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Social insects and beyond: The physics of soft, dense invertebrate aggregations

Collective Intelligence 2022年第2期1卷

作者： Olga Shishkov Orit Peleg BioFrontiers Institute University of Colorado Boulder Boulder CO USA Department of Computer Science University of Colorado Boulder Boulder CO USA Department of Physics University of Colorado Boulder Boulder CO USA Department of Applied Math University of Colorado Boulder Boulder CO USA Department of Ecology and Evolutionary Biology University of Colorado Boulder Boulder CO USA Santa Fe Institute Santa Fe NM USA

Aggregation is a common behavior by which groups of organisms arrange into cohesive groups. Whether suspended in the air (like honey bee clusters), built on the ground (such as army ant bridges), or immersed in water (such as sludge worm blobs), these collectives serve a multitude of biological functions, from protection against predation to the ability to maintain a relatively desirable local environment despite a variable ambient environment. In this review, we survey dense aggregations of a variety of insects, other arthropods, and worms from a soft matter standpoint. An aggregation can be orders of magnitude larger than its individual organisms, consisting of tens to hundreds of thousands of individuals, and yet functions as a coherent entity. Understanding how aggregating organisms coordinate with one another to form a superorganism requires an interdisciplinary approach. We discuss how considering the physics of an aggregation can yield additional insights to those gained from ecological and physiological considerations, given that the aggregating individuals exchange information, energy, and matter continually with the environment and one another. While the connection between animal aggregations and the physics of non-living materials has been proposed since the early 1900s, the recent advent of physics of behavior studies provides new insights into social interactions governed by physical principles. Current efforts focus on eusocial insects; however, we show that these may just be the tip of an iceberg of superorganisms that take advantage of physical interactions and simple behavioral rules to adapt to changing environments. By bringing attention to a wide range of invertebrate aggregations, we wish to inspire a new generation of scientists to explore collective dynamics and bring a deeper understanding of the physics of dense living aggregations.

关键词： Collective behavior aggregation invertebrates soft matter survey

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Building Ramps and Pathways to Data science in K-12, Minority-Serving Institutions, and Two-Year Colleges

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Scatterplot 2024年第1期1卷

作者： Rachel Saidi Helen Burn Ben Baumer Jason Black Debzani Deb Zarek Drozda a Math Statistics and Data Science Department Montgomery College – Rockville Campus Rockville MD USA b Mathematics Department Highline College Des Moines Washington Des Moines WA USA c Statistical and Data Sciences Department Smith College Northampton MA USA d School of Business and Interdisciplinary Center for Creativity and Innovation (ICCI) Florida A&M University Tallahassee FL USA e Computer Science Department Center for Applied Data Science (CADS) Winston-Salem State University Winston-Salem NC USA f Data Science 4 Everyone (DS4E) Program University of Chicago Chicago IL USA

Global demand for data scientists and analysts is on a trajectory of sustained growth, underscoring the need to expand enrollment of students in data science and data analytics courses and programs. This article explores diverse pathways to data science for various groups, including high school students, those in two-year colleges, and students in small colleges and minority-serving institutions. This article identifies opportunities and challenges associated with pursuing data science for students in these sectors, including factors such as building partnerships and awareness of the field and difficulties in establishing articulation agreements between institutions. The authors, representing various organizations participating in a panel discussion at the 2023 Data science Leadership Summit of the Academic Data science Alliance (ADSA), share insights into efforts to develop nontraditional pathways, serving as a resource for schools, colleges, and organizations contemplating creation of data science programs. The panelists’ combined experience spans work with a broad range of organizations including ADSA, American math.matics Association of Two-Year Colleges, American Statistical Association, Data science for Everyone, the department of Education, HBCU Data science Consortium, math.matical Association of America, National Academies of science, Engineering, and Medicine, HBCU Data science Consortium, National science Foundation, and StatPREP.

