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arXiv 2021年

作者： Kang, Seoung-Hun Jeon, Sangjun Kim, Hyun-Jung Ko, Wonhee Cho, Suyeon Kang, Se Hwang Kim, Sung Wng Yang, Heejun Kim, Hyo Won Son, Young-Woo Korea Institute for Advanced Study Seoul02455 Korea Republic of Department of Physics Chung-Ang University Seoul06974 Korea Republic of Peter Grünberg Institute Institute for Advanced Simulation Forschungszentrum Jülich Jülich52428 Germany Samsung Advanced Institute of Technology Suwon16678 Korea Republic of Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Chemical Engineering and Materials Science Graduate Program in System Health Science and Engineering Ewha Womans University Seoul03760 Korea Republic of Department of Energy Science Sungkyunkwan University Suwon16419 Korea Republic of Department of Physics Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of

We report the direct evidence of impacts of the Coulomb interaction in a prototypical Weyl semimetal, MoTe2, that alter its bare bands in a wide range of energy and momentum. Our quasiparticle interference patterns measured using scanning tunneling microscopy are shown to match the joint density of states of quasiparticle energy bands including momentum-dependent self-energy corrections, while electronic energy bands based on the other simpler local approximations of the Coulomb interaction fail to explain neither the correct number of quasiparticle pockets nor shape of their dispersions observed in our spectrum. With this, we predict a transition between type-I and type-II Weyl fermions with doping and resolve its disparate quantum oscillation experiments, thus highlighting the critical roles of Coulomb interactions in layered Weyl semimetals. © 2021, CC BY-NC-ND.

关键词： Dispersions

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Predictability of Ensemble Forecasting Estimated Using the Kullback–Leibler Divergence in the Lorenz Model

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Advances in Atmospheric sciences 2019年第8期36卷 837-846页

作者： Ruiqiang DING Baojia LIU Bin GU Jianping LI Xuan LI State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China College of Earth Sciences University of Chinese Academy of SciencesBeijing 100049China Institute of Space Weather School of Math and StatisticsNanjing University of Information Science and TechnologyNanjing 210044China College of Physics and Optoelectronic Engineering Nanjing University of Information Science and TechnologyNanjing 210044China College of Global Change and Earth System Sciences Beijing Normal UniversityBeijing 100875China

A new method to quantify the predictability limit of ensemble forecasting is presented using the Kullback–Leibler(KL)divergence(also called the relative entropy), which provides a measure of the difference between the probability distributions of ensemble forecasts and local reference(true) states. The KL divergence is applicable to a non-normal distribution of ensemble forecasts, which is a substantial improvement over the previous method using the ensemble spread. An example from the three-variable Lorenz model illustrates the effectiveness of the KL divergence, which can effectively quantify the predictability limit of ensemble forecasting. On this basis, the KL divergence is used to investigate the dependence of the predictability limit of ensemble forecasting on the initial states and the magnitude of initial errors. The local predictability limit of ensemble forecasting varies considerably with the initial states, as well as with the magnitude of initial errors. Further research is needed to examine the real-world applications of the KL divergence in measuring the predictability of ensemble weather forecasts.

关键词： predictability ensemble forecasting Kullback–Leibler divergence

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A Comparative Analysis of Machine-learning Models for Solar Flare Forecasting: Identifying High-performing Active Region Flare Indicators

arXiv

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arXiv 2022年

作者： Sinha, Suvadip Gupta, Om Singh, Vishal Lekshmi, B. Nandy, Dibyendu Mitra, Dhrubaditya Chatterjee, Saikat Bhattacharya, Sourangshu Chatterjee, Saptarshi Srivastava, Nandita Brandenburg, Axel Pal, Sanchita Center of Excellence in Space Sciences India Indian Institute of Science Education and Research Kolkata West Bengal Mohanpur741246 India Department of Physical Sciences Indian Institute of Science Education and Research Kolkata West Bengal Mohanpur741246 India Max Planck Institute for Solar System Research Göttingen37077 Germany Nordita KTH Royal Institute of Technology Stockholm University Hannes Alfvéns väg 12 StockholmSE-10691 Sweden KTH Royal Institute of Technology Stockholm Sweden Indian Institute of Technology Kharagpur India Udaipur Solar Observatory Physical Research Laboratory P.O. Box 198 Badi Road Udaipur313001 India The Oskar Klein Centre Department of Astronomy Stockholm University AlbaNova StockholmSE-10691 Sweden Department of Physics University of Helsinki P.O. Box 64 HelsinkiFI-00014 Finland

