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Ambient carbon monoxide and daily mortality: a global time-series study in 337 cities

The Lancet. Planetary health 2021年第4期5卷 e191-e199页

作者： Kai Chen Susanne Breitner Kathrin Wolf Massimo Stafoggia Francesco Sera Ana M Vicedo-Cabrera Yuming Guo Shilu Tong Eric Lavigne Patricia Matus Nicolás Valdés Haidong Kan Jouni J K Jaakkola Niilo R I Ryti Veronika Huber Matteo Scortichini Masahiro Hashizume Yasushi Honda Baltazar Nunes Joana Madureira Iulian Horia Holobâcă Simona Fratianni Ho Kim Whanhee Lee Aurelio Tobias Carmen Íñiguez Bertil Forsberg Christofer Åström Martina S Ragettli Yue-Liang Leon Guo Bing-Yu Chen Shanshan Li Ai Milojevic Antonella Zanobetti Joel Schwartz Michelle L Bell Antonio Gasparrini Alexandra Schneider Department of Environmental Health Sciences Yale School of Public Health New Haven CT USA. Electronic address: kai.chen@yale.edu. Institute of Epidemiology Helmholtz Zentrum München-German Research Center for Environmental Health Neuherberg Germany Institute for Medical Information Processing Biometry and Epidemiology Ludwig-Maximilians-Universität München Munich Germany. Institute of Epidemiology Helmholtz Zentrum München-German Research Center for Environmental Health Neuherberg Germany. Department of Epidemiology Lazio Regional Health Service Rome Italy. Department of Public Health Environments and Society London School of Hygiene & Tropical Medicine London UK Department of Statistics Computer Science and Applications "G. Parenti" University of Florence Florence Italy. Institute of Social and Preventive Medicine University of Bern Bern Switzerland Oeschger Center for Climate Change Research University of Bern Bern Switzerland. Climate Air Quality Research Unit School of Public Health and Preventive Medicine Monash University Melbourne VIC Australia. Shanghai Children's Medical Center Shanghai Jiao Tong University School of Medicine Shanghai China School of Public Health Institute of Environment and Population Health Anhui Medical University Hefei China School of Public Health and Social Work Queensland University of Technology Brisbane QLD Australia Center for Global Health School of Public Health Nanjing Medical University Nanjing China. Air Health Science Division Health Canada Ottawa ON Canada School of Epidemiology and Public Health University of Ottawa Ottawa ON Canada. Department of Public Health Universidad de los Andes Santiago Chile. Faculty of Nursing and Midwifery Universidad de los Andes Santiago Chile. School of Public Health Key Lab of Public Health Safety of the Ministry of Education and Key Lab of Health Technology Assessment of the Ministry of Health Fudan University Shanghai China Shanghai Key Laboratory of Atmospheric Part

BACKGROUND:Epidemiological evidence on short-term association between ambient carbon monoxide (CO) and mortality is inconclusive and limited to single cities, regions, or countries. Generalisation of results from previous studies is hindered by potential publication bias and different modelling approaches. We therefore assessed the association between short-term exposure to ambient CO and daily mortality in a multicity, multicountry setting. METHODS:We collected daily data on air pollution, meteorology, and total mortality from 337 cities in 18 countries or regions, covering various periods from 1979 to 2016. All included cities had at least 2 years of both CO and mortality data. We estimated city-specific associations using confounder-adjusted generalised additive models with a quasi-Poisson distribution, and then pooled the estimates, accounting for their statistical uncertainty, using a random-effects multilevel meta-analytical model. We also assessed the overall shape of the exposure-response curve and evaluated the possibility of a threshold below which health is not affected. FINDINGS:Overall, a 1 mg/m increase in the average CO concentration of the previous day was associated with a 0·91% (95% CI 0·32-1·50) increase in daily total mortality. The pooled exposure-response curve showed a continuously elevated mortality risk with increasing CO concentrations, suggesting no threshold. The exposure-response curve was steeper at daily CO levels lower than 1 mg/m, indicating greater risk of mortality per increment in CO exposure, and persisted at daily concentrations as low as 0·6 mg/m or less. The association remained similar after adjustment for ozone but was attenuated after adjustment for particulate matter or sulphur dioxide, or even reduced to null after adjustment for nitrogen dioxide. INTERPRETATION:This international study is by far the largest epidemiological investigation on short-term CO-related mortality. We found significant associations between ambient

