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Fine scale elastic structures are widespread in nature, for instances in plants or bones, whenever stiffness and low weight are required. These patterns frequently refine towards a Dirichlet boundary to ensure an effective load transfer.…

Numerical Analysis · Mathematics 2017-11-13 Nora Lüthen , Martin Rumpf , Sascha Tölkes , Orestis Vantzos

The emergence of hydrodynamics is one of the deepest phenomena in many-body systems. Arguably, the hydrodynamic equations are also the most important tools for predicting large-scale behaviour. Understanding how such equations emerge from…

Statistical Mechanics · Physics 2025-03-13 Sun Woo P. Kim , Friedrich Hübner , Juan P. Garrahan , Benjamin Doyon

Wrinkling is the phenomenon of out-of-plane deformation patterns in thin walled structures, as a result of a local compressive (internal) loads in combination with a large membrane stiffness and a small but non-zero bending stiffness.…

Numerical Analysis · Mathematics 2025-03-20 H. M. Verhelst , M. Möller , J. H. Den Besten

Dynamical systems theory describes how interacting quantities change over time and space, from molecular oscillators to large-scale biological patterns. Such systems often involve nonlinear feedbacks, delays, and interactions across scales.…

Quantitative Methods · Quantitative Biology 2025-09-09 Bartosz Prokop , Lendert Gelens

An approach is suggested for treating multiscale fluctuations in macromolecular systems. The emphasis is on the statistical properties of such fluctuations. The approach is illustrated by a macromolecular system with mesoscopic fluctuations…

Chemical Physics · Physics 2012-08-07 V. I. Yukalov , E. P. Yukalova

Despite their deterministic nature, dynamical systems often exhibit seemingly random behaviour. Consequently, a dynamical system is usually represented by a probabilistic model of which the unknown parameters must be estimated using…

Dynamical Systems · Mathematics 2021-08-20 Kasun Fernando , Nan Zou

We develop a diffusion approximation for systems subject to fast random resetting by small amplitudes. Equivalently, this describes systems with frequent but small catastrophes. We demonstrate the validity of the approximation by computing…

Statistical Mechanics · Physics 2026-02-26 Tobias Galla

Understanding fluctuation phenomena plays a dominant role in the development of many-body physics. The time evolution of entanglement is essential to a broad range of subjects in many-body physics, ranging from exotic quantum matter to…

Mesoscale and Nanoscale Physics · Physics 2024-03-06 Lih-King Lim , Cunzhong Lou , Chushun Tian

Slow-fast dynamical systems, i.e., singularly or non-singularly perturbed dynamical systems possess slow invariant manifolds on which trajectories evolve slowly. Since the last century various methods have been developed for approximating…

Chaotic Dynamics · Physics 2021-06-30 Jean-Marc Ginoux

Filtering is concerned with the sequential estimation of the state, and uncertainties, of a Markovian system, given noisy observations. It is particularly difficult to achieve accurate filtering in complex dynamical systems, such as those…

Probability · Mathematics 2015-12-14 Wonjung Lee , Andrew Stuart

Traditional DTA models of large cities suffer from prohibitive computation times and calibration/validation can become major challenges faced by practitioners. The empirical evidence in 2008 in support of the existence of a Macroscopic…

Analysis of PDEs · Mathematics 2018-12-04 Rafegh Aghamohammadi , Jorge A. Laval

The paper introduces a novel topological method for prediction and modeling for a nonlinear time--series that exhibit recurring patterns. According to the model, global manifold of the reconstructed state--space can be approximated by a few…

Chaotic Dynamics · Physics 2017-11-21 Sajini Anand P S , Prabhakar G Vaidya

Switching dynamical systems provide a powerful, interpretable modeling framework for inference in time-series data in, e.g., the natural sciences or engineering applications. Since many areas, such as biology or discrete-event systems, are…

Machine Learning · Computer Science 2021-09-30 Lukas Köhs , Bastian Alt , Heinz Koeppl

We present a method of discrete modeling and analysis of multilevel dynamics of complex large-scale hierarchical dynamic systems subject to external dynamic control mechanism. Architectural model of information system supporting simulation…

Computational Engineering, Finance, and Science · Computer Science 2008-09-23 Armen Bagdasaryan

Over the last two decades, network science has greatly advanced our understanding of how the collective behaviors of a complex system emerge from the interactions among its basic units. Multiplex networks, i.e. networks with many layers,…

In sustained growth with random dynamics stationary distributions can exist without detailed balance. This suggests thermodynamical behavior in fast growing complex systems. In order to model such phenomena we apply both a discrete and a…

Statistical Mechanics · Physics 2017-03-22 Tamás Biró , Zoltán Néda

Complex systems are fascinating because their rich macroscopic properties emerge from the interaction of many simple parts. Understanding the building principles of these emergent phenomena in nature requires assessing natural complex…

Neurons and Cognition · Quantitative Biology 2022-11-17 Anna Levina , Viola Priesemann , Johannes Zierenberg

We consider numerical solution of elliptic problems with heterogeneous diffusion coefficients containing thin highly conductive structures. Such problems arise e.g. in fractured porous media, reinforced materials, and electric circuits. The…

Numerical Analysis · Mathematics 2020-07-22 Fredrik Hellman , Axel Målqvist , Siyang Wang

Biomaterial systems have allowed for the in vitro production of complex, emergent tissue behaviors that were not possible with conventional 2D culture systems allowing for analysis of the normal development as well as disease processes. We…

Tissues and Organs · Quantitative Biology 2019-10-16 Matthew S Hall , Joseph T Decker , Lonnie D Shea

We adapt Vertex models to understand the physical origin of the formation of long-range ordered structures in repulsive soft particles. The model incorporates contributions from the volume and surface area of each particle. Sampling using…

Soft Condensed Matter · Physics 2022-06-28 Toluwanimi O. Bello , Sangwoo Lee , Patrick T. Underhill
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