Evolution in range expansions with competition at rough boundaries.

When a biological population expands into new territory, genetic drift develops an enormous influence on evolution at the propagating front. In such range expansion processes, fluctuations in allele frequencies occur through stochastic spatial wandering of both genetic lineages and the boundaries between genetically segregated sectors. Laboratory experiments on microbial range expansions have shown that this stochastic wandering, transverse to the front, is superdiffusive due to the front's growing roughness, implying much faster loss of genetic diversity than predicted by simple flat front diffusive models. We study the evolutionary consequences of this superdiffusive wandering using two complementary numerical models of range expansions: the stepping stone model, and a new interpretation of the model of directed paths in random media, in the context of a roughening population front. Through these approaches we compute statistics for the times since common ancestry for pairs of individuals with a given spatial separation at the front, and we explore how environmental heterogeneities can locally suppress these superdiffusive fluctuations

On thermodynamics of N=6 superconformal Chern-Simons theories at strong coupling

Recently it has been conjectured that N=6, U(N)_{k} \times U(N)_{-k} Chern-Simons theory is dual to M-theory on AdS_4\times S^7/Z_{k}. By studying one-loop correction to the M-theory effective action, we calculate the correction to the entropy of thermal field theory at strong coupling. For large k level, we have also found the alpha' correction to the entropy from the string correction of the type IIA effective action. The structure of these two corrections at strong t'Hooft coupling are different.Comment: 17 pages; v4: Section 4.1 modifie

An Effective Membrane Model of the Immunological Synapse

The immunological synapse is a patterned collection of different types of receptors and ligands that forms in the intercellular junction between T Cells and antigen presenting cells (APCs) during recognition. The synapse is implicated in information transfer between cells, and is characterized by different spatial patterns of receptors at different stages in the life cycle of T cells. We obtain a minimalist model that captures this experimentally observed phenomenology. A functional RG analysis provides further insights.Comment: 6 pages, 3 figures, submitted for publicatio

Apex Exponents for Polymer--Probe Interactions

We consider self-avoiding polymers attached to the tip of an impenetrable probe. The scaling exponents $\gamma_1$ and $\gamma_2$, characterizing the number of configurations for the attachment of the polymer by one end, or at its midpoint, vary continuously with the tip's angle. These apex exponents are calculated analytically by $\epsilon$-expansion, and numerically by simulations in three dimensions. We find that when the polymer can move through the attachment point, it typically slides to one end; the apex exponents quantify the entropic barrier to threading the eye of the probe

Pinning of Diffusional Patterns by Non-Uniform Curvature

Diffusion-driven patterns appear on curved surfaces in many settings, initiated by unstable modes of an underlying Laplacian operator. On a flat surface or perfect sphere, the patterns are degenerate, reflecting translational/rotational symmetry. Deformations, e.g. by a bulge or indentation, break symmetry and can pin a pattern. We adapt methods of conformal mapping and perturbation theory to examine how curvature inhomogeneities select and pin patterns, and confirm the results numerically. The theory provides an analogy to quantum mechanics in a geometry-dependent potential and yields intuitive implications for cell membranes, tissues, thin films, and noise-induced quasipatterns.Comment: substantial re-write of arXiv:1710.0010

Performance and design of consensus on matrix-weighted and time scaled graphs

In this paper, we consider the $\mathcal{H}_2$-norm of networked systems with multi-time scale consensus dynamics and vector-valued agent states. This allows us to explore how measurement and process noise affect consensus on matrix-weighted graphs by examining edge-state consensus. In particular, we highlight an interesting case where the influences of the weighting and scaling on the $\mathcal{H}_2$ norm can be separated in the design problem. We then consider optimization algorithms for updating the time scale parameters and matrix weights in order to minimize network response to injected noise. Finally, we present an application to formation control for multi-vehicle systems.Comment: 10 pages, 5 figures, accepted to the IEEE Transactions on Control of Network Systems. arXiv admin note: text overlap with arXiv:1909.0786