arXiv subjects

Stefan Klumpp

Publications and source records attributed to Stefan Klumpp.

At least 19 recordsLinked to original sources

arXiv2025

Patterns of active dipolar particles in external magnetic fields

Active particles with a (magnetic) dipole moment are of interest for steering self-propelled motion, but also result in novel collective effects due to their dipole-dipole interaction. Here systems of active dipolar particles are studied with Brownian dynamics simulations to systematically characterize the different patterns they form, specifically in the presence of an external (magnetic) field. The combination of three types of order - clustering, orientational alignment and chain formation - is used to classify the patterns observed in these systems. In the presence of an external field, oriented chains and bands are found to be dominant. These structures show some similarities with columnar cluster seen in (passive) ferrofluids and display columnar spacing and number of lanes per cluster that both decrease with increasing field strength.

cond-mat.soft↗

arXiv2025

Stability of bond clusters with a characteristic length scale for load distribution

In biological materials, strong binding despite an applied load force is often based on clusters of dynamic bonds that share the load. Different macroscopic behaviors have been described depending on whether the load is shared locally or globally in the force-depended unbinding rate. Here we introduce and study a model in which the load is distributed over a characteristic length scale, introduced by an exponential decay. The model contains the local and global scenario as limiting cases and smoothly interpolates between them. We derive approximations in which some analytical results can be obtained. In particular, we derive rupture conditions and validate these with stochastic simulations. The model shows two main pathways for failure of the bond cluster, due to rupture of all bonds above a critical force and due to the formation of a critical crack, a large gap between closed bonds that spreads in both directions.

physics.bio-ph↗

arXiv2025

Stochastic bubble dynamics in phase-separated scalar active matter

In ABP systems, phase separation is accompanied by the emergence of vapor bubbles within liquid domains. Using large-scale particle-based simulations, we study the stochastic dynamics of these bubbles and find that most nucleate, grow, and dissolve within liquid domains. We show that their area dynamics can be described by a Langevin equation with a constant negative drift and noise proportional to the perimeter, fully characterizing bubble area and lifetime statistics. Additionally, we develop a lattice gas model that captures the morphological properties, including the decrease in bubble asphericity with increasing area. These findings provide new insights into phase separation in active matter and highlight limitations in current continuum theories.

cond-mat.soft↗

arXiv2025

Enhanced condensate fluidity in modified patchy particle models

Biomolecular condensates are formed via liquid-liquid phase separation of proteins, often together with nucleic acids, typically driven by interactions between low-affinity binding sites. The computational study of such condensates that accounts both for the droplet-scale fluid behavior and the internal structure of the condensate requires coarse-grained models. Recently, patchy particle models, representing proteins as sphere with a repulsive core and directional attractive patches, have emerged as a powerful tool. However, these simulations are typically limited by slow dynamics and struggle to capture the full range of material properties of fluid-like condensates. Here we study modified patchy particle models to simulate the formation and dynamics of biomolecular condensates. By incorporating flexible patches and weak isotropic attractions between cores, our models preserve key equilibrium characteristics, including the phase behavior and the local structure of the condensate, while significantly accelerating the system dynamics. These modifications enable the simulation of larger, more complex systems previously inaccessible due to prohibitive relaxation times and provide a versatile tool for studying condensate dynamics.

cond-mat.soft↗

arXiv2024

Bayesian inference of wall torques for active Brownian particles

The motility of living things and synthetic self-propelled objects is often described using Active Brownian particles. To capture the interaction of these particles with their often complex environment, this model can be augmented with empirical forces or torques, for example, to describe their alignment with an obstacle or wall after a collision. Here, we assess the quality of these empirical models by comparing their output predictions with trajectories of rod-shaped active particles that scatter sterically at a flat wall. We employ a classical least-squares method to evaluate the instantaneous torque. In addition, we lay out a Bayesian inference procedure to construct the posterior distribution of plausible model parameters. In contrast to the least squares fit, the Bayesian approach does not require orientational data of the active particle and can readily be applied to experimental tracking data.

cond-mat.stat-mech↗

arXiv2023

Quantifying gliding forces of filamentous cyanobacteria by self-buckling

Filamentous cyanobacteria are one of the oldest and today still most abundant lifeforms on earth, with manifold implications in ecology and economics. Their flexible filaments, often several hundred cells long, exhibit gliding motility in contact with solid surfaces. The underlying force generating mechanism is not yet understood. Here, we demonstrate that propulsion forces and friction coefficients are strongly coupled in the gliding motility of filamentous cyanobacteria. We directly measure their bending moduli using micropipette force sensors, and quantify propulsion and friction forces by analyzing their self-buckling behavior, complemented with analytical theory and simulations. The results indicate that slime extrusion unlikely generates the gliding forces, but support adhesion-based hypotheses, similar to the better-studied single-celled myxobacteria. The critical self-buckling lengths align well with the peaks of natural length distributions, indicating the importance of self-buckling for the organization of their collective in natural and artificial settings.

physics.bio-ph↗

arXiv2023

The motility-matrix production switch in Bacillus subtilis -- a modeling perspective