Solar flares create adverse space weather impacting space and Earth-based technologies. However, the difficulty of forecasting flares, and by extension severe space weather, is accentuated by the lack of any unique flare trigger or a single physical pathway. Studies indicate that multiple physical properties contribute to active region flare potential, compounding the challenge. Recent developments in machine learning (ML) have enabled analysis of higher-dimensional data leading to increasingly better flare forecasting techniques. However, consensus on high-performing flare predictors remains elusive. In the most comprehensive study to date, we conduct a comparative analysis of four popular ML techniques (k-nearest neighbor, logistic regression, random forest classifier, and support vector machine) by training these on magnetic parameters obtained from the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) for the entirety of solar cycle 24. We demonstrate that the logistic regression and support vector machine algorithms perform extremely well in forecasting active region flaring potential. The logistic regression algorithm returns the highest true skill score of 0.967 ± 0.018, possibly the highest classification performance achieved with any strictly parametric study. From a comparative assessment, we establish that the magnetic properties like total current helicity, total vertical current density, total unsigned flux, R VALUE, and total absolute twist are the top-performing flare indicators. We also introduce and analyze two new performance metrics, namely, severe and clear space weather indicators. Our analysis constrains the most successful ML algorithms and identifies physical parameters that contribute most to active region flare productivity. Copyright © 2022, The Authors. All rights reserved.

关键词： Parameter estimation

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Seamless maps of major elements of the Moon: Results from high-resolution geostationary satellite

arXiv

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arXiv 2020年

作者： Lu, Yu Wu, Yun-Zhao Li, Cui Ma, Jin-Song Qi, Wen-Wen Tan, Wei Li, Xiao-Man Shi, Zhi-Cheng He, Hong-Yan Dai, Shu-Wu Li, Guo Liu, Feng-Jing Wang, Jing-Qiao Wang, Xiao-Yan Wang, Qi Meng, Ling-Jie Key Laboratory of Planetary Sciences Purple Mountain Observatory Chinese Academy of Sciences Nanjing210034 China School of Astronomy and Space Science University of Science and Technology of China Hefei230026 China CAS Center for Excellence in Comparative Planetology Hefei230026 China Space Science Institute Macau University of Science and Technology China School of Geography and Ocean Science Nanjing University Nanjing210023 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing210023 China Beijing Institute of Space Mechanics and Electricity Beijing China Beijing Institute of Spacecraft System Engineering Beijing China China Centre for Resources Satellite Data and Application Beijing China Earth Observation System and Data Center China National Space Administration Beijing China

Major elements such as Fe, Ti, Mg, Al, Ca, and Si play very important roles in understanding the origin and evolution of the Moon. Previous maps of these major elements derived from orbital data are based on mosaic images or low-resolution Gamma ray data. The hue variations and gaps among orbital boundaries in the mosaic images are not conducive to geological studies. This paper aims to produce seamless and homogenous distribution maps of major elements using the single-exposure image of the whole lunar disk obtained by China's high-resolution geostationary satellite, Gaofen-4, with a spatial resolution of ~500 m. The elemental contents of soil samples returned by Apollo and Luna missions were used as ground truth, and were correlated with the reflectance of the sampling sites extracted from Gaofen-4 data. The final distribution maps of these major oxides are generated with the statistical regression model. With these products the average contents and proportions of the major elements for maria and highlands were estimated and compared. The results showed that SiO2 and TiO2 have the highest and lowest fractions in mare and highland areas, respectively. Besides, the relative concentrations of these elements could serve as indicators of geologic processes, e.g., the obviously asymmetric distributions of Al2O3, CaO, and SiO2 around Tycho crater may suggest that Tycho crater was formed by an oblique impact from the southwest direction. Copyright © 2020, The Authors. All rights reserved.

