检索结果-内蒙古大学图书馆

arXiv 2018年

作者： Maier-Hein, Lena Eisenmann, Matthias Reinke, Annika Onogur, Sinan Stankovic, Marko Scholz, Patrick Arbel, Tal Bogunovic, Hrvoje Bradley, Andrew P. Carass, Aaron Carolin Feldmann Frangi, Alejandro F. Ful, Peter M. van Ginneken, Bram Hanbury, Allan Honauer, Katrin Kozubek, Michal Landman, Bennett A. Marz, Keno Maier, Oskar Maier-Hein, Klaus Menze, Bjoern H. Müller, Henning Neher, Peter F. Niessen, Wiro Rajpoot, Nasir Sharp, Gregory C. Sirinukunwattana, Korsuk Speidel, Stefanie Stock, Christian Stoyanov, Danail Taha, Abdel Aziz van der Sommen, Fons Wang, Ching-Wei Weber, Marc-André Zheng, Guoyan Jannin, Pierre Kopp-Schneider, Annette Heidelberg Germany Centre for Intelligent Machines McGill University MontrealQC Canada Christian Doppler Laboratory for Ophthalmic Image Analysis Department of Ophthalmology Medical University Vienna Vienna Austria Science and Engineering Faculty Queensland University of Technology BrisbaneQLD Australia Department of Electrical and Computer Engineering Department of Computer Science Johns Hopkins University Baltimore United States CISTIB Centre for Computational Imaging and Simulation Technologies in Biomedicine University of Sheffield Sheffield United Kingdom Department of Radiology and Nuclear Medicine Medical Image Analysis Radboud University Center Nijmegen Netherlands Institute of Information Systems Engineering TU Wien Vienna Austria Heidelberg University Heidelberg Germany Centre for Biomedical Image Analysis Masaryk University Brno Czech Republic Electrical Engineering Vanderbilt University NashvilleTN United States Institute of Medical Informatics Universität zu Lübeck Lübeck Germany Heidelberg Germany Institute for Advanced Studies Department of Informatics Technical University of Munich Munich Germany Information System Institute HES-SO Sierre Switzerland Departments of Radiology Nuclear Medicine and Medical Informatics Erasmus MC Rotterdam Netherlands Department of Computer Science University of Warwick Coventry United Kingdom Department of Radiation Oncology Massachusetts General Hospital BostonMA United States Institute of Biomedical Engineering University of Oxford Oxford United Kingdom National Center for Tumor Diseases Dresden Dresden Germany Heidelberg Germany Department of Computer Science University College London London United Kingdom Data Science Studio Research Studios Austria FG Vienna Austria Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands AIExplore NTUST Center of Computer Vision and Medical Imaging Graduate Institute of Biomedical Engineering National Ta

International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of common practices related to the organization of challenges has not yet been performed. In this paper, we present a comprehensive analysis of biomedical image analysis challenges conducted up to now. We demonstrate the importance of challenges and show that the lack of quality control has critical consequences. First, reproducibility and interpretation of the results is often hampered as only a fraction of relevant information is typically provided. Second, the rank of an algorithm is generally not robust to a number of variables such as the test data used for validation, the ranking scheme applied and the observers that make the reference annotations. To overcome these problems, we recommend best practice guidelines and define open research questions to be addressed in the future. Copyright © 2018, The Authors. All rights reserved.

关键词： Quality control

来源：评论

学校读者我要写书评

暂无评论

Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026

引用

The Lancet Global Health 2023年第3期11卷 e385-e413页

作者： Micah, Angela E. Bhangdia, Kayleigh Cogswell, Ian E. Lasher, Dylan Lidral-Porter, Brendan Maddison, Emilie R. Nguyen, Trang Nhu Ngoc Patel, Nishali Pedroza, Paola Solorio, Juan Stutzman, Hayley Tsakalos, Golsum Wang, Yifeng Warriner, Wesley Zhao, Yingxi Zlavog, Bianca S. Abbafati, Cristiana Abbas, Jaffar Abbasi-Kangevari, Mohsen Abbasi-Kangevari, Zeinab Abdelmasseh, Michael Abdulah, Deldar Morad Abedi, Aidin Abegaz, Kedir Hussein Abhilash, E.S. Aboagye, Richard Gyan Abolhassani, Hassan Abrigo, Michael R.M. Abubaker Ali, Hiwa Abu-Gharbieh, Eman Adem, Mohammed Hussien Afzal, Muhammad Sohail Ahmadi, Ali Ahmed, Haroon Ahmed Rashid, Tarik Aji, Budi Akbarialiabad, Hossein Akelew, Yibeltal Al Hamad, Hanadi Alam, Khurshid Alanezi, Fahad Mashhour Alanzi, Turki M. Al-Hanawi, Mohammed Khaled Alhassan, Robert Kaba Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Ameyaw, Edward Kwabena Amini-Rarani, Mostafa Amu, Hubert Ancuceanu, Robert Andrei, Tudorel Anwar, Sumadi Lukman Appiah, Francis Aqeel, Muhammad Arabloo, Jalal Arab-Zozani, Morteza Aravkin, Aleksandr Y. Aremu, Olatunde Aruleba, Raphael Taiwo Athari, Seyyed Shamsadin Avila-Burgos, Leticia Ayanore, Martin Amogre Azari, Samad Baig, Atif Amin Bantie, Abere Tilahun Barrow, Amadou Baskaran, Pritish Basu, Sanjay Batiha, Abdul-Monim Mohammad Baune, Bernhard T. Berezvai, Zombor Bhardwaj, Nikha Bhardwaj, Pankaj Bhaskar, Sonu Boachie, Micheal Kofi Bodolica, Virginia Botelho, João Silva Botelho Braithwaite, Dejana Breitborde, Nicholas J.K. Busse, Reinhard Cahuana-Hurtado, Lucero Catalá-López, Ferrán Chansa, Collins Charan, Jaykaran Chattu, Vijay Kumar Chen, Simiao Chukwu, Isaac Sunday Dadras, Omid Dandona, Lalit Dandona, Rakhi Dargahi, Abdollah Debela, Sisay Abebe Denova-Gutiérrez, Edgar Desye, Belay Dharmaratne, Samath Dhamminda Diao, Nancy Doan, Linh Phuong Dodangeh, Milad dos Santos, Wendel Mombaque Doshmangir, Leila Dube, John Eini, Ebrahim El Sayed Zaki, Maysaa El Tantawi, Maha Enyew, Daniel Berhanie Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Applied Mathematics University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Nuffield Department of Medicine University of Oxford Oxford United Kingdom Department of Juridical and Economic Studies La Sapienza University Rome Italy Antai College of Economics Shanghai Jiao Tong University Shanghai China Non-communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Children’s Medical Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Tehran Heart Center Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Tehran University of Medical Sciences Tehran Iran National Institute for Health Research Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Department of Cardiology Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Center Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Department of Neurology Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Epidemiology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Health Economics and Statistics Shahid Beheshti University of Medical Sciences Tehran Iran Department of Neurosurgery Shahid Beheshti University of Medical Sciences Tehran Iran Ophthalmic R

