| 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 … |
| 05/2026 TeraGram: A Structured Longitudinal Dataset of the Telegram Messenger Anastasia Golovin et al. Here we present a massive longitudinal dataset of public Telegram content, comprising over 5.9 billion messages dating from 2015 to 2025, collected from 712 thousand channels and groups, enriched with metadata on forwards, reactions, and polls. The dataset spans multiple languages including Russian and Farsi, representing countries where Telegram shows mainstream adoption, as well as Western langu … |
| 05/2026 Conformity Generates Collective Misalignment in AI Agents Societies Giordano De Marzo et al. Artificial intelligence safety research focuses on aligning individual language models with human values, yet deployed AI systems increasingly operate as interacting populations where social influence may override individual alignment. Here we show that populations of individually aligned AI agents can be driven into stable misaligned states through conformity dynamics. Simulating opinion dynamics … |
| 04/2026 Coexistence of patterned phases in chemically active multicomponent mixtures Chengjie Luo et al. Chemically active mixtures exhibit complex patterns that emerge from the interplay of physical interactions and reactions among components. Individually, these two processes are well-understood: Physical interactions can give rise to phase separation, whereas reactions can form reaction-diffusion patterns. To understand the combination of both processes, we identify a Lyapunov functional for a cla … |