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On the base of modified mode matching method we obtain some results that can be useful in the process of tuning of nonunifrom disk-loaded structures. Our consideration has shown that there are some parameters that depend only on the…

Accelerator Physics · Physics 2016-04-20 M. I. Ayzatsky , V. V. Mytrochenko

Two essential methods, the symmetry analysis and of the singularity analysis, for the study of the integrability of nonlinear ordinary differential equations are discussed. The main similarities and differences of these two different…

Mathematical Physics · Physics 2016-08-04 Andronikos Paliathanasis , P. G. L. Leach

It is shown that regularisation by dimensional reduction is a viable alternative to dimensional regularisation in non-supersymmetric theories.

High Energy Physics - Phenomenology · Physics 2009-10-22 I. Jack , D. R. T. Jones , K. L. Roberts

A nonlinear inequality is formulated in the paper. An estimate of the rate of decay of solutions to this inequality is obtained. This inequality is of interest in a study of dynamical systems and nonlinear evolution equations. It can be…

Classical Analysis and ODEs · Mathematics 2009-03-05 N. S. Hoang , A. G. Ramm

We propose a learning paradigm for the numerical approximation of differential invariants of planar curves. Deep neural-networks' (DNNs) universal approximation properties are utilized to estimate geometric measures. The proposed framework…

Computer Vision and Pattern Recognition · Computer Science 2023-03-08 Roy Velich , Ron Kimmel

A new method for analyzing the morphological features of point patterns is presented. The method is taken from the study of molecular liquids, where it has been introduced for making a statistical description of anisotropic distributions.…

Astrophysics · Physics 2007-05-23 R. Valdarnini

We propose a learning paradigm for numerical approximation of differential invariants of planar curves. Deep neural-networks' (DNNs) universal approximation properties are utilized to estimate geometric measures. The proposed framework is…

Computer Vision and Pattern Recognition · Computer Science 2022-02-15 Roy Velich , Ron Kimmel

Dimensionality reduction techniques are fundamental for analyzing and visualizing high-dimensional data. With established methods like t-SNE and PCA presenting a trade-off between representational power and interpretability. This paper…

Machine Learning · Computer Science 2025-04-25 Erik Bergh

We briefly sketch the noncommutative geometry approach to the Standard Model, with attention to what can be inferred about particle masses.

High Energy Physics - Theory · Physics 2008-02-03 Jose M. Gracia-Bondia

The popular generalized additive model framework is extended to allow both the mean curves and the response distribution to be nonparametric. The approach is demonstrated to be a flexible yet parsimonious tool for data analysis in its own…

Methodology · Statistics 2017-09-18 Alan Huang , Nanxi Zhang

Co lombeau's construction of generalized functions (in its special variant) is extended to a theory of generalized sections of vector bundles. As particular cases, generalized tensor analysis and exterior algebra are studied. A point value…

Functional Analysis · Mathematics 2007-05-23 Michael Kunzinger , Roland Steinbauer

Diagrammatic techniques are invented to implement QCD gauge transformations. These techniques can be used to discover how gauge-dependent terms are cancelled among diagrams to yield gauge-invariant results in the sum. In this way a…

High Energy Physics - Phenomenology · Physics 2016-09-01 Y. J. Feng , C. S. Lam

A nonlinear inequality is formulated in the paper. An estimate of the rate of growth/decay of solutions to this inequality is obtained. This inequality is of interest in a study of dynamical systems and nonlinear evolution equations. It can…

Classical Analysis and ODEs · Mathematics 2010-01-29 N. S. Hoang , A. G. Ramm

Stochastic-gradient sampling methods are often used to perform Bayesian inference on neural networks. It has been observed that the methods in which notions of differential geometry are included tend to have better performances, with the…

Machine Learning · Computer Science 2024-04-02 Hanlin Yu , Marcelo Hartmann , Bernardo Williams , Arto Klami

Following the previous authors works (joint with I.A.Dynnikov) we develop a theory of the discrete analogs of the differential-geometrical (DG) connections in the triangulated manifolds. We study a nonstandard discretization based on the…

Mathematical Physics · Physics 2007-05-23 S. P. Novikov

Flexible slender structures such as rods, ribbons, plates, and shells exhibit extreme nonlinear responses bending, twisting, buckling, wrinkling, and self contact, that defy conventional simulation frameworks. Discrete Differential Geometry…

By presenting the proofs of a few sample results, we introduce the reader to the use of nonstandard analysis in aspects of combinatorics of numbers.

Logic · Mathematics 2016-09-22 Mauro Di Nasso

In this paper we present a unified approach to the study of geometric and dynamic properties of nonlinear resolvents of holomorphic generators. The idea is to apply the distortion theorem we have established. This method allows us to find…

Complex Variables · Mathematics 2024-06-06 Mark Elin , Fiana Jacobzon

Program invariants are important for defect detection, program verification, and program repair. However, existing techniques have limited support for important classes of invariants such as disjunctions, which express the semantics of…

Software Engineering · Computer Science 2019-04-17 ThanhVu Nguyen , Deepak Kapur , Westley Weimer , Stephanie Forrest

Nonlinear analysis has played a prominent role in the recent developments in geometry and topology. The study of the Yang-Mills equation and its cousins gave rise to the Donaldson invariants and more recently, the Seiberg-Witten invariants.…

Differential Geometry · Mathematics 2007-05-23 Gang Tian