Background: The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic;characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic;and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods: In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings: In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95% uncertainty interval [UI] 9·1–9·3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7·3 trillion (95% UI 7·2–7·4) in 2019;293·7 times the $24·8 billion (95% UI 24·3–25·3) spent by low-income countries in 2019. That same year, $43·1 billion in development assistance was provided

关键词：

来源：评论

学校读者我要写书评

暂无评论

ALMAGAL IV. Morphological comparison of molecular and thermal dust emission using the histogram of oriented gradients (HOG) method

arXiv

引用

arXiv 2025年

作者： Mininni, C. Molinari, S. Soler, J.D. Sánchez-Monge, Á. Coletta, A. Benedettini, M. Traficante, A. Schisano, E. Elia, D. Pezzuto, S. Nucara, A. Schilke, P. Battersby, C. Ho, P.T.P. Beltrán, M.T. Beuther, H. Fuller, G.A. Jones, B. Klessen, R.S. Zhang, Q. Walch, S. Tang, Y. Ahmadi, A. Allande, J. Avison, A. Brogan, C.L. De Angelis, F. Fontani, F. Hennebelle, P. Hunter, T.R. Johnston, K.G. Koch, P. Kuiper, R. Law, C.-Y. Lis, D.C. Liu, S. Liu, T. Liu, S.-Y. Moscadelli, L. Möller, T. Rigby, A.J. Rygl, K.L.J. Sanhueza, P. Testi, L. Su, Y.-N. van der Tak, F.F.S. Wells, M.R.A. Bronfman, L. Zhang, T. Zinnecker, H. INAF-Istituto di Astrofisica e Planetologia Spaziale Via Fosso del Cavaliere 100 RomaI-00133 Italy CSIC Campus UAB Carrer de Can Magrans s/n Bellaterra BarcelonaE-08193 Spain Castelldefels BarcelonaE-08860 Spain Dipartimento di Fisica Sapienza Università di Roma Piazzale Aldo Moro 2 RomeI-00185 Italy Dipartimento di Fisica Università di Roma Tor Vergata Via della Ricerca Scientifica 1 RomaI-00133 Italy I. Physikalisches Institut Universität zu Köln Zülpicher Str. 77 KölnD-50937 Germany University of Connecticut Department of Physics 2152 Hillside Road Unit 3046 StorrsCT06269 United States Institute of Astronomy and Astrophysics Academia Sinica 11F of ASMAB AS/NTU No. 1 Sec. 4 Roosevelt Road Taipei10617 Taiwan East Asian Observatory 660 N. A’ohoku Hawaii HiloHI96720 United States INAF-Osservatorio Astrofisico di Arcetri Largo E. Fermi 5 FirenzeI-50125 Italy Max Planck Institute for Astronomy Königstuhl 17 HeidelbergD-69117 Germany Jodrell Bank Centre for Astrophysics The University of Manchester Oxford Road ManchesterM13 9PL United Kingdom Universität Heidelberg Zentrum für Astronomie Institut für Theoretische Astrophysik Heidelberg Germany Universität Heidelberg Interdisziplinäres Zentrum für Wissenschaftliches Rechnen Heidelberg Germany Center for Astrophysics Harvard & Smithsonian 60 Garden St CambridgeMA02138 United States Radcliffe Institute for Advanced Studies Harvard University 10 Garden Street CambridgeMA02138 United States Center for Data and Simulation Science University of Cologne Germany ASTRON Netherlands Institute for Radio Astronomy Oude Hoogeveensedijk 4 Dwingeloo7991 PD Netherlands Dipartimento di Fisica e Astronomia Università degli Studi di Firenze Via G. Sansone 1 Sesto Fiorentino FirenzeI-50019 Italy SKA Observatory Jodrell Bank Lower Withington MacclesfieldSK11 9FT United Kingdom UK ALMA Regional Centre Node M13 9PL United Kingdom National Radio Astronomy Observatory 520 Edgemont Road Ch

Context. The study of molecular line emission is crucial to unveil the kinematics and the physical conditions of gas in star-forming regions. We utilize data from the ALMAGAL survey which provides an unprecedentedly large statistical sample of high-mass star-forming clumps that helps to remove bias and reduce noise (e.g. due to source peculiarities, selection or environmental effects) to determine how well individual molecular species trace continuum emission. Aims. Our aim is to quantify the reliability of using individual molecular transitions to derive physical properties of the bulk of the H2 gas, looking at morphological correlations in their overall integrated molecular line emission with the cold dust. For this study we selected transitions of H2CO, CH3OH, DCN, HC3N, CH3CN, CH3OCHO, SO, and SiO and compared them with the 1.38 mm dust continuum emission at different spatial scales in the ALMAGAL sample. We included two transitions of H2CO to understand the validity of the results depending on the excitation condition of the selected transition of a molecular specie. The ALMAGAL project observed more than 1000 candidate high-mass star-forming clumps in ALMA Band 6 at a spatial resolution down to 1000 au. A total of 1013 targets have been analyzed in the present paper, covering all evolutionary stages of the high-mass star-formation process and different conditions of clump fragmentation. Methods. We used, for the first time on a large statistical sample, the method of the histogram of oriented gradients (HOG) implemented in the tool astroHOG to compare the morphology of integrated line emission with maps of the 1.38 mm dust continuum emission. For each clump, we defined two masks: one that covers the extended more diffuse continuum emission and a smaller one that contains only the compact sources. We select these two masks to study if and how the correlation among the selected molecules changes with the spatial scale of the emission, from extended more diffuse

关键词： Giant stars

来源：评论

学校读者我要写书评

暂无评论

Generating summarized preview for education resource based on exploring and comparing GUIs 28

Generating summarized preview for education resource based o...

