Optics (physics.optics)

Abstract: With the end of Moore's Law and the increasing demand for computing, photonic accelerators are garnering considerable attention. This is due to the physical characteristics of light, such as high bandwidth and multiplicity, and the various synchronization phenomena that emerge in the realm of laser physics. These factors come into play as computer performance approaches its limits. In this study, we explore the application of a laser network, acting as a photonic accelerator, to the competitive multi-armed bandit problem. In this context, conflict avoidance is key to maximizing environmental rewards. We experimentally demonstrate cooperative decision-making using zero-lag and lag synchronization within a network of four semiconductor lasers. Lag synchronization of chaos realizes effective decision-making and zero-delay synchronization is responsible for the realization of the collision avoidance function. We experimentally verified a low collision rate and high reward in a fundamental 2-player, 2-slot scenario, and showed the scalability of this system. This system architecture opens up new possibilities for intelligent functionalities in laser dynamics.

Abstract: A Fabry-Perot resonator utilizes two solid, non-resonating, reflecting mirrors to form resonant patterns when the separation between the mirrors satisfies the resonance conditions. The resonant mode concentrates at the middle of the cavity. In this study, we constructed a Fabry-Perot cavity with nanostructured resonant metasurfaces as meta-mirrors. The individual metasurfaces exhibit resonant transmission dips with a minimum transmission and a quality factor of t0 and Qs, respectively. The coherent interference between the two metasurfaces changes the behavior of the entire resonant system, generating an induced transparency in the original spectrum. The sharpness of the induced transparency peak is linearly related to the group delay of the single metasurface. Assuming a Lorentzian lineshape, we show that for small t0, the quality factor of the induced transparency peak is Qs/t0^3. The field confines to the meta-mirrors region rather than at the middle of the Fabry-Perot cavity. We provide examples of practical metasurfaces made from dielectric scatters composed of silicon thin nanodisks and demonstrate high quality factors and phase dispersion that are unattainable by any nano or microscale flat optics systems.

Abstract: In this article, we demonstrate dense resonant peaks in the transmission spectra of a rectangular waveguide inscribed with a stretched moir\'e pattern. We investigated an array of silicon waveguides with sinusoidally modulated cladding of varying depth of modulation. The investigation reveals a critical depth of modulation that splits the geometries into weakly scattering and strongly scattering regimes. Geometries in the weakly scattering regime resemble Bragg waveguides with shallow cladding modulation, whereas in the strongly scattering regime, the geometries resemble chains of isolated dielectric particles. The guided mode photonic bandgap for geometries in the strongly scattering regime is much larger than that of the weakly scattering regime. By inscribing stretched moir\'e patterns in the strongly scattering regime, we show that a large number of sharp peaks can be created in the transmission spectra of the waveguide. All periodic stretched moir\'e patterns can be identified with an R parameter. The R parameter indicates the ratio of the supercell period of the stretched system to the unstretched system. Our empirical study shows that the density of peaks linearly increases with R. The multiple resonance peaks evolve along well-defined trajectories with quality factor defined by exponential functions of R.

Abstract: Time-distributed optical feedback in semiconductor lasers has gained attention for its ability to produce high-quality chaos and effectively suppress the time-delay signature. However, the fundamental impact of the distribution of feedback in time on laser dynamics remains unexplored. In this paper, we investigate this topic by using fiber Bragg grating (FBG) feedback. We theoretically study the laser response using FBGs of different lengths but similar reflectivity, effectively stretching the impulse response over a longer period while maintaining its overall shape. We observe that above a critical value corresponding to a grating length of approximately $1$\,cm, fluctuations in laser stability emerge. We attribute this phenomenon to the damping of relaxation oscillations when the zeros of the FBG reflectivity spectrum align with the laser side lobes around the relaxation oscillation frequency. We also uncover an asymmetrical dynamical behavior of the laser for positive and negative frequency detuning. We deduce that this asymmetry is a characteristic feature of FBG feedback and delve into the specificities that trigger such behavior.

Abstract: We report on the design, realization and experimental investigation by spatially resolved monochromated electron energy loss spectroscopy (EELS) of high quality factor cavities with modal volumes smaller than $\lambda^3$, with $\lambda$ the free-space wavelength of light. The cavities are based on a slot defect in a 2D photonic crystal slab made up of silicon. They are optimized for high coupling of electrons accelerated to 100 kV, to quasi-Transverse Electrical modes polarized along the slot direction. We studied the cavities in two geometries. The first geometry, for which the cavities have been designed, corresponds to an electron beam travelling along the slot direction. The second consists in the electron beam travelling perpendicular to the slab. In both cases, a large series of modes is identified. The dielectric slot modes energies are measured to be in the 0.8- 0.85 eV range, as per design, and surrounded by two bands of dielectric and air modes of the photonic structure. The dielectric even slot modes, to which the cavity mode belongs, are highly coupled to the electrons with up to 3.2$\%$ probability of creating a slot photon per incident electron. Although the experimental spectral resolution (around 30 meV) alone does not allow to disentangle cavity photons from other slot photons, the remarkable agreement between the experiments and FDTD simulations permits us to deduce that amongst the photons created in the slot, around 30$\%$ are stored in the cavity mode. A systematic study of the energy and coupling strength as a function of the photonic band gap parameters permits to foresee increase of coupling strength by fine-tuning phase matching. Our work demonstrates free electron coupling to high quality factor cavities with low mode density, sub-$\lambda^3$ modal volume, making it an excellent candidate for applications such as quantum nano-optics with free electrons.

Abstract: Analog physical neural networks, which hold promise for improved energy efficiency and speed compared to digital electronic neural networks, are nevertheless typically operated in a relatively high-power regime so that the signal-to-noise ratio (SNR) is large (>10). What happens if an analog system is instead operated in an ultra-low-power regime, in which the behavior of the system becomes highly stochastic and the noise is no longer a small perturbation on the signal? In this paper, we study this question in the setting of optical neural networks operated in the limit where some layers use only a single photon to cause a neuron activation. Neuron activations in this limit are dominated by quantum noise from the fundamentally probabilistic nature of single-photon detection of weak optical signals. We show that it is possible to train stochastic optical neural networks to perform deterministic image-classification tasks with high accuracy in spite of the extremely high noise (SNR ~ 1) by using a training procedure that directly models the stochastic behavior of photodetection. We experimentally demonstrated MNIST classification with a test accuracy of 98% using an optical neural network with a hidden layer operating in the single-photon regime; the optical energy used to perform the classification corresponds to 0.008 photons per multiply-accumulate (MAC) operation, which is equivalent to 0.003 attojoules of optical energy per MAC. Our experiment used >40x fewer photons per inference than previous state-of-the-art low-optical-energy demonstrations, to achieve the same accuracy of >90%. Our work shows that some extremely stochastic analog systems, including those operating in the limit where quantum noise dominates, can nevertheless be used as layers in neural networks that deterministically perform classification tasks with high accuracy if they are appropriately trained.