检索结果-内蒙古大学图书馆

Spatially-resolved spectro-photometric SED Modeling of NGC 253’s Central Molecular Zone I. Studying the star formation in extragalactic giant molecular clouds

arXiv

引用

arXiv 2025年

作者： Humire, Pedro K. Dey, Subhrata Ronconi, Tommaso Sasse, Victor H. Fernandes, Roberto Cid Martín, Sergio Donevski, Darko Malek, Katarzyna Fernández-Ontiveros, Juan A. Song, Yiqing Hamed, Mahmoud Mangum, Jeffrey G. Henkel, Christian Rivilla, Víctor M. Colzi, Laura Harada, N. Demarco, Ricardo Goyal, Arti Meier, David S. Panda, Swayamtrupta Krabbe, Ângela C. Yan, Yaoting Lopes, Amanda R. Sakamoto, K. Muller, S. Tanaka, K. Yoshimura, Y. Nakanishi, K. Kanaan, Antonio Ribeiro, Tiago Schoenell, William de Oliveira, Claudia Mendes Departamento de Astronomia Instituto de Astronomia Geofísica e Ciências Atmosféricas da USP Cidade Universitária SP São Paulo05508-090 Brazil Astronomical Observatory The Jagiellonian University Orla 171 Kraków30-244 Poland National Center for Nuclear Research ul. Pasteura 7 Warsaw02-093 Poland Via Bonomea 265 TriesteIT-34136 Italy Via Beirut 2 TriesteIT-34151 Italy Via Gobetti 93/3 BolognaI-40127 Italy ICSC – Centro Nazionale di Ricerca in High Performance Computing Big Data e Quantum Computing Via Magnanelli 2 Bologna Italy Universidade Federal de Santa Catarina Campus Universitário Reitor João David Ferreira Lima SC Florianópolis88040-900 Brazil European Southern Observatory Alonso de Córdova 3107 Vitacura Santiago763-0355 Chile Joint ALMA Observatory Alonso de Córdova 3107 Vitacura Santiago763-0355 Chile Plaza San Juan 1 TeruelE–44001 Spain CSIC-INTA Carretera de Ajalvir km 4 Torrejón de Ardoz Madrid28850 Spain National Radio Astronomy Observatory 520 Edgemont Road CharlottesvilleVA22903-2475 United States Max-Planck-Institut für Radioastronomie Auf-dem-Hügel 69 Bonn53121 Germany Xinjiang Astronomical Observatory Chinese Academy of Sciences Urumqi830011 China National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Institute of Astronomy and Astrophysics Academia Sinica 11F of AS/NTU Astronomy-Mathematics Building No.1 Sec. 4 Roosevelt Rd Taipei106319 Taiwan 2-21-1 Osawa Mitaka Tokyo181-1855 Japan Institute of Astrophysics Facultad de Ciencias Exactas Universidad Andrés Bello Sede Concepción Talcahuano Chile New Mexico Institute of Mining and Technology 801 Leroy Place SocorroNM87801 United States International Gemini Observatory NSF NOIRLab Casilla 603 La Serena Chile Instituto de Astrofísica de La Plata CONICET-UNLP Paseo del Bosque s/n B1900FWA Argentina Department of Space Earth and Environment Chalmers University of Technology Onsala Space Observatory OnsalaSE-4

Context. Studying the interstellar medium in nearby starbursts is essential for gaining insights into the physical mechanisms driving these extreme objects, thought to be analogs of young, primeval, star-forming galaxies. This task is now feasible due to deep spectro-photometric data enabled by rapid advancements in ground- and space-based facilities. To fully leverage this wealth of information, extracting insights from the spectral line properties, and the spectral energy distribution (SED) is imperative. Aims. This study aims to produce and analyze the physical properties of the first spatially-resolved multi-wavelength SED of an extragalactic source that covers six decades in frequency (from near-ultraviolet to centimeter wavelengths) at an angular resolution of 3′′ which corresponds to linear scale of ∼51 pc at the distance of NGC 253. We focus on the central molecular zone (CMZ) of this starburst galaxy, which contains giant molecular clouds (GMCs) responsible for half of the galaxy’s star formation. Methods. We retrieve archival data from optical to centimeter wavelengths, covering six decades of spectral range. We compute SEDs to fit the observations using the GalaPy code and confronting results with the CIGALE code for validation. We also employ starlight library to analyze the stellar optical spectra of the GMCs. Results. Our results reveal significant differences between central and external GMCs in terms of stellar and dust masses, star formation rates (SFRs), and bolometric luminosities, to provide a few. We have obtained tight relations between monochromatic stellar tracers and star-forming conditions obtained from panchromatic emission. We find that the best SFR tracers are radio continuum bands at 33 GHz, radio recombination lines (RRLs), and the total infrared (IR) luminosity range (LIR;8–1000µm) as well as the IR emission at 60µm. The emission line diagnostics based on the BPT and WHAN diagrams suggest that the nuclear region of NGC 253 exhibits sh

