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In this paper we derive the optimal linear shrinkage estimator for the high-dimensional mean vector using random matrix theory. The results are obtained under the assumption that both the dimension $p$ and the sample size $n$ tend to…

Statistics Theory · Mathematics 2018-07-17 Taras Bodnar , Ostap Okhrin , Nestor Parolya

An efficient way to calculate one-loop counterterms within the Feynman diagrammatic approach and dimensional regularization is to expand the propagators in the integrands of the Feynman integrals around vanishing external momentum. In this…

High Energy Physics - Phenomenology · Physics 2019-09-04 Christian F. Steinwachs

Accelerator magnets steer particle beams according to the field integrated along the trajectory over the magnet length. Purpose-wound coils measure these relevant parameters with high precision and complement efficiently point-like…

Accelerator Physics · Physics 2011-04-20 L. Walckiers

The numerical simulation of three-dimensional charged-particle dynamics (CPD) under strong magnetic field is a basic and challenging algorithmic task in plasma physics. In this paper, we introduce a new methodology to design two-scale…

Numerical Analysis · Mathematics 2024-09-20 Bin Wang , Zhen Miao , Yaolin Jiang

We develop Monte Carlo simulations for uniformly charged polymers and machine learning algorithm to interpret the intra-polymer structure factor of the charged polymer system, which can be obtained from small-angle scattering experiments.…

Soft Condensed Matter · Physics 2025-11-21 Lijie Ding , Chi-Huan Tung , Jan-Michael Y. Carrillo , Wei-Ren Chen , Changwoo Do

The periodic standing wave method studies circular orbits of compact objects coupled to helically symmetric standing wave gravitational fields. From this solution an approximation is extracted for the strong field, slowly inspiralling…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Christopher Beetle , Benjamin Bromley , Napoleón Hernández , Richard H. Price

In this paper, a novel linear algorithm is proposed for state estimation including bad data detection of power systems that are monitored both by conventional and synchrophasor measurements. Both types of data are treated simultaneously and…

Systems and Control · Electrical Eng. & Systems 2020-01-30 Aleksandar Jovicic , Gabriela Hug

Circuits play a fundamental role in polyhedral theory and linear programming. For instance, circuits are used as step directions in various augmentation schemes for solving linear programs or to leave degenerate vertices while running the…

Optimization and Control · Mathematics 2019-07-01 Steffen Borgwardt , Charles Viss

This paper proposes a tuning methodology for proportional resonant (PR) controllers by using the design philosophy of the Ziegler-Nichols forced oscillation method. Unlike such related methods that are usual for PID design, and those that…

Signal Processing · Electrical Eng. & Systems 2018-07-18 Charles Lorenzini , Luís Fernando Alves Pereira , Alexandre Sanfelice Bazanella

An extended theoretical approach is proposed to predict the average power of wind turbines in a large finite-size wind farm. The approach is based on the two-scale momentum theory proposed recently for the modelling of ideal very large wind…

Fluid Dynamics · Physics 2018-10-12 Takafumi Nishino

Reflection, propagation and energy analysis are crucially important in designing structures, especially plates. A thick plate is considered based on first order shear deformation theory. Wave Propagation Method (WPM) is employed to exactly…

In a previous paper, I demonstrated the accuracy of simple, precessing, power ellipse (p-ellipse) approximations to orbits of low-to-moderate eccentricity in power-law potentials. Here I explore several extensions of these approximations to…

Astrophysics of Galaxies · Physics 2015-06-23 Curtis Struck

Using elementary methods, we define and derive a particular weighted average of the trapezoidal and composite trapezoidal rules and show that this approximation, as well as its composite, is straightforward in computation. This…

Numerical Analysis · Mathematics 2012-08-06 Michael Brandon Youngberg

Low-rank inducing unitarily invariant norms have been introduced to convexify problems with low-rank/sparsity constraint. They are the convex envelope of a unitary invariant norm and the indicator function of an upper bounding rank…

Optimization and Control · Mathematics 2022-02-17 Christian Grussler , Pontus Giselsson

An extension of the regularized least-squares in which the estimation parameters are stretchable is introduced and studied in this paper. The solution of this ridge regression with stretchable parameters is given in primal and dual spaces…

Machine Learning · Computer Science 2018-06-12 Kar-Ann Toh , Lei Sun , Zhiping Lin

The proximal generalized alternating direction method of multipliers (p-GADMM) is substantially efficient for solving convex composite programming problems of high-dimensional to moderate accuracy. The global convergence of this method was…

Optimization and Control · Mathematics 2022-08-19 Han Wang , Yunhai Xiao

The method of stable random projections is a tool for efficiently computing the $l_\alpha$ distances using low memory, where $0<\alpha \leq 2$ is a tuning parameter. The method boils down to a statistical estimation task and various…

Machine Learning · Computer Science 2008-12-18 Ping Li

Dimensional regularization of Euclidean momentum space integrals is a highly successful technique in renormalization of quantum field theories. While it yields a straightforward algorithmic method, with which to evaluate diagrams beyond…

Mathematical Physics · Physics 2020-09-03 Juuso Österman

Symmetric polynomial quadrature rules for triangles are commonly used to efficiently integrate two-dimensional domains in finite-element-type problems. While the development of such rules focuses on the maximum degree a given number of…

Numerical Analysis · Mathematics 2025-12-19 Brian A. Freno , Neil R. Matula , Joseph E. Bishop

Polynomial optimization encompasses a broad class of problems in which both the objective function and constraints are polynomial functions of the decision variables. In recent years, a substantial body of research has focused on…

Optimization and Control · Mathematics 2026-01-05 Haibin Chen , Hong Yan , Guanglu Zhou