关键词： Data science pathways access K-12 minority-serving institution two-year college

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Organ-on-a-Chip: Ex vivo Dynamics of Human Glioblastoma Cells in a Microvasculature-on-a-Chip System Correlates with Tumor Heterogeneity and Subtypes (Adv. Sci. 8/2019)

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Advanced science 2019年第8期6卷 1970046-1970046页

作者： Yang Xiao Dongjoo Kim Burak Dura Kerou Zhang Runchen Yan Huamin Li Edward Han Joshua Ip Pan Zou Jun Liu Ann Tai Chen Alexander O. Vortmeyer Jiangbing Zhou Rong Fan Department of Biomedical Engineering Yale University New Haven CT 06520 USA School of Computer Science Carnegie Mellon University Pittsburgh PA 15213 USA Applied Math Program Yale University New Haven CT 06520 USA Department of Neurosurgery Yale School of Medicine New Haven CT 06520 USA Department of Pathology Indiana University Health Pathology Laboratory Indianapolis IN 46202 USA Yale Comprehensive Cancer Center New Haven CT 06520 USA

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HIV and COVID-19 co-infection: A math.matical model and optimal control

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Informatics in Medicine Unlocked 2022年 31卷 100978页

作者： Ringa, N. Diagne, M.L. Rwezaura, H. Omame, A. Tchoumi, S.Y. Tchuenche, J.M. Data and Analytic Services British Columbia Centre for Disease Control 655 W 12th Ave Vancouver BC V5Z 4R4 Canada School of Population and Public Health University of British Columbia 2329 West Mall Vancouver BC V6T 1Z4 Canada Département de Mathématiques UFR des Sciences et Technologies Université de Thiès Thiès BP 967 Senegal Mathematics Department University of Dar es Salaam P.O. Box 35062 Dar es Salaam Tanzania Department of Mathematics Federal University of Technology Owerri Nigeria Abdus Salam School of Mathematical Sciences Government College University Lahore Pakistan Department of Mathematics and Computer Sciences ENSAI University of Ngaoundéré P.O. Box 455 Ngaoundéré Cameroon School of Computer Science and Applied Mathematics University of the Witwatersrand Private Bag 3 Wits 2050 Johannesburg South Africa School of Computational and Communication Sciences and Engineering Nelson Mandela African Institution of Science and Technology P.O. Box 447 Arusha Tanzania

A new math.matical model for COVID-19 and HIV/AIDS is considered to assess the impact of COVID-19 on HIV dynamics and vice-versa. Investigating the epidemiologic synergy between COVID-19 and HIV is important. The dynamics of the full model is driven by that of its sub-models;therefore, basic analysis of the two sub-models;HIV-only and COVID-19 only is carried out. The basic reproduction number is computed and used to prove local and global asymptotic stability of the sub-models’ disease-free and endemic equilibria. Using the fmincon function in the Optimization Toolbox of MATLAB, the model is fitted to real COVID-19 data set from South Africa. The impact of intervention measures, namely, COVID-19 and HIV prevention interventions and COVID-19 treatment are incorporated into the model using time-dependent controls. It is observed that HIV prevention measures can significantly reduce the burden of co-infections with COVID-19, while effective treatment of COVID-19 could reduce co-infections with opportunistic infections such as HIV/AIDS. In particular, the COVID-19 only prevention strategy averted about 10,500 new co-infection cases, with similar number also averted by the HIV-only prevention control. © 2022 The Author(s)

关键词： Basic reproduction number Co-infection COVID-19 HIV Optimal control

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Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

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The Lancet 2020年第10258期396卷 1204-1222页

