Large-scale photonic natural language processing

Modern machine-learning applications require huge artificial networks demanding computational power and memory. Light-based platforms promise ultrafast and energy-efficient hardware, which may help realize next -generation data processing devices. However, current photonic networks are limited by the number of input-output nodes that can be processed in a single shot. This restricted network capacity prevents their application to relevant large-scale problems such as natural language processing. Here, we realize a photonic processor for supervised learning with a capacity exceeding 1.5 x 1010 optical nodes, more than one order of magnitude larger than any previous implementation, which enables photonic large-scale text encoding and classification. By exploiting the full three-dimensional structure of the optical field propagating in free space, we overcome the interpolation threshold and reach the over-parameterized region of machine learning, a condition that allows high-performance sentiment analysis with a minimal fraction of training points. Our results provide a novel sol-ution to scale up light-driven computing and open the route to photonic natural language processin

Deep reinforcement learning control of white-light continuum generation

White-light continuum (WLC) generation in bulk media finds numerous applications in ultrafast optics and spectroscopy. Due to the complexity of the underlying spatiotemporal dynamics, WLC optimization typically follows empirical procedures. Deep reinforcement learning (RL) is a branch of machine learning dealing with the control of automated systems using deep neural networks. In this Letter, we demonstrate the capability of a deep RL agent to generate a long-term-stable WLC from a bulk medium without any previous knowledge of the system dynamics or functioning. This work demonstrates that RL can be exploited effectively to control complex nonlinear optical experiments

Artificial Intelligence in Classical and Quantum Photonics

The last decades saw a huge rise of artificial intelligence (AI) as a powerful tool to boost industrial and scientific research in a broad range of fields. AI and photonics are developing a promising two-way synergy: on the one hand, AI approaches can be used to control a number of complex linear and nonlinear photonic processes, both in the classical and quantum regimes; on the other hand, photonics can pave the way for a new class of platforms to accelerate AI-tasks. This review provides the reader with the fundamental notions of machine learning (ML) and neural networks (NNs) and presents the main AI applications in the fields of spectroscopy and chemometrics, computational imaging (CI), wavefront shaping and quantum optics. The review concludes with an overview of future developments of the promising synergy between AI and photonics

Broadband Coherent Raman Scattering Microscopy

Spontaneous Raman (SR) microscopy allows label-free chemically specificimaging based on the vibrational response of molecules; however, due to thelow Raman scattering cross section, it is intrinsically slow. Coherent Ramanscattering (CRS) techniques, by coherently exciting vibrational oscillators inthe focal volume, increase signal levels by several orders of magnitude underappropriate conditions. In its single-frequency version, CRS microscopy hasreached very high imaging speeds, up to the video rate; however, it providesinformation which is not sufficient to distinguish spectrally overlappedchemical species within complex heterogeneous systems, such as cells andtissues. Broadband CRS combines the acquisition speed of CRS with theinformation content of SR, but it is technically very demanding. In this Review,the current state of the art in broadband CRS microscopy, both in the coherentanti-Stokes Raman scattering (CARS) and the stimulated Raman scattering(SRS) versions are reviewed. Different technical solutions for broadband CARSand SRS, working both in the frequency and in the time domains, arecompared and their merits and drawbacks assesse

Broadband stimulated Raman imaging based on multi-channel lock-in detection for spectral histopathology

Spontaneous Raman microscopy reveals the chemical composition of a sample in a label-free and non-invasive fashion by directly measuring the vibrational spectra of molecules. However, its extremely low cross section prevents its application to fast imaging. Stimulated Raman scattering (SRS) amplifies the signal by several orders of magnitude thanks to the coherent nature of the nonlinear process, thus unlocking high-speed microscopy applications that provide analytical information to elucidate biochemical mechanisms with subcellular resolution. Nevertheless, in its standard implementation, narrowband SRS provides images at only one frequency at a time, which is not sufficient to distinguish constituents with overlapping Raman bands. Here, we report a broadband SRS microscope equipped with a home-built multichannel lock-in amplifier simultaneously measuring the SRS signal at 32 frequencies with integration time down to 44 μs, allowing for detailed, high spatial resolution mapping of spectrally congested samples. We demonstrate the capability of our microscope to differentiate the chemical constituents of heterogeneous samples by measuring the relative concentrations of different fatty acids in cultured hepatocytes at the single lipid droplet level and by differentiating tumor from peritumoral tissue in a preclinical mouse model of fibrosarcoma

The 2013 European Seismic Hazard Model: key components and results

The 2013 European Seismic Hazard Model (ESHM13) results from a community-based probabilistic seismic hazard assessment supported by the EU-FP7 project “Seismic Hazard Harmonization in Europe” (SHARE, 2009–2013). The ESHM13 is a consistent seismic hazard model for Europe and Turkey which overcomes the limitation of national borders and includes a through quantification of the uncertainties. It is the first completed regional effort contributing to the “Global Earthquake Model” initiative. It might serve as a reference model for various applications, from earthquake preparedness to earthquake risk mitigation strategies, including the update of the European seismic regulations for building design (Eurocode 8), and thus it is useful for future safety assessment and improvement of private and public buildings. Although its results constitute a reference for Europe, they do not replace the existing national design regulations that are in place for seismic design and construction of buildings. The ESHM13 represents a significant improvement compared to previous efforts as it is based on (1) the compilation of updated and harmonised versions of the databases required for probabilistic seismic hazard assessment, (2) the adoption of standard procedures and robust methods, especially for expert elicitation and consensus building among hundreds of European experts, (3) the multi-disciplinary input from all branches of earthquake science and engineering, (4) the direct involvement of the CEN/TC250/SC8 committee in defining output specifications relevant for Eurocode 8 and (5) the accounting for epistemic uncertainties of model components and hazard results. Furthermore, enormous effort was devoted to transparently document and ensure open availability of all data, results and methods through the European Facility for Earthquake Hazard and Risk (www.​efehr.​org)

Broadband stimulated Raman scattering microscopy with wavelength‐scanning detection

We introduce a high-sensitivity broadband stimulated Raman scattering (SRS) setup featuring wide spectral coverage (up to 500 cm(-1)) and high-frequency resolution (approximate to 20 cm(-1)). The system combines a narrowband Stokes pulse, obtained by spectral filtering an Yb laser, with a broadband pump pulse generated by a home-built optical parametric oscillator. A single-channel lock-in amplifier connected to a single-pixel photodiode measures the stimulated Raman loss signal, whose spectrum is scanned rapidly using a galvanometric mirror after the sample. We use the in-line balanced detection approach to suppress laser fluctuations and achieve close to shot-noise-limited sensitivity. The setup is capable of measuring accurately the SRS spectra of several solvents and of obtaining hyperspectral data cubes consisting in the broadband SRS microscopy images of polymer beads test samples as well as of the distribution of different biological substances within plant cell walls