Deep learning enabled laser speckle wavemeter with a high dynamic range
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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.
Gupta , R K , Bruce , G D , Powis , S J & Dholakia , K 2020 , ' Deep learning enabled laser speckle wavemeter with a high dynamic range ' , Laser & Photonics Reviews , vol. 14 , no. 9 , 2000120 . https://doi.org/10.1002/lpor.202000120
Laser & Photonics Reviews
DescriptionFunding: This work was supported by a Medical Research Scotland PhD studentship PhD 873-2015 awarded to R.K.G, and grant funding from Leverhulme Trust (RPG-2017-197) and UK Engineering and Physical Sciences Research Council (grant EP/P030017/1).
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