作者： Abbafati, Cristiana Abbas, Kaja M. Abbasi, Mohammad Abbasifard, Mitra Abbasi-Kangevari, Mohsen Abbastabar, Hedayat Abd-Allah, Foad Abdelalim, Ahmed Abdollahi, Mohammad Abdollahpour, Ibrahim Abedi, Aidin Abedi, Parisa Abegaz, Kedir Hussein Abolhassani, Hassan Abosetugn, Akine Eshete Aboyans, Victor Abrams, Elissa M. Abreu, Lucas Guimarães Abrigo, Michael R.M. Abu Haimed, Abdulaziz Khalid Abualhasan, Ahmed Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Abushouk, Abdelrahman I. Acebedo, Alyssa Ackerman, Ilana N. Adabi, Maryam Adair, Tim Adamu, Abdu A. Adebayo, Oladimeji M. Adedeji, Isaac Akinkunmi Adekanmbi, Victor Adelson, Jaimie D. Adeoye, Abiodun Moshood Adetokunboh, Olatunji O. Adham, Davoud Advani, Shailesh M. Afarideh, Mohsen Afshari, Mahdi Afshin, Ashkan Agardh, Emilie E. Agarwal, Gina Agasthi, Pradyumna Agesa, Kareha M. Aghaali, Mohammad Aghamir, Seyed Mohammad Kazem Agrawal, Anurag Ahmad, Tauseef Ahmadi, Alireza Ahmadi, Keivan Ahmadi, Mehdi Ahmadieh, Hamid Ahmadpour, Ehsan Ahmed, Muktar Beshir Aji, Budi Akalu, Temesgen Yihunie Akinyemi, Rufus Olusola Akinyemiju, Tomi Akombi, Blessing Akunna, Chisom Joyqueenet Alahdab, Fares Al-Aly, Ziyad Alam, Khurshid Alam, Noore Alam, Samiah Alam, Tahiya Alanezi, Fahad Mashhour Alanzi, Turki M. Albertson, Samuel B. Alcalde-Rabanal, Jacqueline Elizabeth Alema, Niguse Meles Alemu, Biresaw Wassihun Alemu, Yihun Mulugeta Alhabib, Khalid F. Alhassan, Robert Kaba Ali, Muhammad Ali, Saqib Alicandro, Gianfranco Alijanzadeh, Mehran Alinia, Cyrus Alipour, Vahid Alizade, Hesam Aljunid, Syed Mohamed Alla, François Allebeck, Peter Almadi, Majid Abdulrahman Hamad Almasi, Ali Almasi-Hashiani, Amir Almasri, Nihad A. Al-Mekhlafi, Hesham M. Almulhim, Abdulaziz M. Alonso, Jordi Al-Raddadi, Rajaa M. Altirkawi, Khalid A. Alumran, Arwa Khalid Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Amare, Bekalu Amini, Saeed Amini-Rarani, Mostafa Aminorroaya, Arya Amiri, Fatemeh Amit, Arianna Maever L. Amugsi, Dickson A. Amul, Gianna Gayle Herrera Anbesu, Etsay Woldu Ancuceanu, Robert Anderl Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Infectious Disease Epidemiology London School of Hygiene and Tropical Medicine London United Kingdom Social Determinants of Health Research Center Tehran Iran Department of Neurology Cairo University Cairo Egypt School of Pharmacy Tehran Iran The Institute of Pharmaceutical Sciences (TIPS) Tehran Iran Neuroscience Research Center Isfahan University of Medical Sciences Isfahan Iran Biostatistics Department Near East University Nicosia Cyprus Biostatistics and Health Informatics Madda Walabu University Bale Robe Ethiopia Research Center for Immunodeficiencies Tehran Iran Karolinska University Hospital Huddinge Sweden Department of Cardiology Dupuytren University Hospital Limoges France University of Limoges Limoges France Department of Pediatric Dentistry Federal University of Minas Gerais Belo Horizonte Brazil Department of Research Philippine Institute for Development Studies Quezon City Philippines Department of Healthcare Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Harvard Medical School Boston MA United States Department of Medicine Ain Shams University Cairo Egypt Hamadan University of Medical Sciences Hamadan Iran School of Medicine Cardiff University Cardiff United Kingdom School of Laboratory Medicine and Science University College Hospital Ibadan Ibadan Nigeria Institute of Cardiovascular Diseases University of Ibadan Ibadan Nigeria Centre of Excellence for Epidemiological Modelling and Analysis Stellenbosch University Cape Town South Africa Department of Global Health Stellenbosch University Cape Town South Africa School of Health Ardabil University of Medical Science Ardabil Iran Social Behavioral Research Branch National Institute of Health Bethesda MD United States Department of Oncology Georgetown University Washington DC DC United States Department of Health Metrics Sciences School of Medicine Seattle WA

