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Related papers: Fluctuations and Correlations in Causal Set Theory

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Understanding the laws that govern a phenomenon is the core of scientific progress. This is especially true when the goal is to model the interplay between different aspects in a causal fashion. Indeed, causal inference itself is…

Artificial Intelligence · Computer Science 2025-08-27 Alessio Zanga , Elif Ozkirimli , Fabio Stella

Fluctuation theorems are fundamental results in non-equilibrium thermodynamics. Considering the fluctuation theorem with respect to the entropy production and an observable, we derive a new thermodynamic uncertainty relation which also…

Statistical Mechanics · Physics 2022-02-02 Gianluca Francica

We analyze the behavior of an ensemble of inertial particles in a one-dimensional smooth Gaussian velocity field, in the limit of large inertia, but considering a finite correlation time for the random field. We derive in this limit a…

Statistical Mechanics · Physics 2009-11-13 Piero Olla , Raffaella Vuolo

An approach for understanding the behavior of multiplicity distributions in restricted phase-space intervals derived on the basis of global observables is proposed. We obtain a unifying connection between local multiparticle clusters and…

High Energy Physics - Phenomenology · Physics 2008-11-26 S. V. Chekanov , V. I. Kuvshinov

We extend our study of a simple model of biological coevolution to its statistical properties. Staring with a complete description in terms of a master equation, we provide its relation to the deterministic evolution equations used in…

Populations and Evolution · Quantitative Biology 2007-05-23 R. K. P. Zia , Per Arne Rikvold

Information transmission in cells occurs quite accurately even when concentration changes are "read" by individual target molecules. In this Letter we study molecule number fluctuations when molecules diffuse and react. We show that, for…

Biological Physics · Physics 2014-12-17 Emiliano Pérez Ipiña , Silvina Ponce Dawson

In distributed systems where strong consistency is costly when not impossible, causal consistency provides a valuable abstraction to represent program executions as partial orders. In addition to the sequential program order of each…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-03-15 Matthieu Perrin , Achour Mostefaoui , Claude Jard

A variety of techniques have been proposed to train machine learning classifiers that are independent of a given feature. While this can be an essential technique for enabling background estimation, it may also be useful for reducing…

High Energy Physics - Phenomenology · Physics 2022-02-09 Aishik Ghosh , Benjamin Nachman

Correlation functions in concentrated ionic systems are studied within the mesoscopic theory at the level of the Gaussian approximation. The previously neglected fluctuation contribution to the inverse charge-charge correlation function is…

Soft Condensed Matter · Physics 2025-06-26 O. Patsahan , A. Ciach

Case-control designs are an important tool in contrasting the effects of well-defined treatments. In this paper, we reconsider classical concepts, assumptions and principles and explore when the results of case-control studies can be…

Methodology · Statistics 2021-05-06 Bas B. L. Penning de Vries , Rolf H. H. Groenwold

We analyze the fluctuation of the loss from default around its large portfolio limit in a class of reduced-form models of correlated firm-by-firm default timing. We prove a weak convergence result for the fluctuation process and use it for…

Probability · Mathematics 2015-02-20 Konstantinos Spiliopoulos , Justin A. Sirignano , Kay Giesecke

We propose a new method of discovering causal structures, based on the detection of local, spontaneous changes in the underlying data-generating model. We analyze the classes of structures that are equivalent relative to a stream of…

Artificial Intelligence · Computer Science 2013-01-14 Jin Tian , Judea Pearl

The Causal Set approach to quantum gravity asserts that spacetime, at its smallest length scale, has a discrete structure. This discrete structure takes the form of a locally finite order relation, where the order, corresponding with the…

General Relativity and Quantum Cosmology · Physics 2007-05-23 David Rideout

We propose a fluctuation analysis to quantify spatial correlations in complex networks. The approach considers the sequences of degrees along shortest paths in the networks and quantifies the fluctuations in analogy to time series. In this…

Data Analysis, Statistics and Probability · Physics 2014-09-15 Diego Rybski , Hernán D. Rozenfeld , Jürgen P. Kropp

The perturbation theory for critical points of causal variational principles is developed. We first analyze the class of perturbations obtained by multiplying the universal measure by a weight function and taking the push-forward under a…

Mathematical Physics · Physics 2020-08-26 Felix Finster

In this paper we consider a claim that in the natural world there is no fact of the matter about the spatio-temporal separation of events. In order to make sense of such a notion and construct useful models of the world, it is proposed to…

Neurons and Cognition · Quantitative Biology 2024-04-18 Bartosz Jura

We address causal reasoning in multivariate time series data generated by stochastic processes. Existing approaches are largely restricted to static settings, ignoring the continuity and emission of variations across time. In contrast, we…

Machine Learning · Computer Science 2024-02-29 Mehdi Fatemi , Sindhu Gowda

The recent development of the theory of fluctuation relations has led to new insights into the ever-lasting question of how irreversible behavior emerges from time-reversal symmetric microscopic dynamics. We provide an introduction to…

Popular Physics · Physics 2011-12-20 Michele Campisi , Peter Hänggi

Recent causal inference literature has introduced causal effect decompositions to quantify sources of observed inequalities or disparities in outcomes, but these approaches are typically limited to pairwise comparisons. In healthcare…

Methodology · Statistics 2026-04-27 Lin Yu , Zhihui Liu , Kathy Han , Olli Saarela

Causality is a non-obvious concept that is often considered to be related to temporality. In this paper we present a number of past and present approaches to the definition of temporality and causality from philosophical, physical, and…

Machine Learning · Computer Science 2010-07-16 Kamran Karimi