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

Observation of Fermi-Pasta-Ulam-Tsingou Recurrence and Its Exact Dynamics

One of the most controversial phenomena in nonlinear dynamics is the reappearance of initial conditions. Celebrated as the Fermi-Pasta-Ulam-Tsingou problem, the attempt to understand how these recurrences form during the complex evolution that leads to equilibrium has deeply influenced the entire development of nonlinear science. The enigma is rendered even more intriguing by the fact that integrable models predict recurrence as exact solutions, but the difficulties involved in upholding integrability for a sufficiently long dynamic has not allowed a quantitative experimental validation. In natural processes, coupling with the environment rapidly leads to thermalization, and finding nonlinear multimodal systems presenting multiple returns is a long-standing open challenge. Here, we report the observation of more than three Fermi-Pasta-Ulam-Tsingou recurrences for nonlinear optical spatial waves and demonstrate the control of the recurrent behavior through the phase and amplitude of the initial field. The recurrence period and phase shift are found to be in remarkable agreement with the exact recurrent solution of the nonlinear Schrödinger equation, while the recurrent behavior disappears as integrability is lost. These results identify the origin of the recurrence in the integrability of the underlying dynamics and allow us to achieve one of the basic aspirations of nonlinear dynamics: the reconstruction, after several return cycles, of the exact initial condition of the system, ultimately proving that the complex evolution can be accurately predicted in experimental conditions.

D. Pierangeli, M. Flammini, L. Zhang, G. Marcucci, A. J. Agranat,
P. G. Grinevich, P. M. Santini, C. Conti, and E. DelRe in PHYSICAL REVIEW X 8, 041017 (2018)

10th Optoelectronics and Photonics Winter School: NLP2019 – Nonlinear Photonics

The School aims in bringing together a large number of PhD students and young researchers from all parts of the world which, during a  one-week intense schedule will follow a series of lectures on nonlinear photonics. The lectures are held by internationally recognized experts in the field. At the same, the students are  encouraged to enjoy the beautiful location where the school is  organized. These Optoelectronics and Photonics Winter School series are traditionally held in Trentino region every second year and have  a very good reputation for the in-depth coverage of a topic and the lively atmosphere where ideas exchanges, discussions and amusements  are all blended to give a strong physical flavor.

https://event.unitn.it/nlp2019/
Website of the school 

Nonlinear transmission matrix of random optical 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, 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 we
report the direct measurement of the nonlinear transmission matrix of complex materials, exploiting the strong optothermal nonlinearity of scattering Silica Aerogel (SA). We show 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.

A. Fleming, C. Conti, A. Di Falco, arXiv:1809.07077