed, normalized, and fit at data rates up to 2.2 GB/s. As an initial demonstration we have applied this approach to rapidly interrogate the motion of an optomechanical accelerometer through the use of an electro-optic frequency comb. However, we note that this approach is readily amenable to both self-heterodyne and dual comb spectrometers for molecular spectroscopy as well as photonic readout where the approach's agility, speed, and simplicity are expected to enable future improvements and applications.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2307.12988
Document Type :
Working Paper