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Gaussian belief propagation (GBP) is a recursive computation method that is widely used in inference for computing marginal distributions efficiently. Depending on how the factorization of the underlying joint Gaussian distribution is…

Information Theory · Computer Science 2018-01-22 Jian Du , Shaodan Ma , Yik-Chung Wu , Soummya Kar , José M. F. Moura

We study optical pulse propagation through a hollow-core fiber filled with a radially inhomogeneous cloud of cold atoms. A co-propagating control field establishes electromagnetically induced transparency. In analogy to a graded index…

Atomic Physics · Physics 2019-07-31 Roman Sulzbach , Thorsten Peters , Reinhold Walser

In this paper, we extend the paraxial conical refraction model to the case of the partially coherent light using the unified optical coherence theory. We demonstrate the decomposition of conical refraction correlation functions into…

Optics · Physics 2022-05-12 V. Yu. Mylnikov , V. V. Dudelev , E. U. Rafailov , G. S. Sokolovskii

We theoretically and experimentally studied a novel class of vortex beams named open vortex beams (OVBs). Such beams are generated using Gaussian beams diffracted by partially blocked fork-shaped gratings (PB-FSGs).The analytical model of…

Optics · Physics 2021-10-27 Ruoyu Zeng , Qi Zhao , Yuanjie Yang

A phenomenological method is developed to consider elastic guided wave propagation in complex curved waveguides. The theory on guided wave propagation in hollow circular cylinders is used in order to verify the method. The results are…

Classical Physics · Physics 2012-09-03 E. Khajeh , L. Breon , J. L. Rose

Reflectionless potentials following the prescription of Kay and Moses allow for total transmission of incoming waves of any kinetic energy. The optical analogue of such potentials occur as dielectric stratified media that can offer null…

3D Gaussian Splatting (3DGS) has recently emerged as a state-of-the-art 3D reconstruction and rendering technique due to its high-quality results and fast training and rendering time. However, pixels covered by the same Gaussian are always…

Computer Vision and Pattern Recognition · Computer Science 2025-10-07 Brian Chao , Hung-Yu Tseng , Lorenzo Porzi , Chen Gao , Tuotuo Li , Qinbo Li , Ayush Saraf , Jia-Bin Huang , Johannes Kopf , Gordon Wetzstein , Changil Kim

The analytical solution for the propagation of the laser beam with optical vortex through the system of lenses is presented. The optical vortex is introduced into the laser beam (described as Gaussian beam) by spiral phase plate. The…

We present a description of the evolution of a polarized Gaussian beam in a smoothly inhomogeneous isotropic medium in frame of the eikonal-based complex geometrical optics which describes the phase front and the cross section of the…

Optics · Physics 2015-06-04 Hehe Li , Peiyong Ji

When a laser-cooled atomic sample is optically excited, the envelope of coherent forward scattering can often be decomposed into a few complex Gaussian profiles. The convenience of Gaussian propagation helps addressing key challenges in…

Atomic Physics · Physics 2024-12-31 Xing Huang , Yuzhuo Wang , Jian Zhao , Saijun Wu

We theoretically study light propagation in guided Bloch surface waves (BSWs) supported by photonic crystal ridges. We demonstrate that low propagation losses can be achieved just by a proper design of the multilayer to obtain photonic band…

Optics · Physics 2020-12-30 Tommaso Perani , Marco Liscidini

3D Gaussian Splatting (3DGS) has advanced radiance field reconstruction by enabling real-time rendering. However, its reliance on Gaussian kernels for geometry and low-order Spherical Harmonics (SH) for color encoding limits its ability to…

Computer Vision and Pattern Recognition · Computer Science 2025-05-07 Rong Liu , Dylan Sun , Meida Chen , Yue Wang , Andrew Feng

Cosmological inhomogeneities gravitationally deflect radiation propagating from distant sources, transforming the spatial and angular correlation functions of intrinsic source properties. For a gaussian distribution of deflections (e.g.…

Astrophysics · Physics 2007-05-23 Eric V. Linder

Gaussian belief propagation (BP) is a computationally efficient method to approximate the marginal distribution and has been widely used for inference with high dimensional data as well as distributed estimation in large-scale networks.…

Information Theory · Computer Science 2017-11-29 Jian Du , Soummya Kar , José M. F. Moura

We show, both theoretically and experimentally, that the propagation of optical vortices in free space can be analysed by using the width ($w(z)$) of the host Gaussian beam and the inner and outer radii of the vortex beam at the source…

This paper introduces the first attempt to employ a localized meshless method to analyze time-harmonic acoustic wave propagation on curved surfaces with periodic holes/inclusions. In particular, the generalized finite difference method is…

Numerical Analysis · Mathematics 2023-07-20 Wen Hu , Zhuojia Fu , Leevan Ling

We have investigated the propagation dynamics of the circular Airy Gaussian vortex beams (CAGVBs) in a (2+1)-dimesional optical system discribed by fractional nonlinear Schr\"odinger equation (FNSE). By combining fractional diffraction with…

Pattern Formation and Solitons · Physics 2021-02-03 Shangling He , Kangzhu Zhou , Xi Peng , Jialong Tu , Yingji He , Dongmei Deng

The Gaussian function (GF) is widely used to explain the behavior or statistical distribution of many natural phenomena as well as industrial processes in different disciplines of engineering and applied science. For example, the GF can be…

Signal Processing · Electrical Eng. & Systems 2020-01-08 Ibrahim Al-Nahhal , Octavia A. Dobre , Ertugrul Basar , Cecilia Moloney , Salama Ikki

Testing a covariance matrix following a Gaussian graphical model (GGM) is considered in this paper based on observations made at a set of distributed sensors grouped into clusters. Ordered transmissions are proposed to achieve the same…

Signal Processing · Electrical Eng. & Systems 2019-10-23 Yicheng Chen , Rick S. Blum , Brian M. Sadler , Jiangfan Zhang

The Gaussian Process Convolution Model (GPCM; Tobar et al., 2015a) is a model for signals with complex spectral structure. A significant limitation of the GPCM is that it assumes a rapidly decaying spectrum: it can only model smooth…

Machine Learning · Statistics 2022-04-15 Wessel P. Bruinsma , Martin Tegnér , Richard E. Turner
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