引用

28th International Conference on software engineering and Knowledge engineering, SEKE 2016

作者： Ma, Chao Chen, Xiangping Rao, Yongsheng Lin, Mouguang School of Data and Computer Science Sun Yat-sen University Guangzhou China Research Institute Sun Yat-sen University in Shenzhen Shenzhen China Institute of Advanced Technology Sun Yat-sen University Guangzhou China School of Computer Science and Educational Software Guangzhou University Guangzhou China Institute of Advanced Technology National Engineering Research Center of Digital Life Sun Yat-sen University Guangzhou China

ISBN: (纸本)189170639X

Compared to traditional education resource, Interactive Education Resource (IER) includes dynamic content to interact with users in order to enhance comprehension. The contents of IERs are relatively complex because of its dynamic feature. Exploring IERs and understanding its content during resource search become time-consuming. In this paper, we propose a preview generation approach based on automated software testing and image processing. Our approach first analyzes IERs to collect interactive elements and the event list. Based on the interaction related information, our approach simulates user actions and record snapshots step by step. Our approach compares snapshots to generate an image including the basic content, interaction region and dynamic contents. The image is used as the overall preview and the animation of snapshots collected during simulation is used as detail preview of the IER. In the experiment, we evaluate the completeness, correctness, and comprehension of the preview. The experiment result shows that the preview can be used to provide most information in the resource correctly and easy to understand. Our approach can save time for users in understanding the IERs. Copyright © 2016 by KSI Research Inc. and Knowledge Systems Institute Graduate School.

关键词： Image processing

来源：评论

学校读者我要写书评

暂无评论

Publisher Correction: Global estimates on the number of people blind or visually impaired by cataract: a meta-analysis from 2000 to 2020

引用

Eye (London, England) 2024年第11期38卷 2229-2231页

作者： Konrad Pesudovs Hugh R. Taylor Tabassom Sedighi Rupert R. A. Bourne Shahina Pardhan Van Charles Lansingh John H. Kempen Ian Tapply Arthur G. Fernandes Maria Vittoria Cicinelli Alessandro Arrigo Nicolas Leveziel Serge Resnikoff Seth Flaxman Mukkharram M. Bikbov Tasanee Braithwaite Alain Bron Ching-Yu Cheng Monte A. Del Monte Joshua R. Ehrlich Leon B. Ellwein David Friedman João M. Furtado Gus Gazzard Ronnie George M. Elizabeth Hartnett Jost B. Jonas Rim Kahloun Moncef Khairallah Rohit C. Khanna Janet Leasher Julie-Anne Little Vinay Nangia Michal Nowak Tunde Peto Pradeep Ramulu Fotis Topouzis Mitiadis Tsilimbaris Ya Xing Wang Ningli Wang Paul Svitil Briant Theo Vos Katrin Burkart Kaleb Coberly Xiaochen Dai Stephen S. Lim Tomislav Mestrovic Ali H. Mokdad Christopher J. L. Murray Jaimie D. Steinmetz Awoke Misganaw Yohannes Habtegiorgis Abate Mohammad Abdollahi Mozhan Abdollahi Ayele Mamo Abebe Olumide Abiodun Richard Gyan Aboagye Woldu Aberhe Abrha Hasan Abualruz Hiwa Abubaker Ali Eman Abu-Gharbieh Salahdein Aburuz Tadele Girum Girum Adal Mesafint Molla Adane Isaac Yeboah Addo Qorinah Estiningtyas Sakilah Adnani Muhammad Sohail Afzal Muhammad Umair Shahin Aghamiri Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Ali Ahmadi Siamak Sabour Ayman Ahmed Haroon Ahmed Ahmad Samir Alfaar Abid Ali Syed Shujait Shujait Ali Awais Altaf Hubert Amu Emmanuel Manu Sofia Androudi Rodrigo Anguita Abhishek Anil Rimple Jeet Kaur Muhammad Aaqib Shamim Saeid Anvari Anayochukwu Edward Anyasodor Francis Appiah Jalal Arabloo Haleh Ayatollahi Mosab Arafat Damelash Areda Reza Arefnezhad Brhane Berhe Aregawi Akeza Awealom Asgedom Tahira Ashraf Seyyed Shamsadin Athari Bantalem Tilaye Tilaye Atinafu Birhan Tsegaw Taye Maha Moh’d Wahbi Atout Alok Atreya Ahmed Y. Azzam Hassan Babamohamadi Sara Bagherieh Yogesh Bahurupi Atif Amin Baig Shumaila Nargus Biswajit Banik Mainak Bardhan Saurav Basu Kavita Batra Nebiyou Simegnew Bayileyegn Fatemeh Bazvand Addisu Shunu Beyene Awoke Masrie Asrat Derese Devidas S. Bhagat Akshaya Srikanth Bhagavathula Pankaj Bh Medicine & Health University of New South Wales Sydney NSW Australia School of Optometry and Vision Science University of New South Wales Sydney NSW Australia School of Population and Global Health University of Melbourne Carlton VIC Australia Vision and Eye Research Institute Anglia Ruskin University Cambridge UK HelpMeSee Instituto Mexicano de Oftalmologia Santiago de Querétaro Mexico University of Miami Gables FL USA University of Utah Salt Lake City UT USA Chief Medical Office HelpMeSee New York NY USA Mexican Institute of Ophthalmology Queretaro Mexico Department of Ophthalmology Massachusetts Eye and Ear/Shepens Eye Research Institute/Harvard Medical School Boston MA USA Eye Unit MyungSung Christian Medical Center (MCM) Comprehensive Specialized Hospital and MyungSun Medical College Addis Ababa Ethiopia Department of Ophthalmology Addis Ababa University Addis Ababa Ethiopia Sight for Souls Bellevue WA USA Department of Ophthalmology Harvard University Boston MA USA Eye Unit MyungSung Medical College Addis Ababa Ethiopia Addenbrooke’s Hospital Cambridge UK Department of Ophthalmology Cambridge University Hospitals Cambridge UK Federal University of Sao Paolo Sao Paolo SP Brazil University of Calgary Calgary AB Canada Department of Ophthalmology and Visual Sciences Federal University of São Paulo Sao Paulo Brazil School of Medicine Vita-Salute San Raffaele University Milan Italy Department of Ophthalmology IRCCS San Raffaele Scientific Institute Milan Italy Department of Ophthalmology San Raffaele Scientific Institute Milano Italy IRCCS San Raffaele Scientific Institute Vita-Salute University Milan Italy Scientific Institute San Raffaele Hospital Vita-Salute University Milan Italy University of Poitiers Poitiers France CHU de Poitiers Poitiers France Ophthalmology Department CHU de Poitiers (Poitiers University Hospital) Poitiers France Unité 1084 National Institute of Health and Medical Research (INSERM) Poitiers France

