Recently, a research team led by Prof. Zhao Bangchuan from the Institute of Solid State Physics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, in collaboration with Prof. Xiao Yao ...
Real-world optimization problems often require an external “modeling engine” that computes fitnesses or data that are then input to an objective function. These programs often have much longer ...
WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
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End-to-end differentiable design of geometric waveguide displays
A novel differentiable approach optimizes geometric waveguide coatings, achieving substantial gains in light efficiency and uniformity for optical AR displays.
Abstract: In this paper, we investigate the design of multi-step-index multimode fibers with a cladding trench for 45 spatial modes at 1550nm using an efficient, gradient based radial fiber mode ...
ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...
Abstract: This paper presents an extended gradient-based optimization framework for optimal control problems governed by general conformable fractional derivatives (GCFDs), which unify various ...
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