Results 51 to 60 of about 13,849 (192)

Efficient First‐Principles Inverse Design of Nanolasers

Laser &Photonics Reviews, EarlyView.
This article introduces a first‐principles inverse‐design framework for nanolasers that directly incorporates nonlinear lasing physics. By unifying steady‐state ab‐initio laser theory (SALT) with topology optimization, it reveals how spatial hole burning, gain saturation, and cavity‐emitter coupling shape laser performance, enabling efficient discovery
Beñat Martinez de Aguirre Jokisch, Alexander Cerjan, Rasmus Ellebæk Christiansen, Jesper Mørk, Ole Sigmund, Steven G. Johnson   +5 more
wiley   +1 more source

Predicting Infrared Optical Properties of Materials Using Machine Learning Interatomic Potentials

Materials Genome Engineering Advances, EarlyView.
This work proposes a new fast computing framework for infrared reflectance spectra, MTP‐FIRE, based on machine learning potential, which can achieve the same accuracy as the existing first‐principles calculation, but can be two orders of magnitude faster on average.
Lianduan Zeng, Xiao Zhou, Xinxi Lu, Li Huang, Lan Yang, Lihao Wang, Gang Liu, Zhongyang Wang, Tongxiang Fan   +8 more
wiley   +1 more source

Semantic Intelligence in Metallurgy: A Dual‐Stage Language Model Framework for Processing‐Aware Magnesium Alloy Design

Materials Genome Engineering Advances, EarlyView.
This study introduces a dual‐stage language model framework that extracts processing information from scientific literature and integrates it with thermodynamic data for magnesium alloy design. By combining semantic intelligence with quantitative modeling, the approach enables processing‐aware prediction of mechanical and thermal properties, bridging ...
Ziliang Lu, Ishwar Kapoor, Takeru Araki, Lu Chen, Tao Song, Yixiang Li, Yang Su, Xiaoqin Zeng, Leyun Wang   +8 more
wiley   +1 more source

High Relative Accuracy Computations With Covariance Matrices of Order Statistics

Mathematical Methods in the Applied Sciences, EarlyView.
ABSTRACT In many statistical applications, numerical computations with covariance matrices need to be performed. The error made when performing such numerical computations increases with the condition number of the covariance matrix, which is related to the number of variables and the strength of the correlation between the variables. In a recent work,
Juan Baz, Pedro Alonso, Juan Manuel Peña, Raúl Pérez‐Fernández   +3 more
wiley   +1 more source

Blind nonnegative source separation using biological neural networks

, 2017
Blind source separation, i.e. extraction of independent sources from a mixture, is an important problem for both artificial and natural signal processing.
Chklovskii, Dmitri B., Mohan, Sreyas, Pehlevan, Cengiz   +2 more
core   +1 more source

Complementary Sensitivity of Fixed‐Time and Fixed‐Oscillation Regimes to Exchange and Structural Disorder in the Human Brain Revealed Using Oscillating‐Gradient Diffusion MRI With Ultra‐Strong Gradients

Magnetic Resonance in Medicine, EarlyView.
ABSTRACT Purpose Oscillating‐gradient spin‐echo (OGSE) diffusion MRI probes cell geometry and membrane integrity through the frequency‐dependence of kurtosis, but prior studies have reported inconsistent findings depending on how frequency is varied. We compared frequency‐dependent kurtosis in the human brain under two regimes: varying frequency with ...
Dongsuk Sung, Kwok‐Shing Chan, Julianna Gerold, Wen Zhong, Jialan Zheng, Qiyuan Tian, Hua Guo, Susie Y. Huang, Hong‐Hsi Lee   +8 more
wiley   +1 more source

Accelerating Nonnegative Matrix Factorization Algorithms using Extrapolation

, 2018
In this paper, we propose a general framework to accelerate significantly the algorithms for nonnegative matrix factorization (NMF). This framework is inspired from the extrapolation scheme used to accelerate gradient methods in convex optimization and ...
Ang, Andersen Man Shun, Gillis, Nicolas
core   +1 more source

Finite‐Time Disturbance Observer‐Based Nonlinear Robust Adaptive Control of Hydraulic Manipulator With Parameter Identification

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT Hydraulic manipulators exhibit strong coupling, pronounced nonlinearities, and significant modeling uncertainties, which hinder high‐precision motion control. This paper proposes a finite‐time disturbance observer–based nonlinear robust adaptive control (RAC‐FTDO) framework enhanced by a physically consistent dynamic parameter identification ...
Tianyu Gao, Xianglong Liang, Wenxiang Deng, Jianyong Yao   +3 more
wiley   +1 more source

Completion, extension, factorization, and lifting of operators with a negative index [PDF]

, 2014
The famous results of M.G. Kre\u{\i}n concerning the description of selfadjoint contractive extensions of a Hermitian contraction $T_1$ and the characterization of all nonnegative selfadjoint extensions $\widetilde A$ of a nonnegative operator $A$ via ...
Baidiuk, D., Hassi, S.
core  

Loss Behavior in Supervised Learning With Entangled States

Advanced Quantum Technologies, EarlyView.
Entanglement in training samples supports quantum supervised learning algorithm in obtaining solutions of low generalization error. Using analytical as well as numerical methods, this work shows that the positive effect of entanglement on model after training has negative consequences for the trainability of the model itself, while showing the ...
Alexander Mandl, Johanna Barzen, Marvin Bechtold, Frank Leymann, Lavinia Stiliadou   +4 more
wiley   +1 more source