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Functional geometry is a framework using concepts from geometry to understand the invariance of amplitudes in quantum field theory under a large class of field redefinitions, including those involving derivatives. It is inspired by…

High Energy Physics - Theory · Physics 2026-04-23 Antonio Delgado , Adam Martin , Runqing Wang

Based on a novel concept of multiplicative multiscale decomposition, we have derived a multiscale micromorphic molecular dynamics (MMMD)to extent the (Andersen)-Parrinello-Rahman molecular dynamics to mesoscale and macroscale. The…

Computational Physics · Physics 2014-03-13 Shaofan Li , Qi Tong

The plasma membrane of living cells is compartmentalized at multiple spatial scales ranging from the nano- to the meso-scale. This non-random organization is crucial for a large number of cellular functions. At the nanoscale, cell membranes…

The biological cell exhibits a fantastic range of behaviors, but ultimately these are governed by a handful of physical and chemical principles. Here we explore simple theory, known for decades and based on the simple thermodynamics of…

Biomolecules · Quantitative Biology 2020-03-25 Daniel M. Zuckerman

Advancement in nanotechnology is dependent on the understanding of the behavior of matter in nanoscale. In this report we have demonstrated, through a unique molecular simulation procedure, that properties of matter in nanosystems do not…

Statistical Mechanics · Physics 2018-04-26 Pirooz Mohazzabi , G. Ali Mansoori

The various mathematical models developed in the past to interpret the behavior of natural and manmade materials were based on observations and experiments made at that time. Classical laws (such as Newton's for gravity, Hooke's for…

Classical Physics · Physics 2020-04-09 Elias C. Aifantis

Attention mechanisms are developing into a viable alternative to convolutional layers as elementary building block of NNs. Their main advantage is that they are not restricted to capture local dependencies in the input, but can draw…

Machine Learning · Computer Science 2021-09-07 Thorben Frank , Stefan Chmiela

Scaling deep learning models has been at the heart of recent revolutions in language modelling and image generation. Practitioners have observed a strong relationship between model size, dataset size, and performance. However,…

Living systems operate far from thermodynamic equilibrium. Enzymatic activity can induce broken detailed balance at the molecular scale. This molecular scale breaking of detailed balance is crucial to achieve biological functions such as…

Biological Physics · Physics 2018-05-02 F. Gnesotto , F. Mura , J. Gladrow , C. P. Broedersz

This dissertation explores various nonlinear responses that arise from the rich interplay between quantum geometry, disorder, magnetism and topology in quantum materials. In addition to presenting generalizations of quantum kinetic theory,…

Mesoscale and Nanoscale Physics · Physics 2026-02-03 M. Mehraeen

We derive and simulate a mathematical model for mechanotransduction related to the Rho GTPase signalling pathway. The model addresses the bidirectional coupling between signalling processes and cell mechanics. A numerical method based on…

Numerical Analysis · Mathematics 2025-06-11 Sofie Verhees , Chandrasekhar Venkataraman , Mariya Ptashnyk

We propose a review of the current knowledge about the synthesis, magnetic properties and applications of magnetic cylindrical nanowires and nanotubes. By "nano" we consider diameters reasonably smaller than a micrometer. At this scale,…

Mesoscale and Nanoscale Physics · Physics 2018-12-19 Michal Stano , Olivier Fruchart

The nanophysics is halfway between the size scales of quantum mechanics and macroscopic physics governed by the laws of Newton and Einstein. The correct definition of nanophysics is the physics of structures and artefacts with dimensions in…

Popular Physics · Physics 2016-06-29 E. Catalano

The last decade has witnessed a swiftly increasing interest in the design and production of novel multivalent molecules as powerful alternatives for conventional antibodies in the fight against cancer and infectious diseases. However, while…

Soft Condensed Matter · Physics 2019-08-23 Suman Saurabh , Francesco Piazza

Over the last few decades, nonlinear optics has become significantly more nonlinear, traversing nearly a billionfold improvement in energy efficiency, with ultrafast nonlinear nanophotonics in particular emerging as a frontier for combining…

Newtonian dynamics is derived from prior information codified into an appropriate statistical model. The basic assumption is that there is an irreducible uncertainty in the location of particles so that the state of a particle is defined by…

Classical Physics · Physics 2009-05-27 Ariel Caticha , Carlo Cafaro

A generalized entropy arising in the context of superstatistics is obtained for an ideal gas. The curvature scalar associated to the thermodynamic space generated by this modified entropy is calculated using two formalisms of the geometric…

Statistical Mechanics · Physics 2018-04-18 J. L. López , O. Obregón , J. Torres-Arenas

In this paper we review some recent results dealing with the transition between microscopic and macroscopic scales in different fields, including kinetic theory, cells movement in biology, chemotaxis, flocking phenomena and agent systems.…

Analysis of PDEs · Mathematics 2024-06-11 Thierry Paul

A couple of orthogonal coordinates for dipole geometry are proposed for numerical simulations of plasma geophysics in the Earth's dipole magnetic field. These coordinates have proper metric profiles along field lines in contrast to the…

Geophysics · Physics 2007-05-23 Akira Kageyama , Tooru Sugiyama , Kunihiko Watanabe , Tetsuya Sato

Discussed is mechanics of objects with internal degrees of freedom in generally non-Euclidean spaces. Geometric peculiarities of the model are investigated detailly. Discussed are also possible mechanical applications, e.g., in dynamics of…

Mathematical Physics · Physics 2009-12-24 J. J. Sławianowski , B. Gołubowska