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In this paper, we design and analyze a novel spectral method for the subdiffusion equation. As it has been known, the solutions of this equation are usually singular near the initial time. Consequently, direct application of the traditional…

Numerical Analysis · Mathematics 2022-04-06 Chuanju Xu , Wei Zeng

(abridged) We discuss the Galactic foreground emission between 20 and 100GHz based on observations by Planck/WMAP. The Commander component-separation tool has been used to separate the various astrophysical processes in total intensity.…

Astrophysics of Galaxies · Physics 2016-09-21 Planck Collaboration , P. A. R. Ade , N. Aghanim , M. I. R. Alves , M. Arnaud , M. Ashdown , J. Aumont , C. Baccigalupi , A. J. Banday , R. B. Barreiro , J. G. Bartlett , N. Bartolo , E. Battaner , K. Benabed , A. Benoit , A. Benoit-Levy , J. -P. Bernard , M. Bersanelli , P. Bielewicz , J. J. Bock , A. Bonaldi , L. Bonavera , J. R. Bond , J. Borrill , F. R. Bouchet , F. Boulanger , M. Bucher , C. Burigana , R. C. Butler , E. Calabrese , J. -F. Cardoso , A. Catalano , A. Challinor , A. Chamballu , R. -R. Chary , H. C. Chiang , P. R. Christensen , S. Colombi , L. P. L. Colombo , C. Combet , F. Couchot , A. Coulais , B. P. Crill , A. Curto , F. Cuttaia , L. Danese , R. D. Davies , R. J. Davis , P. de Bernardis , A. de Rosa , G. de Zotti , J. Delabrouille , J. -M. Delouis , F. -X. Desert , C. Dickinson , J. M. Diego , H. Dole , S. Donzelli , O. Dore , M. Douspis , A. Ducout , X. Dupac , G. Efstathiou , F. Elsner , T. A. Ensslin , H. K. Eriksen , E. Falgarone , J. Fergusson , F. Finelli , O. Forni , M. Frailis , A. A. Fraisse , E. Franceschi , A. Frejsel , S. Galeotta , S. Galli , K. Ganga , T. Ghosh , M. Giard , Y. Giraud-Heraud , E. Gjerlow , J. Gonzalez-Nuevo , K. M. Gorski , S. Gratton , A. Gregorio , A. Gruppuso , J. E. Gudmundsson , F. K. Hansen , D. Hanson , D. L. Harrison , G. Helou , S. Henrot-Versille , C. Hernandez-Monteagudo , D. Herranz , S. R. Hildebrandt , E. Hivon , M. Hobson , W. A. Holmes , A. Hornstrup , W. Hovest , K. M. Huffenberger , G. Hurier , A. H. Jaffe , T. R. Jaffe , W. C. Jones , M. Juvela , E. Keihanen , R. Keskitalo , T. S. Kisner , R. Kneissl , J. Knoche , M. Kunz , H. Kurki-Suonio , G. Lagache , A. Lahteenmaki , J. -M. Lamarre , A. Lasenby , M. Lattanzi , C. R. Lawrence , J. P. Leahy , R. Leonardi , J. Lesgourgues , F. Levrier , M. Liguori , P. B. Lilje , M. Linden-Vornle , M. Lopez-Caniego , P. M. Lubin , J. F. Macias-Perez , G. Maggio , D. Maino , N. Mandolesi , A. Mangilli , M. Maris , D. J. Marshall , P. G. Martin , E. Martinez-Gonzalez , S. Masi , S. Matarrese , P. McGehee , P. R. Meinhold , A. Melchiorri , L. Mendes , A. Mennella , M. Migliaccio , S. Mitra , M. -A. Miville-Deschenes , A. Moneti , L. Montier , G. Morgante , D. Mortlock , A. Moss , D. Munshi , J. A. Murphy , P. Naselsky , F. Nati , P. Natoli , C. B. Netterfield , H. U. Norgaard-Nielsen , F. Noviello , D. Novikov , I. Novikov , E. Orlando , C. A. Oxborrow , F. Paci , L. Pagano , F. Pajot , R. Paladini , D. Paoletti , B. Partridge , F. Pasian , G. Patanchon , T. J. Pearson , M. Peel , O. Perdereau , L. Perotto , F. Perrotta , V. Pettorino , F. Piacentini , M. Piat , E. Pierpaoli , D. Pietrobon , S. Plaszczynski , E. Pointecouteau , G. Polenta , G. W. Pratt , G. Prezeau , S. Prunet , J. -L. Puget , J. P. Rachen , W. T. Reach , R. Rebolo , M. Reinecke , M. Remazeilles , C. Renault , A. Renzi , I. Ristorcelli , G. Rocha , C. Rosset , M. Rossetti , G. Roudier , J. A. Rubino-Martin , B. Rusholme , M. Sandri , D. Santos , M. Savelainen , G. Savini , D. Scott , M. D. Seiffert , E. P. S. Shellard , L. D. Spencer , V. Stolyarov , R. Stompor , A. W. Strong , R. Sudiwala , R. Sunyaev , D. Sutton , A. -S. Suur-Uski , J. -F. Sygnet , J. A. Tauber , L. Terenzi , L. Toffolatti , M. Tomasi , M. Tristram , M. Tucci , J. Tuovinen , G. Umana , L. Valenziano , J. Valiviita , B. Van Tent , M. Vidal , P. Vielva , F. Villa , L. A. Wade , B. D. Wandelt , R. Watson , I. K. Wehus , A. Wilkinson , D. Yvon , A. Zacchei , A. Zonca

