Non-equilibrium dynamics of an active colloidal "chucker"

We report Monte Carlo simulations of the dynamics of a "chucker": a colloidal particle which emits smaller solute particles from its surface, isotropically and at a constant rate k_c. We find that the diffusion constant of the chucker increases for small k_c, as recently predicted theoretically. At large k_c the chucker diffuses more slowly due to crowding effects. We compare our simulation results to those of a "point particle" Langevin dynamics scheme in which the solute concentration field is calculated analytically, and in which hydrodynamic effects can be included albeit in an approximate way. By simulating the dragging of a chucker, we obtain an estimate of its apparent mobility coefficient which violates the fluctuation-dissipation theorem. We also characterise the probability density profile for a chucker which sediments onto a surface which either repels or absorbs the solute particles, and find that the steady state distributions are very different in the two cases. Our simulations are inspired by the biological example of exopolysaccharide-producing bacteria, as well as by recent experimental, simulation and theoretical work on phoretic colloidal "swimmers".Comment: re-submission after referee's comment

How Damage Diversification Can Reduce Systemic Risk

We consider the problem of risk diversification in complex networks. Nodes represent e.g. financial actors, whereas weighted links represent e.g. financial obligations (credits/debts). Each node has a risk to fail because of losses resulting from defaulting neighbors, which may lead to large failure cascades. Classical risk diversification strategies usually neglect network effects and therefore suggest that risk can be reduced if possible losses (i.e., exposures) are split among many neighbors (exposure diversification, ED). But from a complex networks perspective diversification implies higher connectivity of the system as a whole which can also lead to increasing failure risk of a node. To cope with this, we propose a different strategy (damage diversification, DD), i.e. the diversification of losses that are imposed on neighboring nodes as opposed to losses incurred by the node itself. Here, we quantify the potential of DD to reduce systemic risk in comparison to ED. For this, we develop a branching process approximation that we generalize to weighted networks with (almost) arbitrary degree and weight distributions. This allows us to identify systemically relevant nodes in a network even if their directed weights differ strongly. On the macro level, we provide an analytical expression for the average cascade size, to quantify systemic risk. Furthermore, on the meso level we calculate failure probabilities of nodes conditional on their system relevance

Ferroelectric properties of charge-ordered alpha-(BEDT-TTF)2I3

A detailed investigation of the out-of-plane electrical properties of charge-ordered alpha-(BEDT-TTF)2I3 provides clear evidence for ferroelectricity. Similar to multiferroic alpha-(BEDT-TTF)2Cu[N(CN)2]Cl, the polar order in this material is ascribed to the occurrence of bond- and site-centered charge order. Dielectric response typical for relaxor ferroelectricity is found deep in the charge-ordered state. We suggest an explanation in terms of the existence of polar and nonpolar stacks of the organic molecules in this material, preventing long-range ferroelectricity. The results are discussed in relation to the formation or absence of electronic polar order in related charge-transfer salts.Comment: 8 pages, 4 figures. Revised version as accepted for publication in Phys. Rev.

Revised metallicity classes for low-mass stars: dwarfs (dM), subdwarfs (sdM), extreme subdwarfs (esdM), and ultra subdwarfs (usdM)

The current classification system of M stars on the main sequence distinguishes three metallicity classes (dwarfs - dM, subdwarfs - sdM, and extreme subdwarfs - esdM). The spectroscopic definition of these classes is based on the relative strength of prominent CaH and TiO molecular absorption bands near 7000A, as quantified by three spectroscopic indices (CaH2, CaH3, and TiO5). We re-examine this classification system in light of our ongoing spectroscopic survey of stars with proper motion \mu > 0.45 "/yr, which has increased the census of spectroscopically identified metal-poor M stars to over 400 objects. Kinematic separation of disk dwarfs and halo subdwarfs suggest deficiencies in the current classification system. Observations of common proper motion doubles indicates that the current dM/sdM and sdM/esdM boundaries in the [TiO5,CaH2+CaH3] index plane do not follow iso-metallicity contours, leaving some binaries inappropriately classified as dM+sdM or sdM+esdM. We propose a revision of the classification system based on an empirical calibration of the TiO/CaH ratio for stars of near solar metallicity. We introduce the parameter \zeta_{TiO/CaH} which quantifies the weakening of the TiO bandstrength due to metallicity effect, with values ranging from \zeta_{TiO/CaH}=1 for stars of near-solar metallicity to \zeta_{TiO/CaH}~0 for the most metal-poor (and TiO depleted) subdwarfs. We redefine the metallicity classes based on the value of the parameter \zeta_{TiO/CaH}; and refine the scheme by introducing an additional class of ultra subdwarfs (usdM). We introduce sequences of sdM, esdM, and usdM stars to be used as formal classification standards.Comment: 15 pages, accepted for publication in the Astrophysical Journa

A complementary view on the growth of directory trees

Trees are a special sub-class of networks with unique properties, such as the level distribution which has often been overlooked. We analyse a general tree growth model proposed by Klemm etal.[Phys. Rev. Lett. 95, 128701 (2005)] to explain the growth of user-generated directory structures in computers. The model has a single parameter q which interpolates between preferential attachment and random growth. Our analysis results in three contributions: first, we propose a more efficient estimation method for q based on the degree distribution, which is one specific representation of the model. Next, we introduce the concept of a level distribution and analytically solve the model for this representation. This allows for an alternative and independent measure of q. We argue that, to capture real growth processes, the q estimations from the degree and the level distributions should coincide. Thus, we finally apply both representations to validate the model with synthetically generated tree structures, as well as with collected data of user directories. In the case of real directory structures, we show that q measured from the level distribution are incompatible with q measured from the degree distribution. In contrast to this, we find perfect agreement in the case of simulated data. Thus, we conclude that the model is an incomplete description of the growth of real directory structures as it fails to reproduce the level distribution. This insight can be generalised to point out the importance of the level distribution for modeling tree growt

A k-shell decomposition method for weighted networks

We present a generalized method for calculating the k-shell structure of weighted networks. The method takes into account both the weight and the degree of a network, in such a way that in the absence of weights we resume the shell structure obtained by the classic k-shell decomposition. In the presence of weights, we show that the method is able to partition the network in a more refined way, without the need of any arbitrary threshold on the weight values. Furthermore, by simulating spreading processes using the susceptible-infectious-recovered model in four different weighted real-world networks, we show that the weighted k-shell decomposition method ranks the nodes more accurately, by placing nodes with higher spreading potential into shells closer to the core. In addition, we demonstrate our new method on a real economic network and show that the core calculated using the weighted k-shell method is more meaningful from an economic perspective when compared with the unweighted one.Comment: 17 pages, 6 figure

An Agent-Based Model of Collective Emotions in Online Communities

We develop a agent-based framework to model the emergence of collective emotions, which is applied to online communities. Agents individual emotions are described by their valence and arousal. Using the concept of Brownian agents, these variables change according to a stochastic dynamics, which also considers the feedback from online communication. Agents generate emotional information, which is stored and distributed in a field modeling the online medium. This field affects the emotional states of agents in a non-linear manner. We derive conditions for the emergence of collective emotions, observable in a bimodal valence distribution. Dependent on a saturated or a superlinear feedback between the information field and the agent's arousal, we further identify scenarios where collective emotions only appear once or in a repeated manner. The analytical results are illustrated by agent-based computer simulations. Our framework provides testable hypotheses about the emergence of collective emotions, which can be verified by data from online communities.Comment: European Physical Journal B (in press), version 2 with extended introduction, clarification