Universal random matrix correlations of ratios of characteristic polynomials at the spectral edges [PDF]
It has been shown recently by Fyodorov and Strahov [math-ph/0204051] that Cauchy transforms of orthogonal polynomials appear naturally in general correlation functions containing ratios of characteristic polynomials of random N×N Hermitian matrices.
Akemann, G +3 more
core +1 more source
This review aims to provide a broad understanding for interdisciplinary researchers in engineering and clinical applications. It addresses the development and control of magnetic actuation systems (MASs) in clinical surgeries and their revolutionary effects in multiple clinical applications.
Yingxin Huo +3 more
wiley +1 more source
An evolution of matrix-valued orthogonal polynomials [PDF]
21 pages, 3 ...
Koelink, E. +2 more
openaire +4 more sources
Toward Fully Soft and Multifunctional Shape Sensing via Optical Waveguide Arrays
This work develops a sheet made with arrays of soft optical fibers that can reconstruct its 3D surface shape. Synergy of the waveguides’ responses to bending and pressing force allows shape reconstruction with resilience to damage. Applied onto surfaces of robotic or living systems, our design can be implemented in virtual reality, teleoperation ...
Qifan Yu, Nina Cao, Kaitlyn Becker
wiley +1 more source
Matrix inversion using orthogonal polynomials
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhang, Ruiming, Chen, Li-Chen
openaire +2 more sources
Contractions of 2D 2nd Order Quantum Superintegrable Systems and the Askey Scheme for Hypergeometric Orthogonal Polynomials [PDF]
We show explicitly that all 2nd order superintegrable systems in 2 dimensions are limiting cases of a single system: the generic 3-parameter potential on the 2-sphere, S9 in our listing.
Willard Miller Jr. +8 more
core +1 more source
Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica +38 more
wiley +1 more source
Jacobi–Sobolev Orthogonal Polynomials, Differential Properties and Structural Formulas
In this paper, we extend some differential and structural results for monic Jacobi–Sobolev orthogonal polynomials, associated with a general discrete Sobolev inner product, with a Jacobi continuous part. We consider finitely many exterior mass points and
Héctor Pijeira-Cabrera +2 more
doaj +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Vector-Valued Polynomials and a Matrix Weight Function with B2-Action
The structure of orthogonal polynomials on $mathbb{R}^{2}$ with the weight function $vert x_{1}^{2}-x_{2}^{2}vert ^{2k_{0}}vertx_{1}x_{2}vert ^{2k_{1}}e^{-( x_{1}^{2}+x_{2}^{2})/2}$ is based on the Dunkl operators of type $B_{2}$.
Charles F. Dunkl
doaj +1 more source