关键词： Silica

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Joint object contour points and semantics for instance segmentation

arXiv

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arXiv 2020年

作者： Zhang, Wenchao Fu, Chong Zhu, Mai Cao, Lin Tie, Ming Sham, Chiu-Wing School of Computer Science and Engineering Northeastern University Shenyang110819 China Engineering Research Center of Security Technology of Complex Network System Ministry of Education China Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Northeastern University Shenyang110819 China School of Information and Communication Engineering Beijing Information Science and Technology University Beijing100101 China Science and Technology on Space Physics Laboratory Beijing100076 China School of Computer Science University of Auckland New Zealand

The attributes of object contours has great significance for instance segmentation task. However, most of the current popular deep neural networks do not pay much attention to the object edge information. Inspired by the human annotation process when making instance segmentation datasets, in this paper, we propose Mask Point R-CNN aiming at promoting the neural network’s attention to the object boundary. Specifically, we innovatively extend the original human keypoint detection task to the contour point detection of any object. Based on this analogy, we present an contour point detection auxiliary task to Mask R-CNN, which can boost the gradient flow between different tasks by effectively using feature fusion strategies and multi-task joint training. As a consequence, the model will be more sensitive to the edges of the object and can capture more geometric features. Quantitatively, the experimental results show that our approach outperforms vanilla Mask R-CNN by 3.8% on Cityscapes dataset and 0.8% on COCO dataset. Copyright © 2020, The Authors. All rights reserved.

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Production of lipopeptides by Bacillus subtilis in solid status fermentation and their application in antifungal and heavy metal remove 3

Production of lipopeptides by Bacillus subtilis in solid sta...

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3rd International Conference on Biological Information and Biomedical Engineering, BIBE 2019

作者： Zhao, Pengpeng Wang, Yan Lei, Shuzhen Zhao, Xixi Zhu, Danni Jiang, Chunmei Shao, Dongyan Shi, Junling Key Laboratory of Space Biological Experiment Simulation Technology College of Life Science Northwestern Polytechnical University Xi'an Shaanxi710072 China Microbiology Institute of Shaanxi Xi'an Shaanxi710043 China College of Life Sciences and Food Engineering Shaanxi Xueqian Normal University Xi'an710100 China

ISBN: (纸本)9783800750269

Lipopeptides have many useful applications in antifungal activity, biomedical and pharmaceutical applications. Due to their unique structure, they have the potential to be a substitute for many antibiotics. At present, the main way to produce lipopeptides is at the laboratory level, and the yield is not very optimistic. In this study, under the premise of selecting agricultural and sideline products as fermentation substrates, the fermentation was carried out by Bacillus subtilis CCTCCM207209, and a series of conditions ranging from medium composition to fermentation conditions were optimized. Results revealed that the optimal conditions for maximum lipopeptides production and total antifungal activity were 3 g soybean flour, 2 g rice straw and 3g wheat bran as the solid substrate in 250ml erlenmeyer with initial pH 7.0, moisture content 60% and a 10% inoculum level at 32 °C for 5 days. Under these conditions, the experimental yield of lipopeptides reached 70.98 mg/gds and the total antifungal activity reached 659.03 U/gds. In addition, this study also found the application of lipopeptides in the removal of heavy metal ions. Under suitable conditions, it has excellent removal effect on heavy metal ions Cd2+ and Pb2+. Through this research, firstly, we can use cheaper agricultural by products to produce lipopeptides, and secondly, we can use the fermentation products to remove heavy metal pollution, which adds a new way for the removal of heavy metals. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Heavy metals

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Autonomous Navigation Using Natural Landmark Measurements for Earth Orbit Satellites

Autonomous Navigation Using Natural Landmark Measurements fo...

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第三十八届中国控制会议

作者： Chao Xu Xiangyu Huang Maodeng Li Dayi Wang Beijing Institute of Control Engineering Science and Technology of Space Intelligent Control Laboratory Beijing Institute of Spacecraft System Engineering

An autonomous navigation based on the line of sight（LOS）measurements of natural landmarks is presented for earth orbit ***,the natural landmark-based navigation scheme is described with the assumption that the camera is installed on a gimbal mount and the criterion of the landmark visibility is *** the mathematical models for landmark-based navigation are *** on the established models,the observability analysis is performed and the result shows that the landmark-based navigation system is observable as long as the observed landmarks are not always on the sub-satellite *** numerical simulation for a low Earth orbit（LEO）satellite is performed,which indicate that the proposed navigation method is effective and feasible.

