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The two-dimensional Heisenberg spin-glass model is investigated by means of a semiclassical expansion around classical states. At leading order, we obtain an effective quadratic spin-wave Hamiltonian and study the localization properties of…

Disordered Systems and Neural Networks · Physics 2026-03-24 Giacomo Bracci-Testasecca , Jacopo Niedda , Aldo Coraggio , Roderich Moessner , Antonello Scardicchio

The grid firing patterns are thought to provide an efficient intrinsic metric capable of supporting universal spatial metric for mammalian spatial navigation in all environments. However, whether spatial representations of grid cells in the…

Neurons and Cognition · Quantitative Biology 2019-10-14 Taiping Zeng , XiaoLi Li , Bailu Si

Probabilistic inference offers a principled framework for understanding both behaviour and cortical computation. However, two basic and ubiquitous properties of cortical responses seem difficult to reconcile with probabilistic inference:…

Neurons and Cognition · Quantitative Biology 2017-01-03 Laurence Aitchison , Máté Lengyel

We have investigated the interrelation between the spin glasses and the structural glasses. Spin glasses in this case are random magnets without reflection symmetry (e.g. $p$ - spin interaction spin glasses and Potts glasses) which contain…

Statistical Mechanics · Physics 2007-05-23 V. G. Rostiashvili , G. Migliorini , T. A. Vilgis

In this paper, we propose novel learning frameworks to tackle optimal control problems by applying the Pontryagin maximum principle and then solving for a Hamiltonian dynamical system. Applying the Pontryagin maximum principle to the…

Optimization and Control · Mathematics 2024-08-13 Chandrajit Bajaj , Minh Nguyen

The brain achieves stability and plasticity in a topologically complex, shifting world through Metric-Topology Factorization (MTF), separating discrete topological indexing for context selection from continuous metric condensation for local…

Neurons and Cognition · Quantitative Biology 2026-03-05 Xin Li

We derive a rigorous, quantum mechanical map of fermionic creation and annihilation operators to continuous Cartesian variables that exactly reproduces the matrix structure of the many-fermion problem. We show how our scheme can be used to…

Chemical Physics · Physics 2018-03-20 Andrés Montoya-Castillo , Thomas E. Markland

Large-scale functional networks have been extensively studied using resting state functional magnetic resonance imaging. However, the pattern, organization, and function of fine-scale network activity remain largely unknown. Here we…

Neurons and Cognition · Quantitative Biology 2017-03-01 Kun-Han Lu , Jun Young Jeong , Haiguang Wen , Zhongming Liu

From the sandpoint of neural network dynamics we consider dynamical system of special type pesesses gradient (symmetric) and Hamiltonian (antisymmetric) flows. The conditions when Hamiltonian flow properties are dominant in the system are…

Disordered Systems and Neural Networks · Physics 2007-05-23 A. K. Prykarpatsky , V. V. Gafiychuk

We derive the dynamics of several rigid bodies of arbitrary shape in a 2-dimensional inviscid and incompressible fluid, whose vorticity field is given by point vortices. We adopt the idea of Vankerschaver et al. (2009) to derive the…

Fluid Dynamics · Physics 2014-02-27 Steffen Weissmann

Spin-orbit coupling in organic crystals is responsible for many spin-relaxation phenomena, going from spin diffusion to intersystem crossing. With the goal of constructing effective spin-orbit Hamiltonians to be used in multiscale…

Materials Science · Physics 2017-03-01 Subhayan Roychoudhury , Stefano Sanvito

Hamiltonian mechanics is an effective tool to represent many physical processes with concise yet well-generalized mathematical expressions. A well-modeled Hamiltonian makes it easy for researchers to analyze and forecast many related…

Machine Learning · Computer Science 2021-02-24 Seungjun Lee , Haesang Yang , Woojae Seong

The nature of dynamics of opinion formation modeled as a decision-by-majority process in complex networks is investigated using eigenmode analysis. Hamiltonian of the system is defined, and estimated by eigenvectors of the adjacency matrix…

Disordered Systems and Neural Networks · Physics 2007-10-08 Makoto Uchida , Susumu Shirayama

We propose and analyze a nonlinear opinion dynamics model for an agent making decisions about a continuous distribution of options in the presence of input. Inspired by perceptual decision-making, we develop new theory for opinion formation…

Analysis of PDEs · Mathematics 2024-11-28 Giovanna Amorim , Anastasia Bizyaeva , Alessio Franci , Naomi Ehrich Leonard

Structured internal representations (cognitive maps) shape cognition, from imagining the future and counterfactual past, to transferring knowledge to new settings. Our understanding of how such representations are formed and maintained in…

Neurons and Cognition · Quantitative Biology 2024-10-07 Matthew M Nour , Yunzhe Liu , Mohamady El-Gaby , Robert A McCutcheon , Raymond J Dolan

Toroidal vortex is a kind of novel and exotic structured light with potential applications in photonic topology and quantum information. Here, we present the study on high harmonic generation (HHG) from the interaction of the intense…

Optics · Physics 2024-10-10 Zijian Lyu , Yiqi Fang , Yunquan Liu

Patterns arise spontaneously in a range of systems spanning the sciences, and their study typically focuses on mechanisms to understand their evolution in space-time. Increasingly, there has been a transition towards controlling these…

Soft Condensed Matter · Physics 2024-10-17 Vishaal Krishnan , Sumit Sinha , L. Mahadevan

In systems where one coordinate undergoes periodic oscillation, the net displacement in any other coordinate over a single period is shown to be given by differentiation of the action integral associated with the oscillating coordinate.…

Classical Physics · Physics 2015-05-19 Rory J. Perkins , Paul M. Bellan

We study optimal design problems involving variational inequalities with unilateral conditions in the domain and pointwise boundary observation. We use regularizing and penalization tehniques in the setting of the Hamiltonian approach to…

Optimization and Control · Mathematics 2025-12-30 Cornel Marius Murea , Dan Tiba

We consider ultracold matter of spin-2 atoms in optical lattices. We derive an effective Hamiltonian for the studies of spin ordering in Mott states and investigate hyperfine spin correlations. Particularly, we diagonalize the Hamiltonian…

Quantum Gases · Physics 2009-12-15 Michiel Snoek , Jun Liang Song , Fei Zhou