arXiv subjects

Robert Großmann

Publications and source records attributed to Robert Großmann.

18 recordsLinked to original sources

arXiv2026

A Likelihood Approach for Inference of Population Heterogeneity in Particle Ensembles with Second-Order Langevin Dynamics

The inherent complexity of biological agents often leads to motility behavior that appears to have random components. Robust stochastic inference methods are therefore required to understand and predict the motion patterns from time-discrete trajectory data provided by experiments. In many cases, second-order Langevin models are needed to adequately capture the motility. Additionally, population heterogeneity needs to be taken into account when analyzing data from several individual organisms. In this work, we describe a maximum likelihood approach to infer dynamical, stochastic models and, simultaneously, estimate the heterogeneity in a population of motile active particles from discretely sampled, stochastic trajectories. To this end, we propose a method to approximate the likelihood for non-linear second-order Langevin models. We show that this maximum likelihood ansatz outperforms alternative approaches, especially for short trajectories. Additionally, we demonstrate how a measure of uncertainty for the heterogeneity estimate can be derived. We thereby pave the way for the systematic, data-driven inference of dynamical models for actively driven entities based on trajectory data, deciphering temporal fluctuations and inter-particle variability.

cond-mat.soft↗

arXiv2026

Likelihood-Based Heterogeneity Inference Reveals Non-Stationary Effects in Biohybrid Cell-Cargo Transport

Variability of motility behavior in populations of microbiological agents is a ubiquitous phenomenon even in the case of genetically identical cells. Accordingly, passive objects introduced into such biological systems and driven by them will also exhibit heterogeneous motion patterns. Here, we study a biohybrid system of passive beads driven by active ameboid cells and use a likelihood approach to estimate the heterogeneity of the bead dynamics from their discretely sampled trajectories. We showcase how this approach can deal with information-scarce situations and provides natural uncertainty bounds for heterogeneity estimates. Using these advantages we particularly uncover that the heterogeneity in the system is time-dependent.

cond-mat.soft↗

arXiv2025

The random walk of intermittently self-propelled particles

Motivated by various recent experimental findings, we propose a dynamical model of intermittently self-propelled particles: active particles that recurrently switch between two modes of motion, namely an active run-state and a turn state, in which self-propulsion is absent. The durations of these motility modes are derived from arbitrary waiting-time distributions. We derive the expressions for exact forms of transport characteristics like mean-square displacements and diffusion coefficients to describe such processes. Furthermore, the conditions for the emergence of sub- and superdiffusion in the long-time limit are presented. We give examples of some important processes that occur as limiting cases of our system, including run-and-tumble motion of bacteria, Lévy walks, hop-and-trap dynamics, intermittent diffusion and continuous time random walks.

cond-mat.soft↗

arXiv2025

Deciphering the dual chemotaxis strategy of bacteria in porous media

Chemotaxis of bacterial swimmers that move in a run-and-turn pattern is well studied in uniform bulk fluid. It is primarily based on modulating the run time in dependence on the swimming direction with respect to the source of chemoattractant (run time bias). Here, we provide evidence that the lophotrichously flagellated soil bacterium Pseudomonas putida may also perform chemotaxis in porous media where the free path length is severely restricted. Besides the classical run time bias, we identify a second chemotactic strategy: the change in swimming direction upon a turn event is adjusted, so that the direction of the next run phase is biased towards the source of chemoattractant (turn angle bias). Agent based simulations, based on the experimentally observed statistical properties of the swimming pattern, indicate that turn angle bias is the predominant chemotaxis strategy of bacteria in porous environments.

cond-mat.soft↗

arXiv2024

Intermittent Run Motility of Bacteria in Gels Exhibits Power-Law Distributed Dwell Times