关键词： Optical emission spectroscopy

来源：评论

学校读者我要写书评

暂无评论

The GAPS program at TNG XLVII: The unusual formation history of V1298 Tau

arXiv

引用

arXiv 2023年

作者： Turrini, D. Marzari, F. Polychroni, D. Claudi, R. Desidera, S. Mesa, D. Pinamonti, M. Sozzetti, A. Mascareño, A. Suárez Damasso, M. Benatti, S. Malavolta, L. Micela, G. Zinzi, A. Béjar, V.J.S. Biazzo, K. bignamini, A. Bonavita, M. Borsa, F. Del Burgo, C. Chauvin, G. Delorme, P. Hernández, J.I. González Gratton, R. Hagelberg, J. Janson, M. Langlois, M. Lanza, A.F. Lazzoni, C. Lodieu, N. Maggio, A. Mancini, L. Molinari, E. Molinaro, M. Murgas, F. Nardiello, D. Inaf - Osservatorio Astrofisico di Torino via Osservatorio 20 Pino TorineseI-10025 Italy Icsc National Research Centre for High Performance Computing Big Data and Quantum Computing Via Magnanelli 2 Casalecchio di RenoI-40033 Italy Inaf - Istituto di Astrofisica e Planetologia Spaziali via Fosso del Cavaliere 100 RomaI-00133 Italy Dipartimento di Fisica e Astronomia Università di Padova Via Marzolo 8 PadovaI-35121 Italy Inaf - Osservatorio Astronomico di Padova Vicolo dell'Osservatorio 5 PadovaI-35122 Italy Inaf - Osservatorio Astronomico di Trieste Via G. B. Tiepolo 11 TriesteI-34143 Italy Inaf - Osservatorio Astronomico di Palermo Piazza del Parlamento 1 Palermo90134 Italy Space Science Data Center - Asi Via del Politecnico snc Roma00133 Italy Instituto de Astrofísica de Canarias Tenerife La LagunaE-38200 Spain Universidad de la Laguna Dept. Astrofísica Tenerife La LagunaE-38206 Spain Inaf - Osservatorio Astronomico di Roma Via Frascati 33 Monte Porzio CatoneI-00040 Italy School of Physical Sciences The Open University Walton Hall Milton KeynesMK7 6AA United Kingdom Supa Institute for Astronomy University of Edinburgh Blackford Hill EdinburghEH9 3HJ United Kingdom Inaf - Osservatorio Astronomico di Brera Via E. Bianchi 46 MerateI-23087 Italy Instituto Nacional de Astrofísica Óptica y Electrónica Luis Enrique Erro 1 Sta. Ma. Tonantzintla Puebla Mexico Universitè Côte d'Azur Observatoire de la Côte d'Azur Cnrs Laboratoire Lagrange Nice France Universitè Grenoble Alpes Cnrs Ipag Grenoble38000 France Geneva Observatory University of Geneva Chemin Pegasi 51 Versoix1290 Switzerland Department of Astronomy Stockholm University AlbaNova University Center Stockholm10691 Sweden Cral Umr 5574 Cnrs Université de Lyon Ecole Normale Supérieure de Lyon 46 allée d'Italie Lyon69364 Cedex 07 France Inaf - Osservatorio Astrofisico di Catania Via Santa Sofia 78 Catania95123 Italy Department of Physics and Astronomy University of Ex