来源：评论

学校读者我要写书评

暂无评论

Euclid Quick data Release (Q1). The Strong Lensing Discovery Engine C - Finding lenses with machine learning

arXiv

引用

arXiv 2025年

作者： Lines, N.E.P. Collett, T.E. Walmsley, M. Rojas, K. Li, T. Leuzzi, L. Manjón-García, A. Vincken, S.H. Wilde, J. Holloway, P. Verma, A. Metcalf, R.B. Andika, I.T. Melo, A. Melchior, M. Domínguez Sánchez, H. Díaz-Sánchez, A. Acevedo Barroso, J.A. Clément, B. Krawczyk, C. Pearce-Casey, R. Serjeant, S. Courbin, F. Despali, G. Gavazzi, R. Schuldt, S. Degaudenzi, H. Ecker, L.R. Enzi, W.J.R. Finner, K. Galan, A. Giocoli, C. Hogg, N.B. Jahnke, K. Kruk, S. Mahler, G. More, A. Nagam, B.C. Pearson, J. Sainz de Murieta, A. Scarlata, C. Sluse, D. Sonnenfeld, A. Spiniello, C. Thai, T.T. Tortora, C. Ulivi, L. Weisenbach, L. Zumalacarregui, M. Aghanim, N. Altieri, B. Amara, A. Andreon, S. Auricchio, N. Aussel, H. Baccigalupi, C. Baldi, M. Balestra, A. Bardelli, S. Battaglia, P. Bender, R. Bernardeau, F. Biviano, A. Bonchi, A. Bonino, D. Branchini, E. Brescia, M. Brinchmann, J. Camera, S. Cañas-Herrera, G. Capobianco, V. Carbone, C. Cardone, V.F. Carretero, J. Casas, S. Castellano, M. Castignani, G. Cavuoti, S. Chambers, K.C. Cimatti, A. Colodro-Conde, C. Congedo, G. Conselice, C.J. Conversi, L. Copin, Y. Costille, A. Courtois, H.M. Cropper, M. Da Silva, A. De Lucia, G. Di Giorgio, A.M. Dolding, C. Dole, H. Dubath, F. Duncan, C.A.J. Dupac, X. Escoffier, S. Fabricius, M. Farina, M. Farinelli, R. Faustini, F. Ferriol, S. Finelli, F. Fotopoulou, S. Frailis, M. Franceschi, E. Fumana, M. Galeotta, S. George, K. Gillard, W. Gillis, B. Gómez-Alvarez, P. Gracia-Carpio, J. Granett, B.R. Grazian, A. Grupp, F. Guzzo, L. Gwyn, S. Haugan, S.V.H. Holmes, W. Hook, I.M. Hormuth, F. Hornstrup, A. Hudelot, P. Jhabvala, M. Keihänen, E. Kermiche, S. Kiessling, A. Kubik, B. Kümmel, M. Kunz, M. Kurki-Suonio, H. Le Boulc’h, Q. Le Brun, A.M.C. Le Mignant, D. Ligori, S. Lilje, P.B. Lindholm, V. Lloro, I. Mainetti, G. Maino, D. Maiorano, E. Mansutti, O. Marcin, S. Marggraf, O. Martinelli, M. Martinet, N. Marulli, F. Massey, R. Institute of Cosmology and Gravitation University of Portsmouth PortsmouthPO1 3FX United Kingdom David A. Dunlap Department of Astronomy & Astrophysics University of Toronto 50 St George Street TorontoONM5S 3H4 Canada Jodrell Bank Centre for Astrophysics Department of Physics and Astronomy University of Manchester Oxford Road ManchesterM13 9PL United Kingdom University of Applied Sciences and Arts of Northwestern Switzerland School of Engineering Windisch5210 Switzerland Dipartimento di Fisica e Astronomia "Augusto Righi" Alma Mater Studiorum Università di Bologna via Piero Gobetti 93/2 Bologna40129 Italy INAF-Osservatorio di Astrofisica e Scienza dello Spazio di Bologna Via Piero Gobetti 93/3 Bologna40129 Italy Departamento Física Aplicada Universidad Politécnica de Cartagena Campus Muralla del Mar Murcia Cartagena30202 Spain Martí i Franquès 1 Barcelona08028 Spain Department of Physics Oxford University Keble Road OxfordOX1 3RH United Kingdom Technical University of Munich TUM School of Natural Sciences Physics Department James-Franck-Str. 1 Garching85748 Germany Max-Planck-Institut für Astrophysik Karl-Schwarzschild-Str. 1 Garching85748 Germany Instituto de Física de Cantabria Edificio Juan Jordá Avenida de los Castros Santander39005 Spain Observatoire de Sauverny Versoix1290 Switzerland Lausanne1015 Switzerland School of Physical Sciences The Open University Milton KeynesMK7 6AA United Kingdom Passeig de Lluís Companys 23 Barcelona08010 Spain INFN-Sezione di Bologna Viale Berti Pichat 6/2 Bologna40127 Italy Aix-Marseille Université CNRS CNES LAM Marseille France Institut d’Astrophysique de Paris UMR 7095 CNRS Sorbonne Université 98 bis boulevard Arago Paris75014 France Dipartimento di Fisica "Aldo Pontremoli" Università degli Studi di Milano Via Celoria 16 Milano20133 Italy INAF-IASF Milano Via Alfonso Corti 12 Milano20133 Italy Department of Astronomy University of Geneva ch. d’Ecogia 16 Versoix1290 Sw

Strong gravitational lensing has the potential to provide a powerful probe of astrophysics and cosmology, but fewer than 1000 strong lenses have been confirmed previously. With 0′′ . 16 resolution covering a third of the sky, the Euclid telescope will revolutionise strong lens finding, with 170 000 lenses forecasted to be discovered amongst its 1.5 billion galaxies. We present an analysis of the performance of five machine-learning models at finding strong gravitational lenses in the quick release of Euclid data (Q1), covering 63 deg2. The models are validated with citizen scientists and expert visual inspection. We focus on the best performing network: a fine-tuned version of the Zoobot pretrained model, originally trained to classify galaxy morphologies in heterogeneous astronomical imaging surveys. Of the one million Q1 objects that Zoobot was tasked to find strong lenses within, the top 1000 ranked objects contained 122 grade A lenses (almost certain lenses), and 41 grade B lenses (probable lenses). A deeper search with the five networks combined with visual inspection discovered 250 (247) grade A (B) lenses, of which 224 (182) are ranked in the top 20 000 by Zoobot. When extrapolated to the full Euclid survey, the highest ranked one million images will contain 75 000 grade A or B strong gravitational lenses. © 2025, CC BY.

