Coylefrantzen9610

Computational cannula microscopy (CCM) is a high-resolution widefield fluorescence imaging approach deep inside tissue, which is minimally invasive. Rather than using conventional lenses, a surgical cannula acts as a lightpipe for both excitation and fluorescence emission, where computational methods are used for image visualization. Here, we enhance CCM with artificial neural networks to enable 3D imaging of cultured neurons and fluorescent beads, the latter inside a volumetric phantom. We experimentally demonstrate transverse resolution of ∼6µm, field of view ∼200µm and axial sectioning of ∼50µm for depths down to ∼700µm, all achieved with computation time of ∼3ms/frame on a desktop computer.We propose and experimentally demonstrate modulation format-independent optical performance monitoring (OPM) based on a multi-task artificial neural network (MT-ANN). Optical power measurements at a series of center wavelengths adjusted using a widely tunable optical bandpass filter (OBPF) are used as the input features for a MT-ANN to simultaneously realize high-precision optical signal-to-noise ratio (OSNR) and launch power monitoring and baud rate identification (BRI). This technique is insensitive to chromatic dispersion (CD) and polarization mode dispersion (PMD). The experimental verification in a 9-channel WDM system shows that for 10 Gbaud QPSK and 32 Gbaud PDM-16QAM signals with OSNR in the range of 1-30 dB, the OSNR mean absolute error (MAE) and root mean square error (RMSE) are 0.28 dB and 0.48 dB, respectively. For launch power in the range of 0-8 dBm, the MAE and RMSE of the launch power monitoring are 0.034 dB and 0.066 dB, respectively, and the identification accuracy for both baud rates is 100%. Furthermore, this technique utilizes a single MT-ANN instead of three ANNs to realize the simultaneous monitoring of three OPM parameters, which greatly reduces the cost and complexity.Local electric fields play the key role in near-field optical examinations and are especially appealing when exploring heterogeneous or even anisotropic nano-systems. Scattering-type near-field optical microscopy (s-SNOM) is the most commonly used method applied to explore and quantify such confined electric fields at the nanometer length scale while most works so far did focus on analyzing the z-component oriented perpendicular to the sample surface under p-polarized tip/sample illumination only, recent experimental efforts in s-SNOM report that material resonant excitation might equally allow to probe in-plane electric field components. We thus explore this local vector-field behavior for a simple particle-tip/substrate system by comparing our parametric simulations based on finite element modelling at mid-IR wavelengths, to the standard analytical tip-dipole model. Notably, we analyze all the 4 different combinations for resonant and non-resonant tip and/or sample excitation. Besides the 3-dimensional field confinement under the particle tip present for all scenarios, it is particularly the resonant sample excitations that enable extremely strong field enhancements associated with vector fields pointing along all cartesian coordinates, even without breaking the tip/sample symmetry! In fact, in-plane (s-) resonant sample excitation exceeds the commonly-used p-polarized illumination on non-resonant samples by more than 6 orders of magnitude. Moreover, a variety of different spatial field distributions is found both at and within the sample surface, ranging from electric fields that are oriented strictly perpendicular to the sample surface, to fields that spatially rotate into different directions. Our approach shows that accessing the full vector fields in order to quantify all tensorial properties in nanoscale and modern-type materials lies well within the possibilities and scope of today's s-SNOM technique.This work reports on high extraction efficiency in subwavelength GaAs/AlGaAs semiconductor nanopillars. We achieve up to 37-fold enhancement of the photoluminescence (PL) intensity from sub-micrometer (sub-µm) pillars without requiring back reflectors, high-Q dielectric cavities, nor large 2D arrays or plasmonic effects. This is a result of a large extraction efficiency for nanopillars less then 500 nm width, estimated in the range of 33-57%, which is much larger than the typical low efficiency (∼2%) of micrometer pillars limited by total internal reflection. Time-resolved PL measurements allow us to estimate the nonradiative surface recombination of fabricated pillars. We conclusively show that vertical-emitting nanopillar-based LEDs, in the best case scenario of both reduced surface recombination and efficient light out-coupling, have the potential to achieve notable large external quantum efficiency (∼45%), whereas the efficiency of large µm-pillar planar LEDs, without further methods, saturates at ∼2%. These results offer a versatile method of light management in nanostructures with prospects to improve the performance of optoelectronic devices including nanoscale LEDs, nanolasers, single photon sources, photodetectors, and solar cells.By developing a 'two-crystal' method for color erasure, we can broaden the scope of chromatic interferometry to include optical photons whose frequency difference falls outside of the 400 nm to 4500 nm wavelength range, which is the passband of a PPLN crystal. We demonstrate this possibility experimentally, by observing interference patterns between sources at 1064.4 nm and 1063.6 nm, corresponding to a frequency difference of about 200 GHz.This Roadmap article on three-dimensional integral imaging provides an overview of some of the research activities in the field of integral imaging. The article discusses various aspects of the field including sensing of 3D scenes, processing of