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Realistic modeling of ecological population dynamics requires spatially explicit descriptions that can take into account spatial heterogeneity as well as long-distance dispersal. Here, we present Monte Carlo simulations and numerical renormalization group results for the paradigmatic model, the contact process, in the combined presence of these factors in both one and two-dimensional systems. Our results confirm our analytic arguments stating that the density vanishes smoothly at the extinction threshold, in a way characteristic of infinite-order transitions. This extremely smooth vanishing of the global density entails an enhanced exposure of the population to extinction events. At the same time, a reverse order parameter, the local persistence displays a discontinuity characteristic of mixed-order transitions, as it approaches a non-universal critical value algebraically with an exponent\beta_p'<1 ${\beta }_p\prime <1$. 

In unconfined environments, bacterial motility patterns are an explicit expression of the internal states of the cell. Bacteria operating a run-and-tumble behavioral program swim forward when in a ‘run’ state, and are stalled in place when in a reorienting ‘tumble’ state. However, in natural environments, motility dynamics often represent a convolution of bacterial behavior and environmental constraints. Recent investigations showed thatEscherichia coliswimming through highly confined porous media exhibit extended periods of ‘trapping’ punctuated by forward ‘hops’, a seemingly drastic restructuring of run-and-tumble behavior. We introduce a microfluidic device to systematically explore bacterial movement in a range of spatially structured environments, bridging the extremes of unconfined and highly confined conditions. We observe that trajectories reflecting unconstrained expression of run-and-tumble behavior and those reflecting ‘hop-and-trap’ dynamics coexist in all structured environments considered, with ensemble dynamics transitioning smoothly between these two extremes. We present a unifying ‘swim-and-stall’ framework to characterize this continuum of observed motility patterns and demonstrate that bacteria employing a consistent set of behavioral rules can present motility patterns that smoothly transition between the two extremes. Our results indicate that the control program underlying run-and-tumble motility is robust to changes in the environment, allowing flagellated bacteria to navigate and adapt to a diverse range of complex, dynamic habitats using the same set of behavioral rules. 

ABSTRACT Multicellularity was accompanied by the emergence of new classes of cell surface and secreted proteins. The nematodeC. elegansis a favorable model to study cell surface interactomes, given its well-defined and stereotyped cell types and intercellular contacts. Here we report ourC. elegansextracellular interactome dataset, the largest yet for an invertebrate. Most of these interactions were unknown, despite recent datasets for flies and humans, as our collection contains a larger selection of protein families. We uncover new interactions for all four major axon guidance pathways, including ectodomain interactions between three of the pathways. We demonstrate that a protein family known to maintain axon locations are secreted receptors for insulins. We reveal novel interactions of cystine-knot proteins with putative signaling receptors, which may extend the study of neurotrophins and growth-factor-mediated functions to nematodes. Finally, our dataset provides insights into human disease mechanisms and how extracellular interactions may help establish connectomes. 

In cluster tomography, we propose measuring the number of clusters 𝑁 intersected by a line segment of length ℓ across a finite sample. As expected, the leading order of 𝑁⁡(ℓ) scales as 𝑎⁢ℓ, where 𝑎 depends on microscopic details of the system. However, at criticality, there is often an additional nonlinearity of the form 𝑏⁢ln⁡(ℓ), originating from the endpoints of the line segment. By performing large scale Monte Carlo simulations of both two- and three-dimensional percolation, we find that 𝑏 is universal and depends only on the angles encountered at the endpoints of the line segment intersecting the sample. Our findings are further supported by analytic arguments in two dimensions, building on results in conformal field theory. Being broadly applicable, cluster tomography can be an efficient tool for detecting phase transitions and characterizing the corresponding universality class in classical or quantum systems with a relevant cluster structure. 

Abstract In the emerging quantum internet, complex network topology could lead to efficient quantum communication and robustness against failures. However, there are concerns about complexity in quantum communication networks, such as potentially limited end-to-end transmission capacity. These challenges call for model systems in which the impact of complex topology on quantum communication protocols can be explored. Here, we present a theoretical model for complex quantum communication networks on a lattice of spins, wherein entangled spin clusters in interacting quantum spin systems serve as communication links between appropriately selected regions of spins. Specifically, we show that ground state Greenberger-Horne-Zeilinger clusters of the two-dimensional random transverse-field Ising model can be used as communication links between regions of spins. Further, the resulting quantum networks can have complexity comparable to that of the classical internet. Our work provides a generative model for further studies towards determining the network characteristics of the emerging quantum internet.