Perturbation of Transmission Matrices in nonlinear random media

Random media with tailored optical properties are attracting burgeoning interest for applications in imaging, biophysics, energy, nanomedicine, spectroscopy, cryptography, and telecommunications. A key paradigm for devices based on this class of materials is the transmission matrix, the tensorial link between the input and the output signals, that describes in full their optical behavior. The transmission matrix has specific statistical properties, such as the existence of lossless channels, that can be used to transmit information, and are determined by the disorder distribution. In nonlinear materials, these channels may be modulated and the transmission matrix tuned accordingly. Here, the direct measurement of the nonlinear transmission matrix of complex materials is reported, exploiting the strong optothermal nonlinearity of scattering silica aerogel (SA). It is shown that the dephasing effects due to nonlinearity are both controllable and reversible, opening the road to applications based on the nonlinear response of random media.

Adam Fleming, Claudio Conti, and Andrea Di Falco in Annalen Der Physics

Optical Spatial Shock Waves in Nonlocal Nonlinear Media

Dispersive shock waves are fascinating phenomena occurring when nonlinearity overwhelms linear effects, such as dispersion and diffraction. Many features of shock waves are still under investigation, as the interplay with noninstantaneity in temporal pulses transmission and nonlocality in spatial beams propagation. Despite the rich and vast literature on nonlinear waves in optical Kerr media, spatial dispersive shock waves in nonlocal materials deserve further attention for their unconventional properties. Indeed, they have been investigated in colloidal matter, chemical physics and biophotonics, for sensing and control of extreme phenomena.
Here we review the last developed theoretical models and recent optical experiments on spatial dispersive shock waves in nonlocal media. Moreover, we discuss observations in novel versatile materials relevant for soft matter and biology.

Giulia Marcucci et al. in arXiv:1907.02823

See also https://giuliasnonlinearworld.wordpress.com/2019/07/08/dswreview/

Graphene oxide photonics

The successful exfoliation of graphite initiated new science in any research field and is employing a huge number of scientists in the world investigating chemical, structural, mechanical and optoelectrical; properties of the atomic-thick sheets of graphene and graphene oxide. Similarly to other carbon-based materials, graphene family have shown exceptional optical responses; and nowadays it is engineered to produce efficient photonic components. In this review we aim to summarize the main results in nonlinear optical response and fluorescence of graphene oxide; moreover, its laser printing is reviewed as a novel promising lithographic technique.

Neda Ghofraniha and Claudio Conti in Journal of Optics


See also …

Deep learning, living, random, optical, and – maybe – useful

In a recent paper, we demonstrated an optical deep neural network with a real living piece of brain tumor (a 3D “tumour model”). We think this is the first example of a hybrid living/photonic hardware: a sort of artificially intelligent device performing optical functions and detecting tumour morphodynamics (including the effect of chemotherapy)

Deep optical neural network by living tumour brain cells

Abstract: The new era of artificial intelligence demands large-scale ultrafast hardware for machine learning. Optical artificial neural networks process classical and quantum information at the speed of light, 
and are compatible with silicon technology, but lack scalability and need expensive manufacturing of many computational layers. New paradigms, as reservoir computing and the extreme learning machine, suggest that disordered and biological materials may realize artificial neural networks with thousands of computational nodes trained only at the input and at the readout. Here we employ biological complex systems, i.e., living three-dimensional tumour brain models, and demonstrate a random neural network (RNN) trained to detect tumour morphodynamics via
image transmission. The RNN, with the tumour spheroid 19 as a three-dimensional deep computational reservoir, performs programmed optical functions and detects cancer morphodynamics from laser-induced hyperthermia inaccessible by optical imaging. Moreover, the RNN quantifies the effect of chemotherapy inhibiting tumour growth. We realize a non-invasive smart probe for cytotoxicity assay, which is at least one order of magnitude more sensitive with respect to conventional imaging. Our random and hybrid photonic/living system is a novel artificial machine for computing and for the real-time investigation of tumour dynamics.

Authors: D. Pierangeli, V. Palmieri, G. Marcucci, C. Moriconi, G. Perini, M. De Spirito, M. Papi, C. Conti

https://arxiv.org/abs/1812.09311