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Related papers: A random process asperity model for adhesion

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The wetting properties of solid substrates with customary (i.e., macroscopic) random roughness are considered as a function of the microscopic contact angle of the wetting liquid and its partial pressure in the surrounding gas phase.…

Soft Condensed Matter · Physics 2015-03-19 S. Herminghaus

Recent works have shown an interest in investigating the frequentist asymptotic properties of Bayesian procedures for high-dimensional linear models under sparsity constraints. However, there exists a gap in the literature regarding…

Statistics Theory · Mathematics 2025-09-23 Marion Naveau , Maud Delattre , Laure Sansonnet

Simple Exponential Smoothing is a classical technique used for smoothing time series data by assigning exponentially decreasing weights to past observations through a recursive equation; it is sometimes presented as a rule of thumb…

Methodology · Statistics 2024-03-08 Enrico Bernardi , Alberto Lanconelli , Christopher S. A. Lauria

The analysis of spatial extremes requires the joint modeling of a spatial process at a large number of stations and max-stable processes have been developed as a class of stochastic processes suitable for studying spatial extremes. Spatial…

Methodology · Statistics 2012-09-28 Soyoung Jeon , Richard L. Smith

Using three-dimensional Discrete Element Method (DEM) simulations, we investigate the erosion dynamics of a cohesive bed composed of wet spherical particles subjected to the shear flow of an overlying non-cohesive granular layer. Cohesion…

Soft Condensed Matter · Physics 2026-03-03 Lama Braysh , Patrick Mutabaruka , Farhang Radjai , Serge Mora

Consider the random graph $G({\mathcal P}_{n},r)$ whose vertex set ${\mathcal P}_{n}$ is a Poisson point process of intensity $n$ on $(- \frac{1}{2}, \frac{1}{2}]^d$, $d \geq 2$. Any two vertices $X_i,X_j \in {\mathcal P}_{n}$ are connected…

Probability · Mathematics 2015-10-20 Srikanth K. Iyer

The thermal effects of plastic and frictional heat generation and elevated temperature were examined along with the role of adhesion in the context of galling wear, using a representative crystal plasticity, normally loaded, sliding surface…

Materials Science · Physics 2019-10-10 Benjamin Poole , Bartosz Barzdajn , Daniele Dini , David Stewart , Fionn Dunne

The Bernstein-von Mises theorem (BvM) gives conditions under which the posterior distribution of a parameter $\theta\in\Theta\subseteq\mathbb R^d$ based on $n$ independent samples is asymptotically normal. In the high-dimensional regime, a…

Statistics Theory · Mathematics 2024-11-05 Anya Katsevich

Consistency models, which were proposed to mitigate the high computational overhead during the sampling phase of diffusion models, facilitate single-step sampling while attaining state-of-the-art empirical performance. When integrated into…

Machine Learning · Statistics 2024-02-13 Gen Li , Zhihan Huang , Yuting Wei

A generic algorithm for the extraction of probabilistic (Bayesian) information about model parameters from data is presented. The algorithm propagates an ensemble of particles in the product space of model parameters and outputs. Each…

Computation · Statistics 2015-09-18 Carlo Albert

A succesful method to describe the asymptotic behavior of a discrete time stochastic process governed by some recursive formula is to relate it to the limit sets of a well chosen mean differential equation. Under an attainability condition,…

Probability · Mathematics 2011-01-19 Mathieu Faure , Gregory Roth

Adhesion is a fundamental phenomenon that plays a role in many engineering and biological applications. This paper concerns the use of machine learning to characterize the effective adhesive properties when a thin film is peeled from a…

Applied Physics · Physics 2023-09-04 Maximo Cravero Baraja , Kaushik Bhattacharya

Motivated by certain problems of statistical physics we consider a stationary stochastic process in which deterministic evolution is interrupted at random times by upward jumps of a fixed size. If the evolution consists of linear decay, the…

Statistical Mechanics · Physics 2009-10-31 O. Deloubriere , H. J. Hilhorst

To date, density functional theory (DFT) is one of the most accurate and yet practical theory to gain insight about materials properties. Although successful, the computational cost is the main hurdle even today. A way out is combining DFT…

Materials Science · Physics 2019-04-19 Shweta Mehta , Sheena Agarwal , Kavita Joshi

We consider an anisotropic version of Baxter's model of `sticky hard spheres', where a nonuniform adhesion is implemented by adding, to an isotropic surface attraction, an appropriate `dipolar sticky' correction (positive or negative,…

Soft Condensed Matter · Physics 2009-11-13 Domenico Gazzillo , Riccardo Fantoni , Achille Giacometti

In some estimation problems, especially in applications dealing with information theory, signal processing and biology, theory provides us with additional information allowing us to restrict the parameter space to a finite number of points.…

Methodology · Statistics 2012-07-25 Christine Choirat , Raffaello Seri

The fidelity-based smooth min-relative entropy is a distinguishability measure that has appeared in a variety of contexts in prior work on quantum information, including resource theories like thermodynamics and coherence. Here we provide a…

Quantum Physics · Physics 2024-05-29 Theshani Nuradha , Mark M. Wilde

In this article, we present a model of heat transfer occurring through a li\-quid film flowing down a vertical wall. This new model is formally derived using the method of asymptotic expansions by introducing appropriately chosen…

Fluid Dynamics · Physics 2020-02-20 Marx Chhay , Denys Dutykh , Marguerite Gisclon , Christian Ruyer-Quil

The wetting properties of solid substrates with macroscopic random roughness are considered as a function of the microscopic contact angle of the wetting liquid and its partial pressure in the surrounding gas phase. It is shown that Wenzel…

Soft Condensed Matter · Physics 2016-10-05 Stephan Herminghaus

Consider the semiparametric transformation model $\Lambda_{\theta_o}(Y)=m(X)+\epsilon$, where $\theta_o$ is an unknown finite dimensional parameter, the functions $\Lambda_{\theta_o}$ and $m$ are smooth, $\epsilon$ is independent of $X$,…

Statistics Theory · Mathematics 2011-10-11 Rawane Samb , Cédric Heuchenne , Ingrid Van Keilegom