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Related papers: Dirac optimal reduction

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Suppose given a Hamiltonian and holomorphic action of $G=U(2)$ on a compact K\"{a}hler manifold $M$, with nowhere vanishing moment map. Given an integral coadjoint orbit $\mathcal{O}$ for $G$, under transversality assumptions we shall…

Symplectic Geometry · Mathematics 2021-09-07 Roberto Paoletti

It is shown that the Lagrangian reduction, in which solutions of equations of motion that do not involve time derivatives are used to eliminate variables, leads to results quite different from the standard Dirac treatment of the first order…

High Energy Physics - Theory · Physics 2009-11-11 N. Kiriushcheva , S. V. Kuzmin

It is proven by explicit construction that regularization by dimensional reduction can be formulated in a mathematically consistent way. In this formulation the quantum action principle is shown to hold. This provides an intuitive and…

High Energy Physics - Phenomenology · Physics 2008-11-26 Dominik Stöckinger

Parameter identification problems typically consist of a model equation, e.g. a (system of) ordinary or partial differential equation(s), and the observation equation. In the conventional reduced setting, the model equation is eliminated…

Numerical Analysis · Mathematics 2016-03-18 Barbara Kaltenbacher

In this article, we discuss the optimal allocation problem in an experiment when a regression model is used for statistical analysis. Monotonic convergence for a general class of multiplicative algorithms for $D$-optimality has been…

Computation · Statistics 2013-10-28 Wei Gao , Ping Shing Chan , Hon Keung Tony Ng , Xiaolei Lu

In this work we analyze the low energy nonrelativistic limit of Dirac theory in the framework of effective field theory. By integrating out the high energy modes of Dirac field, given in terms of a combination of the two-components Weyl…

High Energy Physics - Theory · Physics 2018-11-26 Rodrigo Corso B. Santos , Pedro R. S. Gomes

This paper proposes several novel optimization algorithms for minimizing a nonlinear objective function. The algorithms are enlightened by the optimal state trajectory of an optimal control problem closely related to the minimized objective…

Optimization and Control · Mathematics 2025-04-01 Hongxia Wang , Yeming Xu , Ziyuan Guo , Huanshui Zhang

We introduce functions for relative maximization in a general context: the beta and alpha applications. After a systematic study concerning regularities, we investigate how to approximate certain values of these functions using periodic…

Dynamical Systems · Mathematics 2007-05-23 Eduardo Garibaldi , Artur O. Lopes

In this paper we prove that Dirac operators on non-compact complete orbifolds which are sufficiently regular at infinity, admit a unique extension. Additonally, we prove a generalized orbifold Stokes'/Divergence theorem.

Differential Geometry · Mathematics 2008-09-22 Carla Farsi

We show that additional solutions must be ignored (in differences of the Schrodinger and Klein-Gordon equations) in the Dirac equation, where usually passed the second order radial equation, called the reduced equation, instead of a system.…

General Physics · Physics 2017-08-01 Anzor Khelashvili , Teimuraz Nadareishvili

We study two special cases of the equivariant index defined in part I of this series. We apply this index to deformations of Spin$^c$-Dirac operators, invariant under actions by possibly noncompact groups, with possibly noncompact orbit…

Differential Geometry · Mathematics 2016-03-11 Peter Hochs , Yanli Song

We generalize Roe's index theorem for graded generalized Dirac operators on amenable manifolds to multigraded elliptic uniform pseudodifferential operators. The generalization will follow from a local index theorem that is valid on any…

Differential Geometry · Mathematics 2018-06-07 Alexander Engel

We present a remarkable discretization of the classical Kepler problem which preserves its trajectories and all integrals of motion. The points of any discrete orbit belong to an appropriate continuous trajectory.

Numerical Analysis · Mathematics 2009-11-11 Jan L. Cieslinski

It is known that orbit reduction can be performed in one or two stages and it has been proven that the two processes are symplectically equivalent. In the context of orbit reduction by one stage we shall write an expression for the reduced…

Symplectic Geometry · Mathematics 2020-01-01 Viviana Alejandra Díaz , Marcela Zuccalli

Regularization and data augmentation methods have been widely used and become increasingly indispensable in deep learning training. Researchers who devote themselves to this have considered various possibilities. But so far, there has been…

Computer Vision and Pattern Recognition · Computer Science 2021-06-15 Xuan Cheng , Tianshu Xie , Xiaomin Wang , Jiali Deng , Minghui Liu , Ming Liu

We study the theory of systems with constraints from the point of view of the formal theory of partial differential equations. For finite-dimensional systems we show that the Dirac algorithm completes the equations of motion to an…

High Energy Physics - Theory · Physics 2009-10-28 Werner M. Seiler , Robin W. Tucker

The paper is mainly devoted to systematic developments and applications of geometric aspects of second-order variational analysis that are revolved around the concept of parabolic regularity of sets. This concept has been known in…

Optimization and Control · Mathematics 2020-06-17 Ashkan Mohammadi , Boris S. Mordukhovich , M. Ebrahim Sarabi

The nilpotent Dirac formalism has been shown, in previous publications, to generate new physical explanations for aspects of particle physics, with the additional possibility of calculating some of the parameters involved in the Standard…

Quantum Physics · Physics 2007-05-23 Peter Rowlands

The paper presents necessary and sufficient conditions for the order reduction of optimal control systems. Exploring the corresponding Hamiltonian system allows to solve the order reduction problem in terms of dynamical systems,…

Optimization and Control · Mathematics 2007-05-23 Igor Borovikov

We propose an extremely versatile approach to address a large family of matrix nearness problems, possibly with additional linear constraints. Our method is based on splitting a matrix nearness problem into two nested optimization problems,…

Numerical Analysis · Mathematics 2025-08-14 Miryam Gnazzo , Vanni Noferini , Lauri Nyman , Federico Poloni
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