TY - JOUR A1 - Dybiec, Bartlomiej A1 - Capala, Karol A1 - Chechkin, Aleksei V. A1 - Metzler, Ralf T1 - Conservative random walks in confining potentials JF - Journal of physics : A, Mathematical and theoretical N2 - Levy walks are continuous time random walks with spatio-temporal coupling of jump lengths and waiting times, often used to model superdiffusive spreading processes such as animals searching for food, tracer motion in weakly chaotic systems, or even the dynamics in quantum systems such as cold atoms. In the simplest version Levy walks move with a finite speed. Here, we present an extension of the Levy walk scenario for the case when external force fields influence the motion. The resulting motion is a combination of the response to the deterministic force acting on the particle, changing its velocity according to the principle of total energy conservation, and random velocity reversals governed by the distribution of waiting times. For the fact that the motion stays conservative, that is, on a constant energy surface, our scenario is fundamentally different from thermal motion in the same external potentials. In particular, we present results for the velocity and position distributions for single well potentials of different steepness. The observed dynamics with its continuous velocity changes enriches the theory of Levy walk processes and will be of use in a variety of systems, for which the particles are externally confined. KW - Levy walk KW - conservative random walks KW - Levy flight Y1 - 2018 U6 - https://doi.org/10.1088/1751-8121/aaefc2 SN - 1751-8113 SN - 1751-8121 VL - 52 IS - 1 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Awad, Emad A1 - Metzler, Ralf T1 - Closed-form multi-dimensional solutions and asymptotic behaviours for subdiffusive processes with crossovers: II. Accelerating case JF - Journal of physics : A, Mathematical and theoretical N2 - Anomalous diffusion with a power-law time dependence vertical bar R vertical bar(2)(t) similar or equal to t(alpha i) of the mean squared displacement occurs quite ubiquitously in numerous complex systems. Often, this anomalous diffusion is characterised by crossovers between regimes with different anomalous diffusion exponents alpha(i). Here we consider the case when such a crossover occurs from a first regime with alpha(1) to a second regime with alpha(2) such that alpha(2) > alpha(1), i.e., accelerating anomalous diffusion. A widely used framework to describe such crossovers in a one-dimensional setting is the bi-fractional diffusion equation of the so-called modified type, involving two time-fractional derivatives defined in the Riemann-Liouville sense. We here generalise this bi-fractional diffusion equation to higher dimensions and derive its multidimensional propagator (Green's function) for the general case when also a space fractional derivative is present, taking into consideration long-ranged jumps (Levy flights). We derive the asymptotic behaviours for this propagator in both the short- and long-time as well the short- and long-distance regimes. Finally, we also calculate the mean squared displacement, skewness and kurtosis in all dimensions, demonstrating that in the general case the non-Gaussian shape of the probability density function changes. KW - multidimensional fractional diffusion equation KW - continuous time random KW - walks KW - crossover anomalous diffusion dynamics KW - non-Gaussian probability KW - density Y1 - 2022 U6 - https://doi.org/10.1088/1751-8121/ac5a90 SN - 1751-8113 SN - 1751-8121 VL - 55 IS - 20 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Vilk, Ohad A1 - Aghion, Erez A1 - Nathan, Ran A1 - Toledo, Sivan A1 - Metzler, Ralf A1 - Assaf, Michael T1 - Classification of anomalous diffusion in animal movement data using power spectral analysis JF - Journal of physics : A, Mathematical and theoretical N2 - The field of movement ecology has seen a rapid increase in high-resolution data in recent years, leading to the development of numerous statistical and numerical methods to analyse relocation trajectories. Data are often collected at the level of the individual and for long periods that may encompass a range of behaviours. Here, we use the power spectral density (PSD) to characterise the random movement patterns of a black-winged kite (Elanus caeruleus) and a white stork (Ciconia ciconia). The tracks are first segmented and clustered into different behaviours (movement modes), and for each mode we measure the PSD and the ageing properties of the process. For the foraging kite we find 1/f noise, previously reported in ecological systems mainly in the context of population dynamics, but not for movement data. We further suggest plausible models for each of the behavioural modes by comparing both the measured PSD exponents and the distribution of the single-trajectory PSD to known theoretical results and simulations. KW - diffusion KW - anomalous diffusion KW - power spectral analysis KW - ecological KW - movement data Y1 - 2022 U6 - https://doi.org/10.1088/1751-8121/ac7e8f SN - 1751-8113 SN - 1751-8121 VL - 55 IS - 33 PB - IOP Publishing CY - Bristol ER - TY - JOUR A1 - Mutothya, Nicholas Mwilu A1 - Xu, Yong A1 - Li, Yongge A1 - Metzler, Ralf T1 - Characterising stochastic motion in heterogeneous media driven by