Institut für Physik und Astronomie
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We investigate the ensemble and time averaged mean squared displacements for particle diffusion in a simple model for disordered media by assuming that the local diffusivity is both fluctuating in time and has a deterministic average growth or decay in time. In this study we compare computer simulations of the stochastic Langevin equation for this random diffusion process with analytical results. We explore the regimes of normal Brownian motion as well as anomalous diffusion in the sub- and superdiffusive regimes. We also consider effects of the inertial term on the particle motion. The investigation of the resulting diffusion is performed for unconfined and confined motion.
We investigate the initiation and early evolution of 12 solar eruptions, including six active-region hot channel and six quiescent filament eruptions, which were well observed by the Solar Dynamics Observatory, as well as by the Solar Terrestrial Relations Observatory for the latter. The sample includes one failed eruption and 11 coronal mass ejections, with velocities ranging from 493 to 2140 km s(-1). A detailed analysis of the eruption kinematics yields the following main results. (1) The early evolution of all events consists of a slow-rise phase followed by a main-acceleration phase, the height-time profiles of which differ markedly and can be best fit, respectively, by a linear and an exponential function. This indicates that different physical processes dominate in these phases, which is at variance with models that involve a single process. (2) The kinematic evolution of the eruptions tends to be synchronized with the flare light curve in both phases. The synchronization is often but not always close. A delayed onset of the impulsive flare phase is found in the majority of the filament eruptions (five out of six). This delay and its trend to be larger for slower eruptions favor ideal MHD instability models. (3) The average decay index at the onset heights of the main acceleration is close to the threshold of the torus instability for both groups of events (although, it is based on a tentative coronal field model for the hot channels), suggesting that this instability initiates and possibly drives the main acceleration.
According to established understanding, deep-water formation in the North Atlantic and Southern Ocean keeps the deep ocean cold, counter-acting the downward mixing of heat from the warmer surface waters in the bulk of the world ocean. Therefore, periods of strong Atlantic meridional overturning circulation (AMOC) are expected to coincide with cooling of the deep ocean and warming of the surface waters. It has recently been proposed that this relation may have reversed due to global warming, and that during the past decades a strong AMOC coincides with warming of the deep ocean and relative cooling of the surface, by transporting increasingly warmer waters downward. Here we present multiple lines of evidence, including a statistical evaluation of the observed global mean temperature, ocean heat content, and different AMOC proxies, that lead to the opposite conclusion: even during the current ongoing global temperature rise a strong AMOC warms the surface. The observed weakening of the AMOC has therefore delayed global surface warming rather than enhancing it.
Social Media Abstract:
The overturning circulation in the Atlantic Ocean has weakened in response to global warming, as predicted by climate models. Since it plays an important role in transporting heat, nutrients and carbon, a slowdown will affect global climate processes and the global mean temperature. Scientists have questioned whether this slowdown has worked to cool or warm global surface temperatures. This study analyses the overturning strength and global mean temperature evolution of the past decades and shows that a slowdown acts to reduce the global mean temperature. This is because a slower overturning means less water sinks into the deep ocean in the subpolar North Atlantic. As the surface waters are cold there, the sinking normally cools the deep ocean and thereby indirectly warms the surface, thus less sinking implies less surface warming and has a cooling effect. For the foreseeable future, this means that the slowing of the overturning will likely continue to slightly reduce the effect of the general warming due to increasing greenhouse gas concentrations.
We present a general analysis of the cooling produced by losses on condensates or quasi-condensates. We study how the occupations of the collective phonon modes evolve in time, assuming that the loss process is slow enough so that each mode adiabatically follows the decrease of the mean density. The theory is valid for any loss process whose rate is proportional to the jth power of the density, but otherwise spatially uniform. We cover both homogeneous gases and systems confined in a smooth potential. For a low-dimensional gas, we can take into account the modified equation of state due to the broadening of the cloud width along the tightly confined directions, which occurs for large interactions. We find that at large times, the temperature decreases proportionally to the energy scale mc2, where m is the mass of the particles and c the sound velocity. We compute the asymptotic ratio of these two quantities for different limiting cases: a homogeneous gas in any dimension and a one-dimensional gas in a harmonic trap.
