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We give a brief account of the development of methods to include thermal fluctuations into lattice Boltzmann algorithms. Emphasis is put on our recent work (Phys. Rev. E 76, 036704 (2007)) which provides a clear understanding in terms of…

Statistical Mechanics · Physics 2009-11-13 Burkhard Duenweg , Ulf D. Schiller , Anthony J. C. Ladd

Experiments in recent years have vividly demonstrated that gene expression can be highly stochastic. How protein concentration fluctuations affect the growth rate of a population of cells, is, however, a wide open question. We present a…

Molecular Networks · Quantitative Biology 2015-05-13 Sorin Tanase-Nicola , Pieter Rein ten Wolde

1. Animal movement patterns contribute to our understanding of variation in breeding success and survival of individuals, and the implications for population dynamics. 2. Over time, sensor technology for measuring movement patterns has…

Quantitative Methods · Quantitative Biology 2018-01-11 Leah R. Johnson , Philipp H. Boersch-Supan , Richard A. Phillips , Sadie J. Ryan

Species evolution is essentially a random process of interaction between biological populations and their environments. As a result, some physical parameters in evolution models are subject to statistical fluctuations. In this paper, two…

Populations and Evolution · Quantitative Biology 2015-06-02 Duo-Fang Li , Tian-Guang Cao , Jin-Peng Geng , Li-Hua Qiao , Jian-Zhong Gu , Yong Zhan

The finite sensitivity of instruments or detection methods means that data sets in many areas of astronomy, for example cosmological or exoplanet surveys, are necessarily systematically incomplete. Such data sets, where the population being…

Instrumentation and Methods for Astrophysics · Physics 2020-10-14 Adam B. Mantz

From scientific experiments to online A/B testing, the previously observed data often affects how future experiments are performed, which in turn affects which data will be collected. Such adaptivity introduces complex correlations between…

Machine Learning · Statistics 2018-01-03 Xinkun Nie , Xiaoying Tian , Jonathan Taylor , James Zou

In some causal inference scenarios, the treatment variable is measured inaccurately, for instance in epidemiology or econometrics. Failure to correct for the effect of this measurement error can lead to biased causal effect estimates.…

Machine Learning · Computer Science 2024-09-13 Antti Pöllänen , Pekka Marttinen

Statistical analysis of financial data most focused on testing the validity of Brownian motion (Bm). Analysis performed on several time series have shown deviation from the Bm hypothesis, that is at the base of the evaluation of many…

Statistical Finance · Quantitative Finance 2009-11-13 Filippo Petroni , Giulia Rotundo

Nanoscale machines are strongly influenced by thermal fluctuations, contrary to their macroscopic counterparts. As a consequence, even the efficiency of such microscopic machines becomes a fluctuating random variable. Using geometric…

Statistical Mechanics · Physics 2019-04-16 Sreekanth K Manikandan , Lennart Dabelow , Ralf Eichhorn , Supriya Krishnamurthy

In regression analysis, associations between continuous predictors and the outcome are often assumed to be linear. However, modeling the associations as non-linear can improve model fit. Many flexible modeling techniques, like (fractional)…

In the past years, a remarkable mapping has been found between the dynamics of a population of M individuals undergoing random mutations and selection, and that of a single system in contact with a thermal bath with temperature 1/M. This…

Statistical Mechanics · Physics 2015-07-28 Tommaso Brotto , Guy Bunin , Jorge Kurchan

Previous work on causal inference has primarily focused on averages and conditional averages of treatment effects, with significantly less attention on variability and uncertainty in individual treatment responses. In this paper, we…

Machine Learning · Computer Science 2026-02-10 Liyuan Xu , Bijan Mazaheri

We consider "nonconventional" averaging setup in the form $\frac {dX^\epsilon(t)}{dt}=\epsilon B\big(X^\epsilon(t),\xi(q_1(t)), \xi(q_2(t)),...,\xi(q_\ell(t))\big)$ where $\xi(t),t\geq 0$ is either a stochastic process or a dynamical system…

Probability · Mathematics 2013-02-21 Yuri Kifer

Population-based evolutionary algorithms (EAs) have been widely applied to solve various optimization problems. The question of how the performance of a population-based EA depends on the population size arises naturally. The performance of…

Neural and Evolutionary Computing · Computer Science 2013-05-13 Jun He , Tianshi Chen , Boris Mitavskiy

We show how statistical thermodynamics can be formulated in situations in which thermodynamics applies, while equilibrium statistical mechanics does not. A typical case is, in the words of Landau and Lifshitz, that of partial (or…

Statistical Mechanics · Physics 2013-04-16 A. Carati , A. Maiocchi , L. Galgani

Significant progress has been made in the field of thermophotovoltaics, with efficiency recently rising to over 40% due to improvements in cell design and material quality, higher emitter temperatures, and better spectral management.…

Performative prediction is an emerging paradigm in machine learning that addresses scenarios where the model's prediction may induce a shift in the distribution of the data it aims to predict. Current works in this field often rely on…

Machine Learning · Computer Science 2025-09-03 Guangzheng Zhong , Yang Liu , Jiming Liu

A thermodynamic device placed outdoors, or a local ecosystem, is subject to a variety of different temperatures given by short-tem (daily) and long-term (seasonal) variations. In the long term a superstatistical description makes sense,…

Atmospheric and Oceanic Physics · Physics 2013-07-31 G. Cigdem Yalcin , Christian Beck

Collective motion - or flocking - is an emergent phenomena that underlies many biological processes of relevance, from cellular migrations to animal groups movement. In this work, we derive scaling relations for the fluctuations of the mean…

Soft Condensed Matter · Physics 2023-02-13 Martino Brambati , Giuseppe Fava , Francesco Ginelli

Groups coordinate more effectively when individuals are able to learn from others' successes. But acquiring such knowledge is not always easy, especially in real-world environments where success is hidden from public view. We suggest that…

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