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The Gaussian Kinematic Formula (GKF, see Adler and Taylor (2007,2011)) is an extremely powerful tool allowing for explicit analytic predictions of expected values of Minkowski functionals under realistic experimental conditions for…

Instrumentation and Methods for Astrophysics · Physics 2015-03-18 Yabebal Fantaye , Frode Hansen , Davide Maino , Domenico Marinucci

The Gaussian Kinematic Formula (GKF) is a powerful and computationally efficient tool to perform statistical inference on random fields and became a well-established tool in the analysis of neuroimaging data. Using realistic error models,…

Methodology · Statistics 2024-04-17 Fabian JE Telschow , Samuel Davenport

We apply methods of algebraic integral geometry to prove a special case of the Gaussian kinematic formula of Adler-Taylor. The idea, suggested already by Adler and Taylor, is to view the GKF as the limit of spherical kinematic formulas for…

Differential Geometry · Mathematics 2024-09-20 Joseph H. G. Fu

In this paper we consider probabilistic analogues of some classical integral geometric formulae: Weyl--Steiner tube formulae and the Chern--Federer kinematic fundamental formula. The probabilistic building blocks are smooth, real-valued…

Probability · Mathematics 2007-05-23 Jonathan E. Taylor

This article constructs simultaneous confidence bands (SCBs) for functional parameters using the Gaussian Kinematic formula of $t$-processes (tGKF). Although the tGKF relies on Gaussianity, we show that a central limit theorem (CLT) for the…

Statistics Theory · Mathematics 2024-04-19 Fabian J. E. Telschow , Armin Schwartzman

Kinetic Field Theory (KFT) is a statistical field theory for an ensemble of point-like classical particles in or out of equilibrium. We review its application to cosmological structure formation. Beginning with the construction of the…

The Gaussian Free Field (GFF) is a canonical random surface in probability theory generalizing Brownian motion to higher dimensions. In two dimensions, it is critical in several senses, and is expected to be the universal scaling limit of a…

Probability · Mathematics 2023-02-28 Shirshendu Ganguly , Reza Gheissari

Accurately modeling and predicting complex dynamical systems, particularly those involving force exchange and dissipation, is crucial for applications ranging from fluid dynamics to robotics, but presents significant challenges due to the…

Robotics · Computer Science 2025-06-24 Andrea Testa , Søren Hauberg , Tamim Asfour , Leonel Rozo

Many filters have been proposed in recent decades for the nonlinear state estimation problem. The linearization-based extended Kalman filter (EKF) is widely applied to nonlinear industrial systems. As EKF is limited in accuracy and…

Systems and Control · Electrical Eng. & Systems 2020-09-29 Chengling Fang , Jiang Liu , Songqing Ye , Ju Zhang

We present cosmological perturbations of kinetic components based on relativistic Boltzmann equations in the context of generalized gravity theories. Our general theory considers an arbitrary number of scalar fields generally coupled with…

Astrophysics · Physics 2011-07-19 J. Hwang , H. Noh

Geometric data and purpose-built generative models on them have become ubiquitous in high-impact deep learning application domains, ranging from protein backbone generation and computational chemistry to geospatial data. Current geometric…

Machine Learning · Computer Science 2026-02-10 Oscar Davis , Michael S. Albergo , Nicholas M. Boffi , Michael M. Bronstein , Avishek Joey Bose

One proposal for deriving effective cosmological models from theories of quantum gravity is to view the former as a mean-field (hydrodynamic) description of the latter, which describes a universe formed by a 'condensate' of quanta of…

General Relativity and Quantum Cosmology · Physics 2015-08-12 Steffen Gielen

In this paper we study a new generalization of the kinetic equation emerging in run-and-tumble models. We show that this generalization leads to a wide class of generalized fractional kinetic (GFK) and telegraph-type equations depending by…

Statistical Mechanics · Physics 2024-10-15 Luca Angelani , Alessandro De Gregorio , Roberto Garra

To predict future trajectories, the normalizing flow with a standard Gaussian prior suffers from weak diversity. The ineffectiveness comes from the conflict between the fact of asymmetric and multi-modal distribution of likely outcomes and…

Computer Vision and Pattern Recognition · Computer Science 2025-01-16 Jiahe Chen , Jinkun Cao , Dahua Lin , Kris Kitani , Jiangmiao Pang

The Gaussian random field (GRF) and the Gaussian Markov random field (GMRF) have been widely used to accommodate spatial dependence under the generalized linear mixed model framework. These models have limitations rooted in the symmetry and…

Methodology · Statistics 2022-12-15 Marcos O. Prates , Dipak K. Dey , Michael R. Willig , Jun Yan

The expected Euler characteristic (EEC) curve of excursion sets of a Gaussian random field is used to approximate the distribution of its supremum for high thresholds. Viewed as a function of the excursion threshold, the EEC is expressed by…

Statistics Theory · Mathematics 2024-04-19 Fabian Telschow , Armin Schwartzman , Dan Cheng , Pratyush Pranav

The gravitational field exterior respectively interior to a spherically symmetric, isolated body made of perfect fluid is examined within the quasi-metric framework (QMF). It is required that the gravitational field is "metrically static",…

General Relativity and Quantum Cosmology · Physics 2024-03-21 Dag Østvang

The evolution of probability distribution functions (PDFs) of continuous density, velocity and velocity derivatives ( deformation tensor) fields in the theory of cosmological gravitational instability are considered. We show that in the…

Astrophysics · Physics 2007-05-23 Lev Kofman

In recent work we developed a description of cosmic large scale structure formation in terms of non-equilibrium ensembles of classical particles, with time evolution obtained in the framework of a statistical field theory. In these works,…

Statistical Mechanics · Physics 2018-04-27 Felix Fabis , Elena Kozlikin , Robert Lilow , Matthias Bartelmann

A generalization of the Heisenberg algebra has been recently constructed. This generalized algebra has a characteristic function which depends on one of its generators. When this function is linear, $qJ_0+s$, it is possible to construct a…

High Energy Physics - Phenomenology · Physics 2016-09-06 C. I. Ribeiro-Silva , N. M. Oliveira-Neto
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