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We consider solution operators of linear ordinary boundary problems with "too many" boundary conditions, which are not always solvable. These generalized Green's operators are a certain kind of generalized inverses of differential…

Symbolic Computation · Computer Science 2014-06-27 Anja Korporal , Georg Regensburger

The two-time Green function method in quantum electrodynamics of high-Z few-electron atoms is described in detail. This method provides a simple procedure for deriving formulas for the energy shift of a single level and for the energies and…

Atomic Physics · Physics 2009-11-06 V. M. Shabaev

Deep Convolutional Neural Networks~(CNNs) offer remarkable performance of classifications and regressions in many high-dimensional problems and have been widely utilized in real-word cognitive applications. However, high computational cost…

Computer Vision and Pattern Recognition · Computer Science 2018-09-10 Chuhan Min , Aosen Wang , Yiran Chen , Wenyao Xu , Xin Chen

Spectral neural operators, particularly Fourier Neural Operators (FNO), are a powerful framework for learning solution operators of partial differential equations (PDEs) due to their efficient global mixing in the frequency domain. However,…

Machine Learning · Computer Science 2026-02-06 Chun-Wun Cheng , Carola-Bibiane Schönlieb , Angelica I. Aviles-Rivero

In this letter, we investigate the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in device-to-device (D2D) communications underlaying cellular networks with uplink channel reuse. The resource allocation problem is…

Computer Science and Game Theory · Computer Science 2016-11-18 Zhenyu Zhou , Mianxiong Dong , Kaoru Ota , Jun Wu , Takuro Sato

A new scheme has been proposed to solve the B.E. condenstates in terms of Green's function approach. It has been shown that the radial wave function of two interacting atoms, moving in a common harmonic oscillator potential modified by an…

Quantum Physics · Physics 2007-05-23 Mahendra Sinha Roy

The Muon optimizer, a matrix-structured algorithm that leverages spectral orthogonalization of gradients, is a milestone in the pretraining of large language models. However, the underlying mechanisms of Muon -- particularly the role of…

Machine Learning · Computer Science 2026-01-21 Jianhao Ma , Yu Huang , Yuejie Chi , Yuxin Chen

This paper introduces a hierarchical interpolative decomposition butterfly-LU factorization (H-IDBF-LU) preconditioner for solving two-dimensional electric-field integral equations (EFIEs) in electromagnetic scattering problems of perfect…

Numerical Analysis · Mathematics 2020-01-08 Yang Liu , Haizhao Yang

A new low-order discretization scheme for the identity operator in the magnetic field integral equation (MFIE) is discussed. Its concept is derived from the weak-form representation of combined sources which are discretized with…

Numerical Analysis · Mathematics 2022-06-27 Jonas Kornprobst , Thomas F. Eibert

We introduce basic aspects of new operator method, which is very suitable for practical solving differential equations of various types. The main advantage of the method is revealed in opportunity to find compact exact operator solutions of…

Mathematical Physics · Physics 2007-05-23 Yu. N. Kosovtsov

We introduce three types of partial fractional operators of variable order. An integration by parts formula for partial fractional integrals of variable order and an extension of Green's theorem are proved. These results allow us to obtain…

Optimization and Control · Mathematics 2013-02-12 Tatiana Odzijewicz , Agnieszka B. Malinowska , Delfim F. M. Torres

The localized operator partitioning method [Y. Khan and P. Brumer, J. Chem. Phys. 137, 194112 (2012)] rigorously defines the electronic energy on any subsystem within a molecule and gives a precise meaning to the subsystem ground and…

Chemical Physics · Physics 2016-10-31 Jayashree Nagesh , Artur F. Izmaylov , Paul Brumer

Using the framework of operator or Calder\'on preconditioning, uniform preconditioners are constructed for elliptic operators discretized with continuous finite (or boundary) elements. The preconditioners are constructed as the composition…

Numerical Analysis · Mathematics 2021-10-27 Rob Stevenson , Raymond van Venetië

The method-of-moments implementation of the electric-field integral equation (EFIE) yields many code-verification challenges due to the various sources of numerical error and their possible interactions. Matters are further complicated by…

Numerical Analysis · Mathematics 2022-09-16 Brian A. Freno , Neil R. Matula

The recently introduced concept of a spectral shift operator is applied in several instances. Explicit applications include Krein's trace formula for pairs of self-adjoint operators, the Birman-Solomyak spectral averaging formula and its…

Spectral Theory · Mathematics 2007-05-23 Fritz Gesztesy , Konstantin A. Makarov

In this paper, we propose a data-driven framework for constructing efficient approximate inverse preconditioners for elliptic partial differential equations (PDEs) by learning the Green's function of the underlying operator with neural…

Numerical Analysis · Mathematics 2025-10-21 Tianshi Xu , Rui Peng Li , Yuanzhe Xi

The mode selection and resource allocation in fog radio access networks (F-RANs) have been advocated as key techniques to improve spectral and energy efficiency. In this paper, we investigate the joint optimization of mode selection and…

Networking and Internet Architecture · Computer Science 2020-02-21 Hongyu Xiang , Mugen Peng , Yaohua Sun , Shi Yan

Dyadic Green's function is an important tool of computational photonics, giving deeper insights into light-matter interaction. We present an operator approach to the derivation of the dyadic Green's function of a generic anisotropic…

Optics · Physics 2026-05-13 Aliaksandr Arlouski , Lei Gao , Dongliang Gao , Andrey Novitsky

The task to construct parametrices of elliptic differential operators on a manifold with edges requires a calculus of operators with a two-component principal symbolic hierarchy, consisting of (edge-degenerate) interior and…

Analysis of PDEs · Mathematics 2007-05-23 B. -W. Schulze , A. Volpato

The Fast Multipole Method (FMM) is an efficient numerical algorithm for computation of long-ranged forces in $N$-body problems within gravitational and electrostatic fields. This method utilizes multipole expansions of the Green's function…

Machine Learning · Computer Science 2025-09-26 Emilio McAllister Fognini , Marta M. Betcke , Ben T. Cox