Context. Observational data from space and ground-based campaigns reveal that the 10-30 Ma old V1298 Tau star hosts a compact and massive system of four planets. Mass estimates are available for the two outer giant planets and point to unexpectedly high densities for their young ages. Aims. We investigate the formation of these two outermost giant planets, V1298 Tau b and e, and the present dynamical state of V1298 Tau's global architecture to shed light on the history of this young and peculiar extrasolar system. Methods. We perform detailed N-body simulations to explore the link between the densities of V1298 Tau b and e and their migration and accretion of planetesimals within the native circumstellar disk. We combine N-body simulations and the normalized angular momentum deficit (NAMD) analysis of the architecture to characterize V1298 Tau's dynamical state and connect it to the formation history of the system. We search for outer planetary companions to constrain V1298 Tau's planetary architecture and the extension of its primordial circumstellar disk. Results. The high densities of V1298 Tau b and e suggest they formed quite distant from their host star, likely beyond the CO2snowline. The higher nominal density of V1298 Tau e suggests it formed farther out than V1298 Tau b. The current architecture of V1298 Tau is not characterized by resonant chains. Planet-planet scattering with an outer giant planet is the most likely cause for the instability, but our search for outer companions using SPHERE and GAIA observations can currently exclude only the presence of planets more massive than 2 MJ. Conclusions. The most plausible scenario for V1298 Tau's formation is that the system is formed by convergent migration and resonant trapping of planets born in a compact and plausibly massive disk. The migration of V1298 Tau b and e leaves in its wake a dynamically excited protoplanetary disk and naturally creates the conditions for the later breaking of the resonant chain

关键词： Stars

来源：评论

学校读者我要写书评

暂无评论

Balanced distribution adaptation for transfer learning

arXiv

引用

arXiv 2018年

作者： Wang, Jindong Chen, Yiqiang Hao, Shuji Feng, Wenjie Shenk, Zhiqi Beijing Key Laboratory of Mobile Computing and Pervasive Device CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Institute of High Performance Computing A*STAR School of Computer Science and Engineering Nanyang Technological University Singapore Singapore

Transfer learning has achieved promising results by leveraging knowledge from the source domain to annotate the target domain which has few or none labels. Existing methods often seek to minimize the distribution divergence between domains, such as the marginal distribution, the conditional distribution or both. However, these two distances are often treated equally in existing algorithms, which will result in poor performance in real applications. Moreover, existing methods usually assume that the dataset is balanced, which also limits their performances on imbalanced tasks that are quite common in real problems. To tackle the distribution adaptation problem, in this paper, we propose a novel transfer learning approach, named as Balanced Distribution Adaptation (BDA), which can adaptively leverage the importance of the marginal and conditional distribution discrepancies, and several existing methods can be treated as special cases of BDA. Based on BDA, we also propose a novel Weighted Balanced Distribution Adaptation (W-BDA) algorithm to tackle the class imbalance issue in transfer learning. W-BDA not only considers the distribution adaptation between domains but also adaptively changes the weight of each class. To evaluate the proposed methods, we conduct extensive experiments on several transfer learning tasks, which demonstrate the effectiveness of our proposed algorithms over several state-of-the-art methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Stochastic modified equations and dynamics of stochastic gradient algorithms I: Mathematical foundations

arXiv

引用

arXiv 2018年

作者： Li, Qianxiao Tai, Cheng Weinan, E. Institute of High Performance Computing Agency for Science Technology and Research 1 Fusionopolis Way Connexis North138632 Singapore Beijing Institute of Big Data Research Peking University Beijing100080 China Princeton University PrincetonNJ08544 United States

We develop the mathematical foundations of the stochastic modified equations (SME) framework for analyzing the dynamics of stochastic gradient algorithms, where the latter is approximated by a class of stochastic differential equations with small noise parameters. We prove that this approximation can be understood mathematically as an weak approximation, which leads to a number of precise and useful results on the approximations of stochastic gradient descent (SGD), momentum SGD and stochastic Nesterov's accelerated gradient method in the general setting of stochastic objectives. We also demonstrate through explicit calculations that this continuous-time approach can uncover important analytical insights into the stochastic gradient algorithms under consideration that may not be easy to obtain in a purely discrete-time setting.65K10, 60H10 Copyright © 2018, The Authors. All rights reserved.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

Multi-Thread Concurrent Compression Algorithm for Genomic big data

Multi-Thread Concurrent Compression Algorithm for Genomic Bi...