关键词： Cosmology

来源：评论

学校读者我要写书评

暂无评论

Euclid: Optimising tomographic redshift binning for 3×2pt power spectrum constraints on dark energy

arXiv

引用

arXiv 2025年

作者： Wong, J.H.W. Brown, M.L. Duncan, C.A.J. Amara, A. Andreon, S. Baccigalupi, C. Baldi, M. Bardelli, S. Bonino, D. Branchini, E. Brescia, M. Brinchmann, J. Caillat, A. Camera, S. Capobianco, V. Carbone, C. Carretero, J. Casas, S. Castellano, M. Castignani, G. Cavuoti, S. Cimatti, A. Colodro-Conde, C. Congedo, G. Conselice, C.J. Conversi, L. Copin, Y. Courbin, F. Courtois, H.M. Da Silva, A. Degaudenzi, H. De Lucia, G. Di Giorgio, A.M. Dinis, J. Dubath, F. Dupac, X. Dusini, S. Farina, M. Farrens, S. Faustini, F. Ferriol, S. Frailis, M. Franceschi, E. Galeotta, S. George, K. Gillard, W. Gillis, B. Giocoli, C. Grazian, A. Grupp, F. Guzzo, L. Haugan, S.V.H. Holmes, W. Hook, I. Hormuth, F. Hornstrup, A. Ilić, S. Jahnke, K. Jhabvala, M. Keihänen, E. Kermiche, S. Kiessling, A. Kubik, B. Kunz, M. Kurki-Suonio, H. Ligori, S. Lilje, P.B. Lindholm, V. Lloro, I. Mainetti, G. Maiorano, E. Mansutti, O. Marggraf, O. Markovic, K. Martinelli, M. Martinet, N. Marulli, F. Massey, R. Medinaceli, E. Mei, S. Melchior, M. Mellier, Y. Meneghetti, M. Merlin, E. Meylan, G. Moresco, M. Moscardini, L. Neissner, C. Niemi, S.-M. Padilla, C. Paltani, S. Pasian, F. Pedersen, K. Pettorino, V. Pires, S. Polenta, G. Poncet, M. Popa, L.A. Raison, F. Renzi, A. Rhodes, J. Riccio, G. Romelli, E. Roncarelli, M. Rossetti, E. Saglia, R. Sakr, Z. Sánchez, A.G. Sapone, D. Sartoris, B. Schneider, P. Schrabback, T. Secroun, A. Seidel, G. Serrano, S. Sirignano, C. Sirri, G. Stanco, L. Steinwagner, J. Tallada-Crespí, P. Taylor, A.N. Tereno, I. Toledo-Moreo, R. Torradeflot, F. Tutusaus, I. Valenziano, L. Vassallo, T. Kleijn, G. Verdoes Veropalumbo, A. Wang, Y. Weller, J. Zamorani, G. Zucca, E. Burigana, C. Calabrese, M. Pezzotta, A. Scottez, V. Mancini, A. Spurio Viel, M. Jodrell Bank Centre for Astrophysics Department of Physics and Astronomy University of Manchester Oxford Road ManchesterM13 9PL United Kingdom School of Mathematics and Physics University of Surrey Guild-ford SurreyGU2 7XH United Kingdom INAF-Osservatorio Astronomico di Brera Via Brera 28 Milano20122 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy INAF-Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 Trieste34143 Italy INFN Sezione di Trieste Via Valerio 2 TS Trieste34127 Italy SISSA International School for Advanced Studies Via Bonomea 265 TS Trieste34136 Italy Dipartimento di Fisica e Astronomia Università di Bologna Via Gobetti 93/2 Bologna40129 Italy INAF-Osservatorio di Astrofisica e Scienza dello Spazio di Bologna Via Piero Gobetti 93/3 Bologna40129 Italy INFN-Sezione di Bologna Viale Berti Pichat 6/2 Bologna40127 Italy INAF-Osservatorio Astrofisico di Torino Via Osservatorio 20 TO Pino Torinese10025 Italy Dipartimento di Fisica Università di Genova Via Dodecaneso 33 Genova16146 Italy INFN-Sezione di Genova Via Dodecaneso 33 Genova16146 Italy Department of Physics "E. Pancini" University Federico II Via Cinthia 6 Napoli80126 Italy INAF-Osservatorio Astronomico di Capodimonte Via Moiariello 16 Napoli80131 Italy INFN section of Naples Via Cinthia 6 Napoli80126 Italy Instituto de Astrofísica e Ciências do Espaço Universidade do Porto CAUP Rua das Estrelas PortoPT4150-762 Portugal Faculdade de Ciências Universidade do Porto Rua do Campo de Alegre Porto4150-007 Portugal Aix-Marseille Université CNRS CNES LAM Marseille France Dipartimento di Fisica Università degli Studi di Torino Via P. Giuria 1 Torino10125 Italy INFN-Sezione di Torino Via P. Giuria 1 Torino10125 Italy INAF-IASF Milano Via Alfonso Corti 12 Milano20133 Italy Avenida Complutense 40 Madrid28040 Spain Port d’Informació Científica Campus UAB C. Albareda s/n Bellaterra Barcelona08193 S

The tomographic approach to analyse the 3×2pt signal involves dividing the observed galaxy sample into a configuration of redshift bins. We present a simulation-based method to explore the optimum tomographic binning strategy for Euclid, focusing on the expected configuration of its first major data release (DR1). To do this, we 1) simulate a Euclid-like observation and generate mock shear catalogues from multiple realisations of the 3×2pt fields on the sky, and 2) measure the 3×2pt Pseudo-C power spectra for a given tomographic configuration and derive the constraints that they place on the standard dark energy equation of state parameters (w0, wa). For a simulation including Gaussian-distributed photometric redshift uncertainty and shape noise under a ΛCDM cosmology, we find that bins equipopulated with galaxies yield the best constraints on (w0, wa) for an analysis of the full 3×2pt signal, or the angular clustering component only. For the cosmic shear component, the optimum (w0, wa) constraints are achieved by bins equally spaced in fiducial comoving distance. However, the advantage with respect to alternative binning choices is only a few percent in the size of the 1 σ (w0, wa) contour, and we conclude that the cosmic shear is relatively insensitive to the binning methodology. We find that the information gain extracted on (w0, wa) for any 3×2pt component starts to saturate at 7–8 bins. Any marginal gains resulting from a greater number of bins is likely to be limited by additional uncertainties present in a real measurement, and the increasing demand for accuracy of the covariance matrix. Finally, we consider a 5% contamination from catastrophic photometric redshift outliers and find that, if these errors are not mitigated in the analysis, the bias induced in the 3×2pt signal for 10 equipopulated bins results in dark energy constraints that are inconsistent with the fiducial ΛCDM cosmology at > 5 σ. © 2025, CC BY.