While bacterial swimming has been well characterized in uniform liquid environments, only little is known about how bacteria propagate through complex environments, such as gel-like matrices or porous media that are typically encountered in tissue or soil. Here, we study swimming motility of the soil bacterium Pseudomonas putida (P. putida) in polysaccharide matrices formed by different concentrations of agar. P. putida cells display intermittent run-motility in the gel, where run times are exponentially distributed and intermittently occurring dwell times follow a waiting-time distribution with a power-law decay. An analysis of the turn angle distribution suggests that both, flagella mediated turning as well as mechanical trapping in the agar matrix play a role in the overall swimming pattern. Based on the experimentally observed motility pattern and measured waiting-time distributions, we propose a minimal active particle model which correctly describes the observed time dependence of the mean square displacement of the bacterial swimmers.

cond-mat.soft↗

arXiv2023

Non-Gaussian displacements in active transport on a carpet of motile cells

We study the dynamics of micron-sized particles on a layer of motile cells. This cell carpet acts as an active bath that propels passive tracer particles via direct mechanical contact. The resulting nonequilibrium transport shows a crossover from superdiffusive to normal-diffusive dynamics. The particle displacement distribution is distinctly non-Gaussian even in the limit of long measurement times -- different from typically reported Fickian yet non-Gaussian transport, for which Gaussianity is restored beyond some system-specific correlation time. We obtain the distribution of diffusion coefficients from the experimental data and introduce a model for the displacement distribution that matches the experimentally observed non-Gaussian statistics and argue why similar transport properties are expected for many composite active matter systems.

cond-mat.soft↗

arXiv2023

Cargo size limits and forces of cell-driven microtransport

The integration of motile cells into biohybrid microrobots offers unique properties such as sensitive responses to external stimuli, resilience, and intrinsic energy supply. Here we study biohybrid microtransporters that are driven by amoeboid Dictyostelium discoideum cells and explore how the speed of transport and the resulting viscous drag force scales with increasing radius of the spherical cargo particle. Using a simplified geometrical model of the cell-cargo interaction, we extrapolate our findings towards larger cargo sizes that are not accessible with our experimental setup and predict a maximal cargo size beyond which active cell-driven transport will stall. The active forces exerted by the cells to move a cargo show mechanoresponsive adaptation and increase dramatically when challenged by an external pulling force, a mechanism that may become relevant when navigating cargo through complex heterogeneous environments.

physics.bio-ph↗

arXiv2021

From single to collective motion of social amoebae: a computational study of interacting cells

The coupling of the internal mechanisms of cell polarization to cell shape deformations and subsequent cell crawling poses many interdisciplinary scientific challenges. Several mathematical approaches have been proposed to model the coupling of both processes, where one of the most successful methods relies on a phase field that encodes the morphology of the cell, together with the integration of partial differential equations that account for the polarization mechanism inside the cell domain as defined by the phase field. This approach has been previously employed to model the motion of single cells of the social amoeba Dictyostelium discoideum, a widely used model organism to study actin-driven motility and chemotaxis of eukaryotic cells. Besides single cell motility, Dictyostelium discoideum is also well-known for its collective behavior. Here, we extend the previously introduced model for single cell motility to describe the collective motion of large populations of interacting amoebae by including repulsive interactions between the cells. We performed numerical simulations of this model, first characterizing the motion of single cells in terms of their polarity and velocity vectors. We then systematically studied the collisions between two cells that provided the basic interaction scenarios also observed in larger ensembles of interacting amoebae. Finally, the relevance of the cell density was analyzed, revealing a systematic decrease of the motility with density, associated with the formation of transient cell clusters that emerge in this system. This model is a prototypical active matter system for the investigation of the emergent collective dynamics of deformable, self-driven cells with a highly complex, nonlinear coupling of cell shape deformations, self-propulsion and repulsive cell-cell interactions.

q-bio.CB↗

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↗

arXiv2020

A novel approach to chemotaxis: active particles guided by internal clocks

Motivated by the observation of non-exponential run-time distributions of bacterial swimmers, we propose a minimal phenomenological model for taxis of active particles whose motion is controlled by an internal clock. The ticking of the clock depends on an external concentration field, e.g. a chemical substance. We demonstrate that these particles can detect concentration gradients and respond to them by moving up- or down-gradient depending on the clock design, albeit measurements of these fields are purely local in space and instantaneous in time. Altogether, our results open a new route in the study of directional navigation, by showing that the use of a clock to control motility actions represents a generic and versatile toolbox to engineer behavioral responses to external cues, such as light, chemical, or temperature gradients.

