Results 81 to 90 of about 128,344 (265)
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
A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
Advanced Intelligent Discovery, EarlyView.The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
wiley +1 more source
2024 IEEE 65th Annual Symposium on Foundations of Computer Science (FOCS)Many problems in linear algebra -- such as those arising from non-Hermitian physics and differential equations -- can be solved on a quantum computer by processing eigenvalues of the non-normal input matrices. However, the existing Quantum Singular Value Transformation (QSVT) framework is ill-suited for this task, as eigenvalues and singular values are
Guang Hao Low, Yuan Su
openaire +2 more sources
Estimates on the eigenvalues for some nonlinear ordinary differential operators [PDF]
, 1989 The nonlinear eigenvalue problem Lu+f(x,u)=λu in (a,b) , with u(a)=u(b)=0 , where Lu=−(p(x)u ′ ) ′ +q(x)u is the usual differential operator for Sturm-Liouville problems, f is continuous and such that f(x,0)=0 for all x , and λ is a real parameter ...
Chiappinelli, Raffaele
core
Renormalisation of random hierarchial systems
, 2003 This thesis considers a number of problems which are related to the study of random fractals. We define a class of iterations (which we call random hierarchical systems) of probability distributions, which are defined by applying a random map to a set of
Jordan, Jonathan., Jordan, Jonathan
core +1 more source
Advanced Intelligent Discovery, EarlyView.This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley +1 more source
Universal Adjacency Matrices with Two Eigenvalues
AMS Mathematics Subject Classification: 05C50.Adjacency matrix;Universal adjacency matrix;Laplacian matrix;signless Laplacian;Graph spectra;Eigenvalues;Strongly regular ...
Omidi, G.R., Haemers, W.H.
core
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
Advanced Intelligent Discovery, EarlyView.This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
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