Phenotype switching can be triggered by external stimuli and by intrinsic stochasticity. Here, we focus on the motility-matrix production switch in Bacillus subtilis. We use modeling to describe the SinR-SlrR bistable switch its regulation by SinI, and to distinguish different sources of stochasticity. Our simulations indicate that intrinsic fluctuations in the synthesis of SinI are insufficient to drive spontaneous switching and suggest that switching is triggered by upstream noise from the Spo0A phosphorelay.

physics.bio-ph↗

arXiv2023

Long-range Velocity Correlations from Active Dopants

One of the most remarkable observations in dense active matter systems is the appearance of long-range velocity correlations without any explicit aligning interaction (of e.g.\ Vicsek type). Here we show that this kind of long range velocity correlation can also be generated in a dense athermal passive system by the inclusion of a very small fraction of active Brownian particles. We develop a continuum theory to explain the emergence of velocity correlations generated via such active dopants. We validate the predictions for the effects of magnitude and persistence time of the active force and the area fractions of active or passive particles using extensive Brownian dynamics simulation of a canonical active-passive mixture. Our work decouples the roles that density and activity play in generating long range velocity correlations in such exotic non-equilibrium steady states.

cond-mat.soft↗

arXiv2021

Biohybrid active matter -- the emergent properties of cell-mediated microtransport

As society paves its way towards device miniaturization and precision medicine, micro-scale actuation and guided transport become increasingly prominent research fields with high impact in both technological and clinical contexts. In order to accomplish directed motion of micron-sized objects towards specific target sites, active biohybrid transport systems, such as motile living cells that act as smart biochemically-powered micro-carriers, have been suggested as an alternative to synthetic micro-robots. Inspired by the motility of leukocytes, we propose the amoeboid crawling of eukaryotic cells as a promising mechanism for transport of micron-sized cargoes and present an in-depth study of this novel type of composite active matter. Its transport properties result from the interactions of an active element (cell) and a passive one (cargo) and reveal an optimal cargo size that enhances the locomotion of the load-carrying cells, even exceeding their motility in the absence of cargo. The experimental findings are rationalized in terms of a biohybrid active matter theory that explains the emergent cell-cargo dynamics and enables us to derive the long-time transport properties of amoeboid micro-carries. As amoeboid locomotion is commonly observed for mammalian cells such as leukocytes, our results lay the foundations for the study of transport performance of other medically relevant cell types and for extending our findings to more advanced transport tasks in complex environments, such as tissues.

physics.bio-ph↗

arXiv2021

Effects of direction reversals on patterns of active filaments

Active matter systems provide fascinating examples of pattern formation and collective motility without counterparts in equilibrium systems. Here, we employ Brownian dynamics simulations to study the collective motion and self-organization in systems of self-propelled semiflexible filaments, inspired by the gliding motility of \textit{filamentous Cyanobacteria}. Specifically, we investigate the influence of stochastic direction reversals on the patterns. We explore pattern formation and dynamics by modulating three relevant physical parameters, the bending stiffness, the activity, and the reversal rate. In the absence of reversals, our results show rich dynamical behavior including spiral formation and collective motion of aligned clusters of various sizes, depending on the bending stiffness and self-propulsion force. The presence of reversals diminishes spiral formation and reduces the sizes of clusters or suppresses clustering entirely. This homogenizing effect of direction reversals can be understood as reversals providing an additional mechanism to either unwind spirals or to resolve clusters.

cond-mat.soft↗

arXiv2021

Coarse graining of biochemical systems described by discrete stochastic dynamics

Many biological systems can be described by finite Markov models. A general method for simplifying master equations is presented that is based on merging adjacent states. The approach preserves the steady-state probability distribution and all steady-state fluxes except the one between the merged states. Different levels of coarse graining of the underlying microscopic dynamics can be obtained by iteration, with the result being independent of the order in which states are merged. A criterion for the optimal level of coarse graining or resolution of the process is proposed via a tradeoff between the simplicity of the coarse-grained model and the information loss relative to the original model. As a case study, the method is applied to the cycle kinetics of the molecular motor kinesin.

physics.bio-ph↗

arXiv2020

Enhanced diffusion of a tracer particle in a lattice model of a crowded active system

Living systems at the sub-cellular, cellular, and multi-cellular level are often crowded systems that contain active particles. The active motion of these particles can also propel passive particles, which typically results in enhanced effective diffusion of the passive particles. Here we study the diffusion of a passive tracer particle in such a dense system of active crowders using a minimal lattice model incorporating particles pushing each other. We show that the model exhibits several regimes of motility and quantify the enhanced diffusion as a function of density and activity of the active crowders. Moreover, we demonstrate an interplay of tracer diffusion and clustering of active particles, which suppresses the enhanced diffusion. Simulations of mixtures of passive and active crowders show that a rather small fraction of active particles is sufficient for the observation of enhanced diffusion.

cond-mat.soft↗

arXiv2019

Force-dependent unbinding rate of molecular motors from stationary optical trap data

