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This review is intended to give a pedagogical and unified view on the subject of the statistics and scaling of physical quantities in disordered electron systems at very low temperatures. Quantum coherence at low temperatures and randomness…

Mesoscale and Nanoscale Physics · Physics 2015-06-25 Martin Janssen

We consider biochemical reaction chains and investigate how random external fluctuations, as characterized by variance and coefficient of variation, propagate down the chains. We perform such a study under the assumption that the number of…

Probability · Mathematics 2007-08-03 David F. Anderson , Jonathan C. Mattingly

Single particle tracking of mRNA molecules and lipid granules in living cells shows that the time averaged mean squared displacement $\overline{\delta^2}$ of individual particles remains a random variable while indicating that the particle…

Statistical Mechanics · Physics 2009-11-13 Y. He , S. Burov , R. Metzler , E. Barkai

The study of moving particles (e.g. molecules, virus, vesicles, organelles, or whole cells) is crucial to decipher a plethora of cellular mechanisms within physiological and pathological conditions. Powerful live-imaging approaches enable…

Numerical Analysis · Mathematics 2023-11-13 Eloina Corradi , Maurizio Tavelli , Marie-Laure Baudet , Walter Boscheri

A general theory of nucleation for colloids and macromolecules in solution is formulated within the context of fluctuating hydrodynamics. A formalism for the determination of nucleation pathways is developed and stochastic differential…

Soft Condensed Matter · Physics 2012-01-23 James F. Lutsko

Complex systems often have features that can be modeled by advanced mathematical tools [1]. Of special interests are the features of complex systems that have a network structure as such systems are important for modeling technological and…

Classical Physics · Physics 2019-06-13 Nikolay K. Vitanov , Kaloyan N. Vitanov , Zlatinka I. Dimitrova

Trajectories of on-off events are the output of many single molecule experiments. Usually, one describes the underlying mechanism that generates the trajectory using a kinetic scheme, and by analyzing the trajectory aims at deducing this…

Subcellular Processes · Quantitative Biology 2010-08-16 Ophir Flomenbom , Joseph Klafter

We consider stochastic systems of interacting particles or agents, with dynamics determined by an interaction kernel which only depends on pairwise distances. We study the problem of inferring this interaction kernel from observations of…

Statistics Theory · Mathematics 2020-07-31 Fei Lu , Mauro Maggioni , Sui Tang

Moment optimization techniques have been recently proposed to solve globally various classes of optimal control problems. As those methods return truncated moment sequences of occupation measures, this paper explores a numeric method for…

Optimization and Control · Mathematics 2014-04-17 Mathieu Claeys

We consider a model system of persistent random walkers that can jam, pass through each other or jump apart (recoil) on contact. In a continuum limit, where particle motion between stochastic changes in direction becomes deterministic, we…

Statistical Mechanics · Physics 2023-05-03 Matthew J Metson , Martin R Evans , Richard A Blythe

We show that a microscopic definition of crystal defect, based on the effective mean single-particle potential energy, makes it possible to detect and visualize various types of local and extended crystal defects and develop an effective…

Materials Science · Physics 2007-05-23 M. Patriarca , M. Robles , K. Kaski

Microorganisms often perform chemotaxis, (i.e., sensing and moving toward a region with a higher concentration of an attractive chemical) by changing the rate of tumbling for random walk. We studied several models with internal adaptive…

Statistical Mechanics · Physics 2009-11-11 Masayo Inoue , Kunihiko Kaneko

Human movement prediction is difficult as humans naturally exhibit complex behaviors that can change drastically from one environment to the next. In order to alleviate this issue, we propose a prediction framework that decouples short-term…

Robotics · Computer Science 2020-03-19 Philipp Kratzer , Marc Toussaint , Jim Mainprice

Many real-world optimisation problems involve dynamic and stochastic components. While problems with multiple interacting components are omnipresent in inherently dynamic domains like supply-chain optimisation and logistics, most research…

Neural and Evolutionary Computing · Computer Science 2020-09-16 Ragav Sachdeva , Frank Neumann , Markus Wagner

We propose an empirical approach centered on the spectral dynamics of weights -- the behavior of singular values and vectors during optimization -- to unify and clarify several phenomena in deep learning. We identify a consistent bias in…

In this paper we theoretically investigate underlying assumptions that have been used for designing adaptive particle swarm optimization algorithms in the past years. We relate these assumptions to the movement patterns of particles…

Neural and Evolutionary Computing · Computer Science 2018-02-15 Mohammad Reza Bonyadi

Model-based prediction of stochastic noise in biomolecular reactions often resorts to approximation with unknown precision. As a result, unexpected stochastic fluctuation causes a headache for the designers of biomolecular circuits. This…

Molecular Networks · Quantitative Biology 2018-08-07 Yuta Sakurai , Yutaka Hori

Time-resolved investigations of ultrafast electronic and molecular dynamics were not possible until recently. The typical time scale of these processes is in the picosecond to attosecond realm. The tremendous technological progress in…

Atomic Physics · Physics 2013-05-14 Stefan Pabst

We theoretically study the transport properties of self-propelled particles on complex structures, such as motor proteins on filament networks. A general master equation formalism is developed to investigate the persistent motion of…

Soft Condensed Matter · Physics 2014-09-19 M. Reza Shaebani , Zeinab Sadjadi , Igor M. Sokolov , Heiko Rieger , Ludger Santen

We study an active random walker model in which a particle's motion is determined by a self-generated field. The field encodes information about the particle's path history. This leads to either self-attractive or self-repelling behavior.…

Statistical Mechanics · Physics 2009-11-11 R. Grima