Condensed Matter Theory

Abstract:

Most living things on Earth - from bacteria to humans - must migrate in some way to find favourable conditions. Therefore, they nearly all use chemotaxis, in which their movement is steered by a gradient of chemicals. Chemotaxis is fundamental to many processes that control our well-being, including inflammation, neuronal patterning, wound healing, tumour spread in cancer, even embryogenesis. Understanding it is a key goal for biologists. Despite the fact that many basic principles appear to have been conserved throughout evolution, most research has focused on understanding the molecular mechanisms that control signal processing and locomotion. Cell signaling - cells responding to time-varying external signals - underlies almost all biological processes at the cellular scale. Chemotaxis of single cells provides particularly amenable model systems for quantitative cell signaling studies, even in the presence of noise and fluctuations, because the output, the cell's motility response, is directly observable. However, the different scientific disciplines involved in chemotaxis research rarely overlap, so biologists, physicists and mathematicians interact far too infrequently, methodologies and models differ and commonalities are often overlooked, such as the possible influence of physical or environmental conditions, which has been largely neglected.

Abstract:

We develop a continuum theory to describe the collective dynamics of deformable epithelial cells, distinguishing the force-generating active filaments in the cells from their shape. The theory demonstrates how active flows driven by active filaments can create nematic domains and topological defects in the cell shape field. We highlight the role of the filament flow-aligning parameter, λQ, a rheological quantity that determines the response of the filaments to velocity gradients in the active flows, and plays a significant, to date unappreciated, role in determining the pattern of extensional and compressional active flows. In a contractile cell layer, local flows are expected to align elongated cells perpendicular to the active filaments. However, with increasing λQ, long-range correlations in the active turbulent flow field lead to extended regions where this alignment is parallel, consistent with recent experiments on confluent Madin-Darby canine kidney (MDCK) cell layers. Further, we distinguish defects in the filament director field, which contribute to the active driving, and those in the shape director field, measured in experiments, which are advected by the active flows. By considering the shape-filament orientation, we explain the unexpected motion of +1/2 defects towards their head in contractile cell layers, consistent with recent experiments on epithelial layers examining stress around shape defects.

Abstract:

We coarse-grain a model of closely packed ellipses that can vary their aspect ratio to derive continuum equations for materials comprising confluent deformable particles such as epithelial cell layers. We show that contractile nearest-neighbor interactions between ellipses can lead to their elongation and nematic ordering. Adding flows resulting from active hydrodynamic stresses produced by the particles also affects the aspect ratio and can result in active turbulence. Our results, which agree well with multiphase field simulations of deformable isotropic cells, provide a bridge between models that explicitly resolve cells and continuum theories of active matter.

Abstract:

SciPost Journals Publication Detail SciPost Phys. 19, 086 (2025) Long-time divergences in the nonlinear response of gapped one-dimensional many-particle systems

Abstract:

We investigate the lifted TASEP and its generalization, the GL-TASEP. We analyze the spectral properties of the transition matrix of the lifted TASEP using its Bethe ansatz solution, and use them to determine the scaling of the relaxation time (the inverse spectral gap) with particle number. The observed scaling with particle number was previously found to disagree with Monte Carlo simulations of the equilibrium autocorrelation times of the structure factor and of other large-scale density correlators for a particular value of the pullback \alpha_{\rm crit} . We explain this discrepancy. We then construct the continuum limit of the lifted TASEP, which remains integrable, and connect it to the event-chain Monte Carlo algorithm. The critical pullback \alpha_{\rm crit} then equals the system pressure. We generalize the lifted TASEP to a large class of nearest-neighbour interactions, which lead to stationary states characterized by non-trivial Boltzmann distributions. By tuning the pullback parameter in the GL-TASEP to a particular value we can again achieve a polynomial speedup in the time required to converge to the steady state. We comment on the possible integrability of the GL-TASEP.