physics.bio-ph↗

arXiv2019

Self-Propelled Rods: Insights and Perspectives for Active Matter

A wide range of experimental systems including gliding, swarming and swimming bacteria, in-vitro motility assays as well as shaken granular media are commonly described as self-propelled rods. Large ensembles of those entities display a large variety of self-organized, collective phenomena, including formation of moving polar clusters, polar and nematic dynamic bands, mobility-induced phase separation, topological defects and mesoscale turbulence, among others. Here, we give a brief survey of experimental observations and review the theoretical description of self-propelled rods. Our focus is on the emergent pattern formation of ensembles of dry self-propelled rods governed by short-ranged, contact mediated interactions and their wet counterparts that are also subject to long-ranged hydrodynamic flows. Altogether, self-propelled rods provide an overarching theme covering many aspects of active matter containing well-explored limiting cases. Their collective behavior not only bridges the well-studied regimes of polar self-propelled particles and active nematics, and includes active phase separation, but also reveals a rich variety of new patterns.

cond-mat.stat-mech↗

arXiv2019

A particle-field representation unifies paradigms in active matter

Active matter research focuses on the emergent behavior among interacting self-propelled particles. Unification of seemingly disconnected paradigms -- active phase-separation of repulsive discs and collective motion of self-propelled rods -- is a major challenge in contemporary active matter. Inspired by the quanto-mechanical wave-particle duality, we develop an approach based on the representation of active particles by smoothed continuum fields. On the basis of the collision kinetics, we demonstrate analytically and numerically how nonequilibrium stresses acting among self-driven, anisotropic objects hinder the formation of phase-separated states as observed for self-propelled discs and facilitate the emergence of orientational order. Besides particle shape, the rigidity of self-propelled objects controlling the symmetry of emergent ordered states is as a crucial parameter: impenetrable, anisotropic rods are found to form polar, moving clusters, whereas large-scale nematic structures emerge for soft rods, notably separated by a bistable coexistence regime. These results indicate that the symmetry of the ordered state is not dictated by the symmetry of the interaction potential but is rather a dynamical, emergent property of active systems. This unifying theoretical framework can represent a variety of active systems: living cell tissues, bacterial colonies, cytoskeletal extracts as well as shaken granular media.

cond-mat.stat-mech↗

arXiv2018

Markovian robots: minimal navigation strategies for active particles

We explore minimal navigation strategies for active particles in complex, dynamical, external fields, introducing a class of autonomous, self-propelled particles which we call Markovian robots (MR). These machines are equipped with a navigation control system (NCS) that triggers random changes in the direction of self-propulsion of the robots. The internal state of the NCS is described by a Boolean variable that adopts two values. The temporal dynamics of this Boolean variable is dictated by a closed Markov chain -- ensuring the absence of fixed points in the dynamics -- with transition rates that may depend exclusively on the instantaneous, local value of the external field. Importantly, the NCS does not store past measurements of this value in continuous, internal variables. We show that, despite the strong constraints, it is possible to conceive closed Markov chain motifs that lead to nontrivial motility behaviors of the MR in one, two and three dimensions. By analytically reducing the complexity of the NCS dynamics, we obtain an effective description of the long-time motility behavior of the MR that allows us to identify the minimum requirements in the design of NCS motifs and transition rates to perform complex navigation tasks such as adaptive gradient following, detection of minima or maxima, or selection of a desired value in a dynamical, external field. We put these ideas in practice by assembling a robot that operates by the proposed minimalistic NCS to evaluate the robustness of MR, providing a proof-of-concept that is possible to navigate through complex information landscapes with such a simple NCS whose internal state can be stored in one bit. These ideas may prove useful for the engineering of miniaturized robots.

