Soft matter physics of the ground beneath our feet.

The soft part of the Earth's surface - the ground beneath our feet - constitutes the basis for life and natural resources, yet a general physical understanding of the ground is still lacking. In this critical time of climate change, cross-pollination of scientific approaches is urgently needed to better understand the behavior of our planet's surface. The major topics in current research in this area cross different disciplines, spanning geosciences, and various aspects of engineering, material sciences, physics, chemistry, and biology. Among these, soft matter physics has emerged as a fundamental nexus connecting and underpinning many research questions. This perspective article is a multi-voice effort to bring together different views and approaches, questions and insights, from researchers that work in this emerging area, the soft matter physics of the ground beneath our feet. In particular, we identify four major challenges concerned with the dynamics in and of the ground: (I) modeling from the grain scale, (II) near-criticality, (III) bridging scales, and (IV) life. For each challenge, we present a selection of topics by individual authors, providing specific context, recent advances, and open questions. Through this, we seek to provide an overview of the opportunities for the broad Soft Matter community to contribute to the fundamental understanding of the physics of the ground, strive towards a common language, and encourage new collaborations across the broad spectrum of scientists interested in the matter of the Earth's surface.

Stability of the Interaction between Two Sand Dunes in an Idealized Laboratory Experiment.

Sand dunes, which arise spontaneously due to the dynamical interplay between a sedimentary interface and a fluid flow, are one of the most famous examples of emergence in a geological system. The large scale organization of a dune field is believed to be controlled by pairwise (either remote or direct) dune-dune interactions. Recent studies have shown that remote long-range feedback is closely related to the turbulent wake structure forming downstream of a dune. Here, we study the stability of an idealized two-dune system arising as a consequence of such remote, wake-induced interactions. The system is realized in a subaqueous quasi-2D laboratory experiment and the results are compared with a qualitative dynamical systems model. Despite its simplicity, the system exhibits rich dynamical behavior. In particular, we show that, depending on the parameter regime, the dune-dune feedback can either stabilize or destabilize the symmetric dune configuration, and we demonstrate the existence of an asymmetric attracting state coupling dunes of different sizes.

Wake Induced Long Range Repulsion of Aqueous Dunes.

Sand dunes rarely occur in isolation, but usually form vast dune fields. The large scale dynamics of these fields is hitherto poorly understood, not least due to the lack of longtime observations. Theoretical models usually abstract dunes in a field as self-propelled autonomous agents, exchanging mass, either remotely or as a consequence of collisions. In contrast to the spirit of these models, here we present experimental evidence that aqueous dunes interact over large distances without the necessity of exchanging mass. Interactions are mediated by turbulent structures forming in the wake of a dune, and lead to dune-dune repulsion, which can prevent collisions. We conjecture that a similar mechanism may be present in wind driven dunes, potentially explaining the observed robust stability of dune fields in different environments.

Flow-Based Network Analysis of the Caenorhabditis elegans Connectome.

We exploit flow propagation on the directed neuronal network of the nematode C. elegans to reveal dynamically relevant features of its connectome. We find flow-based groupings of neurons at different levels of granularity, which we relate to functional and anatomical constituents of its nervous system. A systematic in silico evaluation of the full set of single and double neuron ablations is used to identify deletions that induce the most severe disruptions of the multi-resolution flow structure. Such ablations are linked to functionally relevant neurons, and suggest potential candidates for further in vivo investigation. In addition, we use the directional patterns of incoming and outgoing network flows at all scales to identify flow profiles for the neurons in the connectome, without pre-imposing a priori categories. The four flow roles identified are linked to signal propagation motivated by biological input-response scenarios.

Lane nucleation in complex active flows.

Laning is a paradigmatic example of spontaneous organization in active two-component flows that has been observed in diverse contexts, including pedestrian traffic, driven colloids, complex plasmas, and molecular transport. We introduce a kinetic theory that elucidates the physical origins of laning and quantifies the propensity for lane nucleation in a given physical system. Our theory is valid in the low-density regime, and it makes different predictions about situations in which lanes may form that are not parallel with the direction of flow. We report on experiments with human crowds that verify two notable consequences of this phenomenon: tilting lanes under broken chiral symmetry and lane nucleation along elliptic, parabolic, and hyperbolic curves in the presence of sources or sinks.