引用

IEEE International Conference on Parallel and Distributed computing, Applications and Technologies (PDCAT)

作者： Yimu Ji Shuai Chen Haichang Yao Houzhi Fang Kui Li Shangdong Liu Zhengyuan Xie Kairui Wang School of Computer Science Nanjing University of Posts and Telecommunications Institute of High Performance Computing and Big Data Nanjing University of Posts and Telecommunications Nanjing Center of HPC China Jiangsu HPC and Intelligent Processing Engineer Research Center Nanjing China School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science Nanjing University of Posts and Telecommunications School of Computer and Software Nanjing Institute of Industry Technology Nanjing China University of Toronto Toronto Canada BSc Mathematics with Finance University of Liverpool Liverpool United Kingdom

ISBN: (数字)9781728126166

ISBN: (纸本)9781728126173

At present, there are many excellent genome compression algorithms with high genome compression ratio. However, there is a lack of highly efficient compression algorithms for simultaneous compression of a large number of genomes. This manuscript presents an algorithm, which is called FastLNGC, for simultaneous compression of a large amount of genome data based on multi-thread concurrency. This algorithm is based on the LNGC (Large Number of Genomes Compressor) algorithm, and adopts multi-thread technology to achieve concurrent processing of genome data compression. A large number of experiments show that FastLNGC has better performance on compression of a large number of genes. The source code of FastLNGC is available at https://***/APandaThief/FastLNGC.

关键词： Bioinformatics Genomics Compression algorithms Instruction sets Telecommunications Computer science Concurrent computing

来源：评论

学校读者我要写书评

暂无评论

A mean-field optimal control formulation of deep learning

arXiv

引用

arXiv 2018年

作者： Weinan, E. Han, Jiequn Li, Qianxiao Princeton University PrincetonNJ08544 United States Beijing Institute of Big Data Research and Peking University Beijing100871 China Institute of High Performance Computing Agency for Science Technology and Research Connexis North 1 Fusionopolis Way Singapore138632 Singapore

Recent work linking deep neural networks and dynamical systems opened up new avenues to analyze deep learning. In particular, it is observed that new insights can be obtained by recasting deep learning as an optimal control problem on difference or differential equations. However, the mathematical aspects of such a formulation have not been systematically explored. This paper introduces the mathematical formulation of the population risk minimization problem in deep learning as a mean-field optimal control problem. Mirroring the development of classical optimal control, we state and prove optimality conditions of both the Hamilton-Jacobi-Bellman type and the Pontryagin type. These mean-field results reflect the probabilistic nature of the learning problem. In addition, by appealing to the mean-field Pontryagin's maximum principle, we establish some quantitative relationships between population and empirical learning problems. This serves to establish a mathematical foundation for investigating the algorithmic and theoretical connections between optimal control and deep learning. Copyright © 2018, The Authors. All rights reserved.

关键词： Optimal control systems

来源：评论

学校读者我要写书评

暂无评论

Optimization of laser-driven quantum beam generation and the applications with artificial intelligence

