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Large loss of CO2 in winter observed across the northern permafrost region (vol 9, pg 852, 2019)

NATURE CLIMATE CHANGE 2019年第12期9卷 1005-1005页

作者： Natali, Susan M. Watts, Jennifer D. Rogers, Brendan M. Potter, Stefano Ludwig, Sarah M. Selbmann, Anne-Katrin Sullivan, Patrick F. Abbott, Benjamin W. Arndt, Kyle A. Birch, Leah Bjorkman, Mats P. Bloom, A. Anthony Celis, Gerardo Christensen, Torben R. Christiansen, Casper T. Commane, Roisin Cooper, Elisabeth J. Crill, Patrick Czimczik, Claudia Davydov, Sergey Du, Jinyang Egan, Jocelyn E. Elberling, Bo Euskirchen, Eugenie S. Friborg, Thomas Genet, Helene Gockede, Mathias Goodrich, Jordan P. Grogan, Paul Helbig, Manuel Jafarov, Elchin E. Jastrow, Julie D. Kalhori, Aram A. M. Kim, Yongwon Kimball, John S. Kutzbach, Lars Lara, Mark J. Larsen, Klaus S. Lee, Bang-Yong Liu, Zhihua Loranty, Michael M. Lund, Magnus Lupascu, Massimo Madani, Nima Malhotra, Avni Matamala, Roser McFarland, Jack McGuire, A. David Michelsen, Anders Minions, Christina Oechel, Walter C. Olefeldt, David Parmentier, Frans-Jan W. Pirk, Norbert Poulter, Ben Quinton, William Rezanezhad, Fereidoun Risk, David Sachs, Torsten Schaefer, Kevin Schmidt, Niels M. Schuur, Edward A. G. Semenchuk, Philipp R. Shaver, Gaius Sonnentag, Oliver Starr, Gregory Treat, Claire C. Waldrop, Mark P. Wang, Yihui Welker, Jeffrey Wille, Christian Xu, Xiaofeng Zhang, Zhen Zhuang, Qianlai Zona, Donatella Woods Hole Research Center Falmouth MA USA University of Bayreuth Bayreuth Germany Environment and Natural Resources Institute University of Alaska Anchorage AK USA Department of Plant and Wildlife Sciences Brigham Young University Provo UT USA Department of Biology San Diego State University San Diego CA USA Department of Earth Sciences University of Gothenburg Göteborg Sweden Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA Center for Ecosystem Science and Society Northern Arizona University Flagstaff AZ USA Department of Bioscience Arctic Research Centre Aarhus University Roskilde Denmark NORCE Norwegian Research Centre Bjerknes Centre for Climate Research Bergen Norway Department of Earth and Environmental Sciences of Lamont-Doherty Earth Observatory Columbia University Palisades NY USA Department of Arctic and Marine Biology Faculty of Biosciences Fisheries and Economics UiT The Arctic University of Norway Tromsø Norway Department of Geological Sciences and Bolin Centre for Climate Research Stockholm University Stockholm Sweden Earth System Science University of California Irvine CA USA Northeast Science Station Pacific Geographical Institute Cherskii Russia Numerical Terradynamic Simulation Group W.A. Franke College of Forestry & Conservation University of Montana Missoula MT USA Department of Earth Sciences Dalhousie University Halifax Nova Scotia Canada Center for Permafrost Department of Geosciences and Natural Resource Management University of Copenhagen Copenhagen Denmark Institute of Arctic Biology University of Alaska Fairbanks Fairbanks AK USA Department of Geosciences and Natural Resource Management University of Copenhagen Copenhagen Denmark Max Planck Institute for Biogeochemistry Jena Germany Scripps Institution of Oceanography University of California San Diego La Jolla CA USA Department of Biology Queen’s University Kingston Ontario Canada School of Geography and Earth Sciences McMa

Recent warming in the Arctic, which has been amplified during the winter1,2,3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO2)4. However, the amount of CO... 详细信息