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The atacama cosmology telescope: DR5 maps of 18000 square degrees of the microwave sky from ACT 2008-2018 data

arXiv

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arXiv 2020年

作者： Naess, Sigurd Aiola, Simone Austermann, Jason E. Battaglia, Nick Beall, James A. Becker, Daniel T. Bond, Richard J. Calabrese, Erminia Choi, Steve K. Cothard, Nicholas F. Crowley, Kevin T. Darwish, Omar Datta, Rahul Denison, Edward V. Devlin, Mark Duell, Cody J. Duff, Shannon M. Duivenvoorden, Adriaan J. Dunkley, Jo Dünner, Rolando Fox, Anna E. Gallardo, Patricio A. Halpern, Mark Han, Dongwon Hasselfield, Matthew Hill, J. Colin Hilton, Gene C. Hilton, Matt Hincks, Adam D. Hložek, Renée Ho, Shuay-Pwu Patty Hubmayr, Johannes Huffenberger, Kevin Hughes, John P. Kosowsky, Arthur B. Louis, Thibaut Madhavacheril, Mathew S. McMahon, Jeff Moodley, Kavilan Nati, Federico Nibarger, John P. Niemack, Michael D. Page, Lyman Partridge, Bruce Salatino, Maria Schaan, Emmanuel Schillaci, Alessandro Schmitt, Benjamin Sherwin, Blake D. Sehgal, Neelima Sifón, Cristóbal Spergel, David Staggs, Suzanne Stevens, Jason Storer, Emilie Ullom, Joel N. Vale, Leila R. van Engelen, Alexander van Lanen, Jeff Vavagiakis, Eve M. Wollack, Edward J. Xu, Zhilei Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States Department of Astrophysical Sciences Peyton Hall Princeton University PrincetonNJ08544 United States Joseph Henry Laboratories of Physics Jadwin Hall Princeton University PrincetonNJ08544 United States Department of Physics and Astronomy Haverford College HaverfordPA19041 United States Laboratoire de l’Accélérateur Linéaire Univ. Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France NASA/Goddard Space Flight Center GreenbeltMD20771 United States Physics and Astronomy Department Stony Brook University Stony BrookNY11794 United States Astrophysics Research Centre University of KwaZulu-Natal Westville Campus Durban4041 South Africa Department of Physics California Institute of Technology PasadenaCA91125 United States Instituto de Física Pontificia Universidad Católica de Valparaíso Chile Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Berkeley Center for Cosmological Physics University of California BerkeleyCA94720 United States School of Physics and Astronomy Cardiff University The Parade Cardiff WalesCF24 3AA United Kingdom Department of Physics University of Milano-Bicocca Piazza della Scienza 3 MilanoMI20126 Italy Astrophysics Research Centre School of Mathematics Statistics and Computer Science University of KwaZulu-Natal Durban4041 South Africa Department of Physics and Astronomy Rutgers State University of New Jersey PiscatawayNJ08854-8019 United States StanfordCA United States Instituto de Astrofísica and Centro de Astro-Ingeniería Facultad de Física Pontificia Universidad Católica de Chile Av. Vicuña Mackenna 4860 Macul Santiago7820436 Chile Department of Physics Cornell University IthacaNY14853 United States Department of Astronomy Cornell University IthacaNY14853 United States Dept. of Physics and Astronomy Johns Hopkins University 3400 N. Charles St. BaltimoreMD21218 United States NIST Q

This paper presents a maximum-likelihood algorithm for combining sky maps with disparate sky coverage, angular resolution and spatially varying anisotropic noise into a single map of the sky. We use this to merge hundreds of individual maps covering the 2008–2018 ACT observing seasons, resulting in by far the deepest ACT maps released so far. We also combine the maps with the full Planck maps, resulting in maps that have the best features of both Planck and ACT: Planck’s nearly white noise on intermediate and large angular scales and ACT’s high-resolution and sensitivity on small angular scales. The maps cover over 18 000 square degrees, nearly half the full sky, at 100, 150 and 220 GHz. They reveal 4 000 optically-confirmed clusters through the Sunyaev Zel’dovich effect (SZ) and 18 500 point source candidates at > 5σ, the largest single collection of SZ clusters and millimeter wave sources to date. The multi-frequency maps provide millimeter images of nearby galaxies and individual Milky Way nebulae, and even clear detections of several nearby stars. Other anticipated uses of these maps include, for example, thermal SZ and kinematic SZ cluster stacking, CMB cluster lensing and galactic dust science. The method itself has negligible bias. However, due to the preliminary nature of some of the component data sets, we caution that these maps should not be used for precision cosmological analysis. The maps are part of ACT DR5, and are available on LAMBDA at https://***/product/act/actpol_prod_***. There is also a web atlas at https://***/public/snaess/actpol/dr5/atlas. © 2020, CC0.