It is quite generally assumed that the overdamped Langevin equation provides a quantitative description of the dynamics of a classical Brownian particle in the long time limit. We establish and investigate a paradigm anomalous diffusion process governed by an underdamped Langevin equation with an explicit time dependence of the system temperature and thus the diffusion and damping coefficients. We show that for this underdamped scaled Brownian motion (UDSBM) the overdamped limit fails to describe the long time behaviour of the system and may practically even not exist at all for a certain range of the parameter values. Thus persistent inertial effects play a non-negligible role even at significantly long times. From this study a general questions on the applicability of the overdamped limit to describe the long time motion of an anomalously diffusing particle arises, with profound consequences for the relevance of overdamped anomalous diffusion models. We elucidate our results in view of analytical and simulations results for the anomalous diffusion of particles in free cooling granular gases.
During the last decade, intracellular actin waves have attracted much attention due to their essential role in various cellular functions, ranging from motility to cytokinesis. Experimental methods have advanced significantly and can capture the dynamics of actin waves over a large range of spatio-temporal scales. However, the corresponding coarse-grained theory mostly avoids the full complexity of this multi-scale phenomenon. In this perspective, we focus on a minimal continuum model of activator–inhibitor type and highlight the qualitative role of mass conservation, which is typically overlooked. Specifically, our interest is to connect between the mathematical mechanisms of pattern formation in the presence of a large-scale mode, due to mass conservation, and distinct behaviors of actin waves.
Diffusion of finite-size particles in two-dimensional channels with random wall configurations
(2014)
Diffusion of chemicals or tracer molecules through complex systems containing irregularly shaped channels is important in many applications. Most theoretical studies based on the famed Fick–Jacobs equation focus on the idealised case of infinitely small particles and reflecting boundaries. In this study we use numerical simulations to consider the transport of finite-size particles through asymmetrical two-dimensional channels. Additionally, we examine transient binding of the molecules to the channel walls by applying sticky boundary conditions. We consider an ensemble of particles diffusing in independent channels, which are characterised by common structural parameters. We compare our results for the long-time effective diffusion coefficient with a recent theoretical formula obtained by Dagdug and Pineda [J. Chem. Phys., 2012, 137, 024107].
Intracellular photoactivation of caged cGMP induces myosin II and actin responses in motile cells
(2013)
Cyclic GMP (cGMP) is a ubiquitous second messenger in eukaryotic cells. It is assumed to regulate the association of myosin II with the cytoskeleton of motile cells. When cells of the social amoeba Dictyostelium discoideum are exposed to chemoattractants or to increased osmotic stress, intracellular cGMP levels rise, preceding the accumulation of myosin II in the cell cortex. To directly investigate the impact of intracellular cGMP on cytoskeletal dynamics in a living cell, we released cGMP inside the cell by laser-induced photo-cleavage of a caged precursor. With this approach, we could directly show in a live cell experiment that an increase in intracellular cGMP indeed induces myosin II to accumulate in the cortex. Unexpectedly, we observed for the first time that also the amount of filamentous actin in the cell cortex increases upon a rise in the cGMP concentration, independently of cAMP receptor activation and signaling. We discuss our results in the light of recent work on the cGMP signaling pathway and suggest possible links between cGMP signaling and the actin system.
Modeling random crawling, membrane deformation and intracellular polarity of motile amoeboid cells
(2018)
Amoeboid movement is one of the most widespread forms of cell motility that plays a key role in numerous biological contexts. While many aspects of this process are well investigated, the large cell-to-cell variability in the motile characteristics of an otherwise uniform population remains an open question that was largely ignored by previous models. In this article, we present a mathematical model of amoeboid motility that combines noisy bistable kinetics with a dynamic phase field for the cell shape. To capture cell-to-cell variability, we introduce a single parameter for tuning the balance between polarity formation and intracellular noise. We compare numerical simulations of our model to experiments with the social amoeba Dictyostelium discoideum. Despite the simple structure of our model, we found close agreement with the experimental results for the center-of-mass motion as well as for the evolution of the cell shape and the overall intracellular patterns. We thus conjecture that the building blocks of our model capture essential features of amoeboid motility and may serve as a starting point for more detailed descriptions of cell motion in chemical gradients and confined environments.
