| 08/2026 Scaling behavior in non-reciprocal and odd conserved dynamics near criticality Martin Kjøllesdal Johnsrud et al. In recent years, non-reciprocity has been explored as a ubiquitous manifestation of non-equilibrium activity at the microscopic scales for various active matter systems, from mixtures of chemically active enzymes, colloids, and droplets, to engineered light-controlled active colloids and robotic meta-materials. A commonly used minimal model to describe the dynamics of a binary mixture of conserved … |
| 08/2026 Network Information Enhances Unreliable News Domain Detection Raphaela Keßler et al. Content-based detection of unreliable news is increasingly difficult, as low-reliability sources mimic credible journalism and generative AI makes fabricated content harder to flag. We ask whether network structure can improve news reliability classification, taking a domain-level approach that shifts the focus from individual articles to source reliability. From URL-sharing patterns in Telegram c … |
| 07/2026 Topological delocalisation of confined 3D active nematics Louise C. Head et al. Defect lines in 3D active nematic systems are intriguing topological singularities whose out-of-equilibrium dynamics remain elusive in confined settings. Here, we numerically study 3D active nematics confined within closed cylinders to elucidate the roles of geometry and activity. We reveal a competition between passive elasticity, which causes localisation of defects near edges, and activity, whi … |
| 07/2026 Mixing induced by microswimmers as probed by mutual information Yihong Shi et al. We investigate fluid mixing induced by microswimmers using mutual information as a global, information-theoretic measure of mixing efficiency. For a two-dimensional squirmer model in a confined domain, we compute numerically the swimmer-generated flows and solve the advection-diffusion equation for the transport of tracer particles in the fluid. We show that the spatial distribution of swimmers st … |
| 06/2026 Oscillating concentrations suppress condensate coarsening Mathias S. Heltberg et al. Living cells utilize condensates to spatially concentrate molecules in response to dynamic signals. For instance, nuclear condensates respond to oscillations in transcription factor levels in the nucleoplasm, including those involved in repairing multiple DNA breaks. To understand how oscillating signals affect condensates, we analyze a theoretical model using numerical simulations and analytical … |
| 06/2026 No need to stay positive: a practical approach to direct numerical simulations of elastic turbulence Damiano Capocci et al. Successfully performing direct numerical simulations of polymeric flows remains a major challenge in computational fluid mechanics. In addition to the velocity field, such simulations must resolve polymeric degrees of freedom, often expressed via the conformation tensor, $\mathbf{c}$, which captures the local stretch of polymer molecules. A key difficulty here lies in maintaining the physical requ … |
| 06/2026 Flow of deformable droplets: self-pinned glasses and string-like flow Achille Quarante et al. We investigate, through numerical simulations, the rheology of a dry suspension of deformable droplets under pressure-driven flow. The system exhibits two force-driven dynamical transitions. At low forcing, the suspension behaves as a yield-stress material: below a critical force, droplets remain arrested in an amorphous solid-like state. Our simulations suggest that yielding is controlled by drop … |
| 06/2026 Controlled Chemical Signaling between Enzymatic Nanomotors Shuqin Chen et al. The coordinated interactions between organisms enhance collective functionality, a feature that artificial systems such as enzymatic nanomotors seek to replicate. A key objective, yet still a major challenge, is to achieve chemical communication among nanomotors. Progress has been limited by the difficulties in verifying effective signaling processes, including chemical signal propagation and the … |
| 05/2026 Mechanics of Pandemics Seba Contreras et al. COVID-19 and previous pandemics have shown how diseases can disrupt, threaten, and transform daily life. Since pathogens and societies are continuously evolving, every pandemic is different. However, certain fundamental principles of disease transmission appear to hold true across different outbreaks. These “mechanisms'' are grounded in natural laws or the very structure of our biology … |
| 05/2026 Learning Through Noise: Why Subliminal Learning Works and When It Fails Vincent C. Brockers et al. In the context of artificial neural networks, subliminal learning refers to the transfer of task-relevant knowledge or unintended biases from teacher to student models through distillation on task-unrelated input$\unicode{x2013}$output pairs. Prior explanations tie this effect to shared or closely matched teacher$\unicode{x2013}$student initialization. We show that a closely matched initialization … |