关键词： Dark energy

来源：评论

学校读者我要写书评

暂无评论

Euclid preparation L. Calibration of the halo linear bias in Λ(ν)CDM cosmologies

arXiv

引用

arXiv 2024年

作者： Castro, T. Fumagalli, A. Angulo, R.E. Bocquet, S. Borgani, S. Costanzi, M. Dakin, J. Dolag, K. Monaco, P. Saro, A. Sefusatti, E. Aghanim, N. Amendola, L. Andreon, S. Baccigalupi, C. Baldi, M. Bodendorf, C. Bonino, D. Branchini, E. Brescia, M. Caillat, A. Camera, S. Capobianco, V. Carbone, C. Carretero, J. Casas, S. Castellano, M. Castignani, G. Cavuoti, S. Cimatti, A. Colodro-Conde, C. Congedo, G. Conselice, C.J. Conversi, L. Copin, Y. Costille, A. Courbin, F. Courtois, H.M. Da Silva, A. Degaudenzi, H. De Lucia, G. Di Giorgio, A.M. Douspis, M. Dupac, X. Dusini, S. Farina, M. Farrens, S. Ferriol, S. Fosalba, P. Frailis, M. Franceschi, E. Fumana, M. Galeotta, S. Gillis, B. Giocoli, C. Gómez-Alvarez, P. Grazian, A. Grupp, F. Guzzo, L. Haugan, S.V.H. Holmes, W. Hormuth, F. Hornstrup, A. Ilić, S. Jahnke, K. Jhabvala, M. Joachimi, B. Keihänen, E. Kermiche, S. Kiessling, A. Kilbinger, M. Kubik, B. Kunz, M. Kurki-Suonio, H. Lilje, P.B. Lindholm, V. Lloro, I. Maiorano, E. Mansutti, O. Marggraf, O. Markovic, K. Martinelli, M. Martinet, N. Marulli, F. Massey, R. Maurogordato, S. Medinaceli, E. Melchior, M. Mellier, Y. Meneghetti, M. Merlin, E. Meylan, G. Moscardini, L. Munari, E. Niemi, S.-M. Padilla, C. Paltani, S. Pasian, F. Pedersen, K. Percival, W.J. Pettorino, V. Pires, S. Polenta, G. Poncet, M. Popa, L.A. Pozzetti, L. Raison, F. Renzi, A. Riccio, G. Romelli, E. Roncarelli, M. Saglia, R. Sakr, Z. Salvignol, J.-C. Sánchez, A.G. Sapone, D. Sartoris, B. Schirmer, M. Secroun, A. Serrano, S. Sirignano, C. Sirri, G. Stanco, L. Steinwagner, J. Tallada-Crespí, P. Taylor, A.N. Tereno, I. Toledo-Moreo, R. Torradeflot, F. Tutusaus, I. Valenziano, L. Vassallo, T. Kleijn, G. Verdoes Wang, Y. Weller, J. Zacchei, A. Zamorani, G. Zucca, E. Biviano, A. Bolzonella, M. Bozzo, E. Burigana, C. Calabrese, M. Di Ferdinando, D. Vigo, J.A. Escartin Finelli, F. Gracia-Carpio, J. Matthew, S. Mauri, N. Pezzotta, A. INAF-Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 Trieste34143 Italy INFN Sezione di Trieste Via Valerio 2 TS Trieste34127 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy ICSC - Centro Nazionale di Ricerca in High Performance Computing Big Data e Quantum Computing Via Magnanelli 2 Bologna Italy Ludwig-Maximilians-University Schellingstrasse 4 Munich80799 Germany Paseo Manuel de Lardizabal 4 Guipuzkoa Donostia-San Sebastián20018 Spain IKERBASQUE Basque Foundation for Science Bilbao48013 Spain Universitäts-Sternwarte München Fakultät für Physik Ludwig-Maximilians-Universität München Scheinerstrasse 1 München81679 Germany Dipartimento di Fisica - Sezione di Astronomia Università di Trieste Via Tiepolo 11 Trieste34131 Italy Department of Astrophysics University of Zurich Winterthurerstrasse 190 Zurich8057 Switzerland Université Paris-Saclay CNRS Institut d’astrophysique spatiale Orsay91405 France Institut für Theoretische Physik University of Heidelberg Philosophenweg 16 Heidelberg69120 Germany INAF-Osservatorio Astronomico di Brera Via Brera 28 Milano20122 Italy SISSA International School for Advanced Studies Via Bonomea 265 TS Trieste34136 Italy Dipartimento di Fisica e Astronomia Università di Bologna Via Gobetti 93/2 Bologna40129 Italy INAF-Osservatorio di Astrofisica e Scienza dello Spazio di Bologna Via Piero Gobetti 93/3 Bologna40129 Italy INFN-Sezione di Bologna Viale Berti Pichat 6/2 Bologna40127 Italy Max Planck Institute for Extraterrestrial Physics Giessenbachstr. 1 Garching85748 Germany Pino Torinese10025 Italy Dipartimento di Fisica Università di Genova Via Dodecaneso 33 Genova16146 Italy INFN-Sezione di Genova Via Dodecaneso 33 Genova16146 Italy Department of Physics "E. Pancini" University Federico II Via Cinthia 6 Napoli80126 Italy INAF-Osservatorio Astronomico di Capodimonte Via Moiariello 16 Napoli80131 Italy INFN section of Naples Vi

The Euclid mission, designed to map the geometry of the dark Universe, presents an unprecedented opportunity for advancing our understanding of the cosmos through its photometric galaxy cluster survey. Central to this endeavor is the accurate calibration of the mass- and redshift-dependent halo bias (HB), which is the focus of this paper. We enhance the precision of HB predictions, which is crucial for deriving cosmological constraints from the clustering of galaxy clusters. Our study is based on the peak-background split (PBS) model linked to the halo mass function (HMF), and extends it with a parametric correction to precisely align with results from an extended set of N-body simulations carried out with the OpenGADGET3 code. Employing simulations with fixed and paired initial conditions, we meticulously analyze the matter-halo cross-spectrum and model its covariance using a large number of mock catalogs generated with Lagrangian Perturbation Theory simulations with the PINOCCHIO code. This ensures a comprehensive understanding of the uncertainties in our HB calibration. Our findings indicate that the calibrated HB model is remarkably resilient against changes in cosmological parameters including those involving massive neutrinos. The robustness and adaptability of our calibrated HB model provide an important contribution to the cosmological exploitation of the cluster surveys to be provided by the Euclid mission. This study highlights the necessity of continuously refining the calibration of cosmological tools like the HB to match the advancing quality of observational data. As we project the impact of our calibrated model on cosmological constraints, we find that, given the sensitivity of the Euclid survey, a miscalibration of the HB could introduce biases in cluster cosmology analyses. Our work fills this critical gap, ensuring the HB calibration matches the expected precision of the Euclid survey. Copyright © 2024, The Authors. All rights reserved.