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw value

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Divertor shaping with neutral baffling as a solution to the tokamak power exhaust challenge

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Communications Physics 2025年第1期8卷 1-15页

作者： Kevin Verhaegh James Harrison David Moulton Nicola Lonigro Nick Osborne Peter Ryan Cyd Cowley Stuart Henderson Andrew Thornton Lingyan Xiang S. Aleiferis S. Allan J. Allcock L. Appel W. Arter I. Balboa O. Bardsley R. Bianchetti Morales A. Bleasdale A. Boboc C. Bowman D. Brunetti I. Carvalho F. J. Casson C. D. Challis B. Chapman N. J. Conway Y. Damizia S. Dowson S. Elmore F. Eriksson T. Farley A. R. Field N. Fil M. Fitzgerald M. Fontana R. Futtersack L. Garzotti S. N. Gerasimov Z. Ghani S. Gibson C. Giroud V. Gopakumar C. J. Ham J. Harrison N. C. Hawkes S. Henderson R. Henriques J. C. Hillesheim L. Horvath Z. Huang P. Jacquet I. Jepu D. Keeling H. T. Kim D. B. King V. G. Kiptily K. K. Kirov F. Köchl G. Kocsis L. Kogan D. Kos K. D. Lawson M. Lennholm E. LitherlandSmith P. J. Lomas C. Lowry C. F. Maggi J. Mailloux S. Marsden M. Maslov G. F. Matthews M. L. Mayoral G. McArdle A. G. Meigs S. Menmuir H. Meyer F. Militello J. Mitchell D. Moulton C. Olde H. J. C. Oliver N. Osborne R. Otin V. V. Parail A. Parrott A. Patel B. Patel M. Poradzinski F. G. Rimini C. Roach P. Ryan D. Ryan S. Saarelma S. Scully S. E. Sharapov R. Sharma A. Shaw S. A. Silburn J. Simpson S. Smith C. Srinivasan Z. Stancar C. I. Stuart H. J. Sun G. Szepesi D. Taylor E. Tholerus B. Thomas A. Thornton A. Tookey D. F. Valcarcel M. Valovic K. Verhaegh I. Voitsekhovitch D. Weston A. Widdowson T. Wilson L. Xiang Y. Zayachuk J. R. Harrison M. Aljunid S. Y. Allan L. C. Appel A. Ash J. Ashton O. Bachmann B. Barrett D. Beckett J. Bennett J. Buchanan N. Bulmer A. Carruthers J. Clark M. Coy G. Cunningham T. Da Assuncao P. Davies I. E. Day S. Dixon T. Eagles J. Edmond H. El-Haroun S. D. Elmore I. Fitzgerald S. Gee R. Harrison S. S. Henderson C. Hickling R. Hussain P. Jepson B. Kandan I. Katramados D. King R. King A. Kirk M. Kochan M. Lees G. Liddiard C. Man-Friel F. Mansfield R. Martin R. McAdams K. G. McClements D. McConville C. McKnight P. McKnight A. McShee J. Measures N. Mehay D. Morbey O. Myatra M. Nicassio E. Parr B. Parry B. S. Patel D. Payne M. Price R. Pr United Kingdom Atomic Energy Authority Culham UK Eindhoven University of Technology Eindhoven The Netherlands York Plasma Institute University of York York UK University of Liverpool Liverpool UK ITER Organization St-Paul-lez-Durance Cedex France Nat. Inst. for Laser Plasma & Radiation Physics Măgurele Romania EUROfusion PMU Garching Germany Dutch Institute for Fundamental Energy Research DIFFER Eindhoven The Netherlands Swiss Plasma Centre École Polytechnique Fédérale de Lausanne Lausanne Switzerland Oak Ridge National Laboratory Oak Ridge TN USA Universidad de Sevilla Seville Spain Electromagnetic Engineering & Fusion Science KTH Royal Institute of Technology Stockholm Sweden UniversitÃ degli Studi della Tuscia DEIM Viterbo Italy Aix-Marseille Univ. CNRS PIIM UMR 7345 Marseille France Politecnico di Milano Milan Italy Center for Energy Research UC San Diego La Jolla CA USA V. N. Karazin Kharkiv National University Kharkiv Ukraine Max Planck Institute for Plasma Physics Garching Germany Institute of Plasma Physics of the CAS Prague 8 Czechia Dublin City University Dublin Ireland VTT Technical Research Centre of Finland Espoo Finland Consorzio RFX Padova Italy University of California Irvine Irvine CA USA Istituto per la Scienza e la Tecnologia dei Plasmi CNR Padova Italy Graz University of Technology Graz Austria Aalto University Aalto Finland Institute for Plasma Science & Technology CNR Milan Italy Dept. of Applied Physics Ghent University Ghent Belgium ENEA Fusion & Nuclear Safety Dept. C.R. Frascati Frascati (RM) Italy National Technical University of Athens Zografou Greece Dept. of Physics & Astronomy Uppsala University Uppsala Sweden Dept. of Physics Durham University Durham UK Consorzio CREATE Naples Italy Aix-Marseille Univ. CNRS PIIM F-13397 Marseille France IRFM-CEA Centre de Cadarache St-Paul-lez-Durance France Centre for Energy Research Budapest Hungary University of Milano-Bicocca Milan Italy Dept. of Ele