The kernel matrix used in kernel methods encodes all the information required for solving complex nonlinear problems defined on data representations in the input space using simple, but implicitly defined, solutions. Spectral analysis on…

Machine Learning · Computer Science 2020-10-26 Alexandros Iosifidis

The present paper is devoted to the evaluation of energy detection based spectrum sensing over different multipath fading and shadowing conditions. This is realized by means of a unified and versatile approach that is based on the…

Rapid and reliable detection and identification of unknown chemical substances is critical to homeland security. It is challenging to identify chemical components from a wide range of explosives. There are two key steps involved. One is a…

Numerical Analysis · Mathematics 2011-10-10 Y. Sun , J. Xin

This work proposes a component based model for the raw ultrasound signals acquired by the transducer elements. Based on this approach, before undergoing the standard digital processing chain, every sampled raw signal is first decomposed…

Information Theory · Computer Science 2018-06-15 Yael Yankelevsky , Zvi Friedman , Arie Feuer

We propose a new method to recover global information about a network of interconnected dynamical systems based on observations made at a small number (possibly one) of its nodes. In contrast to classical identification of full graph…

Dynamical Systems · Mathematics 2016-10-18 A. Mauroy , J. Hendrickx

[Abridged] An increasing number of astronomical instruments (on Earth and space-based) provide hyperspectral images, that is three-dimensional data cubes with two spatial dimensions and one spectral dimension. The intrinsic limitation in…

Instrumentation and Methods for Astrophysics · Physics 2021-03-17 Axel Boulais , Olivier Berné , Guillaume Faury , Yannick Deville

This paper introduces a novel approach for automated estimation of plasma temperature and density using emission spectroscopy, integrating Bayesian inference with sophisticated physical models. We provide an in-depth examination of Bayesian…

Plasma Physics · Physics 2023-12-21 Todd A. Oliver , Craig Michoski , Samuel Langendorf , Andrew LaJoie

We propose a new model-free feature screening method based on energy distances for ultrahigh-dimensional binary classification problems. With a high probability, the proposed method retains only relevant features after discarding all the…

Methodology · Statistics 2023-05-19 Sarbojit Roy , Soham Sarkar , Subhajit Dutta , Anil K. Ghosh

WMAP data when combined with ancillary data on free-free, synchrotron and dust allow an improved understanding of the spectrum of emission from each of these components. Here we examine the sky variation at intermediate and high latitudes…

Cosmology and Nongalactic Astrophysics · Physics 2013-09-27 Tuhin Ghosh , A. J. Banday , Tess Jaffe , Clive Dickinson , Rod Davies , Richard Davis , Krzysztof Gorski

In these proceedings, we discuss the extraction, in WMAP 5 year data, of a clean CMB map, of foreground emission (dominated by emission of the interstellar medium of our galaxy), and of the tiny signal from Sunyaev Zel'dovich effect in the…

Cosmology and Nongalactic Astrophysics · Physics 2010-06-29 Jacques Delabrouille

Recent advances in detectors and computer science have enabled the acquisition and the processing of multidimensional datasets, in particular in the field of spectral imaging. Benefiting from these new developments, earth scientists try to…

Materials Science · Physics 2012-06-04 Nicolas Dobigeon , Nathalie Brun

A novel approach to study transmission through waveguides in terms of optical streamlines is presented. This theoretical framework combines the computational performance of beam propagation methods with the possibility to monitor the…

Optics · Physics 2012-04-12 A. S. Sanz , J. Campos-Martinez , S. Miret-Artes

Thermal distribution functions can only be of the Fermi-Dirac or Bose-Einstein types, whereas distorted spectra encompass any possible deviations from these shapes. It is fruitful to devise parametrizations of these distortions with only a…

High Energy Physics - Phenomenology · Physics 2026-03-27 Gabriela Barenboim , Julien Froustey , Cyril Pitrou , Héctor Sanchis

Spectral unmixing is an important task in hyperspectral image processing for separating the mixed spectral data pertaining to various materials observed individual pixels. Recently, nonlinear spectral unmixing has received particular…

Image and Video Processing · Electrical Eng. & Systems 2021-10-07 Min Zhao , Mou Wang , Jie Chen , Susanto Rahardja

Light echoes give us a unique perspective on the nature of supernovae and non-terminal stellar explosions. Spectroscopy of light echoes can reveal details on the kinematics of the ejecta, probe asymmetry, and reveal details on its…

The direct detection of exoplanets with high-contrast instruments can be boosted with high spectral resolution. For integral field spectrographs yielding hyperspectral data, this means that the field of view consists of diffracted starlight…

Instrumentation and Methods for Astrophysics · Physics 2021-06-09 Julien Rameau , Jocelyn Chanussot , Alexis Carlotti , Mickael Bonnefoy , Philippe Delorme

Optical spectroscopy is an important and widely used technique, for instance, to characterize new materials and to identify unknown compounds. Spectra are typically reported as a function of the wavelength of light, yet the information…

Optics · Physics 2026-05-06 Erik F. Woering , Richard Hildner

We present the first diffusion-based framework that can learn an unknown distribution using only highly-corrupted samples. This problem arises in scientific applications where access to uncorrupted samples is impossible or expensive to…

Machine Learning · Computer Science 2023-05-31 Giannis Daras , Kulin Shah , Yuval Dagan , Aravind Gollakota , Alexandros G. Dimakis , Adam Klivans