关键词： Galaxies

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The atacama cosmology telescope: Combined kinematic and thermal sunyaev-zel’dovich measurements from BOSS CMASS and LOWZ halos

arXiv

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arXiv 2020年

作者： Schaan, Emmanuel Ferraro, Simone Amodeo, Stefania Battaglia, Nicholas Aiola, Simone Austermann, Jason E. Beall, James A. Bean, Rachel Becker, Daniel T. Bond, Richard J. Calabrese, Erminia Calafut, Victoria Choi, Steve K. Denison, Edward V. Devlin, Mark J. Duff, Shannon M. Duivenvoorden, Adriaan J. Dunkley, Jo Dünner, Rolando Gallardo, Patricio A. Guan, Yilun Han, Dongwon Hill, J. Colin Hilton, Gene C. Hilton, Matt Hložek, Renée Hubmayr, Johannes Huffenberger, Kevin M. Hughes, John P. Koopman, Brian J. MacInnis, Amanda McMahon, Jeff Madhavacheril, Mathew S. Moodley, Kavilan Mroczkowski, Tony Naess, Sigurd Nati, Federico Newburgh, Laura B. Niemack, Michael D. Page, Lyman A. Partridge, Bruce Salatino, Maria Sehgal, Neelima Schillaci, Alessandro Sifón, Cristóbal Smith, Kendrick M. Spergel, David N. Staggs, Suzanne Storer, Emilie R. Trac, Hy Ullom, Joel N. van Lanen, Jeff Vale, Leila R. van Engelen, Alexander Magaña, Mariana Vargas Vavagiakis, Eve M. Wollack, Edward J. Xu, Zhilei Lawrence Berkeley National Laboratory One Cyclotron Road BerkeleyCA94720 United States Berkeley Center for Cosmological Physics UC Berkeley CA94720 United States Department of Astronomy Cornell University IthacaNY14853 United States Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States Quantum Sensors Group NIST 325 Broadway BoulderCO80305 United States Canadian Institute for Theoretical Astrophysics University of Toronto 60 St. George Street TorontoONM5S 3H8 Canada School of Physics and Astronomy Cardiff University The Parade Cardiff WalesCF24 3AA United Kingdom Department of Physics Cornell University IthacaNY14853 United States Department of Physics and Astronomy University of Pennsylvania 209 South 33rd Street PhiladelphiaPA19104 United States Joseph Henry Laboratories of Physics Jadwin Hall Princeton University PrincetonNJ08544 United States Department of Astrophysical Sciences Peyton Hall Princeton University PrincetonNJ08544 United States Instituto de Astrofísica Centro de Astro-Ingeniería Facultad de Física Pontificia Universidad Católica de Chile Av. Vicuña Mackenna 4860 Macul Santiago7820436 Chile Department of Physics and Astronomy University of Pittsburgh PittsburghPA15260 United States Physics and Astronomy Department Stony Brook University Stony BrookNY11794 United States Department of Physics Columbia University New YorkNY10027 United States Astrophysics Research Centre University of KwaZulu-Natal Westville Campus Durban4041 South Africa School of Mathematics Statistics & Computer Science University of KwaZulu-Natal Westville Campus Durban4041 South Africa David A. Dunlap Department of Astronomy and Astrophysics University of Toronto 50 St. George Street TorontoONM5S3H4 Canada Dunlap Institute for Astronomy and Astrophysics University of Toronto 50 St. George Street TorontoONM5S3H4 Canada Department of Physics Florida State University TallahasseeFL32306 Uni

The scattering of cosmic microwave background (CMB) photons off the free-electron gas in galaxies and clusters leaves detectable imprints on high resolution CMB maps: the thermal and kinematic Sunyaev-Zel’dovich effects (tSZ and kSZ respectively). We use combined microwave maps from the Atacama Cosmology Telescope (ACT) DR5 and Planck in combination with the CMASS (mean redshift hzi = 0.55 and host halo mass hMviri = 3 × 1013M) and LOWZ (hzi = 0.31, hMviri = 5 × 1013M) galaxy catalogs from the Baryon Oscillation Spectroscopic Survey (BOSS DR10 and DR12), to study the gas associated with these galaxy groups. Using individual reconstructed velocities, we perform a stacking analysis and reject the no-kSZ hypothesis at 6.5 σ, the highest significance to date. This directly translates into a measurement of the electron number density profile, and thus of the gas density profile. Despite the limited signal to noise, the measurement shows at high significance that the gas density profile is more extended than the dark matter density profile, for any reasonable baryon abundance (formally > 90 σ for the cosmic baryon abundance). We simultaneously measure the tSZ signal, i.e. the electron thermal pressure profile of the same CMASS objects, and reject the no-tSZ hypothesis at 10 σ. We combine tSZ and kSZ measurements to estimate the electron temperature to 20% precision in several aperture bins, and find it comparable to the virial temperature. In a companion paper, we analyze these measurements to constrain the gas thermodynamics and the properties of feedback inside galaxy groups. We present the corresponding LOWZ measurements in this paper, ruling out a null kSZ (tSZ) signal at 2.9 (13.9) σ, and leave their interpretation to future work. This paper and the companion paper demonstrate that current CMB experiments can detect and resolve gas profiles in low mass halos and at high redshifts, which are the most sensitive to feedback in galaxy formation and the most difficult to

