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A next generation atmospheric Cherenkov observatory is described based on the Whipple Observatory $\gamma$-ray telescope. A total of nine such imaging telescopes will be deployed in an array that will permit the maximum versatility and give…

Gamma-ray astronomy from hundreds of GeV to PeV is confined to ground-based experiments that detect air showers induced by $\gamma$-rays entering Earth's atmosphere. While particle detector arrays feature huge detection areas, accurately…

Instrumentation and Methods for Astrophysics · Physics 2026-04-13 Markus Pirke , Youngwan Son , Jonas Glombitza , Martin Schneider , Ian James Watson , Christopher van Eldik

We present a maximum likelihood (ML) algorithm that is fast enough to detect gamma-ray transients in real time on low-performance processors often used for space applications. We validate the routine with simulations and find that, relative…

High Energy Astrophysical Phenomena · Physics 2023-08-09 Matthew Kerr , Wade Duvall , Neil Johnson , Richard Woolf , J. Eric Grove , Hannah Kim

Estimation of quantum states is one of the most important steps in any quantum information processing experiment. A naive reconstruction of the density matrix from experimental measurements can often give density matrices which are not…

Quantum Physics · Physics 2016-08-24 Harpreet Singh , Arvind , Kavita Dorai

VERITAS is a new, major ground-based gamma-ray observatory designed to significantly advance our understanding of extreme astrophysical processes in the universe. The observatory comprises seven large-aperture (12m diameter) Cherenkov…

Astrophysics · Physics 2019-08-14 Rene A. Ong

Computed Tomography is one of the efficient and vital modalities of non-destructive techniques (NDT). Various factors influence the CT reconstruction result, including limited projection data, detector electronics optimization, background…

Image and Video Processing · Electrical Eng. & Systems 2022-05-31 Kajal Kumari , Mayank Goswami

Large-scale structure distorts the images of background galaxies, which allows one to measure directly the projected distribution of dark matter in the universe and determine its power spectrum. Here we address the question of how to…

Astrophysics · Physics 2009-10-30 Uros Seljak

This paper considers the problem of networks reconstruction from heterogeneous data using a Gaussian Graphical Mixture Model (GGMM). It is well known that parameter estimation in this context is challenging due to large numbers of variables…

Machine Learning · Statistics 2013-10-08 Anani Lotsi , Ernst Wit

Many standard optimization methods for segmentation and reconstruction compute ML model estimates for appearance or geometry of segments, e.g. Zhu-Yuille 1996, Torr 1998, Chan-Vese 2001, GrabCut 2004, Delong et al. 2012. We observe that the…

Computer Vision and Pattern Recognition · Computer Science 2015-05-04 Yuri Boykov , Hossam Isack , Carl Olsson , Ismail Ben Ayed

Modern technology for producing extremely bright and coherent X-ray laser pulses provides the possibility to acquire a large number of diffraction patterns from individual biological nanoparticles, including proteins, viruses, and DNA.…

Methodology · Statistics 2018-07-11 Stefan Engblom , Carl Nettelblad , Jing Liu

Objective: Breast tissue is mainly a mixture of adipose and fibro-glandular tissue. Cancer risk and risk of undetected breast cancer increases with the amount of glandular tissue in the breast. Therefore, radiologists must report the total…

Medical Physics · Physics 2023-10-12 Bryce J. Smith , Joyoni Dey , Lacey Medlock , David Solis , Krystal Kirby

The ultimate goal of many image-based modeling systems is to render photo-realistic novel views of a scene without visible artifacts. Existing evaluation metrics and benchmarks focus mainly on the geometric accuracy of the reconstructed…

Computer Vision and Pattern Recognition · Computer Science 2016-01-27 Michael Waechter , Mate Beljan , Simon Fuhrmann , Nils Moehrle , Johannes Kopf , Michael Goesele

Imaging distributions of radioactive sources plays a substantial role in nuclear medicine as well as in monitoring nuclear waste and its deposit. Coded Aperture Imaging has been proposed as an alternative to parallel or pinhole collimators,…

Medical Physics · Physics 2023-01-12 T. Meißner , V. Rozhkov , J. Hesser , W. Nahm , N. Loew

The field of gamma ray astronomy relies heavily on the statistical analysis of data. Because of the paucity of data, and the often large errors associated with detecting gamma rays, analysis and interpretation of the data require…

Astrophysics · Physics 2007-05-23 W. F. Tompkins

Based on the binary time series data of social infection dynamics, we propose a general framework to reconstruct 2-simplex complexes with two-body and three-body interactions by combining the maximum likelihood estimation in statistical…

Physics and Society · Physics 2023-07-25 Kaiwei Liu , Xing Lv , Fei Gao , Jiang Zhang

A track finding algorithm has been developed for reconstruction of e+e- pairs. It combines the information of the electromagnetic calorimeter with the information provided by the Tracker. Results on reconstruction efficiency of converted…