关键词： Autonomous Navigation Natural landmark Earth orbit satellite Observability analysis

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DID Code:A Bridge Connecting the Materials Genome Engineering Database w让h Inheritable Integrated Intelligent Manufacturing

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Engineering 2020年第6期6卷 612-620页

作者： William Yi Wang Peixuan Li Deye Lin Bin Tang Jun Wang Quanmei Guan Qian Ye Haixing Dai Jun Gao Xiaoli Fan Hongchao Kou Haifeng Song Feng Zhou Jijun Ma Zi-Kui Liu Jinshan Li Weimin Liu State Key Laboratory of Solidification Processing Northwestern Polytechnical UniversityXi'an 710072China CAEP Software Center for High Performance Numerical Simulation Institute of Applied Physics and Computational MathematicsBeijing 100088China CRRC Tangshan Co. Ltd.Tangshan 063035China Beijing Star Travel Space Technology Co. Ltd.Beijing 100013China Department of Materials Science and Engineering Pennsylvania State UniversityUniversity ParkPA 16802USA

A data identifier(DID)is an essential tag or label in all kinds of databases—particularly those related to integrated computational materials engineering(ICME),inheritable integrated intelligent manufacturing(I3M),and the Industrial Internet *** the guidance and quick acceleration of the developme nt of advanced materials,as envisioned by official documents worldwide,more investigations are required to construct relative numerical standards for material *** work proposes a universal DID format consisting of a set of build chains,which aligns with the classical form of identifier in both international and national standards,such as ISO/IEC 29168-1:2000,GB/T 27766-2011,GA/T 543.2-2011,GM/T 0006-2012,GJB 7365-2011,SL 325-2014,SL 607-201&WS 363.2-2011,and QX/T *** build chain is made up of capital letters and numbers,with no ***,the total length of each build chain is not restricted,which follows the formation of the Universal Coded Character Set in the international standard of ISO/IEC *** on these rules,the proposed DID is flexible and convenient for extendi ng and sharing in and between various cloud-based ***,classical two-dimensional(2D)codes,including the Hanxin Code,Lots Perception Matrix(LP)Code,Quick Response(Q.R)code,Grid Matrix(GM)code,and Data Matrix(DM)Code,can be constructed and precisely recognized and/or decoded by either smart phones or specific *** utilizing these 2D codes as the fingerprints of a set of data linked with cloud-based platforms,progress and updates in the composition-processing-structure-property-performance workflow process can be tracked spontaneously,paving a path to accelerate the discovery and manufacture of advanced materials and enhance research productivity,performance,and collaboration.

关键词： Data identifier Database Digital twin Integrated computational materials engineering

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A ring-like accretion structure in M87 connecting its black hole and jet

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Nature 2023年第7958期616卷 686-690页