引用

Physics of Plasmas 2024年第5期31卷

作者： Kuramitsu, Y. Taguchi, T. Nikaido, F. Minami, T. Hihara, T. Suzuki, S. Oda, K. Kuramoto, K. Yasui, T. Abe, Y. Ibano, K. Takabe, H. Chu, C.M. Wu, K.T. Woon, W.Y. Chen, S.H. Jao, C.S. Chen, Y.C. Liu, Y.L. Morace, A. Yogo, A. Arikawa, Y. Kohri, H. Tokiyasu, A. Kodaira, S. Kusumoto, T. Kanasaki, M. Asai, T. Fukuda, Y. Kondo, K. Kiriyama, H. Hayakawa, T. Tanaka, S.J. Isayama, S. Watamura, N. Suzuki, H. Kumar, H.S. Ohnishi, N. Pikuz, T. Filippov, E. Sakai, K. Yasuhara, R. Nakata, M. Ishikawa, R. Hoshi, T. Mizuta, A. Bolouki, N. Saura, N. Benkadda, S. Koenig, M. Hamaguchi, S. Graduate School of Engineering Osaka University 2-1 Yamadaoka Osaka Suita565-0871 Japan Institute of Laser Engineering Osaka University 2-6 Yamadaoka Osaka Suita565-0871 Japan 8-1-7 Umemidai Kyoto Kizugawa619-0215 Japan Department of Physics National Central University No. 300 Jhongda Rd. Taoyuan Jhongli320 Taiwan Department of Physics National Cheng Kung University Tainan701 Taiwan National Center for High-Performance Computing National Applied Research Laboratories Tainan City711010 Taiwan Institute of Space and Plasma Sciences National Cheng Kung University Tainan701 Taiwan Research Center for Nuclear Physics Osaka University 10-1 Mihogaoka Osaka Ibaraki567-0047 Japan Research Center for Accelerator and Radioisotope Science Tohoku University 1-2-1 Mikamine Taihaku-ku Miyagi Sendai982-0826 Japan Inage Chiba263-8555 Japan Graduate School of Maritime Sciences Kobe University Kobe658-0022 Japan Department of Physical Sciences Aoyama Gakuin University 5-10-1 Fuchinobe Kanagawa Sagamihara252-5258 Japan Department of Advanced Environmental Science and Engineering Kyushu University 6-1 Kasuga-Kohen Fukuoka Kasuga816-8580 Japan Graduate School of Information Science and Technology Osaka University 2-1 Yamadaoka Suita565-0871 Japan Department of Aerospace Engineering Tohoku University 6-6-01 Aramakiazaaoba Aoba-ku Sendai980-8579 Japan Institute for Open and Transdisciplinary Research Initiatives Osaka University 2-1 Yamadaoka Osaka Suita565-0871 Japan Villamayor Salamanca37185 Spain National Institute for Fusion Science 322-6 Oroshicho Gifu Toki509-5292 Japan Faculty of Arts and Sciences Komazawa University 1-23-1 Komazawa Setagaya-ku Tokyo154-8525 Japan Astrophysical Big Bang Laboratory RIKEN Saitama Wako351-0198 Japan Department of Plasma Physics and Technology Faculty of Science Masaryk University Kotlářská 2 Brno611 37 Czech Republic Aix-Marseille Université CNRS PIIM UMR 7345 Marseille France LULI CN

We have investigated space and astrophysical phenomena in nonrelativistic laboratory plasmas with long high-power lasers, such as collisionless shocks and magnetic reconnections, and have been exploring relativistic regimes with intense short pulse lasers, such as energetic ion acceleration using large-area suspended graphene. Increasing the intensity and repetition rate of the intense lasers, we have to handle large amounts of data from the experiments as well as the control parameters of laser beamlines. Artificial intelligence (AI) such as machine learning and neural networks may play essential roles in optimizing the laser and target conditions for efficient laser ion acceleration. Implementing AI into the laser system in mind, as the first step, we are introducing machine learning in ion etch pit analyses detected on plastic nuclear track detectors. Convolutional neural networks allow us to analyze big ion etch pit data with high precision and recall. We introduce one of the applications of laser-driven ion beams using AI to reconstruct vector electric and magnetic fields in laser-produced turbulent plasmas in three dimensions. © 2024 Author(s).

关键词： Ions

来源：评论

学校读者我要写书评

暂无评论

Unveiling latent behaviors of video viewers with cross-platform information 27

Unveiling latent behaviors of video viewers with cross-platf...

引用

27th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video, NOSSDAV 2017

作者： Gu, Xuhong Zhou, Yipeng Wu, Di Chan, Terence H. Chen, Min School of Data and Computer Science Sun Yat-sen University China Institute for Telecommunications Research University of South Australia Australia Guangdong Province Key Laboratory of Big Data Analysis and Processing Sun Yat-sen University China Collaborative Innovation Center of High Performance Computing National University of Defense Technology China School of Computer Science and Technology Huazhong University of Science and Technology China

ISBN: (纸本)9781450350037

The online video streaming service is of huge market values with billions of worldwide users. For online video providers, e.g., Net-flix, Youku, the crucial question is how to understand users' view behaviors and preferences because this knowledge is important for their business operation. Existing solutions mainly rely on analyzing users' historical view records, which however are not always available, especially for new videos and unprovided videos. Different from existing solutions, we propose to infer user behaviors and preferences by jointly analyzing data collected from multiple platforms (e.g., video streaming systems, video databases, etc.). In particular, we use the movie data crawled from a leading video streaming system (i.e., Youku), and a well-known video database in China (i.e, Douban) for this study. Our investigation points out that movie quality (evaluated in terms of Douban scores) and release date jointly influence viewers' preferences. In addition, we reveal a series of user behaviors, e.g., users are reluctant to post comments or ratings for movies they do not like, and user eyeballs are heavily captured by new movies. Understanding of these user behaviors covered by this study is essential for video recommendation and video popularity prediction which can benefit video procurement and advertisement campaign. © 2017 ACM.