Molecular motors walk along filaments until they detach stochastically with a force-dependent unbinding rate. Here, we show that this unbinding rate can be obtained from the analysis of experimental data of molecular motors moving in stationary optical traps. Two complementary methods are presented, based on the analysis of the distribution for the unbinding forces and of the motor's force traces. In the first method, analytically derived force distributions for slip bonds, slip-ideal bonds, and catch bonds are used to fit the cumulative distributions of the unbinding forces. The second method is based on the statistical analysis of the observed force traces. We validate both methods with stochastic simulations and apply them to experimental data for kinesin-1.

physics.bio-ph↗

arXiv2017

Twitching Motility of Bacteria with Type IV Pili: Fractal Walks, First passage time and their Consequences on Microcolonies

A human pathogen, \textit{Neisseria gonorrhoeae} (NG), moves on surfaces by attaching and retracting polymeric structures called Type IV pili. The \textit{tug-of-war} between the pili results in a two-dimensional stochastic motion called \textit{twitching motility}. In this paper, with the help of real time NG trajectories, we develop coarse-grained models for their description. The \textit{fractal properties} of these trajectories are determined and their influence on \textit{first passage time} and formation of bacterial microcolonies is studied. Our main observations are as follows: (i) NG performs a fast ballistic walk on small time scales and a slow diffusive walk over long time scales with a long crossover region; (ii) There exists a characteristic persistent length $l_p^*$ which yields the fastest growth of bacterial aggregates or biofilms. Our simulations reveal that $l_{p}^{*} \sim L^{0.6}$, where $L\times L$ is the surface on which the bacteria move; (iii) The morphologies have distinct fractal characteristics as a consequence of the ballistic and diffusive motion of the constituting bacteria.

physics.bio-ph↗

arXiv2017

Buckling of elastic filaments by discrete magnetic moments

We study the buckling of an idealized, semiflexible filament along whose contour magnetic moments are placed. {We give analytic expressions for the critical stiffness of the filament below which it buckles due to the magnetic compression. For this, we consider various scenarios of the attachment of the magnetic particles to the filament. One possible application for this model are the magnetosome chains of magnetotactic bacteria. An estimate of the critical bending stiffness indicates that buckling may occur within the range of biologically relevant parameters and suggests a role for the bending stiffness of the filament to stabilize the filament against buckling, which would compromise the functional relevance of the bending stiffness of the used filament.

cond-mat.soft↗

arXiv2016

Modeling sRNA-regulated Plasmid Maintenance

We study a theoretical model for the toxin-antitoxin (hok/sok) mechanism for plasmid maintenance in bacteria. Toxin-antitoxin systems enforce the maintenance of a plasmid through post-segregational killing of cells that have lost the plasmid. Key to their function is the tight regulation of expression of a protein toxin by an sRNA antitoxin. Here, we focus on the nonlinear nature of the regulatory circuit dynamics of the toxin-antitoxin mechanism. The mechanism relies on a transient increase in protein concentration rather than on the steady state of the genetic circuit. Through a systematic analysis of the parameter dependence of this transient increase, we confirm some known design features of this system and identify new ones: for an efficient toxin-antitoxin mechanism, the synthesis rate of the toxin's mRNA template should be lower that of the sRNA antitoxin, the mRNA template should be more stable than the sRNA antitoxin, and the mRNA-sRNA complex should be more stable than the sRNA antitoxin. Moreover, a short half-life of the protein toxin is also beneficial to the function of the toxin-antitoxin system. In addition, we study a therapeutic scenario in which a competitor mRNA is introduced to sequester the sRNA antitoxin, causing the toxic protein to be expressed.

physics.bio-ph↗

arXiv2013

Mass transport perspective on an accelerated exclusion process: Analysis of augmented current and unit-velocity phases

In an accelerated exclusion process (AEP), each particle can "hop" to its adjacent site if empty as well as "kick" the frontmost particle when joining a cluster of size $\ell \leq \ell_\text{max}$. With various choices of the interaction range, $\ell_\text{max}$, we find that the steady state of AEP can be found in a homogeneous phase with augmented currents (AC) or a segregated phase with holes moving at unit velocity (UV). Here we present a detailed study on the emergence of the novel phases, from two perspectives: the AEP and a mass transport process (MTP). In the latter picture, the system in the UV phase is composed of a condensate in coexistence with a fluid, while the transition from AC to UV can be regarded as condensation. Using Monte Carlo simulations, exact results for special cases, and analytic methods in a mean field approach (within the MTP), we focus on steady state currents and cluster sizes. Excellent agreement between data and theory is found, providing an insightful picture for understanding this model system.

cond-mat.stat-mech↗

arXiv2012

Entrainment and unit velocity: Surprises in an accelerated exclusion process

We introduce a class of distance-dependent interactions in an accelerated exclusion process (AEP) inspired by the observation of transcribing RNA polymerase speeding up when "pushed" by a trailing one. On a ring, the AEP steady state displays a discontinuous transition, from being homogeneous (with augmented currents) to phase-segregated. In the latter state, the holes appear loosely bound and move together, much like a train. Surprisingly, the current-density relation is simply $J=1-ρ$, signifying that the "hole-train" travels with \textit{unit} velocity.

cond-mat.stat-mech↗