作者： Ru-Sen Lu Keiichi Asada Thomas P Krichbaum Jongho Park Fumie Tazaki Hung-Yi Pu Masanori Nakamura Andrei Lobanov Kazuhiro Hada Kazunori Akiyama Jae-Young Kim Ivan Marti-Vidal José L Gómez Tomohisa Kawashima Feng Yuan Eduardo Ros Walter Alef Silke Britzen Michael Bremer Avery E Broderick Akihiro Doi Gabriele Giovannini Marcello Giroletti Paul T P Ho Mareki Honma David H Hughes Makoto Inoue Wu Jiang Motoki Kino Shoko Koyama Michael Lindqvist Jun Liu Alan P Marscher Satoki Matsushita Hiroshi Nagai Helge Rottmann Tuomas Savolainen Karl-Friedrich Schuster Zhi-Qiang Shen Pablo de Vicente R Craig Walker Hai Yang J Anton Zensus Juan Carlos Algaba Alexander Allardi Uwe Bach Ryan Berthold Dan Bintley Do-Young Byun Carolina Casadio Shu-Hao Chang Chih-Cheng Chang Song-Chu Chang Chung-Chen Chen Ming-Tang Chen Ryan Chilson Tim C Chuter John Conway Geoffrey B Crew Jessica T Dempsey Sven Dornbusch Aaron Faber Per Friberg Javier González García Miguel Gómez Garrido Chih-Chiang Han Kuo-Chang Han Yutaka Hasegawa Ruben Herrero-Illana Yau-De Huang Chih-Wei L Huang Violette Impellizzeri Homin Jiang Hao Jinchi Taehyun Jung Juha Kallunki Petri Kirves Kimihiro Kimura Jun Yi Koay Patrick M Koch Carsten Kramer Alex Kraus Derek Kubo Cheng-Yu Kuo Chao-Te Li Lupin Chun-Che Lin Ching-Tang Liu Kuan-Yu Liu Wen-Ping Lo Li-Ming Lu Nicholas MacDonald Pierre Martin-Cocher Hugo Messias Zheng Meyer-Zhao Anthony Minter Dhanya G Nair Hiroaki Nishioka Timothy J Norton George Nystrom Hideo Ogawa Peter Oshiro Nimesh A Patel Ue-Li Pen Yurii Pidopryhora Nicolas Pradel Philippe A Raffin Ramprasad Rao Ignacio Ruiz Salvador Sanchez Paul Shaw William Snow T K Sridharan Ranjani Srinivasan Belén Tercero Pablo Torne Efthalia Traianou Jan Wagner Craig Walther Ta-Shun Wei Jun Yang Chen-Yu Yu Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai People's Republic of China. rslu@***. Key Laboratory of Radio Astronomy Chinese Academy of Sciences Nanjing People's Republic of China. rslu@***. Max-Planck-Institut für Radioastronomie Bonn Germany. rslu@***. Institute of Astronomy and Astrophysics Academia Sinica Taipei Taiwan ROC. asada@asiaa.sinica.edu.tw. Max-Planck-Institut für Radioastronomie Bonn Germany. tkrichbaum@mpifr-bonn.mpg.de. Institute of Astronomy and Astrophysics Academia Sinica Taipei Taiwan ROC. Korea Astronomy and Space Science Institute Daejeon Republic of Korea. Simulation Technology Development Department Tokyo Electron Technology Solutions Oshu Japan. Mizusawa VLBI Observatory National Astronomical Observatory of Japan Oshu Japan. Department of Physics National Taiwan Normal University Taipei Taiwan ROC. Center of Astronomy and Gravitation National Taiwan Normal University Taipei Taiwan ROC. Department of General Science and Education National Institute of Technology Hachinohe College Hachinohe City Japan. Max-Planck-Institut für Radioastronomie Bonn Germany. Mizusawa VLBI Observatory National Astronomical Observatory of Japan Oshu Japan. kazuhiro.hada@nao.ac.jp. Department of Astronomical Science The Graduate University for Advanced Studies SOKENDAI Mitaka Japan. kazuhiro.hada@nao.ac.jp. Black Hole Initiative Harvard University Cambridge MA USA. Massachusetts Institute of Technology Haystack Observatory Westford MA USA. National Astronomical Observatory of Japan Mitaka Japan. Department of Astronomy and Atmospheric Sciences Kyungpook National University Daegu Republic of Korea. Departament d'Astronomia i Astrofísica Universitat de València Valencia Spain. Observatori Astronòmic Universitat de València Valencia Spain. Instituto de Astrofísica de Andalucía-CSIC Granada Spain. Institute for Cosmic Ray Research The University of Tokyo Chiba Japan. Shanghai Astronomical Observatory Chinese Academy of S

The nearby radio galaxy M87 is a prime target for studying black hole accretion and jet formation. Event Horizon Telescope observations of M87 in 2017, at a wavelength of 1.3 mm, revealed a ring-like structure, which was interpreted as gravitationally lensed emission around a central black hole. Here we report images of M87 obtained in 2018, at a wavelength of 3.5 mm, showing that the compact radio core is spatially resolved. High-resolution imaging shows a ring-like structure of [Formula: see text] Schwarzschild radii in diameter, approximately 50% larger than that seen at 1.3 mm. The outer edge at 3.5 mm is also larger than that at 1.3 mm. This larger and thicker ring indicates a substantial contribution from the accretion flow with absorption effects, in addition to the gravitationally lensed ring-like emission. The images show that the edge-brightened jet connects to the accretion flow of the black hole. Close to the black hole, the emission profile of the jet-launching region is wider than the expected profile of a black-hole-driven jet, suggesting the possible presence of a wind associated with the accretion flow.

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The PLATO mission

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Experimental Astronomy 2025年第3期59卷 1-111页