Recent warming in the Arctic, which has been amplified during the winter^1,2,3, greatly enhances microbial decomposition of soil organic matter and subsequent release of carbon dioxide (CO₂)⁴. However, the amount of CO₂ released in winter is not known and has not been well represented by ecosystem models or empirically based estimates^5,6. Here we synthesize regional in situ observations of CO₂ flux from Arctic and boreal soils to assess current and future winter carbon losses from the northern permafrost domain. We estimate a contemporary loss of 1,662 TgC per year from the permafrost region during the winter season (October-April). This loss is greater than the average growing season carbon uptake for this region estimated from process models (−1,032 TgC per year). Extending model predictions to warmer conditions up to 2100 indicates that winter CO₂ emissions will increase 17% under a moderate mitigation scenario—Representative Concentration Pathway 4.5—and 41% under business-as-usual emissions scenario—Representative Concentration Pathway 8.5. Our results provide a baseline for winter CO₂ emissions from northern terrestrial regions and indicate that enhanced soil CO₂ loss due to winter warming may offset growing season carbon uptake under future climatic conditions.

关键词： Climate sciences Ecology Ecosystem ecology

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Research on knowledge network modelling for aero-craft system design 7

Research on knowledge network modelling for aero-craft syste...

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7th International Conference on simulation and Modeling Methodologies, Technologies and Applications, SIMULTECH 2017

作者： Zhai, Xiang Dai, Feng Qu, Huiyang Zhong, Lingling Du, Chenyong Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center Beijing China School of Mechanical Engineering Zhejiang University Hangzhou China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Aviation Engineering Institute Civil Aviation Flight University of China Sichuan China Beijing ZhiYuanChuangTong IT Co Ltd Beijing China

ISBN: (纸本)9789897582653

A great amount of existing knowledge is required during the development of aero-craft system. At present, the existing knowledge organization model construct different knowledge model for different stages is difficult to adapt to the complicated product life cycle application. This study proposes a product development oriented knowledge network model focusing on expressing the knowledge demands and connecting the computer-aided system. Under the overall knowledge network model, this study describes the ontology description method of spacecraft product model, development tasks and aerospace terminology. Recommending missile aerodynamic knowledge within the design stage is presented as a case study, and the framework and the method is proved to be effective. © Copyright 2017 by SCITEPRESS - science and technology Publications, Lda. All rights reserved.

关键词： Ontology

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Driving factors of carbon dioxide emissions in China： an empirical study using 2006-2010 provincial data

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Frontiers of Earth science 2017年第1期11卷 156-161页

作者： Yu LIU Zhan-Ming CHEN Hongwei XIAO Wei YANG Danhe LIU Bin CHEN Institute of Policy and Management Chinese Academy of Sciences Beijing 100190 China Department of Energy Economics School of Economics Renmin University of China Beijing 100872 China National Academy of Development and Strategy Renmin University of China Beijing 100872 China Economic Forecasting Department State Information Center Beijing 100045 China School of Economics and Management Beijing University of Chemical Technology Beijing 100029 China School of Humanities and Social Science Beijing Institute of Technology Beijing 100081 China State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Beijing Normal University Beijing 100875 China

The rapid urbanization of China has increased pressure on its environmental and ecological well being. In this study, the temporal and spatial profiles of China＇s carbon dioxide emissions are analyzed by taking heterogeneities into account based on an integration of the extended stochastic impacts using a geographically and temporally weighted regression model on population, affluence, and technology. Population size, urbanization rate, GDP per capita, energy intensity, industrial structure, energy consumption pattern, energy prices, and economy openness are identified as the key driving factors of regional carbon dioxide emissions and examined through the empirical data for 30 provinces during 2006-2010. The results show the driving factors and their spillover effects have distinct spatial and temporal heterogeneities. Most of the estimated time and space coefficients are consistent with expectation. According to the results of this study, the heterogeneous spatial and temporal effects should be taken into account when designing policies to achieve the goals of carbon dioxide emissions reduction in different regions.

