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We extend the Weak Adversarial Neural Pushforward Method (WANPM) to fractional Fokker-Planck equations, in which the classical Laplacian diffusion operator is replaced by the fractional Laplacian of order alpha in (0, 2]. The solution…

Numerical Analysis · Mathematics 2026-03-23 Andrew Qing He , Wei Cai

Computing the optimal solution to a spatial filtering problems in a Wireless Sensor Network can incur large bandwidth and computational requirements if an approach relying on data centralization is used. The so-called distributed adaptive…

Signal Processing · Electrical Eng. & Systems 2023-03-01 Charles Hovine , Alexander Bertrand

We study the network localization problem, i.e., the problem of determining node positions of a wireless sensor network modeled as a unit disk graph. In an arbitrarily deployed network, positions of all nodes of the network may not be…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-08-04 Kaustav Bose , Manash Kumar Kundu , Ranendu Adhikary , Buddhadeb Sau

This paper presents an algorithm for the preprocessing of observation data aimed at improving the robustness of orbit determination tools. Two objectives are fulfilled: obtain a refined solution to the initial orbit determination problem…

Numerical Analysis · Mathematics 2023-11-07 Alberto Fossà , Roberto Armellin , Emmanuel Delande , Matteo Losacco , Francesco Sanfedino

The numerical simulation of wave propagation in semiclassical (high-frequency) problems is well known to pose a formidable challenge. In this work, a new phase-space approach for the numerical simulation of semiclassical wave propagation,…

Analysis of PDEs · Mathematics 2008-10-30 Agissilaos G. Athanassoulis

In this paper, we consider Wiener filters to reconstruct deterministic and (wide-band) stationary graph signals from their observations corrupted by random noises, and we propose distributed algorithms to implement Wiener filters and…

Signal Processing · Electrical Eng. & Systems 2022-05-10 Cong Zheng , Cheng Cheng , Qiyu Sun

A quantum phase space with Wannier basis is constructed: (i) classical phase space is divided into Planck cells; (ii) a complete set of Wannier functions are constructed with the combination of Kohn's method and L\"owdin method such that…

Quantum Physics · Physics 2018-03-02 Yuan Fang , Fan Wu , Biao Wu

We introduce a Wannier-type formulation of periodic local vibrational mode theory that yields real-space-localized vibrational modes associated with individual internal coordinates in crystalline solids. These modes are constructed as…

Materials Science · Physics 2026-05-12 Mateusz Mojsak , Elfi Kraka , Adam A. L. Michalchuk

We investigate the electronic structure of over-coordinated defects in amorphous silicon via density-functional total-energy calculations, with the aim of understanding the relationship between topological and electronic properties on a…

Materials Science · Physics 2007-05-23 M. Fornari , N. Marzari , M. Peressi , A. Baldereschi

Using the shift-operator technique, a compact formula for the Fourier transform of a product of two Slater-type orbitals located on different atomic centers is derived. The result is valid for arbitrary quantum numbers and was found to be…

Materials Science · Physics 2009-11-13 T. A. Niehaus , R. López , J. F. Rico

In increasing number of electronic devices implement wideband radio technologies for localization and sensing purposes, like ultra-wideband (UWB). Such radio technologies benefit from a large number of antennas, but space for antennas is…

Signal Processing · Electrical Eng. & Systems 2025-09-23 Tobias Lafer , Erik Leitinger , Klaus Witrisal

Modeling non-stationary processes, where statistical properties vary across the input domain, is a critical challenge in machine learning; yet most scalable methods rely on a simplifying assumption of stationarity. This forces a difficult…

Machine Learning · Computer Science 2026-02-03 Sawan Kumar , Souvik Chakraborty

Maximally localized Wannier functions use the gauge freedom of Bloch wavefunctions to define the optimally smooth subspace with matrix elements that depend smoothly on crystal momentum. The associated Wannier functions are real-space…

Materials Science · Physics 2024-10-24 Giulio Volpato , Stefano Mocatti , Giovanni Marini , Matteo Calandra

We present a spin-dependent extension of the non-orthogonal generalized Wannier function (NGWF) formalism within the framework of linear-scaling density functional theory (LS-DFT) as implemented in the ONETEP code. In traditional LS-DFT…

In non-stationary signal processing, prior work has incorporated the quadratic-phase Fourier transform (QPFT) into the ambiguity function (AF) and Wigner distribution (WD) to enhance their performance. This paper introduces an advanced…

Functional Analysis · Mathematics 2025-03-21 Aamir H. Dar , Neeraj Kumar Sharma

This paper proposes a distributed weighted regularized least squares algorithm (DWRLS) based on spherical radial basis functions and spherical quadrature rules to tackle spherical data that are stored across numerous local servers and…

Machine Learning · Computer Science 2022-11-15 Han Feng , Shao-Bo Lin , Ding-Xuan Zhou

In this paper, we correct a mistake we made in [Phys. Rev. Lett. $\textbf{122}$, 190402 (2019)] and [Phys. Rev. A $\textbf{103}$, 012213 (2021)] regarding the Wigner function of the so-called smoothed Weak-Valued state (SWV state). Here…

Quantum Physics · Physics 2025-08-07 Kiarn T. Laverick , Areeya Chantasri , Howard M. Wiseman

This work presents a novel approach to distribute orbitals into subspaces within electron-pairing-based natural orbital functionals (NOFs). This approach modifies the coupling between weakly and strongly occupied orbitals by applying an…

Chemical Physics · Physics 2025-02-05 Élodie Boutou , Juan Felipe Huan Lew-Yee , Jose Maria Mercero , Mario Piris

In a tight-binding lattice model with $n$ orbitals (single-particle states) per site, Wannier functions are $n$-component vector functions of position that fall off rapidly away from some location, and such that a set of them in some sense…

Mesoscale and Nanoscale Physics · Physics 2017-03-29 N. Read

Bayesian optimization has proven to be a highly effective methodology for the global optimization of unknown, expensive and multimodal functions. The ability to accurately model distributions over functions is critical to the effectiveness…

Machine Learning · Statistics 2014-06-13 Jasper Snoek , Kevin Swersky , Richard S. Zemel , Ryan P. Adams