coloured non-Gaussian noise JF - Journal of physics : A, Mathematical and theoretical N2 - We study the stochastic motion of a test particle in a heterogeneous medium in terms of a position dependent diffusion coefficient mimicking measured deterministic diffusivity gradients in biological cells or the inherent heterogeneity of geophysical systems. Compared to previous studies we here investigate the effect of the interplay of anomalous diffusion effected by position dependent diffusion coefficients and coloured non-Gaussian noise. The latter is chosen to be distributed according to Tsallis' q-distribution, representing a popular example for a non-extensive statistic. We obtain the ensemble and time averaged mean squared displacements for this generalised process and establish its non-ergodic properties as well as analyse the non-Gaussian nature of the associated displacement distribution. We consider both non-stratified and stratified environments. KW - diffusion KW - anomalous diffusion KW - non-extensive statistics KW - coloured KW - noise KW - heterogeneous diffusion process Y1 - 2021 U6 - https://doi.org/10.1088/1751-8121/abfba6 SN - 1751-8113 SN - 1751-8121 VL - 54 IS - 29 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Varghese, Alan J. A1 - Chechkin, Aleksei A1 - Metzler, Ralf A1 - Sujith, Raman I. T1 - Capturing multifractality of pressure fluctuations in thermoacoustic systems using fractional-order derivatives JF - Chaos : an interdisciplinary journal of nonlinear science N2 - The stable operation of a turbulent combustor is not completely silent; instead, there is a background of small amplitude aperiodic acoustic fluctuations known as combustion noise. Pressure fluctuations during this state of combustion noise are multifractal due to the presence of multiple temporal scales that contribute to its dynamics. However, existing models are unable to capture the multifractality in the pressure fluctuations. We conjecture an underlying fractional dynamics for the thermoacoustic system and obtain a fractional-order model for pressure fluctuations. The data from this model has remarkable visual similarity to the experimental data and also has a wide multifractal spectrum during the state of combustion noise. Quantitative similarity with the experimental data in terms of the Hurst exponent and the multifractal spectrum is observed during the state of combustion noise. This model is also able to produce pressure fluctuations that are qualitatively similar to the experimental data acquired during intermittency and thermoacoustic instability. Furthermore, we argue that the fractional dynamics vanish as we approach the state of thermoacoustic instability. Y1 - 2021 U6 - https://doi.org/10.1063/5.0032585 SN - 1054-1500 SN - 1089-7682 VL - 31 IS - 3 PB - American Institute of Physics, AIP CY - Melville ER - TY - JOUR A1 - Emanuel, Marc D. A1 - Cherstvy, Andrey G. A1 - Metzler, Ralf A1 - Gompper, Gerhard T1 - Buckling transitions and soft-phase invasion of two-component icosahedral shells JF - Physical review / publ. by The American Physical Society. E, Statistical, nonlinear, and soft matter physics N2 - What is the optimal distribution of two types of crystalline phases on the surface of icosahedral shells, such as of many viral capsids? We here investigate the distribution of a thin layer of soft material on a crystalline convex icosahedral shell. We demonstrate how the shapes of spherical viruses can be understood from the perspective of elasticity theory of thin two-component shells. We develop a theory of shape transformations of an icosahedral shell upon addition of a softer, but still crystalline, material onto its surface. We show how the soft component "invades" the regions with the highest elastic energy and stress imposed by the 12 topological defects on the surface. We explore the phase diagram as a function of the surface fraction of the soft material, the shell size, and the incommensurability of the elastic moduli of the rigid and soft phases. We find that, as expected, progressive filling of the rigid shell by the soft phase starts from the most deformed regions of the icosahedron. With a progressively increasing soft-phase coverage, the spherical segments of domes are filled first (12 vertices of the shell), then the cylindrical segments connecting the domes (30 edges) are invaded, and, ultimately, the 20 flat faces of the icosahedral shell tend to be occupied by the soft material. We present a detailed theoretical investigation of the first two stages of this invasion process and develop a model of morphological changes of the cone structure that permits noncircular cross sections. In conclusion, we discuss the biological relevance of some structures predicted from our calculations, in particular for the shape of viral capsids. Y1 - 2020 U6 - https://doi.org/10.1103/PhysRevE.102.062104 SN - 2470-0045 SN - 2470-0053 SN - 2470-0061 SN - 1538-4519 VL - 102 IS - 6 PB - Woodbury CY - New York ER - TY - JOUR A1 - Metzler, Ralf T1 - Brownian motion and beyond: first-passage, power spectrum, non-Gaussianity, and anomalous diffusion JF - Journal of statistical mechanics: theory and experiment N2 - Brownian motion is a ubiquitous physical phenomenon across the sciences. After its discovery by Brown and intensive