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Seminars

SoSe 2019

LocationTopic, SpeakerInvited by
2019-10-17 16:00
  W15 0-023

2019-10-24 16:00
  W15 0-023

2019-11-07 16:00
  W15 0-023
Synchronisation in yeast cell populations
Marcus Hauser (Otto-von-Guericke-Universität Magdeburg) biophysics

Glycolytic oscillations of intact yeast cells were investigated at both the levels of cell populations and of individual cells. Individual cells showed glycolytic oscillations even at very low cell densities. By contrast, the collective behaviour on the population level depended on the cell density: at high cell densities it is oscillatory, but below a critical density the collective dynamics becomes quiescent. We demonstrate that the transition in the collective dynamics is caused by the desynchronisation of the oscillations of individual cells. This is characteristic for a Kuramoto transition.

The transition between synchronized and an asynchronous behaviour of intact, immobilized yeast cells of is investigated in populations of intermediate cell densities. Here, the individual cells remain oscillatory, whereas on the level of the cell population, both a partially synchronized and an asynchronous state is accessible for experimental studies. In the partially synchronized state, the mean oscillatory frequency is larger than that of the cells in the asynchronous state, suggesting that the cells are entrained by the cells that oscillate more rapidly. This is typical for synchronisation due to phase advancement. Furthermore, the synchronisation of the frequency of the glycolytic oscillations precedes the synchronisation of their phases. However, the cells do not synchronize completely, as the distribution of the oscillatory frequencies only narrows but does not collapse to a unique frequency.

Chimera states, i.e., the coexistence of a synchronized and an asynchronous part of the population, could not be observed.

Ulrike Feudel
2019-11-14 16:00
  W15 0-023

2019-11-21 16:00
  W15 0-023

2019-11-28 16:00
  W15 0-023

2019-12-05 16:00
  W15 0-023

2019-12-12 16:00
  W15 0-023

2019-12-19 16:00
  W15 0-023

2020-01-09 16:00
  W15 0-023

2020-01-16 16:00
  W15 0-023

2020-01-23 16:00
  W15 0-023

2020-01-30 16:00
  W15 0-023

Past Events:

2019-04-25 16:00
  W15 0-023
TBA
Kirsten Thonicke ( Potsdam Institute of Climate Impact Research)
Ulrike Feudel
2019-05-02 16:00
  W15 0-023
"Propagation of wind power induced fluctuations in power grids"
Hauke Haehne (Institut fuer Physik, Universität Oldenburg)

Renewable generators perturb the electric power grid with heavily non-Gaussian and time correlated fluctuations. While changes in generated power on time scales of minutes and hours are compensated by frequency control measures, we report sub-second distribution grid frequency measurements with local non-Gaussian fluctuations which depend on the magnitude of wind power generation in the grid. Motivated by such experimental findings, we simulate the sub-second grid frequency dynamics by perturbing the power grid, as modeled by a network of phase coupled nonlinear oscillators, with synthetically generated wind power feed-in time series. We derive a linear response theory and obtain analytical results for the variance of frequency increment distributions. We find that the variance of short-term fluctuations decays, for large inertia, exponentially with distance to the feed-in node in quantitative agreement with the numerical results both for a linear chain of nodes and for the German transmission grid topology. In sharp contrast, the kurtosis of frequency increments is numerically found to decay only slowly, not exponentially, in both systems, indicating that the non-Gaussian shape of frequency fluctuations persists over long ranges. Moreover, the kurtosis is found to be larger for lower inertia but to decay faster with distance.

Ulrike Feudel
2019-06-06 16:00
  W15 0-023
Multiple stable states and abrupt transitions in spatial ecosystems
Sabiha Majumder (Department of Environmental Systems Science, ETH Zurich)

Ecosystems can exhibit multiple stable states at similar external conditions. Such systems shift from one stable state to another abruptly and discontinuously, when they cross certain threshold parameters. Some examples of such abrupt shifts include coral bleaching, woodland encroachment of grasslands and desertification in semi-arid ecosystems. In this seminar, I will talk about mechanisms that cause abrupt transitions in spatially extended ecosystems and the statistical properties of these systems which can help us predict them. We used a lattice based model of vegetation dynamics with basic processes as birth, death and positive feedback among individuals. In its simple version, this model is known to exhibit a continuous phase transition from an active state to an absorbing state. We show that stochasticity caused by finite sized systems can lead to discontinuous transition in the model. In addition, I will show a method to quantitatively estimate the threshold at which transition may occur. We hypothesize that the point at which spatial variance and correlation in the state variable are maximum, will be the critical point of the system. We then test this method of finding the critical point in real ecosystems by analysing spatial data from regions of Africa and Australia that exhibit alternative vegetation biomes. This works presents an example of how principles of nonequilibrium phase transitions can be applied to a complex biological system, by modelling and testing their predictions with data from ecosystems.