cond-mat.stat-mech↗

arXiv2016

Mesoscale pattern formation of self-propelled rods with velocity reversal

We study self-propelled particles with velocity reversal interacting by uniaxial (nematic) alignment within a coarse-grained hydrodynamic theory. Combining analytical and numerical continuation techniques, we show that the physics of this active system is essentially controlled by the reversal frequency. In particular, we find that elongated, high-density, ordered patterns, called bands, emerge via subcritical bifurcations from spatially homogeneous states. Our analysis reveals further that the interaction of bands is weakly attractive and, consequently, bands fuse upon collision in analogy with nonequilibrium nucleation processes. Moreover, we demonstrate that a renormalized positive line tension can be assigned to stable bands below a critical reversal rate, beyond which they are transversally unstable. In addition, we discuss the kinetic roughening of bands as well as their nonlinear dynamics close to the threshold of transversal instability. Altogether, the reduction of the multi-particle system onto the dynamics of bands provides a framework to understand the impact of the reversal frequency on the emerging nonequilibrium patterns in self-propelled particle systems. In this regard, our results constitute a proof-of-principle in favor of the hypothesis in microbiology that reversal of gliding rod-shaped bacteria regulates the occurrence of various self-organized pattens observed during life-cycle phases.

cond-mat.stat-mech↗

arXiv2016

Diffusion properties of active particles with directional reversal

The diffusion properties of self-propelled particles which move at constant speed and, in addition, reverse their direction of motion repeatedly are investigated. The internal dynamics of particles triggering these reversal processes is modeled by a stochastic clock. The velocity correlation function as well as the mean squared displacement is investigated and, furthermore, a general expression for the diffusion coefficient for self-propelled particles with directional reversal is derived. Our analysis reveals the existence of an optimal, finite rotational noise amplitude which maximizes the diffusion coefficient. We comment on the relevance of these results with regard to microbiological systems and suggest further experiments in this context.

physics.bio-ph↗

arXiv2016

A geometric approach to self-propelled motion in isotropic and anisotropic environments

We propose a geometric perspective to describe the motion of self-propelled particles moving at constant speed in d dimensions. We exploit the fact that the vector that conveys the direction of motion of the particle performs a random walk on a $(d-1)$-dimensional manifold. We show that the particle performs isotropic diffusion in d-dimensions if the manifold corresponds to a hypersphere. In contrast, we find that the self-propelled particle exhibits anisotropic diffusion if this manifold corresponds to a deformed hypersphere (e.g. an ellipsoid). This simple approach provides an unified framework to deal with isotropic as well as anisotropic diffusion of particles moving at constant speed in any dimension.

physics.bio-ph↗

arXiv2016

Superdiffusion, large-scale synchronization and topological defects

We study an ensemble of random walkers carrying internal noisy phase oscillators which are synchronized among the walkers by local interactions. Due to individual mobility, the interaction partners of every walker change randomly, hereby introducing an additional, independent source of fluctuations, thus constituting the intrinsic nonequilibrium nature of the temporal dynamics. We employ this paradigmatic model system to discuss how the emergence of order is affected by motion of individual entities. In particular, we consider both, normal diffusive motion and superdiffusion. A non-Hamiltonian field theory including multiplicative noise terms is derived which describes the nonequilibrium dynamics at the macroscale. This theory reveals a defect-mediated transition from incoherence to quasi long-range order for normal diffusion of oscillators in two dimensions, implying a power-law dependence of all synchronization properties on system size. In contrast, superdiffusive transport suppresses the emergence of topological defects, thereby inducing a continuous synchronization transition to long-range order in two dimensions. These results are consistent with particle-based simulations.

cond-mat.stat-mech↗

arXiv2015

Pattern formation in active particle systems due to competing alignment interactions

Recently, we proposed a self-propelled particle model with competing alignment interactions: nearby particles tend to align their velocities whereas they anti-align their direction of motion with particles which are further away [R. Grossmann et al., Phys. Rev. Lett. 113, 258104 (2014)]. Here, we extend our previous numerical analysis of the high density regime considering low particle densities too. We report on the emergence of various macroscopic patterns such as vortex arrays, mesoscale turbulence as well as the formation of polar clusters, polar bands and nematically ordered states. Furthermore, we study analytically the instabilities leading to pattern formation in mean-field approximation. We argue that these instabilities are well described by a reduced set of hydrodynamic equations in the limit of high density.

cond-mat.soft↗