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The exact analytical expressions for the time-dependent cross-correlations of the translational and rotational Brownian displacements of a particle with arbitrary shape were derived by us in [J. Chem. Phys. 142, 214902 (2015) and 144,…

Soft Condensed Matter · Physics 2018-10-09 B. Cichocki , M. L. Ekiel-Jezewska , E. Wajnryb

Proteins are made of atoms constantly fluctuating, but can occasionally undergo large-scale changes. Such transitions are of biological interest, linking the structure of a protein to its function with a cell. Atomic-level simulations, such…

Computational Physics · Physics 2022-10-26 Amélie Chatelain , Elena Tommasone , Laurent Daudet , Iacopo Poli

Active particles self-propel themselves with a stochastically evolving velocity, generating a persistent motion leading to a non-diffusive behavior of the position distribution. Nevertheless, an effective diffusive behavior emerges at times…

Statistical Mechanics · Physics 2022-09-14 Ion Santra , Urna Basu , Sanjib Sabhapandit

A change point problem occurs in many statistical applications. If there exist change points in a model, it is harmful to make a statistical analysis without any consideration of the existence of the change points and the results derived…

Methodology · Statistics 2011-01-24 Xiaoping Shi , Yuehua Wu , Baisuo Jin

We investigate proteins within heterogeneous cell membranes where non-equilibrium phenomena arises from spatial variations in concentration and temperature. We develop simulation methods building on non-equilibrium statistical mechanics to…

Soft Condensed Matter · Physics 2025-08-28 D. Jasuja , P. J. Atzberger

Many astrophysical phenomena are time-varying, in the sense that their intensity, energy spectrum, and/or the spatial distribution of the emission suddenly change. This paper develops a method for modeling a time series of images. Under the…

Instrumentation and Methods for Astrophysics · Physics 2021-03-24 Cong Xu , Hans Moritz Günther , Vinay L. Kashyap , Thomas C. M. Lee , Andreas Zezas

Diffusion models have transformed image synthesis through iterative denoising, by defining trajectories from noise to coherent data. While their capabilities are widely celebrated, a critical challenge remains unaddressed: ensuring…

Computer Vision and Pattern Recognition · Computer Science 2025-12-22 Andreas Floros , Seyed-Mohsen Moosavi-Dezfooli , Pier Luigi Dragotti

The Mean Square Displacement is a central tool in the analysis of Single Particle Tracking experiments, shedding light on various biophysical phenomena. Frequently, parameters are extracted by performing time-averages on single particle…

Biological Physics · Physics 2013-05-24 Eldad Kepten Irena Bronshtein , Yuval Garini

Diffusion of tracer particles in the cytoplasm of mammalian cells is often anomalous with a marked heterogeneity even within individual particle trajectories. Despite considerable efforts, the mechanisms behind these observations have…

Biological Physics · Physics 2020-08-05 Adal Sabri , Xinran Xu , Diego Krapf , Matthias Weiss

Diffusion can be strongly affected by ballistic flights (long jumps) as well as long-lived sticking trajectories (long sticks). Using statistical inference techniques in the spirit of Granger causality, we investigate the appearance of long…

Statistical Mechanics · Physics 2014-12-02 S. Hallerberg , A. S. de Wijn

The diffusion of a particle in a crowded environment typically proceeds through three regimes: for very short times the particle diffuses freely until it collides with an obstacle for the first time, while for very long times diffusion the…

Biological Physics · Physics 2019-10-09 Nguiya P. Neo , Gary W. Slater

Single-particle tracking offers detailed information about the motion of molecules in complex environments such as those encountered in live cells, but the interpretation of experimental data is challenging. One of the most powerful tools…

Statistical Mechanics · Physics 2022-01-12 Zachary R Fox , Eli Barkai , Diego Krapf

Local diffusion coefficients in disordered systems such as spin glass systems and living cells are highly heterogeneous and may change over time. Such a time-dependent and spatially heterogeneous environment results in irreproducibility of…

Statistical Mechanics · Physics 2016-12-21 Takuma Akimoto , Eiji Yamamoto

Extensive time-series encoding the position of particles such as viruses, vesicles, or individual proteins are routinely garnered in single-particle tracking experiments or supercomputing studies. They contain vital clues on how viruses…

Dynamical phase transitions (DPTs) arise from qualitative changes in the long-time behavior of stochastic trajectories, often observed in systems with kinetic constraints or driven out of equilibrium. Here we demonstrate that first-order…

Statistical Mechanics · Physics 2024-07-29 Takahiro Kanazawa , Kyogo Kawaguchi , Kyosuke Adachi

Single-molecule tracking (SMT) methods are under considerable expansion in many fields of cell biology, as the dynamics of cellular components in biological mechanisms becomes increasingly relevant. Despite the development of SMT…

Quantitative Methods · Quantitative Biology 2015-06-08 Sylvain Tollis

Cellular networks are often composed of thin tubules connecting much larger node compartments. These structures serve for active or diffusion transport of proteins. Examples are glial networks in the brain, the endoplasmic reticulum in…

Soft Condensed Matter · Physics 2024-07-31 Frédéric Paquin-Lefebvre , Kanishka Basnayake , David Holcman

We reveal the mechanism of subdiffusion which emerges in a straightforward, one dimensional classical nonequilibrium dynamics of a Brownian ratchet driven by both a time-periodic force and Gaussian white noise. In a tailored parameter set…

Statistical Mechanics · Physics 2021-03-25 Jakub Spiechowicz , Jerzy Łuczka

It is increasingly common to encounter data from dynamic processes captured by static cross-sectional measurements over time, particularly in biomedical settings. Recent attempts to model individual trajectories from this data use optimal…

Machine Learning · Statistics 2020-07-28 Alexander Tong , Jessie Huang , Guy Wolf , David van Dijk , Smita Krishnaswamy

Change points in real-world systems mark significant regime shifts in system dynamics, possibly triggered by exogenous or endogenous factors. These points define regimes for the time evolution of the system and are crucial for understanding…

Machine Learning · Statistics 2025-09-30 Ioanna-Yvonni Tsaknaki , Fabrizio Lillo , Piero Mazzarisi
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