关键词： carbon dioxide emission heterogeneity space spillover

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Magnetic and topological transitions in three-dimensional topological Kondo insulator

arXiv

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arXiv 2018年

作者： Li, Huan Wang, Zhi-Yong Zheng, Xiao-Jun Liu, Yu Zhong, Yin College of Science Guilin University of Technology Guilin541004 China Institute of Applied Physics and Computational Mathematics Beijing100088 China Software Center for High Performance Numerical Simulation China Academy of Engineering Physics Beijing100088 China Center for Interdisciplinary Studies & Key Laboratory for Magnetism and Magnetic Materials of the MoE Lanzhou University Lanzhou730000 China

By using an extended slave-boson method, we draw a global phase diagram summarizing both magnetic phases and paramagnetic (PM) topological insulating phases (TIs) in three-dimensional topological Kondo insulator (TKI). By including electron hopping (EH) up to third neighbor, we identify four strong topological insulating (STI) phases and two weak topological insulating (WTI) phases, then the PM phase diagrams characterizing topological transitions between these TIs are depicted as functions of EH, f-electron energy level and hybridization constant. We also find an insulator-metal transition from a STI phase which has surface Fermi rings and spin textures in qualitative agreement to TKI candidate SmB6. In weak hybridization regime, anti-ferromagnetic (AF) order naturally arises in the phase diagrams, and depending on how the magnetic boundary crosses the PM topological transition lines, AF phases are classified into AF topological insulator (AFTI) and non-topological AF insulator (nAFI), according to their Z2 indices. In two small regions of parameter space, two distinct topological transition processes between AF phases occur, leading to two types of AFTI, showing distinguishable surface dispersions around their Dirac points. Copyright © 2018, The Authors. All rights reserved.

关键词： Phase diagrams

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Affinity Propagation for Hyperspectral Band Selection

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IOP Conference Series: Earth and Environmental science 2018年第2期170卷

作者： Zhiwei Ren Lingda Wu Department of Graduate Management Space Engineering University Beijing 101416 China Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing 101416 China

Because hyperspectral images have the characteristics of high correlation between bands and strong information redundancy, the reduction in dimension of hyperspectral images is an important step in the pre-processing of hyperspectral images. Band selection can preserve the physical meaning of the original data while reducing dimension and has application in many aspects. Affinity Propagation Clustering (AP) is a clustering method proposed by Fray et al. in 2007. AP clusters based on the correlation between data points and treats all data points as potential cluster centers. This paper proposes a band selection method based on AP clustering, which introduces wavelet transform into the calculation of similarity and preference value in clustering algorithm. The dimensionality reduction results are input into the minimum distance classifier for classification, and the classification accuracy was calculated. The dataset is validated by the Indiana Pines dataset. The experimental results verify the effectiveness of the proposed method.