关键词： Cosmology

来源：评论

学校读者我要写书评

暂无评论

Euclid: The rb-M* relation as a function of redshift. I. The 5×109M☉ black hole in NGC 1272

arXiv

引用

arXiv 2024年

作者： Saglia, R. Mehrgan, K. de Nicola, S. Thomas, J. Kluge, M. Bender, R. Delley, D. Erwin, P. Fabricius, M. Neureiter, B. Andreon, S. Baccigalupi, C. Baldi, M. Bardelli, S. Bonino, D. Branchini, E. Brescia, M. Brinchmann, J. Caillat, A. Camera, S. Capobianco, V. Carbone, C. Carretero, J. Casas, S. Castellano, M. Castignani, G. Cavuoti, S. Cimatti, A. Colodro-Conde, C. Congedo, G. Conselice, C.J. Conversi, L. Copin, Y. Courbin, F. Courtois, H.M. Degaudenzi, H. De Lucia, G. Dinis, J. Dupac, X. Dusini, S. Farina, M. Farrens, S. Faustini, F. Ferriol, S. Fourmanoit, N. Frailis, M. Franceschi, E. Fumana, M. Galeotta, S. George, K. Gillis, B. Giocoli, C. Grazian, A. Grupp, F. Guzzo, L. Haugan, S.V.H. Hoar, J. Holmes, W. Hormuth, F. Hornstrup, A. Jahnke, K. Jhabvala, M. Keihänen, E. Kermiche, S. Kiessling, A. Kilbinger, M. Kubik, B. Kümmel, M. Kunz, M. Kurki-Suonio, H. Le Mignant, D. Ligori, S. Lilje, P.B. Lindholm, V. Lloro, I. Mainetti, G. Maiorano, E. Mansutti, O. Marggraf, O. Markovic, K. Martinelli, M. Martinet, N. Marulli, F. Massey, R. Medinaceli, E. Melchior, M. Mellier, Y. Meneghetti, M. Merlin, E. Meylan, G. Moresco, M. Moscardini, L. Munari, E. Nakajima, R. Neissner, C. Nichol, R.C. Niemi, S.-M. Nightingale, J.W. Padilla, C. Paltani, S. Pasian, F. Pedersen, K. Percival, W.J. Pettorino, V. Pires, S. Polenta, G. Poncet, M. Popa, L.A. Pozzetti, L. Raison, F. Rebolo, R. Renzi, A. Rhodes, J. Riccio, G. Romelli, E. Roncarelli, M. Rossetti, E. Sakr, Z. Sánchez, A.G. Sapone, D. Sartoris, B. Schirmer, M. Schneider, P. Schrabback, T. Secroun, A. Seiffert, M. Serrano, S. Sirignano, C. Sirri, G. Skottfelt, J. Stanco, L. Steinwagner, J. Tallada-Crespí, P. Tavagnacco, D. Taylor, A.N. Tereno, I. Toledo-Moreo, R. Torradeflot, F. Tutusaus, I. Valenziano, L. Vassallo, T. Kleijn, G. Verdoes Wang, Y. Weller, J. Zamorani, G. Zucca, E. Burigana, C. Scottez, V. Ferrarese, L. Lusso, E. Scott, D. Universitäts-Sternwarte München Fakultät für Physik Ludwig-Maximilians-Universität München Scheinerstrasse 1 München81679 Germany Max Planck Institute for Extraterrestrial Physics Giessenbachstr. 1 Garching85748 Germany Ludwig-Maximilians-University Schellingstrasse 4 Munich80799 Germany INAF-Osservatorio Astronomico di Brera Via Brera 28 Milano20122 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy INAF-Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 Trieste34143 Italy INFN Sezione di Trieste Via Valerio 2 TS Trieste34127 Italy SISSA International School for Advanced Studies Via Bonomea 265 TS Trieste34136 Italy Dipartimento di Fisica e Astronomia Università di Bologna Via Gobetti 93/2 Bologna40129 Italy INAF-Osservatorio di Astrofisica e Scienza dello Spazio di Bologna Via Piero Gobetti 93/3 Bologna40129 Italy INFN-Sezione di Bologna Viale Berti Pichat 6/2 Bologna40127 Italy Pino Torinese10025 Italy Dipartimento di Fisica Università di Genova Via Dodecaneso 33 Genova16146 Italy INFN-Sezione di Genova Via Dodecaneso 33 Genova16146 Italy Department of Physics E. Pancini University Federico II Via Cinthia 6 Napoli80126 Italy INAF-Osservatorio Astronomico di Capodimonte Via Moiariello 16 Napoli80131 Italy INFN section of Naples Via Cinthia 6 Napoli80126 Italy Instituto de Astrofísica e Ciências do Espaço Universidade do Porto CAUP Rua das Estrelas PortoPT4150-762 Portugal Faculdade de Ciências Universidade do Porto Rua do Campo de Alegre Porto4150-007 Portugal Aix-Marseille Université CNRS CNES LAM Marseille France Dipartimento di Fisica Università degli Studi di Torino Via P. Giuria 1 Torino10125 Italy INFN-Sezione di Torino Via P. Giuria 1 Torino10125 Italy INAF-IASF Milano Via Alfonso Corti 12 Milano20133 Italy Avenida Complutense 40 Madrid28040 Spain Port d’Informació Científica Campus UAB C. Albareda s/n Bellaterra Barcelona08193 Spain RWTH

Core ellipticals, massive early-type galaxies with almost constant inner surface brightness profiles, are the results of dry mergers. During these events a binary black hole is formed, destroying the original cuspy central regions of the merging objects and scattering stars that are not on tangential orbits. The size of the emerging core correlates with the mass of the finally merged black hole. Therefore, the determination of the size of the core of massive early type galaxies provides key insights not only on the mass of the black hole, but also on the origin and evolution of these objects. In this work we report the first Euclid-based dynamical mass determination of a supermassive black hole. We perform it by studying the centre of NGC 1272, the second most luminous elliptical galaxy in the Perseus cluster, combining the Euclid VIS photometry coming from the Early Release Observations of the Perseus cluster with VIRUS spectroscopic observations at the Hobby-Eberly Telescope. The core of NGC 1272 is detected on the Euclid VIS image. Its size is 1″. 29±0″. 07 or 0.45 kpc, determined by fitting PSF-convolved core-Sérsic and Nuker-law functions. We deproject the surface brightness profile of the galaxy, finding that the galaxy is axisymmetric and nearly spherical. The two-dimensional stellar kinematics of the galaxy is measured from the VIRUS spectra by deriving optimally regularized non-parametric line-of-sight velocity distributions. Dynamical models of the galaxy are constructed using our axisymmetric and triaxial Schwarzschild codes. We measure a black hole mass of (5 ± 3) × 109M☉, in line with the expectation from the MBH-rb correlation, but eight times larger than predicted by the MBH-σ correlation (at 1.8σ significance). The core size, rather than the velocity dispersion, allows one to select galaxies harboring the most massive black holes. The spatial resolution, wide area coverage, and depth of the Euclid (Wide and Deep) surveys allow us to find cores of pas

