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Dynamic network analysis has found an increasing interest in the literature because of the importance of different kinds of dynamic social networks, biological networks, and economic networks. Most available probability and statistical…

Methodology · Statistics 2017-10-18 Elynn Yi Chen , Rong Chen

We introduce a systematic mathematical language for describing fixed point models and apply it to the study to topological phases of matter. The framework is reminiscent of state-sum models and lattice topological quantum field theories,…

Quantum Physics · Physics 2022-07-28 A. Bauer , J. Eisert , C. Wille

In this paper we provide novel results on the infinite level normal form and orbital normal form classifications of nonlinear Eulerian and rotational vector fields with two pairs of non-resonant imaginary modes. We use the method of…

Optimization and Control · Mathematics 2019-11-14 Majid Gazor , Ahmad Shoghi

Even if a linear system of ordinary differential equations has a globally attracting equilibrium at the origin, small disturbances from the equilibrium may lead to large transient excursions before the system stabilizes. This…

Dynamical Systems · Mathematics 2026-05-13 James Broda , Alanna Haslam-Hyde , Mary Lou Zeeman

Normalizing Flows provide a principled framework for high-dimensional density estimation and generative modeling by constructing invertible transformations with tractable Jacobian determinants. We propose Fractal Flow, a novel normalizing…

Machine Learning · Statistics 2025-08-28 Binhui Zhang , Jianwei Ma

Contrary to many recent models of growing networks, we present a model with fixed number of nodes and links, where it is introduced a dynamics favoring the formation of links between nodes with degree of connectivity as different as…

Statistical Mechanics · Physics 2007-05-23 M. Baiesi , S. S. Manna

Backpropagation algorithm is the cornerstone for neural network analysis. Paper extends it for training any derivatives of neural network's output with respect to its input. By the dint of it feedforward networks can be used to solve or…

Neural and Evolutionary Computing · Computer Science 2017-12-13 V. I. Avrutskiy

We strengthen the standard bifurcation theorems for saddle-node, transcritical, pitchfork, and period-doubling bifurcations of maps. Our new formulation involves adding one or two extra terms to the standard truncated normal forms with…

Dynamical Systems · Mathematics 2022-06-13 Paul A. Glendinning , David J. W. Simpson

We analyse the following inverse problem. Given a nonconvex functional (from a specific, but quite general class) of normal, codimension-1 currents (which in two spatial dimensions can be interpreted as transportation networks), find the…

Optimization and Control · Mathematics 2018-05-15 Benedikt Wirth

We propose a Multi-Layer Network based on the Bayesian framework of the Factor Graphs in Reduced Normal Form (FGrn) applied to a two-dimensional lattice. The Latent Variable Model (LVM) is the basic building block of a quadtree hierarchy…

Computer Vision and Pattern Recognition · Computer Science 2015-02-17 Amedeo Buonanno , Francesco A. N. Palmieri

In recent years, nonlinear dynamic system identification using artificial neural networks has garnered attention due to its broad potential applications across science and engineering. However, purely data-driven approaches often struggle…

Machine Learning · Computer Science 2025-11-06 Fabian J. Roth , Dominik K. Klein , Maximilian Kannapinn , Jan Peters , Oliver Weeger

There is a growing attention given to utilizing Lagrangian and Hamiltonian mechanics with network training in order to incorporate physics into the network. Most commonly, conservative systems are modeled, in which there are no frictional…

Machine Learning · Computer Science 2024-05-28 Veera Sundararaghavan , Megna N. Shah , Jeff P. Simmons

This paper aims to illustrate the applications of resonant Hamiltonian normal forms to some problems of galactic dynamics. We detail the construction of the 1:1 resonant normal form corresponding to a wide class of potentials with…

Astrophysics of Galaxies · Physics 2014-01-15 Antonella Marchesiello , Giuseppe Pucacco

We show that logarithmic conformal field theories may be derived using nilpotent scale transformation. Using such nilpotent weights we derive properties of LCFT's, such as two and three point correlation functions solely from symmetry…

High Energy Physics - Theory · Physics 2009-11-07 S. Moghimi-Araghi , S. Rouhani , M. Saadat

We study "circular net" (discrete orthogonal net) equations for angular data generalized by external spectral parameters. A criterion defining physical regimes of these Hamiltonian equations is the reality of Lagrangian density. There are…

Exactly Solvable and Integrable Systems · Physics 2009-07-22 Sergey M. Sergeev

High-Dimensional and Incomplete (HDI) data is commonly encountered in big data-related applications like social network services systems, which are concerning the limited interactions among numerous nodes. Knowledge acquisition from HDI…

Artificial Intelligence · Computer Science 2023-09-20 Yurong Zhong , Zhe Xie , Weiling Li , Xin Luo

We implement modular flavor symmetries within the Standard Model Effective Field Theory (SMEFT) framework, using the flavor group $A_4^{(q)} \times A_4^{(e)}$ with distinct moduli $\tau_q$ and $\tau_e$, and assigning different modular…

High Energy Physics - Phenomenology · Physics 2026-02-02 Luo-Jia Kang , Hao Sun , Jiang-Hao Yu

We develop a new method for constructing $3d$ $\mathcal{N}=4$ Coulomb branch chiral rings in terms of gauge-invariant generators and relations while making the global symmetry manifest. Our examples generalise to all balanced quivers of…

High Energy Physics - Theory · Physics 2019-03-27 Amihay Hanany , Dominik Miketa

The phase-space structure of two families of galactic potentials is approximated with a resonant detuned normal form. The normal form series is obtained by a Lie transform of the series expansion around the minimum of the original…

Chaotic Dynamics · Physics 2011-10-05 Giuseppe Pucacco , Dino Boccaletti , Cinzia Belmonte

Future power grids will be operating a large number of heterogeneous dynamical actors. Many of these will contribute to the fundamental dynamical stability of the system. By taking a complexity theoretic perspective we derive a normal form…

Adaptation and Self-Organizing Systems · Physics 2022-01-14 Raphael Kogler , Anton Plietzsch , Paul Schultz , Frank Hellmann
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