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

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 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

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

Numerical study on basin-edge effects in the seismic response of the Gubbio valley, Central Italy

The Gubbio basin in Central Italy is a intermountain basin of extensional tectonic origin, typical of Central and Southern Apennines, characterized by moderate seismicity. The strongest recorded event within the area is a magnitude 5.7 earthquake which occurred on 29 April 1984 along the Gubbio fault, bordering the eastern side of the basin. The main objective of this study is to analyze the features of earthquake ground motion as related to basin-edge effects, by performing physics-based numerical simulations of the 1984 earthquake through a high-performance spectral element code. The simulated ground motions are found in reasonable agreement with the recorded motions when using the kinematic source model developed by Ameri et al. (Bull Seismol Soc Am 99:647–663, 2009), with a rise-time equal to 1 s and a nucleation point located in the middle of the fault. Pronounced differences were noted between records from the basin and adjacent sites at outcropping bedrock, owing to both the strong impedance contrast between soft alluvial sites and bedrock formations (lithostratigraphic amplification), as well as lateral discontinuities related to the 2D/3D geometry of the basin (generation of surface waves). Since the fault was located beneath the basin, 1D amplification effects were found to be more relevant than those associated with the generation of surface waves from the basin edge. Finally, an envelope delay spectrum was computed for the simulated ground motions, showing that surface waves are excited in the frequency band of 0.2–0.8 Hz with a significant increase of ground motion duration within the basin