captured information, and 3D display and visualization of information. The paper consists of a series of 15 sections from the experts presenting various aspects of the field on sensing, processing, displays, augmented reality, microscopy, object recognition, and other applications. Each section represents the vision of its author to describe the progress, potential, vision, and challenging issues in this field.This article presents a non-classical imaging mechanism that produces a diffraction-limited and magnified ghost image of the internal structure of an object through the measurement of intensity fluctuation correlation formed by two-photon interference. In principle, the lensless X-ray ghost imaging mechanism may achieve a spatial resolution determined by the wavelength and the angular diameter of the X-ray source, ∼λ/Δθs, with possible reduction caused by additional optics. In addition, it has the ability to image select "slices" deep within an object, which can be used for constructing 3D view of its internal structure.Resonant biosensors are attractive for diagnostics because they can detect clinically relevant biomarkers with high sensitivity and in a label-free fashion. Most of the current solutions determine their detection limits in a highly stabilised laboratory environment, which does, however, not apply to real point-of-care applications. Here, we consider the more realistic scenario of low-cost components and an unstabilised environment and consider the related design implications. We find that sensors with lower quality-factor resonances are more fault tolerant, that a filtered LED lightsource is advantageous compared to a diode laser, and that a CMOS camera is preferable to a CCD camera for detection. We exemplify these findings with a guided mode resonance sensor and experimentally determine a limit of detection of 5.8 ± 1.7×10-5 refractive index units (RIU), which is backed up by a model identifying the various noise sources. Our findings will inform the design of high performance, low cost biosensors capable of operating in a real-world environment.We present simulations suggesting that it is possible to minimize the systematic errors of differential absorption lidar (DIAL) measurements caused by the Rayleigh-Doppler effect by selecting an online frequency close to one of the inflection points on either side of the absorption line. Thus, it seems advantageous to select an absorption line of suitable cross section at these points on the line slopes rather than at the peak. First, we extend the classical simulation study of Ansmann (1985) for another water vapor absorption line but again with the online frequency at the line peak. As expected, we also found large systematic errors of more than 40% at the edges of aerosol layers and clouds. Second, we simulate the systematic errors for other online frequencies away from the peak for the same input profile. The results demonstrate that the errors vanish close to the inflection points. Since both the shape of the absorption lines and the width of the broadened backscatter signal depend on the atmospheric conditions, these optimum frequencies vary slightly with height and climatology. Third, we calculate the errors for a typical aerosol profile of the planetary boundary layer obtained from lidar measurements. With this case, we discuss how to select practically the online frequency so that the errors are minimized for all heights of interest. We found that the error reduces from 20 to less then 1% at the top of the planetary boundary layer while, at the same time, the error reduces from 6 to 2% in 5 km.The design of complex freeform imaging systems with advanced system specification is often a tedious task that requires extensive human effort. In addition, the lack of design experience or expertise that result from the complex and uncertain nature of freeform optics, in addition to the limited history of usage, also contributes to the design difficulty. In this paper, we propose a design framework of freeform imaging systems using reinforcement learning. A trial-and-error method employing different design routes that use a successive optimization process is applied in different episodes under an ε-greedy policy. An "exploitation-exploration, evaluation and back-up" approach is used to interact with the environment and discover optimal policies. Design results with good imaging performance and related design routes can be found automatically. The design experience can be further summarized using the obtained data directly or through other methods such as clustering-based machine learning. The experience offers valuable insight for completing other related design tasks. Human effort can be significantly reduced in both the design process and the tedious process of summarizing experience. This design framework can be integrated into optical design software and runs nonstop in the background or on servers to complete design tasks and acquire experience automatically for various types of systems.A novel approach to fabricate efficient nitride light-emitting diodes (LEDs) grown on gallium polar surface operating at cryogenic temperatures is presented. We investigate and compare LEDs with standard construction with structures where p-n junction field is inverted through the use of bottom tunnel junction (BTJ). BTJ LEDs show improved turn on voltage, reduced parasitic recombination and increased quantum efficiency at cryogenic temperatures. This is achieved by moving to low resistivity n-type contacts and nitrogen polar-like built-in field with respect to current flow. It inhibits the electron overflow past quantum wells and improves hole injection even at T=12K. Therefore, as cryogenic light sources, BTJ LEDs offer significantly enhanced performance over standard LEDs.