Multifocal multilevel diffractive lens by wavelength multiplexing.

Flat lenses with focal length tunability can enable the development of highly integrated imaging systems. This work explores machine learning to inverse design a multifocal multilevel diffractive lens (MMDL) by wavelength multiplexing. The MMDL output is multiplexed in three color channels, red (650 nm), green (550 nm), and blue (450 nm), to achieve varied focal lengths of 4 mm, 20 mm, and 40 mm at these three color channels, respectively.

Machine learning enables the design of a bidirectional focusing diffractive lens.

Machine learning can efficiently empower the inverse design of cascaded diffractive optical elements. In this work, we explore the inverse design of a bidirectional focusing diffractive lens in a cascaded configuration through the diffractive optical neural network (DONN) machine learning method. The bidirectional focusing diffractive lens consists of two on-axially cascaded multi-level diffractive lenses.

Effects of interlayer reflection and interpixel interaction in diffractive optical neural networks.

Multilayer diffractive optical neural networks (DONNs) can perform machine learning (ML) tasks at the speed of light with low energy consumption. Decreasing the number of diffractive layers can reduce inevitable material and diffraction losses to improve system performance, and incorporating compact devices can reduce the system footprint. However, current analytical DONN models cannot accurately describe such physical systems.

Visible and near-infrared programmable multi-level diffractive lenses with phase change material SbS.

In this paper, we discuss flat programmable multi-level diffractive lenses (PMDL) enabled by phase change materials working in the near-infrared and visible ranges. The high real part refractive index contrast (Δn ∼ 0.6) of SbS between amorphous and crystalline states, and extremely low losses in the near-infrared, enable the PMDL to effectively shift the lens focus when the phase of the material is altered between its crystalline and amorphous states.

Effect of extended defects on photoluminescence of gallium oxide and aluminum gallium oxide epitaxial films.

In this work, a systematic photoluminescence (PL) study on three series of gallium oxide/aluminum gallium oxide films and bulk single crystals is performed including comparing doping, epitaxial substrates, and aluminum concentration. It is observed that blue/green emission intensity strongly correlates with extended structural defects rather than the point defects frequently assumed. Bulk crystals or Si-doped films homoepitaxially grown on (010) β-GaO yield an intense dominant UV emission, while samples with extended structural defects, such as gallium oxide films grown on either (-201) β-GaO or sapphire, as well as thick aluminum gallium oxide films grown on either (010) β-GaO or sapphire, all show a very broad PL spectrum with intense dominant blue/green emission.

Monolithic all-silicon flat lens for broadband LWIR imaging.

We designed, fabricated, and characterized a flat multi-level diffractive lens comprised of only silicon with =15.2, focal =19, numerical aperture of 0.371, and operating over the long-wave infrared (LWIR) =8µ to 14 µm.

Imaging from the visible to the longwave infrared wavelengths via an inverse-designed flat lens.

It is generally assumed that correcting chromatic aberrations in imaging requires multiple optical elements. Here, we show that by allowing the phase in the image plane to be a free parameter, it is possible to correct chromatic variation of focal length over an extremely large bandwidth, from the visible (Vis) to the longwave infrared (LWIR) wavelengths using a single diffractive surface, i.e.

Real-time multi-task diffractive deep neural networks via hardware-software co-design.

Deep neural networks (DNNs) have substantial computational requirements, which greatly limit their performance in resource-constrained environments. Recently, there are increasing efforts on optical neural networks and optical computing based DNNs hardware, which bring significant advantages for deep learning systems in terms of their power efficiency, parallelism and computational speed. Among them, free-space diffractive deep neural networks (DNNs) based on the light diffraction, feature millions of neurons in each layer interconnected with neurons in neighboring layers.

Terahertz characterization of two-dimensional low-conductive layers enabled by metal gratings.

While terahertz spectroscopy can provide valuable information regarding the charge transport properties in semiconductors, its application for the characterization of low-conductive two-dimensional layers, i.e., σ <  < 1 mS, remains elusive.

Super-resolution imaging with an achromatic multi-level diffractive microlens array.

Compound eyes found in insects provide intriguing sources of biological inspiration for miniaturized imaging systems. Inspired by such insect eye structures, we demonstrate an ultrathin arrayed camera enabled by a flat multi-level diffractive microlens array for super-resolution visible imaging. We experimentally demonstrate that the microlens array can achieve a large fill factor (hexagonal close packing with =120µ), thickness of 2.

Impact of fabrication errors and refractive index on multilevel diffractive lens performance.

Multilevel diffractive lenses (MDLs) have emerged as an alternative to both conventional diffractive optical elements (DOEs) and metalenses for applications ranging from imaging to holographic and immersive displays. Recent work has shown that by harnessing structural parametric optimization of DOEs, one can design MDLs to enable multiple functionalities like achromaticity, depth of focus, wide-angle imaging, etc. with great ease in fabrication.

Ultra-thin near infrared camera enabled by a flat multi-level diffractive lens: erratum.

In Opt. Lett.44, 5450 (2019)OPLEDP0146-959210.

Ultra-thin near infrared camera enabled by a flat multi-level diffractive lens.

