An optical coupler includes a plurality of volume gratings in a substrate. The gratings include an array of fringes extending along length and thickness dimensions of the substrate. A difference between a refractive index of the fringes and a refractive index of the substrate depends on a depth coordinate along the thickness dimension of the substrate. A dependence of the difference on the depth coordinate has a bell-shaped function which suppresses ghost image formation due to optical crosstalk between gratings of neighboring spatial pitches.

A grating coupler may be fabricated by exposing a photopolymer layer to grating forming light for forming periodic refractive index variations in the photopolymer layer. The photopolymer layer may be exposed to apodization light for reducing an amplitude of the periodic refractive index variations in a spatially-selective manner. The apodization may also be achieved or facilitated by subjecting outer surface(s) of the photopolymer layer to a chemically reactive agent that causes the refractive index contrast to be reduced near the surface(s) of application. The apodized refractive index profile of the gratings facilitates the reduction of optical crosstalk between different gratings of the grating coupler.

An apparatus and method to produce a hologram of an object includes an electromagnetic radiation assembly configured to receive a received electromagnetic radiation, such as light, from the object. The electromagnetic radiation assembly is further configured to diffract the received electromagnetic radiation and transmit a diffracted electromagnetic radiation. An image capture assembly is configured to capture an image of the diffracted electromagnetic radiation and produce the hologram of the object from the captured image.

An all-optical Diffractive Deep Neural Network (D.sup.2NN) architecture learns to implement various functions or tasks after deep learning-based design of the passive diffractive or reflective substrate layers that work collectively to perform the desired function or task. This architecture was successfully confirmed experimentally by creating 3D-printed D.sup.2NNs that learned to implement handwritten classifications and lens function at the terahertz spectrum. This all-optical deep learning framework can perform, at the speed of light, various complex functions and tasks that computer-based neural networks can implement, and will find applications in all-optical image analysis, feature detection and object classification, also enabling new camera designs and optical components that can learn to perform unique tasks using D.sup.2NNs. In alternative embodiments, the all-optical D.sup.2NN is used as a front-end in conjunction with a trained, digital neural network back-end.

Improvements to gratings for use in waveguides and methods of producing them are described herein. Deep surface relief gratings (SRGs) may offer many advantages over conventional SRGs, an important one being a higher S-diffraction efficiency. In one embodiment, deep SRGs can be implemented as polymer surface relief gratings or evacuated periodic structures (EPSs). EPSs can be formed by first recording a holographic polymer dispersed liquid crystal (HPDLC) periodic structure. Removing the liquid crystal from the cured periodic structure provides a polymer surface relief grating. Polymer surface relief gratings have many applications including for use in waveguide-based displays.

Improvements to gratings for use in waveguides and methods of producing them are described herein. Deep surface relief gratings (SRGs) may offer many advantages over conventional SRGs, an important one being a higher S-diffraction efficiency. In one embodiment, deep SRGs can be implemented as polymer surface relief gratings or evacuated periodic structures (EPSs). EPSs can be formed by first recording a holographic polymer dispersed liquid crystal (HPDLC) periodic structure. Removing the liquid crystal from the cured periodic structure provides a polymer surface relief grating. Polymer surface relief gratings have many applications including for use in waveguide-based displays.

An apparatus and method to produce a hologram of an object includes an electromagnetic radiation assembly configured to receive a received electromagnetic radiation, such as light, from the object. The electromagnetic radiation assembly is further configured to diffract the received electromagnetic radiation and transmit a diffracted electromagnetic radiation. An image capture assembly is configured to capture an image of the diffracted electromagnetic radiation and produce the hologram of the object from the captured image.

An all-optical Diffractive Deep Neural Network (D.sup.2NN) architecture learns to implement various functions or tasks after deep learning-based design of the passive diffractive or reflective substrate layers that work collectively to perform the desired function or task. This architecture was successfully confirmed experimentally by creating 3D-printed D.sup.2NNs that learned to implement handwritten classifications and lens function at the terahertz spectrum. This all-optical deep learning framework can perform, at the speed of light, various complex functions and tasks that computer-based neural networks can implement, and will find applications in all-optical image analysis, feature detection and object classification, also enabling new camera designs and optical components that can learn to perform unique tasks using D.sup.2NNs. In alternative embodiments, the all-optical D.sup.2NN is used as a front-end in conjunction with a trained, digital neural network back-end.

Techniques disclosed herein relate to optical devices. Resins with different optical properties can be deposited in different areas to provide increased optical functionality. It can be difficult to design a single photopolymer material that meets several technical requirements. Different resins can be deposited on the same substrate to make a single film with spatially varying properties. Different resins can also be applied to different substrates in a stack. By using different resins, an optical component can be made that meets several technical requirements.

Provided is a method of manufacturing a full-color holographic optical element in a full-color holographic optical element manufacturing apparatus including a lens and a holographic recording medium located farther away than a focal length of the lens, the method including: allowing a signal beam including a mixture of laser beams having wavelengths of R (Red), G (Green), and B (Blue) to be incident on the lens; and recording a hologram in such a manner that a reference beam including a mixture of laser beams having wavelengths of R, G, and B is allowed to be incident on the holographic recording medium, wherein the holographic recording medium is configured with a single medium.