We present different tests for phase synchronization which improve the procedures currently used in the literature. This is accomplished by using a two-samples test setup and by utilizing insights and methods from directional statistics and bootstrap theory. The tests differ in the generality of the situation in which they can be applied as well as in their complexity, including computational cost. A modification of the resampling technique of the bootstrap is introduced, making it possible to fully utilize data from time series.
A method for the multivariate analysis of statistical phase synchronization phenomena in empirical data is presented. A first statistical approach is complemented by a stochastic dynamic model, to result in a data analysis algorithm which can in a specific sense be shown to be a generic multivariate statistical phase synchronization analysis. The method is applied to EEG data from a psychological experiment, obtaining results which indicate the relevance of this method in the context of cognitive science as well as in other fields.
In order to investigate the temporal characteristics of cognitive processing, we apply multivariate phase synchronization analysis to event-related potentials. The experimental design combines a semantic incongruity in a sentence context with a physical mismatch (color change). In the ERP average, these result in an N400 component and a P300-like positivity, respectively. The synchronization analysis shows an effect of global desynchronization in the theta band around 288ms after stimulus presentation for the semantic incongruity, while the physical mismatch elicits an increase of global synchronization in the alpha band around 204ms. Both of these effects clearly precede those in the ERP average. Moreover, the delay between synchronization effect and ERP component correlates with the complexity of the cognitive processes.
Phase synchronization analysis, including our recently introduced multivariate approach, is applied to event-related EEG data from an experiment on language processing, following a classic psycholinguistic paradigm. For the two types of experimental manipulation distinct effects in overall synchronization are found; for one of them they can also be localized. The synchronization effects occur earlier than those found by the conventional analysis method, indicating that the new approach provides additional information on the underlying neuronal process.
In Allefeld & Kurths [2004], we introduced an approach to multivariate phase synchronization analysis in the form of a Synchronization Cluster Analysis (SCA). A statistical model of a synchronization cluster was described, and an abbreviated instruction on how to apply this model to empirical data was given, while an implementation of the corresponding algorithm was (and is) available from the authors. In this letter, the complete details on how the data analysis algorithm is to be derived from the model are filled in.
Bacterial chemotaxis-a fundamental example of directional navigation in the living world-is key to many biological processes, including the spreading of bacterial infections. Many bacterial species were recently reported to exhibit several distinct swimming modes-the flagella may, for example, push the cell body or wrap around it. How do the different run modes shape the chemotaxis strategy of a multimode swimmer? Here, we investigate chemotactic motion of the soil bacterium Pseudomonas putida as a model organism. By simultaneously tracking the position of the cell body and the configuration of its flagella, we demonstrate that individual run modes show different chemotactic responses in nutrition gradients and, thus, constitute distinct behavioral states. On the basis of an active particle model, we demonstrate that switching between multiple run states that differ in their speed and responsiveness provides the basis for robust and efficient chemotaxis in complex natural habitats.
We report on the detection of very high energy (VHE; E > 100 GeV) gamma-ray emission from the BL Lac objects KUV 00311-1938 and PKS 1440-389 with the High Energy Stereoscopic System (H.E.S.S.). H.E.S.S. observations were accompanied or preceded by multiwavelength observations with Fermi/LAT, XRT and UVOT onboard the Swift satellite, and ATOM. Based on an extrapolation of the Fermi/LAT spectrum towards the VHE gamma-ray regime, we deduce a 95 per cent confidence level upper limit on the unknown redshift of KUV 00311-1938 of z < 0.98 and of PKS 1440-389 of z < 0.53. When combined with previous spectroscopy results, the redshift of KUV 00311-1938 is constrained to 0.51 <= z < 0.98 and of PKS 1440-389 to 0.14 (sic) z < 0.53.