Jan Freund
2019-06-20 16:00
  W15 0-023
"Controlling unstable complex dynamics: from coupled oscillators to fluid mechanics"
Oleh Omel'chenko (Universitaet Potsdam) Nonlinear dynamics

The classical goal of control is to force a given system to show robustly a behavior a priori chosen by the engineer (say, track a desired trajectory). However, feedback control can also be an analysis tool in nonlinear dynamics: whenever the feedback input $u(t)$ is zero, i.e. the control is noninvasive, one can observe natural but dynamically unstable regimes of the uncontrolled nonlinear system such as equilibria or periodic orbits. In this talk, we present two examples illustrating the latter control strategy. First, we describe a proportional control scheme that is able to stabilize the so called edge states, i.e. the attractors within the laminar-turbulent separatrix of a cylindrical pipe flow. Second, we show that the analogous proportional control scheme can also be used to stabilize a high-dimensional chaotic regime (e.g. chimera state) in a large system of coupled oscillators.

Ulrike Feudel
2019-06-27 16:00
  W15 0-023
Movement strategies of a polarly flagellated swimmer with multiple modes of motility
Carsten Beta (Universitaet Potsdam) Biological Physics

Bacteria swim in sequences of straight runs that are interrupted by turning events. They drive their swimming locomotion with the help of rotating helical flagella. Depending on the number of flagella and their arrangement across the cell body, different run-and-turn patterns can be observed. The soil bacterium Pseudomonas putida (P. putida) propels itself with a tuft of helical flagella polarly attached to one end of its elongated cell body (lophotrichous flagellation). Similar to monotrichous bacteria, P. putida swims in straight runs that are interrupted by sharp reversals in the swimming direction. However, in contrast to other bacterial swimmers, P. putida may also change its swimming speed upon a reversal in the swimming direction. Here, we present fluorescence microscopy recordings showing that P. putida not only displays the classical push-pull-push cycle that is well known from monotrichous bacteria but can also enter a third slow swimming phase, where cell propel themselves with their helical bundle wrapped around the cell body. We also studied the statistics of transitions between the different swimming modes to elucidate P. putida’s swimming strategy when navigating in the direction of a chemoattractant gradient. Our results reveal that the wrapped mode plays the most prominent role for directional navigation: the run time in the wrapped mode depends on the swimming direction with respect to the gradient orientation. We interpret and discuss these experimental findings in the light of efficiency and robustness of bacterial chemotaxis strategies based on a coarse-grained theoretical model.

Ulrike Feudel
2019-07-04 16:00
  W15 0-023
Nonlinear dynamics in multiplex networks
Albert Diaz-Guilera (University Barcelona, Spain) complex networks

We will show some of the recent result in our group concerning dynamics in multiplex networks. On the one hand we consider multiplex networks as set of nodes in different layers. At each layer the set of nodes is the same but the connections among the nodes can be different in the layers. Furthermore the connections among the layers is described by a ”network of layers”. We have studied different processes across the layers (diffusion) and between the layers (reaction). In this case Turing patterns appear as an effect of different average connectivities in different layers. We also show that a multiplex construction where the layers correspond to contexts in which agents make different sets of connections can make a model of opinion formation to show stationary states of coexistence that are not observed in simple layers. Finally, as a particular case of multiplex network, one can also analyze networks that change in time, since in this case each layer of the multiplex corresponds to a snapshot of the interaction pattern. For this situation, we have shown that there are different mechanisms that dominate the diffusion of information in the system depending on the relative effect of mobility and diffusion among the nodes.

Ulrike Feudel
ICBMj3o-Webmalga1pstercx (sibeen6dtt.rie96xinlti2ger2ij@uomafl0l.de0ne3) (Changed: 2018-11-19)