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Reservoir computing is a popular approach to design recurrent neural networks, due to its training simplicity and approximation performance. The recurrent part of these networks is not trained (e.g., via gradient descent), making them…

Neural and Evolutionary Computing · Computer Science 2021-02-15 Pietro Verzelli , Cesare Alippi , Lorenzo Livi , Peter Tino

Active systems across scales, ranging from molecular machines to human crowds, are usually modeled as assemblies of self-propelled particles driven by internally generated forces. However, these models often assume memoryless dynamics and…

Statistical Mechanics · Physics 2025-12-10 Marc Besse , Raphaël Voituriez

Reservoir computing is a recently introduced, highly efficient bio-inspired approach for processing time dependent data. The basic scheme of reservoir computing consists of a non linear recurrent dynamical system coupled to a single input…

Emerging Technologies · Computer Science 2012-07-06 Yvan Paquot , François Duport , Anteo Smerieri , Joni Dambre , Benjamin Schrauwen , Marc Haelterman , Serge Massar

We have studied by Molecular Dynamics computer simulations the dynamics of water confined in ionic surfactants phases, ranging from well ordered lamellar structures to micelles at low and high water loading, respectively. We have analysed…

Soft Condensed Matter · Physics 2016-03-23 Samuel Hanot , Sandrine Lyonnard , Stefano Mossa

Signals recorded from neurons with extracellular planar sensors have a wide range of waveforms and amplitudes. This variety is a result of different physical conditions affecting the ion currents through a cellular membrane. The…

In the context of energy transition, industrial plants that heavily rely on electricity face more and more price volatility. To continue operating in these conditions, the directors become continually more willing to increase their…

Optimization and Control · Mathematics 2021-04-20 Thibaut Cuvelier

The more we learn about the cytoplasm of cells, the more we realise that the cytoplasm is not uniform but instead is highly inhomogeneous. In any inhomogeneous solution, there are concentration gradients, and particles move either up or…

Subcellular Processes · Quantitative Biology 2019-04-03 Richard P. Sear

Environmental fluctuations can shape replicator dynamics, with important consequences for both prebiotic and modern ecosystems. However, it remains unclear how simple replicators can acquire and use information about fluctuating…

Biological Physics · Physics 2026-05-25 Jordi Piñero , Damian R. Sowinski , Gourab Ghoshal , Adam Frank , Artemy Kolchinsky

Ions in water are important in biology, from molecules to organs. Classically, ions in water are treated as ideal noninteracting particles in a perfect gas. Excess free energy of ion was zero. Mathematics was not available to deal…

Biomolecules · Quantitative Biology 2015-06-15 Bob Eisenberg

Ionic liquids constrained at interfaces or restricted in subnanometric pores are increasingly employed in modern technologies, including energy applications. Understanding the details of their behavior in these conditions is therefore…

Materials Science · Physics 2018-09-25 Stefano Mossa

This work describes preliminary steps towards nano-scale reservoir computing using quantum dots. Our research has focused on the development of an accumulator-based sensing system that reacts to changes in the environment, as well as the…

Reaction-diffusion models with nonlocal constraints naturally arise as limiting cases of coupled bulk-surface models of intracellular signalling. In this paper, a minimal, mass-conserving model of cell-polarization on a curved membrane is…

Pattern Formation and Solitons · Physics 2022-10-04 Pearson W. Miller , Daniel Fortunato , Matteo Novaga , Stanislav Y. Shvartsman , Cyrill B. Muratov

Information flow is central to contemporary accounts of cognition, yet its physical basis in living neural matter remains poorly specified. Here, we develop a multiscale resource-theoretical framework motivated by the \textit{thermocoherent…

Neurons and Cognition · Quantitative Biology 2026-04-14 Onur Pusuluk

We present a general and systematic theory of non-equilibrium dynamics of multi-component fluid membranes, in general, and membranes containing transmembrane proteins, in particular. Developed based on a minimal number of principles of…

Soft Condensed Matter · Physics 2009-11-10 Michael A. Lomholt , Per L. Hansen , Ling Miao

The ubiquity of information transmission via molecular communication between cells is comprehensively documented on Earth; this phenomenon might even have played a vital role in the origin(s) and early evolution of life. Motivated by these…

Earth and Planetary Astrophysics · Physics 2024-01-26 Manasvi Lingam

Deciphering the underpinnings of the dynamical processes leading to information transmission, processing, and storing in the brain is a crucial challenge in neuroscience. An inspiring but speculative theoretical idea is that such dynamics…

Statistical Mechanics · Physics 2023-07-21 Guillermo B. Morales , Serena Di Santo , Miguel A. Muñoz

Biological information processing manifests a huge variety in its complexity and capability among different organisms, which presumably stems from the evolutionary optimization under limited computational resources. Starting from the…

Biological Physics · Physics 2025-10-21 Takehiro Tottori , Tetsuya J. Kobayashi

The molecular mechanism of ion channel gating and substrate modulation is elusive for many voltage gated ion channels, such as eukaryotic sodium ones. The understanding of channel functions is a pressing issue in molecular biophysics and…

Biomolecules · Quantitative Biology 2016-11-15 Duan Chen , Guowei Wei

Physical reservoir computing has recently been attracting attention for its ability to significantly reduce the computational resources required to process time-series data. However, the physical reservoirs that have been reported to date…

Emerging Technologies · Computer Science 2022-07-07 Daiki Nishioka , Takashi Tsuchiya , Wataru Namiki , Makoto Takayanagi , Masataka Imura , Yasuo Koide , Tohru Higuchi , Kazuya Terabe

We study the problem of predicting rare critical transition events for a class of slow-fast nonlinear dynamical systems. The state of the system of interest is described by a slow process, whereas a faster process drives its evolution and…

Computational Physics · Physics 2020-12-14 Soon Hoe Lim , Ludovico Theo Giorgini , Woosok Moon , J. S. Wettlaufer