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Smart radio environments

arXiv

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arXiv 2021年

作者： Gradoni, Gabriele Renzo, Marco Di Díaz-Rubio, Ana Tretyakov, Sergei A. Caloz, Christophe Gradoni, Gabriele Peng, Zhen Alu, Andrea Lerosey, Geoffroy Fink, Mathias Galdi, Vincenzo Cui, Tie Jun Frazier, Benjamin W. Anlage, Steven M. Salucci, Marco Massa, Andrea Cheng, Qiang Wang, Jinghe Jin, Shi Dardari, Davide Decarli, Nicoló Yurduseven, Okan Matthaiou, Michail Kenney, Mitchell Gordon, George Georgiou, Orestis Nguyen, Cam Ly Martini, Enrica Maci, Stefano Wakatsuchi, Hiroki Phang, Sendy School of Mathematical Sciences Department of Electrical and Electronic Engineering University of Nottingham Nottingham United Kingdom Laboratoire des Signaux et Systémes CNRS CentraleSupélec Université Paris-Saclay Gif-sur-Yvette Paris France Department of of Electronics and Nanoengineering Aalto University Espoo Finland META Research Group KU Leuven Belgium School of Mathematical Sciences Department of Electrical and Electronic Engineering University of Nottingham University Park NG72RD United Kingdom Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign IL United States Advanced Science Research Center City University of New York United States Greenerwave 6 rue Jean Calvin Paris75005 France Institut Langevin 1 rue Jussieu Paris75005 France Fields & Waves Lab Department of Engineering University of Sannio Benevento Italy State Key Laboratory of Millimeter Waves Southeast University Nanjing China Applied Physics Laboratory Johns Hopkins University LaurelMD20723 United States Department of Electrical and Computer Engineering Department of Physics Quantum Materials Center University of Maryland College ParkMD20742 United States Trento Italy Chengdu China Beijing China Institute of Electromagnetic Space State Key Laboratory of Millimeter Waves Southeast University Nanjing210096 China National Mobile Communications Research Laboratory Southeast University Nanjing China University of Bologna Bologna Italy Bologna Italy Centre for Wireless Innovation Institute of Electronics Communications and Information Technology Queen’s University Belfast Belfast United Kingdom Department of Electrical and Electronic Engineering University of Nottingham Nottingham United Kingdom Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Wireless System Laboratory Corporate Research & Development Center Toshiba Corporation Kawasaki Japan Department of Information Engineering an

This Roadmap takes the reader on a journey through the research in electromagnetic wave propagation control via reconfigurable intelligent surfaces. Meta-surface modelling and design methods are reviewed along with physical realisation techniques. Several wireless applications are discussed, including beam-forming, focusing, imaging, localisation, and sensing, some rooted in novel architectures for future mobile communications networks towards 6G. © 2021, CC BY.

关键词： Electromagnetic wave propagation

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A large sub-Neptune transiting the thick-disk M4 V TOI-2406

arXiv

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arXiv 2021年

作者： Wells, Robert D. Rackham, B.V. Schanche, N. Petrucci, R. Gómez Maqueo Chew, Y. Demory, B.-O. Burgasser, A.J. Burn, R. Pozuelos, F.J. Günther, M.N. Sabin, L. Schroffenegger, U. Gómez-Muñoz, M.A. Stassun, K.G. van Grootel, V. Howell, S.B. Sebastian, D. Triaud, A.H.M.J. Apai, D. Plauchu-Frayn, I. Guerrero, C.A. Guillén, P.F. Landa, A. Melgoza, G. Montalvo, F. Serrano, H. Riesgo, H. Barkaoui, K. Bixel, A. Burdanov, A. Chen, W.P. Chinchilla, P. Collins, K.A. Daylan, T. de Wit, J. Delrez, L. Dévora-Pajares, M. Dietrich, J. Dransfield, G. Ducrot, E. Fausnaugh, M. Furlan, E. Gabor, P. Gan, T. Garcia, L. Ghachoui, M. Giacalone, S. Gibbs, A.B. Gillon, M. Gnilka, C. Gore, R. Guerrero, N. Henning, T. Hesse, K. Jehin, E. Jenkins, J.M. Latham, D.W. Lester, K. McCormac, J. Murray, C.A. Niraula, P. Pedersen, P.P. Queloz, D. Ricker, G. Rodriguez, D.R. Schroeder, A. Schwarz, R.P. Scott, N. Seager, S. Theissen, C.A. Thompson, S. Timmermans, M. Twicken, J.D. Winn, J.N. Center for Space and Habitability University of Bern Gesellschaftsstrasse 6 Bern3012 Switzerland Department of Earth Atmospheric and Planetary Science Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology CambridgeMA02139 United States Universidad Nacional de Córdoba - Observatorio Astronómico de Córdoba Laprida 854 CórdobaX5000BGR Argentina Buenos Aires Argentina Universidad Nacional Autónoma de México Instituto de Astronomía AP 70-264 CDMX 04510 Mexico Center for Astrophysics and Space Science University of California San Diego San diegoCA92093 United States Koenigstuhl 17 HeidelbergD-69117 Germany Astrobiology Research Unit Université de Liège Allée du 6 Août 19C LiègeB-4000 Belgium Institute Universitde ´ Liège Allée du 6 Août 19C LiègeB-4000 Belgium Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Universidad Nacional Autónoma de México Instituto de Astronomía AP 106 Ensenada BC 22800 Mexico Department of Physics & Astronomy Vanderbilt University 6301 Stevenson Center Ln. NashvilleTN37235 United States NASA Ames Research Center Moffett FieldCA94035 United States School of Physics & Astronomy University of Birmingham Edgbaston BirmimghamB15 2TT United Kingdom Steward Observatory University of Arizona 933 N. Cherry Avenue TucsonAZ85721 United States NASA Nexus For Exoplanetary System Science Alien Earths Team Lunar and Planetary Laboratory University of Arizona 1639 E. University Boulevard TucsonAZ85721 United States Oukaimeden Observatory High Energy Physics and Astrophysics Laboratory Cadi Ayyad University Marrakech Morocco Graduate Institute of Astronomy National Central University 300 Jhongda Road Taoyuan Zhongli32001 Taiwan Calle Vía Láctea s/n Tenerife La Laguna38200 Spain Center for Astrophysics Harvard & Smithsonian 60 Garden Stre

