Results 91 to 100 of about 480,148 (242)
The strength of Ramsey Theorem for coloring relatively large sets
We characterize the computational content and the proof-theoretic strength of a Ramsey-type theorem for bi-colorings of so-called {\em exactly large} sets. An {\it exactly large} set is a set $X\subset\Nat$ such that $\card(X)=\min(X)+1$.
Carlucci, Lorenzo, Zdanowski, Konrad
core
Ultrafast pulsed laser technology enables precise material processing. This study examines molybdenum oxide formation under varying laser parameters. A dataset of 187 samples is generated, and eight deep neural networks (DNNs) with different architectures are trained. Models are validated using three learning rates and evaluated with mean squared error,
Jose R. Paredes‐Miguel+6 more
wiley +1 more source
An enhanced homogenization method for periodic lattices, applicable to any asymmetrical multipart structures, is proposed. This method simplifies intricate gratings into slab waveguides, predicts guided‐mode resonances and bound states in the continuum, without relying on numerical methods.
Atefe Taheri, Mehrdad Shokooh‐Saremi
wiley +1 more source
This work introduces a low‐loss diffractive neural network, fabricated using an imprinting technique with parowax material, for recognizing and manipulating the topological charge of orbital angular momentum (OAM) waves. It is also demonstrated that the low‐loss diffractive network can perform mathematical operations based on the topological charges of
Wei Jia+4 more
wiley +1 more source
This study investigates the optoelectronic response of Al/p‐Si photodiodes with and without a (PVP:Gr‐ZnTiO3) interlayer under varying light intensities. Key parameters are analyzed, revealing that the interlayer enhances photosensitivity, optical responsivity, and specific detectivity.
Ali Barkhordari+5 more
wiley +1 more source
Digitized Phase‐Change Material Heterostack for Transmissive Diffractive Optical Neural Network
A phase‐change‐material‐based digitized heterostack is experimentally demonstrated and theoretically analyzed for future energy‐efficient, fast reconfigured, and compact transmissive diffractive optical neural networks. All‐optical and fully reconfigurable transmissive diffractive optical neural network (DONN) architectures emerge as high‐throughput ...
Ruiyang Chen+3 more
wiley +1 more source
This work presents a systematic review of atmospheric turbulence fundamentals, including theoretical formulations and adaptive optics‐based mitigation strategies. This includes an in‐depth examination of the devices, theories, and methodologies associated with traditional correction approaches.
Qinghui Liu+5 more
wiley +1 more source
A pair of Sb2Te3 topological insulator (TI) nanotips is fabricated by using the focused ion beam lithography to demonstrate the plasmonic hot spot effect at the visible range. The strong enhancement of electric field can be generated on the TI nanotips due to the plasmonic effect, giving rise to the obvious improvement of photoluminescence emission ...
Yiqiao Zhang+5 more
wiley +1 more source
Optical Chaos Generation and Applications
This review comprehensively examines optical chaos generation via feedback, injection, and optoelectronic methods, emphasizing bandwidth enhancement and time‐delay suppression. Applications include chaos‐synchronized secure communication, physical random number generation, chaotic lidar for cm‐level detection, distributed fiber sensing, and terahertz ...
Wenhui Chen+8 more
wiley +1 more source
A Theoretical Investigation on Coupled Mass‐charge Transport in a Binary Fluid
This study presents a theoretical framework for coupled mass‐charge transport in binary fluids using molecular dynamics simulations. By deriving governing equations from conservation laws and Onsager's theory, the approach introduces generalized diffusivity and electrostatic friction terms.
Antonio Cappai+3 more
wiley +1 more source