作者： Rauer, Heike Aerts, Conny Cabrera, Juan Deleuil, Magali Erikson, Anders Gizon, Laurent Goupil, Mariejo Heras, Ana Walloschek, Thomas Lorenzo-Alvarez, Jose Marliani, Filippo Martin-Garcia, César Mas-Hesse, J. Miguel O’Rourke, Laurence Osborn, Hugh Pagano, Isabella Piotto, Giampaolo Pollacco, Don Ragazzoni, Roberto Ramsay, Gavin Udry, Stéphane Appourchaux, Thierry Benz, Willy Brandeker, Alexis Güdel, Manuel Janot-Pacheco, Eduardo Kabath, Petr Kjeldsen, Hans Min, Michiel Santos, Nuno Smith, Alexis Suarez, Juan-Carlos Werner, Stephanie C. Aboudan, Alessio Abreu, Manuel Acuña, Lorena Adams, Moritz Adibekyan, Vardan Affer, Laura Agneray, François Agnor, Craig Aguirre Børsen-Koch, Victor Ahmed, Saad Aigrain, Suzanne Al-Bahlawan, Ashraf Alcacera Gil, Ma de los Angeles Alei, Eleonora Alencar, Silvia Alexander, Richard Alfonso-Garzón, Julia Alibert, Yann Allende Prieto, Carlos Almeida, Leonardo Alonso Sobrino, Roi Altavilla, Giuseppe Althaus, Christian Alvarez Trujillo, Luis Alonso Amarsi, Anish Ammler-von Eiff, Matthias Amôres, Eduardo Andrade, Laerte Antoniadis-Karnavas, Alexandros António, Carlos Aparicio del Moral, Beatriz Appolloni, Matteo Arena, Claudio Armstrong, David Aroca Aliaga, Jose Asplund, Martin Audenaert, Jeroen Auricchio, Natalia Avelino, Pedro Baeke, Ann Baillié, Kevin Balado, Ana Ballber Balagueró, Pau Balestra, Andrea Ball, Warrick Ballans, Herve Ballot, Jerome Barban, Caroline Barbary, Gaële Barbieri, Mauro Barceló Forteza, Sebastià Barker, Adrian Barklem, Paul Barnes, Sydney Barrado Navascues, David Barragan, Oscar Baruteau, Clément Basu, Sarbani Baudin, Frederic Baumeister, Philipp Bayliss, Daniel Bazot, Michael Beck, Paul G. Belkacem, Kevin Bellinger, Earl Benatti, Serena Benomar, Othman Bérard, Diane Bergemann, Maria Bergomi, Maria Bernardo, Pierre Biazzo, Katia Bignamini, Andrea Bigot, Lionel Billot, Nicolas Binet, Martin Biondi, David Biondi, Federico Birch, Aaron C. Bitsch, Bertram Bluhm Ceballos, Paz Victoria Bódi, Attila Bognár, Zsófia Boisse, Isabelle Bolmont, Emeline Bonanno, Alfio Bonavita, Institut für Planetenforschung Deutsches Zentrum für Luft- und Raumfahrt DLR Rutherfordstrasse 2 Berlin 12489 Germany Fachbereich Geowissenschaften Institut für Geologische Freie Universität Berlin Malteserstr. 74-100 Berlin 12249 Germany Institute of Astronomy KU Leuven Leuven Belgium CNRS CNES LAM Aix Marseille University Marseille France Max Planck Institute for Solar System Research Göttingen Germany LESIA Paris Observatory PSL University Sorbonne University Paris Cité University CNRS Meudon France ESTEC European Space Agency Noordwijk Netherlands ESAC European Space Agency Madrid Spain Centro de Astrobiología CSIC-INTA Campus ESAC Madrid Spain Center for Space and Habitability University of Bern Bern Switzerland INAF - Osservatorio Astrofisico di Catania Catania Italy Department of Physics and Astronomy University of Padua Padua Italy Department of Physics University of Warwick Coventry United Kingdom Astronomical Observatory of Padova INAF - Italian National Institute for Astrophysics Padua Italy Armagh Observatory and Planetarium College Hill Armagh United Kingdom Geneve Observatory University of Geneve Geneve Switzerland IAS University of Paris-Saclay Orsay France AlbaNove University Centre Stockholm University Stockholm Sweden Department of Astrophysics University of Vienna Vienna Austria Department of Astronomy University of Sao Paulo Sao Paulo Brazil Astronomical Institute of the Czech Academy of Sciences Ondřejov Czech Republic Department of Physics and Astronomy Aarhus University Aarhus Denmark Institute for Space Research SRON Leiden Netherlands Instituto de Astrofísica e Ciências do Espaço CAUP Universidade do Porto Porto Portugal Departamento de Física e Astronomia Faculdade da Ci ncias Universidade do Porto Porto Portugal Mullard Space Science Laboratory University College London Holmbury Saint Mary United Kingdom Dept. Theoretical Physics and the Cosmos University of Granada Granada Spain Centre for Plan

PLATO (PLAnetary Transits and Oscillations of stars) is ESA’s M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2REarth) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5%, 10%, 10% for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar system planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO‘s target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile towards the end of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases. © The Author(s) 2025.

关键词： Asteroseismology Exoplanets PLATO mission

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