Exhausting power from the hot fusion core to the plasma-facing components is one fusion energy’s biggest challenges. The MAST Upgrade tokamak uniquely integrates strong containment of neutrals within the exhaust area (divertor) with extreme divertor shaping capability. By systematically altering the divertor shape, this study shows the strongest evidence to date to our knowledge that long-legged divertors with a high magnetic field gradient (total flux expansion) deliver key power exhaust benefits without adversely impacting the hot fusion core. These benefits are already achieved with relatively modest geometry adjustments that are more feasible to integrate in reactor designs. Benefits include reduced target heat loads and improved access to, and stability of, a neutral gas buffer that ‘shields’ the target and enhances power exhaust (detachment). Analysis and model comparisons shows these benefits are obtained by combining multiple shaping aspects: long-legged divertors have expanded plasma-neutral interaction volume that drive reductions in particle and power loads, while total flux expansion enhances detachment access and stability. Containing the neutrals in the exhaust area with physical structures further augments these shaping benefits. These results demonstrate strategic variation in the divertor geometry and magnetic topology is a potential solution to one of fusion’s power exhaust challenge.

关键词： Fusion reactor divertors

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The unintended consequences of inconsistent closure policies and mobility restrictions during epidemics

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BMC global and public health 2023年第1期1卷 28页

作者： Benjamin M Althouse Brendan Wallace B K M Case Samuel V Scarpino Antoine Allard Andrew M Berdahl Easton R White Laurent Hébert-Dufresne University of Washington Seattle 98105 WA USA. New Mexico State University Las Cruces 88003 NM USA. Department of Applied Mathematics University of Washington Seattle 98195 WA USA. Present Address: Quantitative Ecology and Resource Management University of Washington Seattle WA 98195 USA. School of Aquatic & Fishery Sciences University of Washington Seattle WA 98195 USA. Department of Computer Science University of Vermont Burlington 05405 VT USA. Vermont Complex Systems Center University of Vermont Burlington 05405 VT USA. Institute for Experiential AI Northeastern University Boston Massachusetts USA. Department of Health Sciences Northeastern University Boston MA USA. Khoury College of Computer Sciences Northeastern University Boston MA USA. Santa Fe Institute Santa Fe NM USA. Département de physique de génie physique et d'optique Université Laval Québec (Québec) G1V 0A6 Canada. Centre interdisciplinaire en modélisation mathématique Université Laval Québec (Québec) G1V 0A6 Canada. School of Aquatic & Fishery Sciences University of Washington Seattle 98195 WA USA. Department of Biological Sciences University of New Hampshire Durham 03824 NH USA. Gund Institute for Environment University of Vermont Burlington 05405 VT USA.

