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Deep learning enabled laser speckle wavemeter with a high dynamic range

Research output: Contribution to journalArticle

Abstract

The speckle pattern produced when a laser is scattered by a disordered medium has recently been shown to give a surprisingly accurate or broadband measurement of wavelength. Here it is shown that deep learning is an ideal approach to analyse wavelength variations using a speckle wavemeter due to its ability to identify trends and overcome low signal to noise ratio in complex datasets. This combination enables wavelength measurement at high precision over a broad operating range in a single step, with a remarkable capability to reject instrumental and environmental noise, which has not been possible with previous approaches. It is demonstrated that the noise rejection capabilities of deep learning provide attometre-scale wavelength precision over an operating range from 488 nm to 976 nm. This dynamic range is six orders of magnitude beyond the state of the art.
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Original languageEnglish
Article number2000120
Number of pages8
JournalLaser & Photonics Reviews
Volume14
Issue number9
Early online date2 Aug 2020
DOIs
Publication statusPublished - Sep 2020

    Research areas

  • Automated noise rejection, Deep learning, Speckle metrology, Wavelength measurement

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