study since the first half of the 20th century, many different aspects of Brownian motion and stochastic processes in general have been addressed in Statistical Physics. In particular, there now exists a very large range of applications of stochastic processes in various disciplines. Here we provide a summary of some of the recent developments in the field of stochastic processes, highlighting both the experimental findings and theoretical frameworks. KW - 15 KW - 4 Y1 - 2019 U6 - https://doi.org/10.1088/1742-5468/ab4988 SN - 1742-5468 VL - 2019 IS - 11 PB - IOP Publ. Ltd. CY - Bristol ER - TY - JOUR A1 - Hou, Ru A1 - Cherstvy, Andrey G. A1 - Metzler, Ralf A1 - Akimoto, Takuma T1 - Biased continuous-time random walks for ordinary and equilibrium cases BT - facilitation of diffusion, ergodicity breaking and ageing JF - Physical chemistry, chemical physics : a journal of European Chemical Societies N2 - We examine renewal processes with power-law waiting time distributions (WTDs) and non-zero drift via computing analytically and by computer simulations their ensemble and time averaged spreading characteristics. All possible values of the scaling exponent alpha are considered for the WTD psi(t) similar to 1/t(1+alpha). We treat continuous-time random walks (CTRWs) with 0 < alpha < 1 for which the mean waiting time diverges, and investigate the behaviour of the process for both ordinary and equilibrium CTRWs for 1 < alpha < 2 and alpha > 2. We demonstrate that in the presence of a drift CTRWs with alpha < 1 are ageing and non-ergodic in the sense of the non-equivalence of their ensemble and time averaged displacement characteristics in the limit of lag times much shorter than the trajectory length. In the sense of the equivalence of ensemble and time averages, CTRW processes with 1 < alpha < 2 are ergodic for the equilibrium and non-ergodic for the ordinary situation. Lastly, CTRW renewal processes with alpha > 2-both for the equilibrium and ordinary situation-are always ergodic. For the situations 1 < alpha < 2 and alpha > 2 the variance of the diffusion process, however, depends on the initial ensemble. For biased CTRWs with alpha > 1 we also investigate the behaviour of the ergodicity breaking parameter. In addition, we demonstrate that for biased CTRWs the Einstein relation is valid on the level of the ensemble and time averaged displacements, in the entire range of the WTD exponent alpha. Y1 - 2018 U6 - https://doi.org/10.1039/c8cp01863d SN - 1463-9076 SN - 1463-9084 VL - 20 IS - 32 SP - 20827 EP - 20848 PB - Royal Society of Chemistry CY - Cambridge ER - TY - JOUR A1 - Seckler, Henrik A1 - Metzler, Ralf T1 - Bayesian deep learning for error estimation in the analysis of anomalous diffusion JF - Nature Communnications N2 - Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed systems. We here augment recently proposed machine-learning techniques for decoding anomalous-diffusion data to include an uncertainty estimate in addition to the predicted output. To avoid the Black-Box-Problem a Bayesian-Deep-Learning technique named Stochastic-Weight-Averaging-Gaussian is used to train models for both the classification of the diffusionmodel and the regression of the anomalous diffusion exponent of single-particle-trajectories. Evaluating their performance, we find that these models can achieve a wellcalibrated error estimate while maintaining high prediction accuracies. In the analysis of the output uncertainty predictions we relate these to properties of the underlying diffusion models, thus providing insights into the learning process of the machine and the relevance of the output. KW - random-walk KW - models Y1 - 2022 U6 - https://doi.org/10.1038/s41467-022-34305-6 SN - 2041-1723 VL - 13 PB - Nature Publishing Group UK CY - London ER - TY - JOUR A1 - Seckler, Henrik A1 - Metzler, Ralf T1 - Bayesian deep learning for error estimation in the analysis of anomalous diffusion JF - Nature Communications N2 - Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed systems. We here augment recently proposed machine-learning techniques for decoding anomalous-diffusion data to include an uncertainty estimate in addition to the predicted output. To avoid the Black-Box-Problem a Bayesian-Deep-Learning technique named Stochastic-Weight-Averaging-Gaussian is used to train models for both the classification of the diffusion model and the regression of the anomalous diffusion exponent of single-particle-trajectories. Evaluating their performance, we find that these models can achieve a well-calibrated error estimate while maintaining high prediction accuracies. In the analysis of the output uncertainty predictions we relate these to properties of the underlying diffusion models, thus providing insights into the learning process of the machine and the relevance of the output.
Diffusive motions in complex environments such as living biological cells or soft matter systems can be analyzed with single-particle-tracking approaches, where accuracy of output may vary. The authors involve a machine-learning technique for decoding anomalous-diffusion data and provide an uncertainty estimate together with predicted output. Y1 - 2022 U6 - https://doi.org/10.1038/s41467-022-34305-6 SN - 2041-1723 VL - 13 IS - 1 PB - Nature portfolio CY - Berlin ER -