相关论文: Recognizing Beam Profiles from Silicon Photonics G…
We have designed, fabricated, and characterized implantable silicon neural probes with nanophotonic grating emitters that focus the emitted light at a specified distance above the surface of the probe for spatially precise optogenetic…
The incorporation of LiDAR technology into some high-end smartphones has unlocked numerous possibilities across various applications, including photography, image restoration, augmented reality, and more. In this paper, we introduce a novel…
Efficient power coupling between on-chip guided and free-space optical modes requires precision spatial mode matching with apodized grating couplers. Yet, grating apodizations are often limited by the minimum feature size of the fabrication…
We demonstrate a "membrane in the middle" optomechanical system using a silicon nitride membrane patterned as a subwavelength grating. The grating has a reflectivity of over 99.8%, effectively creating two sub-cavities, with free spectral…
The use of silicon photomultipliers (SiPMs) in imaging atmospheric Cherenkov telescopes is expected to extend the observation times of very-high-energy gamma-ray sources, particularly within the highest energy domain of 50-300 TeV, where…
In integrated ground-air-space (IGAS) wireless networks, numerous services require sensing knowledge including location, angle, distance information, etc., which usually can be acquired during the beam training stage. On the other hand,…
Optical systems capable of generating fields with sub-wavelength spatial features have become standard in science and engineering research and industry. Pertinent examples include atom- and ion-based quantum computers and optical…
The challenge of object categorization in images is largely due to arbitrary translations and scales of the foreground objects. To attack this difficulty, we propose a new approach called collaborative receptive field learning to extract…
Silicon photomultipliers are regarded as a very promising technology for next-generation, cutting-edge detectors for low-background experiments in particle physics. This work presents systematic reflectivity studies of Silicon…
Silicon photonics is being extended from the near-infrared (near-IR) window of 1.3-1.5 {\mu}m for optical fiber communications to the mid-infrared (mid-IR) wavelength-band of 2 {\mu}m or longer for satisfying the increasing demands in many…
We show that doubly peaked electric fields are necessary to describe grazing-angle charge collection measurements of irradiated silicon pixel sensors. A model of irradiated silicon based upon two defect levels with opposite charge states…
Recent Transformer-based low-light enhancement methods have made promising progress in recovering global illumination. However, they still struggle with non-uniform lighting scenarios, such as backlit and shadow, appearing as over-exposure…
We introduce a machine learning approach to determine the transition dynamics of silicon atoms on a single layer of carbon atoms, when stimulated by the electron beam of a scanning transmission electron microscope (STEM). Our method is…
In this paper we present a deep learning method to estimate the illuminant of an image. Our model is not trained with illuminant annotations, but with the objective of improving performance on an auxiliary task such as object recognition.…
We present {\tt deepSIP} (deep learning of Supernova Ia Parameters), a software package for measuring the phase and -- for the first time using deep learning -- the light-curve shape of a Type Ia supernova (SN~Ia) from an optical spectrum.…
Accurate characterization of quantum yield is crucial to the reconstruction of energy depositions in silicon at the eV scale. This work presents a new method for experimentally calculating quantum yield using vacuum UV-sensitive silicon…
Future NASA X-ray spectroscopy missions will require high throughput, high resolution grating spectrometers. Off-plane reflection gratings are capable of meeting the performance requirements needed to realize the scientific goals of these…
Most codec designs rely on the mean squared error (MSE) as a fidelity metric in rate-distortion optimization, which allows to choose the optimal parameters in the transform domain but may fail to reflect perceptual quality. Alternative…
We present prototype modules for a tracking detector consisting of multiple layers of 0.25 mm diameter scintillating fibers that are read out by linear arrays of silicon photomultipliers. The module production process is described and…
Inverse modelling with deep learning algorithms involves training deep architecture to predict device's parameters from its static behaviour. Inverse device modelling is suitable to reconstruct drifted physical parameters of devices…