Background:Controlling the spread of infectious diseases-even when safe, transmission-blocking vaccines are available-may require the effective use of non-pharmaceutical interventions (NPIs), e.g., mask wearing, testing, limits on group sizes, venue closure. During the SARS-CoV-2 pandemic, many countries implemented NPIs inconsistently in space and time. This inconsistency was especially pronounced for policies in the United States of America (US) related to venue closure. Methods:Here, we investigate the impact of inconsistent policies associated with venue closure using math.matical modeling and high-resolution human mobility, Google search, and county-level SARS-CoV-2 incidence data from the USA. Specifically, we look at high-resolution location data and perform a US-county-level analysis of nearly 8 million SARS-CoV-2 cases and 150 million location visits, including 120 million church visitors across 184,677 churches, 14 million grocery visitors across 7662 grocery stores, and 13.5 million gym visitors across 5483 gyms. Results:Analyzing the interaction between venue closure and changing mobility using a math.matical model shows that, across a broad range of model parameters, inconsistent or partial closure can be worse in terms of disease transmission as compared to scenarios with no closures at all. Importantly, changes in mobility patterns due to epidemic control measures can lead to increase in the future number of cases. In the most severe cases, individuals traveling to neighboring jurisdictions with different closure policies can result in an outbreak that would otherwise have been contained. To motivate our math.matical models, we turn to mobility data and find that while stay-at-home orders and closures decreased contacts in most areas of the USA, some specific activities and venues saw an increase in attendance and an increase in the distance visitors traveled to attend. We support this finding using search query data, which clearly shows a shift in in

关键词： Adaptive behavior COVID-19 Disease modeling Metapopulation models Mobility data

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Microwave spectro-polarimetry of matter and radiation across space and time

