Results 81 to 90 of about 197,953 (292)
A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons
Advanced Intelligent Discovery, EarlyView.We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam +5 more
wiley +1 more source
Characteristically Near Stable Vector Fields in the Polar Complex Plane
Communications in Advanced Mathematical SciencesThis paper introduces results for characteristically proximal vector fields that are stable or non-stable in the polar complex plane $\mathbb{C}$. All characteristic vectors (aka eigenvectors) emanate from the same fixed point in $\mathbb{C}$, namely, 0.
Enze Cui, James F. Peters
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Advanced Intelligent Discovery, EarlyView.This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah +3 more
wiley +1 more source
On the Spectrum of a Discrete Non-Hermitian Quantum System
Symmetry, Integrability and Geometry: Methods and Applications, 2009 In this paper, we develop spectral analysis of a discrete non-Hermitian quantum system that is a discrete counterpart of some continuous quantum systems on a complex contour.
Ebru Ergun
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Product Wave Function Renormalization Group: construction from the matrix product point of view
, 2005 We present a construction of a matrix product state (MPS) that approximates the largest-eigenvalue eigenvector of a transfer matrix T, for the purpose of rapidly performing the infinite system density matrix renormalization group (DMRG) method applied to
Akutsu N. +27 more
core +1 more source
Advanced Intelligent Discovery, EarlyView.Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez +4 more
wiley +1 more source
The diversity of quasars unified by accretion and orientation
, 2014 Quasars are rapidly accreting supermassive black holes at the center of massive galaxies. They display a broad range of properties across all wavelengths, reflecting the diversity in the physical conditions of the regions close to the central engine ...
Ho, Luis C., Shen, Yue
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Advanced Intelligent Discovery, EarlyView.The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu +11 more
wiley +1 more source
Machine Learning‐Driven Variability Analysis of Process Parameters for Semiconductor Manufacturing
Advanced Intelligent Systems, EarlyView.This research presents a machine learning approach that integrates nonlinear variation decomposition (NLVD) with statistical techniques to quantify the contribution of individual unit processes to performance and variance of figure of merit (FoM) at the LOT level.
Sinyeong Kang +6 more
wiley +1 more source
Discrete inequalities of Wirtinger's type for higher differences
Journal of Inequalities and Applications, 1997 Discrete version of Wirtinger's type inequality for higher differences, where and is considered. Under some conditions, the best constants , and are determined.
Milovanović Gradimir V +1 more
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