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Register a new userOptical transmission matrix as a probe of the photonic interaction strength
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We demonstrate that optical transmission matrices (TM) of disordered complex media provide a powerful tool to extract the photonic interaction strength, independent of surface effects. We measure TM of strongly scattering GaP nanowires and plot the singular value density of the measured matrices and a random matrix model. By varying the free parameters of the model, the transport mean free path and effective refractive index, we retrieve the photonic interaction strength. From numerical simulations we conclude that TM statistics is hardly sensitive to surface effects, in contrast to enhanced backscattering or total transmission based methods.
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We study the electromagnetic transmission $T$ through one-dimensional (1D) photonic heterostructures whose random layer thicknesses follow a long-tailed distribution --Levy-type distribution. Based on recent predictions made for 1D coherent transport with Levy-type disorder, we show numerically that for a system of length $L$ (i) the average $<-ln T> propto L^alpha$ for $0<alpha<1$, while $<-ln T> propto L$ for $1lealpha<2$, $alpha$ being the exponent of the power-law decay of the layer-thickness probability distribution; and (ii) the transmission distribution $P(T)$ is independent of the angle of incidence and frequency of the electromagnetic wave, but it is fully determined by the values of $alpha$ and $<ln T>$.
Measurement of the optical transmission matrix (TM) of an opaque material is an advanced form of space-variant aberration correction. Beyond imaging, TM-based methods are emerging in a range of fields including optical communications, optical micro-manipulation, and optical computing. In many cases the TM is very sensitive to perturbations in the configuration of the scattering medium it represents. Therefore applications often require an up-to-the-minute characterisation of the fragile TM, typically entailing hundreds to thousands of probe measurements. In this work we explore how these measurement requirements can be relaxed using the framework of compressive sensing: incorporation of prior information enables accurate estimation from fewer measurements than the dimensionality of the TM we aim to reconstruct. Examples of such priors include knowledge of a memory effect linking input and output fields, an approximate model of the optical system, or a recent but degraded TM measurement. We demonstrate this concept by reconstructing a full-size TM of a multimode fibre supporting 754 modes at compression ratios down to ~5% with good fidelity. The level of compression achievable is dependent upon the strength of our priors. We show in this case that imaging is still possible using TMs reconstructed at compression ratios down to ~1% (8 probe measurements). This compressive TM sampling strategy is quite general and may be applied to any form of scattering system about which we have some prior knowledge, including diffusers, thin layers of tissue, fibre optics of any known refractive profile, and reflections from opaque walls. These approaches offer a route to measurement of high-dimensional TMs quickly or with access to limited numbers of measurements.
The optical memory effect has emerged as a powerful tool for imaging through multiple-scattering media; however, the finite angular range of the memory effect limits the field of view. Here, we demonstrate experimentally that selective coupling of incident light into a high-transmission channel increases the angular memory-effect range. This enhancement is attributed to the robustness of the high-transmission channels against perturbations such as sample tilt or wavefront tilt. Our work shows that the high-transmission channels provide an enhanced field of view for memory effect-based imaging through diffusive media.
Optical non-linearities usually appear for large intensities, but discrete transitions allow for giant non-linearities operating at the single photon level. This has been demonstrated in the last decade for a single optical mode with cold atomic gases, or single two-level systems coupled to light via a tailored photonic environment. Here we demonstrate a two-modes giant non-linearity by using a three-level structure in a single semiconductor quantum dot (QD) embedded in a photonic wire antenna. The large coupling efficiency and the broad operation bandwidth of the photonic wire enable us to have two different laser beams interacting with the QD in order to control the reflectivity of a laser beam with the other one using as few as 10 photons per QD lifetime. We discuss the possibilities offered by this easily integrable system for ultra-low power logical gates and optical quantum gates.
Resonant transmission of light is a surface-wave assisted phenomenon that enables funneling light through subwavelength apertures milled in otherwise opaque metallic screens. In this work, we introduce a deep learning approach to efficiently compute and design the optical response of a single subwavelength slit perforated in a metallic screen and surrounded by periodic arrangements of indentations. First, we show that a semi-analytical framework based on a coupled-mode theory formalism is a robust and efficient method to generate the large training datasets required in the proposed approach. Second, we discuss how simple, densely connected artificial neural networks can accurately learn the mapping from the geometrical parameters defining the topology of the system to its corresponding transmission spectrum. Finally, we report on a deep learning tandem architecture able to perform inverse design tasks for the considered class of systems. We expect this work to stimulate further work on the application of deep learning to the analysis of light-matter interaction in nanostructured metallic films.
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