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Preprints, Working Papers, ... Year : 2023

Time-domain Compressed Sensing

Kilian Scheffter
  • Function : Author
Jonathan Will
  • Function : Author
Claudius Riek
  • Function : Author
Herve Jousselin
  • Function : Author
Sebastien Coudreau
  • Function : Author
Nicolas Forget
Hanieh Fattahi
  • Function : Author

Abstract

Ultrashort time-domain spectroscopy, particularly field-resolved spectroscopy, are established methods for identifying the constituents and internal dynamics of samples. However, these techniques are often encumbered by the Nyquist criterion, leading to prolonged data acquisition and processing times as well as sizable data volumes. To mitigate these issues, we have successfully implemented the first instance of time-domain compressed sensing, enabling us to pinpoint the primary absorption peaks of atmospheric water vapor in response to tera-hertz light transients that exceed the Nyquist limit. Our method demonstrates successful identification of water absorption peaks up to 2.5 THz, even for sampling rates where the Nyquist frequency is as low as 0.75 THz, with a mean squared error of 12*10-4. Time-domain sparse sampling achieves considerable data compression while also expediting both the measurement and data processing time, representing a significant stride towards the realm of real-time spectroscopy
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Dates and versions

hal-04308317 , version 1 (27-11-2023)

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Kilian Scheffter, Jonathan Will, Claudius Riek, Herve Jousselin, Sebastien Coudreau, et al.. Time-domain Compressed Sensing. 2023. ⟨hal-04308317⟩
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