We experimentally demonstrate a ∼1-mm-thick near infrared camera comprised of a multi-level diffractive lens coupled with a conventional monochrome image sensor. We performed careful measurements of the point-spread function, the modulation transfer function, focusing efficiency, aberrations, and the field of view of the camera.

Broadband lightweight flat lenses for long-wave infrared imaging.

We experimentally demonstrate imaging in the long-wave infrared (LWIR) spectral band (8 μm to 12 μm) using a single polymer flat lens based upon multilevel diffractive optics. The device thickness is only 10 μm, and chromatic aberrations are corrected over the entire LWIR band with one surface. Due to the drastic reduction in device thickness, we are able to utilize polymers with absorption in the LWIR, allowing for inexpensive manufacturing via imprint lithography.

A Computational Design Framework for Efficient, Fabrication Error-Tolerant, Planar THz Diffractive Optical Elements.

We demonstrate ultra-thin (1.5-3λ), fabrication-error tolerant efficient diffractive terahertz (THz) optical elements designed using a computer-aided optimization-based search algorithm. The basic operation of these components is modeled using scalar diffraction of electromagnetic waves through a pixelated multi-level 3D-printed polymer structure.

Manifestation of Kinetic Inductance in Terahertz Plasmon Resonances in Thin-Film CdAs.

Three-dimensional (3D) semimetals have been predicted and demonstrated to have a wide variety of interesting properties associated with their linear energy dispersion. In analogy to two-dimensional (2D) Dirac semimetals, such as graphene, CdAs has shown ultrahigh mobility and large Fermi velocity and has been hypothesized to support plasmons at terahertz frequencies. In this work, we experimentally demonstrate synthesis of high-quality large-area CdAs thin films through thermal evaporation as well as the experimental realization of plasmonic structures consisting of periodic arrays of CdAs stripes.

Incident wavelength and polarization dependence of spectral shifts in β-GaO UV photoluminescence.

We report polarization dependent photoluminescence studies on unintentionally-, Mg-, and Ca-doped β-GaO bulk crystals grown by the Czochralski method. In particular, we observe a wavelength shift of the highest-energy UV emission which is dependent on the pump photon energy and polarization. For 240 nm (5.

THz characterization and demonstration of visible-transparent/terahertz-functional electromagnetic structures in ultra-conductive La-doped BaSnO Films.

We report on terahertz characterization of La-doped BaSnO (BSO) thin-films. BSO is a transparent complex oxide material, which has attracted substantial interest due to its large electrical conductivity and wide bandgap. The complex refractive index of these films is extracted in the 0.

Terahertz magneto-plasmonics using cobalt subwavelength aperture arrays.

We characterize the terahertz (THz) magneto-plasmonic response of a cobalt-based periodic aperture array. The bare cobalt surface allows for low loss propagation of surface plasmon-polaritons, as evidenced by comparing the reflection from aperture arrays coated with Au and with Co. When an external magnetic field is applied in a polar Kerr geometry, we observe a maximum polarization rotation of ~0.

Geometrical tradeoffs in graphene-based deeply-scaled electrically reconfigurable metasurfaces.

In this work we study the terahertz light propagation through deeply-scaled graphene-based reconfigurable metasurfaces, i.e. metasurfaces with unit-cell dimensions much smaller than the terahertz wavelength.

Terahertz imaging employing graphene modulator arrays.

In this paper we propose and experimentally demonstrate arrays of graphene electro-absorption modulators as electrically reconfigurable patterns for terahertz cameras. The active element of these modulators consists of only single-atom-thick graphene, achieving a modulation of the THz wave reflectance > 50% with a potential modulation depth approaching 100%. Although the prototype presented here only contains 4x4 pixels, it reveals the possibility of developing reliable low-cost video-rate THz imaging systems employing single detector.

A new class of electrically tunable metamaterial terahertz modulators.

Switchable metamaterials offer unique solutions for efficiently manipulating electromagnetic waves, particularly for terahertz waves, which has been difficult since naturally occurring materials rarely respond to terahertz frequencies controllably. However, few terahertz modulators demonstrated to date exhibit simultaneously low attenuation and high modulation depth. In this letter we propose a new class of electrically-tunable terahertz metamaterial modulators employing metallic frequency-selective-surfaces (FSS) in conjunction with capacitively-tunable layers of electrons, promising near 100% modulation depth and < 15% attenuation.

Extraordinary control of terahertz beam reflectance in graphene electro-absorption modulators.

We demonstrate a graphene-based electro-absorption modulator achieving extraordinary control of terahertz reflectance. By concentrating the electric field intensity in an active layer of graphene, an extraordinary modulation depth of 64% is achieved while simultaneously exhibiting low insertion loss (∼2 dB), which is remarkable since the active region of the device is atomically thin. This modulator performance, among the best reported to date, indicates the enormous potential of graphene for terahertz reconfigurable optoelectronic devices.

Broadband graphene terahertz modulators enabled by intraband transitions.

Terahertz technology promises myriad applications including imaging, spectroscopy and communications. However, one major bottleneck at present for advancing this field is the lack of efficient devices to manipulate the terahertz electromagnetic waves. Here we demonstrate that exceptionally efficient broadband modulation of terahertz waves at room temperature can be realized using graphene with extremely low intrinsic signal attenuation.