Context. Large sub-Neptunes are uncommon around the coolest stars in the Galaxy and are rarer still around those that are metal-poor. However, owing to the large planet-to-star radius ratio, these planets are highly suitable for atmospheric study via transmission spectroscopy in the infrared, such as with JWST. Aims. Here we report the discovery and validation of a sub-Neptune orbiting the thick-disk, mid-M dwarf star TOI-2406. The star’s low metallicity and the relatively large size and short period of the planet make TOI-2406 b an unusual outcome of planet formation, and its characterisation provides an important observational constraint for formation models. Methods. We first infer properties of the host star by analysing the star’s near-infrared spectrum, spectral energy distribution, and Gaia parallax. We use multi-band photometry to confirm that the transit event is on-target and achromatic, and we statistically validate the TESS signal as a transiting exoplanet. We then determine physical properties of the planet through global transit modelling of the TESS and ground-based time-series data. Results. We determine the host to be a metal-poor M4 V star, located at a distance of 56 pc, with properties Teff = 3100 ± 75 K, M∗ = 0.162 ± 0.008 M, R∗ = 0.202 ± 0.011 R, and [Fe/H] = −0.38 ± 0.07, and a member of the thick disk. The planet is a relatively large sub-Neptune for the M-dwarf planet population, with Rp = 2.94 ± 0.17 R and P = 3.077 d, producing transits of 2% depth. We note the orbit has a non-zero eccentricity to 3σ, prompting questions about the dynamical history of the system. Conclusions. This system is an interesting outcome of planet formation and presents a benchmark for large-planet formation around metal-poor, low-mass stars. The system warrants further study, in particular radial velocity follow-up to determine the planet mass and constrain possible bound companions. Furthermore, TOI-2406 b is a good target for future atmospheric study through tr

关键词： Infrared devices

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Author Correction: Near-real-time monitoring of global CO2 emissions reveals the effects of the COVID-19 pandemic

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Nature communications 2020年第1期11卷 6292页

