Search

We demonstrate machine-learning assisted dynamic tracking of the shape of a multimode fiber whose spatial configuration is manipulated by the movement of three linear stages. The data source used for the analysis is the coherent speckle pattern of light that has made a round trip in the fiber.

Light propagation in optical fibers is accompanied by random omnidirectional scattering. The small fraction of coherent guided light that escapes outside the cladding of the fiber forms a speckle pattern. Here, visual information imaged into the input facet of a multimode fiber with a transparent buffer is retrieved, using a convolutional neural network, from the side-scattered light at several locations along the fiber. This demonstration can promote the development of distributed optical imaging systems and optical links interfaced via the sides of the fiber.

Using a superposition of shifted Bessel beams with different longitudinal wave vectors and orbital angular momenta, we realize an optical beam having simultaneous axial, angular, and radial focusing narrower than the Fourier limit. Our findings can be useful for optical particle manipulation and high-resolution microscopy.