Data Analysis, Statistics and Probability · Physics 2017-08-23 Nancy Marinelli

Gamma-Ray Bursts (GRBs), observed at high-z, are probes of the evolution of the Universe and can be used as cosmological tools. Thus, we need correlations with small dispersion among key parameters. To reduce such a dispersion, we mitigate…

Standard dual-energy computed tomography (CT) uses two different X-ray energies to obtain energy-dependent tissue attenuation information to allow quantitative material decomposition. The combined use of dual-energy CT and positron emission…

Medical Physics · Physics 2020-12-30 Guobao Wang

This paper presents the Planck 2015 likelihoods, statistical descriptions of the 2-point correlations of CMB data, using the hybrid approach employed previously: pixel-based at $\ell<30$ and a Gaussian approximation to the distribution of…

Cosmology and Nongalactic Astrophysics · Physics 2016-09-21 Planck Collaboration , N. Aghanim , M. Arnaud , M. Ashdown , J. Aumont , C. Baccigalupi , A. J. Banday , R. B. Barreiro , J. G. Bartlett , N. Bartolo , E. Battaner , K. Benabed , A. Benoît , A. Benoit-Lévy , 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 , H. C. Chiang , P. R. Christensen , D. L. Clements , L. P. L. Colombo , C. Combet , 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 , F. -X. Désert , E. Di Valentino , C. Dickinson , J. M. Diego , K. Dolag , H. Dole , S. Donzelli , O. Doré , M. Douspis , A. Ducout , J. Dunkley , X. Dupac , G. Efstathiou , F. Elsner , T. A. Enßlin , H. K. Eriksen , J. Fergusson , F. Finelli , O. Forni , M. Frailis , A. A. Fraisse , E. Franceschi , A. Frejsel , S. Galeotta , S. Galli , K. Ganga , C. Gauthier , M. Gerbino , M. Giard , E. Gjerløw , J. González-Nuevo , K. M. Górski , S. Gratton , A. Gregorio , A. Gruppuso , J. E. Gudmundsson , J. Hamann , F. K. Hansen , D. L. Harrison , G. Helou , S. Henrot-Versillé , C. Hernández-Monteagudo , D. Herranz , S. R. Hildebrandt , E. Hivon , W. A. Holmes , A. Hornstrup , K. M. Huffenberger , G. Hurier , A. H. Jaffe , W. C. Jones , M. Juvela , E. Keihänen , R. Keskitalo , K. Kiiveri , J. Knoche , L. Knox , M. Kunz , H. Kurki-Suonio , G. Lagache , A. Lähteenmäki , J. -M. Lamarre , A. Lasenby , M. Lattanzi , C. R. Lawrence , M. Le Jeune , R. Leonardi , J. Lesgourgues , F. Levrier , A. Lewis , M. Liguori , P. B. Lilje , M. Lilley , M. Linden-Vørnle , V. Lindholm , M. López-Caniego , J. F. Macías-Pérez , B. Maffei , G. Maggio , D. Maino , N. Mandolesi , A. Mangilli , M. Maris , P. G. Martin , E. Martínez-González , S. Masi , S. Matarrese , P. R. Meinhold , A. Melchiorri , M. Migliaccio , M. Millea , S. Mitra , M. -A. Miville-Deschênes , A. Moneti , L. Montier , G. Morgante , D. Mortlock , S. Mottet , D. Munshi , J. A. Murphy , A. Narimani , P. Naselsky , F. Nati , P. Natoli , F. Noviello , D. Novikov , I. Novikov , C. A. Oxborrow , F. Paci , L. Pagano , F. Pajot , D. Paoletti , B. Partridge , F. Pasian , G. Patanchon , T. J. Pearson , O. Perdereau , L. Perotto , V. Pettorino , F. Piacentini , M. Piat , E. Pierpaoli , D. Pietrobon , S. Plaszczynski , E. Pointecouteau , G. Polenta , N. Ponthieu , G. W. Pratt , S. Prunet , J. -L. Puget , J. P. Rachen , M. Reinecke , M. Remazeilles , C. Renault , A. Renzi , I. Ristorcelli , G. Rocha , M. Rossetti , G. Roudier , B. Rouillé d'Orfeuil , J. A. Rubiño-Martín , B. Rusholme , L. Salvati , M. Sandri , D. Santos , M. Savelainen , G. Savini , D. Scott , P. Serra , L. D. Spencer , M. Spinelli , V. Stolyarov , R. Stompor , R. Sunyaev , D. Sutton , A. -S. Suur-Uski , J. -F. Sygnet , J. A. Tauber , L. Terenzi , L. Toffolatti , M. Tomasi , M. Tristram , T. Trombetti , M. Tucci , J. Tuovinen , G. Umana , L. Valenziano , J. Valiviita , F. Van Tent , P. Vielva , F. Villa , L. A. Wade , B. D. Wandelt , I. K. Wehus , D. Yvon , A. Zacchei , A. Zonca

Maximum likelihood estimators are proposed for the parameters and the densities in a semiparametric density ratio model in which the nonparametric baseline density is approximated by the Bernstein polynomial model. The EM algorithm is used…

Methodology · Statistics 2021-03-02 Zhong Guan