作者： Zhu Liu Philippe Ciais Zhu Deng Ruixue Lei Steven J Davis Sha Feng Bo Zheng Duo Cui Xinyu Dou Biqing Zhu Rui Guo Piyu Ke Taochun Sun Chenxi Lu Pan He Yuan Wang Xu Yue Yilong Wang Yadong Lei Hao Zhou Zhaonan Cai Yuhui Wu Runtao Guo Tingxuan Han Jinjun Xue Olivier Boucher Eulalie Boucher Frédéric Chevallier Katsumasa Tanaka Yiming Wei Haiwang Zhong Chongqing Kang Ning Zhang Bin Chen Fengming Xi Miaomiao Liu François-Marie Bréon Yonglong Lu Qiang Zhang Dabo Guan Peng Gong Daniel M Kammen Kebin He Hans Joachim Schellnhuber Department of Earth System Science Tsinghua University Beijing China. zhuliu@***. Laboratoire des Sciences du Climat et de l'Environnement LSCE CEA CNRS UVSQ Centre d'Etudes Orme de Merisiers Gif-sur-Yvette France. Department of Earth System Science Tsinghua University Beijing China. Department of Meteorology and Atmospheric Science The Pennsylvania State University University Park PA USA. Department of Earth System Science University of California Irvine 3232Croul Hall Irvine CA USA. Division of Geological and Planetary Sciences California Institute of Technology Pasadena CA USA. Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA. Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science and Technology Nanjing China. Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China. Climate Change Research Center Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China. Key Laboratory of Middle Atmosphere and Global Environment Observation Institute of Atmospheric Physics Chinese Academy of Sciences Beijing China. School of Environment Tsinghua University Beijing China. School of Mathematical School Tsinghua University Beijing China. Department of Mathematical Sciences Tsinghua University Beijing China. Center of Hubei Cooperative Innovation for Emissions Trading System Wuhan China. Faculty of Management and Economics Kunming University of Science and Technology 13 Kunming China. Economic Research Centre of Nagoya University Furo-cho Chikusa-ku Nagoya Japan. Institut Pierre-Simon Laplace Sorbonne Université/CNRS Paris France. Université Paris Dauphine Place du Maréchal de Lattre de Tassigny 75016 Paris France.

A Correction to this paper has been published: https://***/10.1038/s41467-020-20254-5.

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Survey on Multilayer Networks Visualization

Survey on Multilayer Networks Visualization

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2017 IEEE 8th International Conference on Software Engineering and Service science

作者： ZHANG Xitao WU Lingda YU Shaobo ZHOU Peng Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University The Chinese People's Liberation Army 91404 Troops

Based on the survey about the criterion of network visualization, some visualization challenges for multilayer networks are introduced. After a brief overview of the strategies and the previous work on multilayer netw... 详细信息

关键词： multilayer networks network visualization information visualization

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Noise subtraction from KAGRA O3GK data using Independent Component Analysis

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Classical and Quantum Gravity 2023年第8期40卷 085015-085015页