关键词： Video streaming

来源：评论

学校读者我要写书评

暂无评论

Context-aware video recommendation by mining users' view preferences based on access points 27

Context-aware video recommendation by mining users' view pre...

引用

27th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video, NOSSDAV 2017

作者： Zhang, Jiaming Zhou, Yipeng Wu, Di Yang, Chunfeng School of Data and Computer Science Sun Yat-sen University Guangzhou Guangdong China Institute for Telecommunications Research University of South Australia Australia Guangdong Province Key Laboratory of Big Data Analysis and Processing Sun Yat-sen University Guangzhou Guangdong China Collaborative Innovation Center of High Performance Computing National University of Defense Technology China Tencent Inc. China

ISBN: (纸本)9781450350037

With the astronomical growth of online video population, the video recommendation system is crucial for users to locate videos fitting their interests. The collaborative filtering (CF) realizing personalized recommendation by analyzing users' historical view records is currently the most prevalent algorithm adopted by existing systems. Nevertheless, video recommendation performance can be improved for most cases, particularly the one with cold-start problem, if additional information is involved. In this article, we propose an AP-based Context-Aware (APCA) recommendation scheme on top of the traditional factor-based CF algorithm by utilizing the information of access points which has not been explored yet by existing works. The underlying principle is that users' view preferences are expected to be different with different contexts, e.g., hotel, home, public areas, which can be inferred by mining the information of access points via which users launch video requests. With the data collected from Tencent Video, a leading online video provider in China, we present a measurement study to show user view preferences in different contexts before our APCA algorithm is introduced. Experiments are executed driven by the trace data collected from Tencent Video to validate the effectiveness of our scheme in improving recommendation performance. © 2017 ACM.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