arXiv

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arXiv 2019年

作者： Delabrouille, Jacques Abitbol, Maximilian H. Aghanim, Nabila Ali-Haïmoud, Yacine Alonso, David Alvarez, Marcelo Banday, Anthony J. Bartlett, James G. Baselmans, Jochem Basu, Kaustuv Battaglia, Nicholas Climent, José Ramón Bermejo Bernal, José L. Béthermin, Matthieu Bolliet, Boris Bonato, Matteo Bouchet, François R. Breysse, Patrick C. Burigana, Carlo Cai, Zhen-Yi Chluba, Jens Churazov, Eugene Dannerbauer, Helmut de Bernardis, Paolo de Zotti, Gianfranco Valentino, Eleonora Di Dimastrogiovanni, Emanuela Endo, Akira Erler, Jens Ferraro, Simone Finelli, Fabio Fixsen, Dale Hanany, Shaul Hart, Luke Hernández-Monteagudo, Carlos Hill, J. Colin Hotinli, Selim C. Karatsu, Kenichi Karkare, Kirit Keating, Garrett K. Khabibullin, Ildar Kogut, Alan Kohri, Kazunori Kovetz, Ely D. Lagache, Guilaine Lesgourgues, Julien Madhavacheril, math.w Maffei, Bruno Mandolesi, Nazzareno Martins, Carlos Masi, Silvia math.r, John Melin, Jean-Baptiste Dizgah, Azadeh Moradinezhad Mroczkowski, Tony Mukherjee, Suvodip Nagai, Daisuke Negrello, Mattia Palanque-Delabrouille, Nathalie Paoletti, Daniela Patil, Subodh P. Piacentini, Francesco Raghunathan, Srinivasan Ravenni, Andrea Remazeilles, math.eu Revéret, Vincent Rodriguez, Louis Rotti, Aditya Martin, Jose-Alberto Rubiño Sayers, Jack Scott, Douglas Silk, Joseph Silva, Marta Souradeep, Tarun Sugiyama, Naonori Sunyaev, Rashid Switzer, Eric R. Tartari, Andrea Trombetti, Tiziana Zubeldia, Íñigo CNRS/IN2P3 Université Paris Diderot Paris Cedex 1375205 France IRFU CEA Université Paris Saclay Gif-sur-Yvette91191 France University of Oxford Denys Wilkinson Building Keble Road OxfordOX1 3RH United Kingdom Université Paris-Sud Bâtiment 121 Orsay91405 France Center for Cosmology and Particle Physics Department of Physics New York University New YorkNY10003 United States School of Physics and Astronomy Cardiff University The Parade CardiffCF24 3AA United Kingdom Berkeley Center for Cosmological Physics University of California BerkeleyCA94720 United States Lawrence Berkeley National Laboratory One Cyclotron Road BerkeleyCA94720 United States Institut de Recherche en Astrophysique et Planétologie 9 av du Colonel Roche BP 44346 Toulouse Cedex 431028 France Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive PasadenaCA91109 United States Faculty of Electrical Eng. Math. and Computer Sc. Delft Univ. of Technology Mekelweg 4 Delft2628 CD Netherlands SRON Netherlands Institute for Space Research Sorbonnelaan 2 Utrecht3584 CA Netherlands Argelander-Institut für Astronomie Universität Bonn Auf dem Hügel 71 BonnD-53121 Germany Department of Astronomy Cornell University IthacaNY14853 United States INAF - Osservatorio di Astrofisica e Scienza dello Spazio Via Gobetti 101 BolognaI-40129 Italy ICC University of Barcelona IEEC-UB Martí i Franques 1 BarcelonaE08028 Spain Aix Marseille Université CNRS CNES LAM Marseille France Jodrell Bank Centre for Astrophysics Dept. of Physics & Astronomy University of Manchester ManchesterM13 9PL United Kingdom INAF - Istituto di Radioastronomia Via Piero Gobetti 101 BolognaI-40129 Italy INAF - Osservatorio Astronomico di Padova Vicolo Osservatorio 5 PadovaI-35122 Italy Institut d’Astrophysique de Paris 98 bis Boulevard Arago Paris75014 France Canadian Institute for Theoretical Astrophysics University of Toronto ONM5S 3H8 Canada CAS Key Laboratory for

In the past few decades, a standard model of cosmology, ΛCDM, has emerged. According to our understanding, our Universe is about 13.8 billion years old, and expanded from an initial hot and dense state. Baryonic matter accounts for 5% of its present matter-energy content, non-baryonic dark matter for about 25%, and some unknown form of energy with negative pressure, dubbed dark energy, for the remaining 70%. The galaxies and clusters of galaxies that we observe today form by the gravitational collapse of tiny primordial fluctuations of the spacetime metric, thought to originate from an early stage of fast accelerated expansion, known as cosmic inflation. But very fundamental questions remain unanswered: we do not know what the dark matter and dark energy are, whether dark matter interacts, or if extra light particles exist. We are unsure whether inflation did indeed take place and exactly what physics was at work in the very early Universe. We still have to reconcile the laws of gravitation with the standard model of particle interactions – both of which are known to be incomplete and require extensions to explain existing observations. We do not know the topology of the Universe, or whether it is finite or infinite. We do not fully understand how structure forms, or why some structures on small scales appear to be incompatible with ΛCDM predictions. We do not have a convincing explanation for anomalies in the large-scale statistics of cosmic microwave background (CMB) anisotropies, except invoking chance multipole alignments and excursions in tails of the realization of a Gaussian random field. The distribution of matter and energy in the Universe, by virtue of being the product of physical laws and their effect on the Universe’s constituents, encodes answers to these questions. We thus propose to conduct an unprecedented full census of this distribution, over scales from one arcminute to the entire sky, and over 99% of cosmic history. The census will be carried ou

关键词： Galaxies

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