Almost all energy on Earth comes from the Sun. It radiates power to Earth using electromagnetic (EM) waves. However, only a small fraction of the radiation was captured in the forms of photovoltaic, solar heat, hydropower, fossil fuel, and wind. The consumption of the energy comes with serious environmental penalties such as global warming and environmental damages. A system and methods are disclosed to allow capturing, storage, conversion and release of electromagnetic waves and their energy.

In a LIDAR device (100) a laser light source (110) generates first laser light having a first laser frequency which is frequency modulated with a first frequency modulation. A non-linear optical element (120) receives the first laser light and generates therefrom second laser light having a comb-like frequency spectrum with a plurality of second laser frequencies which are each frequency modulated with a second frequency modulation defined by the first frequency modulation. A frequency excursion of the second frequency modulation is smaller than a spacing of the second laser frequencies. A diffractive element (140) spatially separates the second laser light according to the second laser frequencies and directs the spatially separated second laser light towards a ranging region (200), with each of the second laser frequencies being directed towards a corresponding spatially distinct target position in the ranging region (200). A detector (150) receives reflections of the second laser light from the ranging region (200) and measures, by simultaneously detecting a frequency modulation of the reflections for each of the second laser frequencies, a distance and/or a velocity at the target position corresponding to the second laser frequency.

Disclosed are systems and techniques for generating and steering laser beams onto atoms for performing locally addressed quantum gate operations. A system may include (i) a high-speed acousto-optic modulator (AOM) for producing a single input beam, (ii) a phase-only spatial light modulator (SLM) for imprinting a phase pattern on the single input beam, the phase pattern being chosen such that after a lens positioned after the SLM, the single input beam is divided into a pattern of secondary beams that correspond to the positions of the atoms or ions in a quantum computer, the lens after the SLM being positioned so the secondary beams are focused to form an image on a digital micromirror device (DMD) amplitude modulator, (iii) a compensation grating after the DMD, in the path of the secondary beams, and (iv) an objective lens after the compensation grating to image the secondary beams onto an atomic array.

The exponential growth in deep learning models is challenging existing computing hardware. Optical neural networks (ONNs) accelerate machine learning tasks with potentially ultrahigh bandwidth and nearly no loss in data movement. Scaling up ONNs involves improving scalability, energy efficiency, compute density, and inline nonlinearity. However, realizing all these criteria remains an unsolved challenge. Here, we demonstrate a three-dimensional spatial time-multiplexed ONN architecture based on dense arrays of microscale vertical cavity surface emitting lasers (VCSELs). The VCSELs, coherently injection-locked to a leader laser, operate at gigahertz data rates with a 7T-phase-shift voltage on the 10-millivolt level. Optical nonlinearity is incorporated into the ONN with no added energy cost using coherent detection of optical interference between VCSELs.

Systems and methods for controlling response times of an all-optical switch are disclosed herein. An example method includes pumping an all-optical switch with a pump beam to induce an adjustment to a probe beam in a first response time, the all-optical switch comprising a plurality of materials that each have a respective response time, and the pump beam having optical characteristics configured to cause the pump beam to excite a first set of materials of the plurality of materials to induce the adjustment. The example method further includes adjusting one or more of the optical characteristics of the pump beam to cause the pump beam to excite a second set of materials of the plurality of materials that is different from the first set of materials; and pumping the all-optical switch with the adjusted pump beam to induce the adjustment to the probe beam in a second response time.

A nonlinear all optical machine learning system (NAOMLS) with nonlinear optical resonator-based continuous wave and/or spiking neurons (NORs) and linear optical components or layers (LOL) learns to implement target tasks after machine learning based direct and/or indirect inverse design and/or optimization of the NORs and/or optimization of the LOL. The inversely designed and/or optimized NORs and the optimized LOL collectively define learnable mapping functions between input lights and output lights of the NAOMLS to meet target objectives for target tasks. In some embodiments, the NORs are indirectly and inversely designed to meet inversely designed objectives in order to be integrated with the NAOMLS so that the NAOMLS can function properly to meet target objectives for target tasks. In some embodiments, the NORs are integrated directly with the NAOMLS and inversely designed and/or optimized with the LOL to directly meet target objectives for target tasks.