作者： H Abe T Akutsu M Ando A Araya N Aritomi H Asada Y Aso S Bae Y Bae R Bajpai K Cannon Z Cao E Capocasa M Chan C Chen D Chen K Chen Y Chen C-Y Chiang Y-K Chu S Eguchi M Eisenmann Y Enomoto R Flaminio H K Fong Y Fujii Y Fujikawa Y Fujimoto I Fukunaga D Gao G-G Ge S Ha I P W Hadiputrawan S Haino W-B Han K Hasegawa K Hattori H Hayakawa K Hayama Y Himemoto N Hirata C Hirose T-C Ho B-H Hsieh H-F Hsieh C Hsiung H-Y Huang P Huang Y-C Huang Y-J Huang D C Y Hui S Ide K Inayoshi Y Inoue K Ito Y Itoh C Jeon H-B Jin K Jung P Jung K Kaihotsu T Kajita M Kakizaki M Kamiizumi N Kanda T Kato K Kawaguchi C Kim J Kim J C Kim Y-M Kim N Kimura T Kiyota Y Kobayashi K Kohri K Kokeyama A K H Kong N Koyama C Kozakai J Kume Y Kuromiya S Kuroyanagi K Kwak E Lee H W Lee R Lee M Leonardi K L Li P Li L C -C Lin C-Y Lin E T Lin F-K Lin F-L Lin H L Lin G C Liu L-W Luo M Ma’arif E Majorana Y Michimura N Mio O Miyakawa K Miyo S Miyoki Y Mori S Morisaki N Morisue Y Moriwaki K Nagano K Nakamura H Nakano M Nakano Y Nakayama T Narikawa L Naticchioni L Nguyen Quynh W-T Ni T Nishimoto A Nishizawa S Nozaki Y Obayashi W Ogaki J J Oh K Oh M Ohashi T Ohashi M Ohkawa H Ohta Y Okutani K Oohara S Oshino S Otabe K-C Pan A Parisi J Park F E Pe na Arellano S Saha Y Saito K Sakai T Sawada Y Sekiguchi L Shao Y Shikano H Shimizu K Shimode H Shinkai T Shishido A Shoda K Somiya I Song R Sugimoto J Suresh T Suzuki H Tagoshi H Takahashi R Takahashi S Takano H Takeda M Takeda K Tanaka T Tanaka S Tanioka A Taruya T Tomaru T Tomura L Trozzo T Tsang J-S Tsao S Tsuchida T Tsutsui D Tuyenbayev N Uchikata T Uchiyama A Ueda T Uehara K Ueno G Ueshima T Ushiba M H P M van Putten J Wang T Washimi C Wu H Wu T Yamada K Yamamoto T Yamamoto K Yamashita R Yamazaki Y Yang S Yeh J Yokoyama T Yokozawa T Yoshioka H Yuzurihara S Zeidler M Zhan H Zhang Y Zhao Z-H Zhu The KAGRA Collaboration Graduate School of Science Tokyo Institute of Technology Meguro-ku Tokyo 152-8551 Japan Gravitational Wave Science Project National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Advanced Technology Center National Astronomical Observatory of Japan (NAOJ) Mitaka City Tokyo 181-8588 Japan Department of Physics The University of Tokyo Bunkyo-ku Tokyo 113-0033 Japan Research Center for the Early Universe (RESCEU) The University of Tokyo Bunkyo-ku Tokyo 113-0033 Japan Earthquake Research Institute The University of Tokyo Bunkyo-ku Tokyo 113-0032 Japan Department of Mathematics and Physics Gravitational Wave Science Project Hirosaki University Hirosaki City Aomori 036-8561 Japan Kamioka Branch National Astronomical Observatory of Japan (NAOJ) Kamioka-cho Hida City Gifu 506-1205 Japan The Graduate University for Advanced Studies (SOKENDAI) Mitaka City Tokyo 181-8588 Japan Korea Institute of Science and Technology Information (KISTI) Yuseong-gu Daejeon 34141 Republic of Korea National Institute for Mathematical Sciences Yuseong-gu Daejeon 34047 Republic of Korea School of High Energy Accelerator Science The Graduate University for Advanced Studies (SOKENDAI) Tsukuba City Ibaraki 305-0801 Japan Department of Astronomy Beijing Normal University Beijing 100875 People’s Republic of China Department of Applied Physics Fukuoka University Jonan Fukuoka City Fukuoka 814-0180 Japan Department of Physics Tamkang University Danshui Dist. New Taipei City 25137 Taiwan Department of Physics and Institute of Astronomy National Tsing Hua University Hsinchu 30013 Taiwan Department of Physics Center for High Energy and High Field Physics National Central University Zhongli District Taoyuan City 32001 Taiwan Department of Physics National Tsing Hua University Hsinchu 30013 Taiwan Institute of Physics Academia Sinica Nankang Taipei 11529 Taiwan Univ. Grenoble Alpes Laboratoire d’Annecy de Physique des Particules (LAPP) Université Savoie M

During April 7–21 2020, KAGRA conducted its first scientific observation in conjunction with the GEO600 detector. The dominant noise sources during this run were found to be suspension control noise in the low-frequency range and acoustic noise in the mid-frequency range. In this study, we show that their contributions in the observational data can be reduced by a signal processing method called independent component analysis (ICA). The model of ICA is extended from that studied in the initial KAGRA data analysis to account for frequency dependence, while the linearity and stationarity of the coupling between the interferometer and the noise sources are still assumed. We identify optimal witness sensors in the application of ICA, leading to successful mitigation of these two dominant contributions. We also analyze the stability of the transfer functions for the entire two weeks of data to investigate the applicability of the proposed subtraction method in gravitational wave searches.

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