The Wide-field Spectroscopic Telescope (WST) Science White Paper

arXiv

引用

arXiv 2024年

作者： Mainieri, Vincenzo Anderson, Richard I. Brinchmann, Jarle Cimatti, Andrea Ellis, Richard Hill, Vanessa Kneib, Jean-Paul McLeod, Anna Opitom, Cyrielle Roth, Martin M. Sáez, Paula Sánchez Smiljanic, Rodolfo Tolstoy, Eline Bacon, Roland Randich, Sofia Pasquini, Luca Barsanti, Stefania Bryant, Julia Bryson, Ian Casali, Mark Colless, Matthew Couch, Warrick Danielski, Camilla Dierickx, Philippe Driver, Simon Fontana, Adriano Garilli, Bianca de Jong, Roelof S. Lee, David Lehnert, Matt Magrini, Laura Montet, Ben Sanchez-Janssen, Ruben Pandey-Pommier, Mamta Sargent, Mark Schipani, Pietro Steinmetz, Matthias Travouillon, Tony Tresse, Laurence Vernet, Joël Yeche, Christophe Ziegler, Bodo Audard, Marc Arévalo, Patricia Bayo Aran, Amelia M. Bisero, Sofia Bisogni, Susanna Blondin, Stéphane Bonito, Rosaria Branchesi, Marica Catelan, Márcio D'Ammando, Filippo Dainotti, Maria G. De Cia, Annalisa Dhawan, Suhail Dupletsa, Ulyana Hazra, Nandini Ilić, Dragana Ivanov, Valentin D. Izzo, Luca Kovačević, Andjelka B. Kuncarayakti, Hanindyo Kwon, Yuna La Forgia, Fiorangela Lazzarin, Monica Lira, Paulina Loffredo, Eleonora Maguire, Kate Majidi, Fatemeh Z. Marconi, Marcella McGee, Sean Migliorini, Alessandra Minniti, Dante Nicholl, Matt Onori, Francesca Pala, Anna F. Panda, Swayamtrupta Pawlak, Michal Pessi, Priscila J. Popović, Luka Č. Smith, Graham P. Vergani, Susanna D. Vietri, Giustina Ye, Quanzhi Zafar, Tayyaba Matsuno, Tadafumi Kordopatis, Georges Annibali, Francesca Bayo, Amelia Bellazzini, Michele Beltran, Maria Teresa Berni, Leda Bianchi, Simone Biazzo, Katia Bland-Hawthorn, Joss Boffin, Henri M.J. Bono, Giuseppe Bowman, Dominic Braga, Vittorio F. Bragaglia, Angela Brucalassi, Anna Busà, Innocenza Casali, Giada Casasola, Viviana Castro, Norberto Cavallo, Lorenzo Chiappini, Cristina Colzi, Laura Damiani, Francesco da Silva, Ronaldo D'Orazi, Valentina Escorza, Ana Fabrizio, Michele Fiorentino, Giuliana Fontani, Francesco François, Patrick Galindo-Guil, Francisco J. Galli, Daniele Garcia-Rojas, Jorge Guarcello, Mario Giuseppe Helmi, Am European Southern Observatory Karl-Schwarzschild-Strasse 2 Garching bei München85748 Germany Switzerland Instituto de Astrofísica e Ciências do Espaço Universidade do Porto Portugal Dipartimento di Fisica e Astronomia "Augusto Righi" Alma Mater Studiorum Università di Bologna Italy Department of Physics and Astronomy University College London United Kingdom Observatoire de la Côte d'Azur Université Côte d'Azur CNRS Laboratoire Lagrange France Centre for Extragalactic Astronomy Department of Physics Durham University United Kingdom Institute for Computational Cosmology Department of Physics University of Durham United Kingdom Institute for Astronomy University of Edinburgh United Kingdom Germany Nicolaus Copernicus Astronomical Center Polish Academy of Sciences Poland Kapteyn Astronomical Institute University of Groningen Netherlands France INAF - Osservatorio Astrofisico di Arcetri Italy Stockholm University Sweden INAF - Osservatorio di Astrofisica e Scienza dello Spazio di Bologna Italy Universidad de Valparaíso Chile University of Geneva Switzerland Research School of Astronomy and Astrophysics Australian National University CanberraACT2611 Australia Australia Instituto de Astrofísica de Canarias Spain Universidad de La Laguna Spain SISSA - Scuola Internazionale Superiore di Studi Avanzati Italy University of Florence Italy INAF - Osservatorio Astronomico di Roma Italy GEPI Observatoire de Paris Universite PSL CNRS France INAF Istituto di Astrofisica Spaziale e Fisica cosmica Milano Italy Sydney Institute for Astronomy School of Physics The University of Sydney Australia Aix Marseille Univ CNRS CNES LAM France INAF - Osservatorio Astronomico di Palermo Italy University of Rome Tor Vergata Italy Newcastle University United Kingdom Italy UK Astronomy Technology Ctr. Royal Observatory Edinburgh United Kingdom INAF OACT Italy Dipartimento di Fisica Università degli Studi di Torino Italy Istituto Nazionale di Fisica Nucleare INFN Sezione di

The WST is proposed as a new facility dedicated to the efficient delivery of spectroscopic surveys and this white paper summarises the initial concept as well as the corresponding science cases. It will provide an end-to-end service from the preparation of surveys to the delivery of high-quality calibrated science data product. Uniquely, it will have the ability to simultaneously deliver fibre-fed multi-object spectroscopy over a large field of view (MOS) and integral field imaging spectroscopy of a central field of 3 × 3 arcmin2 (IFS). WST will fill a crucial gap in the astronomical landscape and will allow full exploitation of major current and upcoming ground and space-based facilities. WST will address outstanding scientific questions in the areas of cosmology;galaxy assembly, evolution, and enrichment, including our own Milky Way;origin of stars and planets;time domain and multi-messenger astrophysics. WST features a 12 meter aperture telescope that covers the UV to the H band and operates in seeing limited conditions. Its field of view (FoV) of 3.1 deg2 will be the largest of any telescope equipped with a MOS. In particular, its FoV is 2.5 times larger than PFS@Subaru and a remarkable 22 times larger than MOONS@VLT. In addition, the WST has a substantial aperture, twice as large (100 square metres) as its 8 meter class competitors. A central circular area with a diameter of 13 arcmin is available for simultaneous IFS observations. Within this area, the IFS with a FoV of 3 × 3 arcmin2 (9 times larger than MUSE@VLT) can be utilised simultaneously with the MOS. In addition, the IFS can be used to mosaic a larger area within the 13 arcmin circle (an area larger than the entire FoV of the ELT) while the MOS positioner can perform multiple configurations. The WST operational model will also implement target of opportunity (ToO) operations at both the telescope and MOS fibre levels to support the time domain science cases. The demand for a facility dedicated to spect

关键词： Telescopes

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：