No Arabic abstract
We grow accustomed to the notion that optical susceptibilities can be treated as a local property of a medium. In the context of nonlinear optics, both Kerr and Raman processes are considered local, meaning that optical fields at one location do not produce a nonlinear response at distinct locations in space. This is because the electronic and phononic disturbances produced within the material are confined to a region that is smaller than an optical wavelength. By comparison, Brillouin interactions can result in a highly nonlocal nonlinear response, as the elastic waves generated through the Brillouin process can occupy a region in space much larger than an optical wavelength. The nonlocality of these interactions can be exploited to engineer new types of processes, where highly delocalized phonon modes serve as an engineerable channel that mediates scattering processes between light waves propagating in distinct optical waveguides. These types of nonlocal optomechanical responses have been recently demonstrated as the basis for information transduction, however the nontrivial dynamics of such systems has yet to be explored. In this work, we show that the third-order nonlinear process resulting from spatially extended Brillouin-active phonon modes involves mixing products from spatially separated, optically decoupled waveguides, yielding a nonlocal joint-susceptibility. We further explore the coupling of multiple acoustic modes and show that multi-mode acoustic interference enables a tailorable nonlocal-nonlinear susceptibility, exhibiting a multi-pole frequency response.
Microwave photonic systems are compelling for their ability to process signals at high frequencies and over extremely wide bandwidths as a basis for next generation communication and radar technologies. However, many applications also require narrow-band $(simtext{MHz})$ filtering operations that are challenging to implement using optical filtering techniques, as this requires reliable integration of ultra-high quality factor $(sim 10^8)$ optical resonators. One way to address this challenge is to utilize long-lived acoustic resonances, taking advantage of their narrow-band frequency response to filter microwave signals. In this paper, we examine new strategies to harness a narrow-band acoustic response within a microwave-photonic signal processing platform through use of light-sound coupling. Our signal processing scheme is based on a recently demonstrated photon-phonon emitter-receiver device, which transfers information between the optical and acoustic domains using Brillouin interactions, and produces narrow-band filtering of a microwave signal. To understand the best way to use this device technology, we study the properties of a microwave-photonic link using this filtering scheme. We theoretically analyze the noise characteristics of this microwave-photonic link, and explore the parameter space for the design and optimization of such systems.
We propose the optical trapping of Rayleigh particles using tailored anisotropic and hyperbolic metasurfaces illuminated with a linearly polarized Gaussian beam. This platform permits to engineer optical traps at the beam axis with a response governed by nonconservative and giant recoil forces coming from the directional excitation of ultra-confined surface plasmons during the light scattering process. Compared to optical traps set over bulk metals, the proposed traps are broadband in the sense that can be set with beams oscillating at any frequency within the wide range in which the metasurface supports surface plasmons. Over that range, the metasurface evolves from an anisotropic elliptic to a hyperbolic regime through a topological transition and enables optical traps with distinctive spatially asymmetric potential distribution, local potential barriers arising from the momentum imbalance of the excited plasmons, and an enhanced potential depth that permits the stable trapping of nanoparticles using low-intensity laser beams. To investigate the performance of this platform, we develop a rigorous formalism based on the Lorentz force within the Rayleigh approximation combined with anisotropic Greens functions and calculate the trapping potential of nonconservative forces using the Helmholtz-Hodge decomposition method. Tailored anisotropic and hyperbolic metasurfaces, commonly implemented by nanostructuring thin metallic layers, enables using low-intensity laser sources operating in the visible or the IR to trap and manipulate particles at the nanoscale, and may enable a wide range of applications in bioengineering, physics, and chemistry.
Modern fiber-optic coherent communications employ advanced spectrally-efficient modulation formats that require sophisticated narrow linewidth local oscillators (LOs) and complex digital signal processing (DSP). Here, we establish a novel approach to carrier recovery harnessing large-gain stimulated Brillouin scattering (SBS) on a photonic chip for up to 116.82 Gbit/sec self-coherent optical signals, eliminating the need for a separate LO. In contrast to SBS processing on-fiber, our solution provides phase and polarization stability while the narrow SBS linewidth allows for a record-breaking small guardband of ~265 MHz, resulting in higher spectral-efficiency than benchmark self-coherent schemes. This approach reveals comparable performance to state-of-the-art coherent optical receivers without requiring advanced DSP. Our demonstration develops a low-noise and frequency-preserving filter that synchronously regenerates a low-power narrowband optical tone that could relax the requirements on very-high-order modulation signaling and be useful in long-baseline interferometry for precision optical timing or reconstructing a reference tone for quantum-state measurements.
Nonlinear phononics relies on the resonant optical excitation of infrared-active lattice vibrations to coherently induce targeted structural deformations in solids. This form of dynamical crystal-structure design has been applied to control the functional properties of many interesting systems, including magneto-resistive manganites, magnetic materials, superconductors, and ferroelectrics. However, phononics has so far been restricted to protocols in which structural deformations occur locally within the optically excited volume, sometimes resulting in unwanted heating. Here, we extend nonlinear phononics to propagating polaritons, effectively separating in space the optical drive from the functional response. Mid-infrared optical pulses are used to resonantly drive an 18 THz phonon at the surface of ferroelectric LiNbO3. A time-resolved stimulated Raman scattering probe reveals that the ferroelectric polarization is reduced over the entire 50 micron depth of the sample, far beyond the ~ micron depth of the evanescent phonon field. We attribute the bulk response of the ferroelectric polarization to the excitation of a propagating 2.5 THz soft-mode phonon-polariton. For the highest excitation amplitudes, we reach a regime in which the polarization is reversed. In this this non-perturbative regime, we expect that the polariton model evolves into that of a solitonic domain wall that propagates from the surface into the materials at near the speed of light.
Optical focusing at depths in tissue is the Holy Grail of biomedical optics that may bring revolutionary advancement to the field. Wavefront shaping is a widely accepted approach to solve this problem, but most implementations thus far have only operated with stationary media which, however, are scarcely existent in practice. In this article, we propose to apply a deep convolutional neural network named as ReFocusing-Optical-Transformation-Net (RFOTNet), which is a Multi-input Single-output network, to tackle the grand challenge of light focusing in nonstationary scattering media. As known, deep convolutional neural networks are intrinsically powerful to solve inverse scattering problems without complicated computation. Considering the optical speckles of the medium before and after moderate perturbations are correlated, an optical focus can be rapidly recovered based on fine-tuning of pre-trained neural networks, significantly reducing the time and computational cost in refocusing. The feasibility is validated experimentally in this work. The proposed deep learning-empowered wavefront shaping framework has great potentials in facilitating optimal optical focusing and imaging in deep and dynamic tissue.