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Dynamical processes on time-varying complex networks are key to understanding and modeling a broad variety of processes in socio-technical systems. Here we focus on empirical temporal networks of human proximity and we aim at understanding…

Physics and Society · Physics 2013-11-01 Laetitia Gauvin , André Panisson , Ciro Cattuto , Alain Barrat

These notes contains an introduction to the theory of Brownian and diffusion local time, as well as its relations to the Tanaka Formula, the extended Ito-Tanaka formula for convex functions, the running maximum process, and the theory of…

Probability · Mathematics 2015-12-31 Tomas Björk

The phenomenon of local dynamical inhomogeneity of time is predicted, which implies that the course of time along the trajectory of motion of a particle in the inertial reference frames moving relative to each other depends on the state of…

Quantum Physics · Physics 2007-05-23 V. P. Oleinik , Yu. C. Borimsky , Yu. D. Arepjev

Many records in environmental sciences exhibit asymmetric trajectories and there is a need for simple and tractable models which can reproduce such features. In this paper we explore an approach based on applying both a time change and a…

Methodology · Statistics 2015-10-09 Pierre Ailliot , Bernard Delyon , Valérie Monbet , Marc Prevosto

As a continuation of Part I [8], a more precise formulation of local time and local system is given. The observation process is reflected in order to give a relation between the classical physics for centers of mass of local systems and the…

General Relativity and Quantum Cosmology · Physics 2007-05-23 Hitoshi Kitada

To relax the apparent tension between nonlocal hidden variables and relativity, we propose that the observable proper time is not the same quantity as the usual proper-time parameter appearing in local relativistic equations. Instead, the…

High Energy Physics - Theory · Physics 2015-05-27 H. Nikolic

This study introduces an innovative local statistical moment approach for estimating Kramers-Moyal coefficients, effectively bridging the gap between nonparametric and parametric methodologies. These coefficients play a crucial role in…

Methodology · Statistics 2024-08-27 Christian Wiedemann , Matthias Wächter , Jan A. Freund , Joachim Peinke

In this paper we give an explicit expression for the local time of the classical risk process and associate it with the density of an occupational measure. To do so, we approximate the local time by a suitable sequence of absolutely…

Probability · Mathematics 2008-01-15 F. Cortes , J. A. León , J. Villa

We investigate the local time $(T_{loc})$ statistics for a run and tumble particle in an one dimensional inhomogeneous medium. The inhomogeneity is introduced by considering the position dependent rate of the form $R(x) = \gamma…

Statistical Mechanics · Physics 2021-04-26 Prashant Singh , Anupam Kundu

We consider stochastic thermodynamics as a theory of statistical inference for experimentally observed fluctuating time-series. To that end, we introduce a general framework for quantifying the knowledge about the dynamical state of the…

Statistical Mechanics · Physics 2015-05-19 Bernhard Altaner , Jürgen Vollmer

The accurate estimation of scaling exponents is central in the observational study of scale-invariant phenomena. Natural systems unavoidably provide observations over restricted intervals; consequently a stationary stochastic process (time…

Data Analysis, Statistics and Probability · Physics 2009-03-17 K. H. Kiyani , S. C. Chapman , N. W. Watkins

The apparent times and positions of moving clocks as predicted by both `non-local' and `local' Lorentz Transformations are considered. Only local transformations respect translational invariance. Such transformations change temporal but not…

General Physics · Physics 2011-11-10 J. H. Field

Complex systems are often characterized by the interplay of multiple interconnected dynamical processes operating across a range of temporal scales. This phenomenon is widespread in both biological and artificial scenarios, making it…

Statistical Mechanics · Physics 2025-09-08 Giorgio Nicoletti , Daniel M. Busiello

We present a simple dynamical model to address the question of introducing a stochastic nature in a time variable. This model includes noise in the time variable but not in the "space" variable, which is opposite to the normal description…

Computational Physics · Physics 2008-11-26 Toru Ohira

The problem of computing the rate of diffusion-aided activated barrier crossings between metastable states is one of broad relevance in physical sciences. The transition path formalism aims to compute the rate of these events by analysing…

Statistical Mechanics · Physics 2022-09-29 Rajeev Bhaskaran , Vijay Ganesh Sadhasivam

Exchangeability -- in which the distribution of an infinite sequence is invariant to reorderings of its elements -- implies the existence of a simple conditional independence structure that may be leveraged in the design of statistical…

Statistics Theory · Mathematics 2022-07-25 Trevor Campbell , Saifuddin Syed , Chiao-Yu Yang , Michael I. Jordan , Tamara Broderick

Space-time metamaterials, or materials with properties changing in space and time, have gained a wide-spread interest due to their exotic properties. In this Letter, we propose a novel temporal metasurface of phononic crystals in one and…

Applied Physics · Physics 2024-04-16 Kshiteej J. Deshmukh

A space fractional diffusion-like equation is introduced, which embodies the nonlocality in time, represented by the memory kernel and the non-locality in space. A specific example of the nonlocal term is considered in combination with…

Statistical Mechanics · Physics 2026-01-06 Pece Trajanovski , Irina Petreska , Katarzyna Gorska , Ljupco Kocarev , Trifce Sandev

We consider estimation of quantile curves for a general class of nonstationary processes. Consistency and central limit results are obtained for local linear quantile estimates under a mild short-range dependence condition. Our results are…

Statistics Theory · Mathematics 2009-08-26 Zhou Zhou , Wei Biao Wu

We address the problem of predicting spatio-temporal processes with temporal patterns that vary across spatial regions, when data is obtained as a stream. That is, when the training dataset is augmented sequentially. Specifically, we…

Machine Learning · Statistics 2018-06-25 Muhammad Osama , Dave Zachariah , Thomas B. Schön