关键词： Luminance

来源：评论

学校读者我要写书评

暂无评论

Euclid. IV. The NISP Calibration Unit

arXiv

引用

arXiv 2024年

作者： Hormuth, F. Jahnke, K. Schirmer, M. Lee, C.G.-Y. Scott, T. Barbier, R. Ferriol, S. Gillard, W. Grupp, F. Holmes, R. Holmes, W. Kubik, B. Macias-Perez, J. Laurent, M. Marpaud, J. Marton, M. Medinaceli, E. Morgante, G. Toledo-Moreo, R. Trifoglio, M. Rix, Hans-Walter Seiffert, M. Stassi, P. Wachter, S. Gutierrez, C.M. Vescovi, C. Amara, A. Andreon, S. Auricchio, N. Baccigalupi, C. Baldi, M. Balestra, A. Bardelli, S. Battaglia, P. Bender, R. Bonino, D. Branchini, E. Brescia, M. Brinchmann, J. Camera, S. Capobianco, V. Carbone, C. Cardone, V.F. Carretero, J. Casas, R. Casas, S. Castellano, M. Castignani, G. Cavuoti, S. Cimatti, A. Colodro-Conde, C. Congedo, G. Conselice, C.J. Conversi, L. Copin, Y. Corcione, L. Courbin, F. Courtois, H.M. Da Silva, A. Degaudenzi, H. De Lucia, G. Dinis, J. Douspis, M. Dubath, F. Ducret, F. Dupac, X. Dusini, S. Fabricius, M. Farina, M. Farrens, S. Faustini, F. Fotopoulou, S. Fourmanoit, N. Frailis, M. Franceschi, E. Franzetti, P. Fumana, M. Galeotta, S. Garilli, B. George, K. Gillis, B. Giocoli, C. Grazian, A. Guzzo, L. Haugan, S.V.H. Hoekstra, H. Hook, I. Hornstrup, A. Hudelot, P. Jhabvala, M. Keihänen, E. Kermiche, S. Kiessling, A. Kilbinger, M. Kitching, T. Kohley, R. Kümmel, M. Kunz, M. Kurki-Suonio, H. Le Mignant, D. Ligori, S. Lilje, P.B. Lindholm, V. Lloro, I. Mainetti, G. Maiorano, E. Mansutti, O. Marcin, S. Marggraf, O. Markovic, K. Martinelli, M. Martinet, N. Marulli, F. Massey, R. Maurogordato, S. McCracken, H.J. Mei, S. Melchior, M. Mellier, Y. Meneghetti, M. Merlin, E. Meylan, G. Mohr, J.J. Moresco, M. Morris, P.W. Moscardini, L. Munari, E. Nakajima, R. Neissner, C. Nichol, R.C. Niemi, S.-M. Nightingale, J.W. Paltani, S. Pasian, F. Pedersen, K. Percival, W.J. Pettorino, V. Pires, S. Polenta, G. Poncet, M. Popa, L.A. Rebolo, R. Renzi, A. Rhodes, J. Riccio, G. Romelli, E. Roncarelli, M. Rossetti, E. Rusholme, B. Saglia, R. Sakr, Z. Sapone, D. Sartoris, B. Felix Hormuth Engineering Goethestr. 17 Leimen69181 Germany Max-Planck-Institut für Astronomie Königstuhl 17 Heidelberg69117 Germany von Hoerner & Sulger GmbH Schlossplatz 8 Schwetzingen68723 Germany Eumetsat Allee 1 DarmstadtD-64295 Germany Université Claude Bernard Lyon 1 CNRS IN2P3 IP2I Lyon UMR 5822 VilleurbanneF-69100 France Aix-Marseille Université CNRS IN2P3 CPPM Marseille France Max Planck Institute for Extraterrestrial Physics Giessenbachstr. 1 Garching85748 Germany Universitäts-Sternwarte München Fakultät für Physik Ludwig-Maximilians-Universität München Scheinerstrasse 1 München81679 Germany Surrey Satellite Technology Limited Tycho House 20 Stephenson Road Surrey Research Park GuildfordGU2 7YE United Kingdom Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive PasadenaCA91109 United States Univ. Grenoble Alpes CNRS Grenoble INP LPSC-IN2P3 53 Avenue des Martyrs Grenoble38000 France Aix-Marseille Université CNRS CNES LAM Marseille France INAF-Osservatorio di Astrofisica e Scienza dello Spazio di Bologna Via Piero Gobetti 93/3 Bologna40129 Italy Universidad Politécnica de Cartagena Departamento de Electrónica y Tecnología de Computadoras Plaza del Hospital 1 Cartagena30202 Spain Carnegie Observatories PasadenaCA91101 United States Tenerife La Laguna38200 Spain School of Mathematics and Physics University of Surrey Guildford Surrey GU2 7XH United Kingdom INAF-Osservatorio Astronomico di Brera Via Brera 28 Milano20122 Italy SISSA International School for Advanced Studies Via Bonomea 265 TS Trieste34136 Italy INAF-Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 Trieste34143 Italy INFN Sezione di Trieste Via Valerio 2 TS Trieste34127 Italy IFPU Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy Dipartimento di Fisica e Astronomia Università di Bologna Via Gobetti 93/2 Bologna40129 Italy INFN-Sezione di Bologna Viale Berti Pi

The near-infrared calibration unit (NI-CU) on board Euclid’s Near-Infrared Spectrometer and Photometer (NISP) is the first astronomical calibration lamp based on light-emitting diodes (LEDs) to be operated in space. Euclid is a mission in ESA’s Cosmic Vision 2015–2025 framework to explore the dark universe and provide a next-level characterisation of the nature of gravitation, dark matter, and dark energy. Calibrating photometric and spectrometric measurements of galaxies to better than 1.5% accuracy in a survey homogeneously mapping ∼ 14 000 deg2 of extragalactic sky requires a very detailed characterisation of near-infrared (NIR) detector properties as well as constant monitoring of them in flight. To cover two of the main contributions – relative pixel-to-pixel sensitivity and non-linearity characteristics – and to support other calibration activities, NI-CU was designed to provide spatially approximately homogeneous (−1 pixel−1 to > 1500 ph s−1 pixel−1. For this functionality, NI-CU is based on LEDs. We describe the rationale behind the decision and design process, the challenges in sourcing the right LEDs, and the qualification process and lessons learned. We also provide a description of the completed NI-CU, its capabilities, and performance as well as its limits. NI-CU has been integrated into NISP and the Euclid satellite, and since Euclid’s launch in July 2023, it has started supporting survey operations. © 2024, CC BY.

关键词： Photometers

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：