Learning and avoiding disorder in multimode fibers

[M.W. Matthès, arxiv, 2010.14813 (2020)]

In the past 10+ years, numerous advances were made for endoscopic imaging, micromanipulation, or telecommunication applications with multimode fiber. The main limitation to real-life applications is the sensitivity to perturbations that sometimes causes the transmission property of the fiber to change in real-time. To address this issue, the authors (we) show that, even in the presence of strong perturbations, there exists a set of channels that are almost insensitive to perturbations. Interestingly, these channels can be found using only measurements from small perturbation leveraging the so-called generalized Wigner-Smith operator. This requires the measurement of the transmission matrix, which is done thanks to a new technique based on deep learning frameworks that compensate automatically for misalignments and aberrations, allowing fast and easy acquisitions.

Controlling multimode laser modes using wavefront shaping inside the cavity

[X. Wei et al., Light Sci. Appl., 9 (2020)]

Multimode cavity lasers, such as multimode fiber lasers, are attractive for the opportunity they offer to generate high energy pulsed lasers, provided that one can achieve spatiotemporal mode-locking. However, it can be complicated to control the laser properties as 1) spatiotemporal dispersion, nonlinearity, gain and loss can nonlinearly interact, and 2) dispersion and mode coupling in such a system are difficult to predict or control. In a typical wavefront shaping experiment, one modulates the output of a laser beam, which can come at the cost of a significant energy loss, and only allows to control the spatial profile of the beam. In this paper, the authors use a spatial light modulator, but inside the laser cavity to modulate its boundary conditions. Using a genetic algorithm, they are able to efficiently control the laser properties, namely the output power, the output mode profile, the optical spectrum, and mode-locking.

Using prior information for speeding up the measurement of fiber transmission matrices

[S. Li et al., arxiv, 2007.15891, (2020)]

Due to disorder and dispersion, knowing the transmission matrix of a multimode fiber is usually required to reconstruct an input image for endoscopic applications. In the general case, its characterization for a fiber allowing \(N\) guided modes requires at least \(N\) complex measurements. However, we usually have additional information, the most common one being that the matrix is never totally random, and usually sparse, when expressed in the mode basis. In this study, the authors use such prior information to reduce drastically the number of measurements for the transmission matrix estimation using the framework of compressed sensing. They demonstrate the validity of such an approach for endoscopic imaging through multimode fibers.

Postdoctoral position at the Langevin Institute

Wavefront shaping and study of light propagation in disordered multimode fibers

We are recruiting a postdoc for 1+ year(s) to work on the study of light propagation in multimode fibers for telecommunication applications using wavefront shaping. Join un in Paris!

See our most recent publication: [Learning and avoiding disorder in multimode fibers, arxiv, 2020]

Contact: Sébastien Popoff - sebastien.popoff(at)espci.fr

More information here.