关键词： Cosmology

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Probing galaxy evolution in massive clusters using ACT and DES: Splashback as a cosmic clock

arXiv

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arXiv 2020年

作者： Adhikari, Susmita Shin, Tae-Hyeon Jain, Bhuvnesh Hilton, Matt Baxter, Eric Chang, Chihway Wechsler, Risa H. Battaglia, Nick Richard Bond, J. Bocquet, Sebastian Derose, Joseph Choi, Steve K. Devlin, Mark Dunkley, Jo Evrard, August E. Ferraro, Simone Colin Hill, J. Hughes, John P. Gallardo, Patricio A. Lokken, Martine Macinnis, Amanda McMahon, Jeffrey Madhavacheril, Mathew S. Nati, Frederico Newburgh, Laura B. Niemack, Michael D. Page, Lyman A. Palmese, Antonella Partridge, Bruce Rozo, Eduardo Rykoff, Eli Salatino, Maria Schillaci, Alessandro Sehgal, Neelima Sifón, Cristóbal To, Chun-Hao Wollack, Ed Wu, Hao-Yi Xu, Zhilei Aguena, Michel Allam, Sahar Amon, Alexandra Annis, James Avila, Santiago Bacon, David Bertin, Emmanuel Bhargava, Sunayana Brooks, David Burke, David L. Rosell, Aurelio C. Kind, Matias Carrasco Carretero, Jorge Castander, Francisco Javier Choi, Ami Costanzi, Matteo da Costa, Luiz N. Vicente, Juan D.E. Desai, Shantanu Diehl, Thomas H. Doel, Peter Everett, Spencer Ferrero, Ismael Ferté, Agnès Flaugher, Brenna Fosalba, Pablo Frieman, Josh García-Bellido, Juan Gaztanaga, Enrique Gruen, Daniel Gruendl, Robert A. Gschwend, Julia Gutierrez, Gaston Hartley, Will G. Hinton, Samuel R. Hollowood, Devon L. Honscheid, Klaus James, David J. Jeltema, Tesla Kuehn, Kyler Kuropatkin, Nikolay Lahav, Ofer Lima, Marcos Maia, Marcio A.G. Marshall, Jennifer L. Martini, Paul Melchior, Peter Menanteau, Felipe Miquel, Ramon Morgan, Robert Ogando, Ricardo L.C. Paz-Chinchón, Francisco Malagón, Andrés Plazas Sanchez, Eusebio Santiago, Basilio Scarpine, Vic Serrano, Santiago Sevilla-Noarbe, Ignacio Smith, Mathew Soares-Santos, Marcelle Suchyta, Eric Swanson, Molly E.C. Varga, Tamas N. Wilkinson, Reese D. Zhang, Yuanyuan Austermann, Jason E. Beall, James A. Becker, Daniel T. Denison, Edward V. Duff, Shannon M. Hilton, Gene C. Hubmayr, Johannes Ullom, Joel N. Lanen, Jeff V.A.N. Vale, Leila R. Kavli Institute for Particle Astrophysics and Cosmology Department of Physics Stanford University StanfordCA94305 United States SLAC National Accelerator Laboratory Menlo ParkCA94025 United States Department of Physics and Astronomy University of Pennsylvania 209 S. 33rd St. PhiladelphiaPA19104 United States Astrophysics Research Centre University of KwaZulu-Natal Westville Campus Durban4041 South Africa School of Mathematics Statistics & Computer Science University of KwaZulu-Natal Westville Campus Durban4041 South Africa Institute for Astronomy University of Hawaii ManoaHI United States Kavli Institute for Cosmological Physics University of Chicago ChicagoIL60637 United States Department of Physics University of Chicago ChicagoIL60637 United States Department of Astronomy Cornell University IthacaNY14853 United States Canadian Institute for Theoretical Astrophysics University of Toronto 60 St. George Street TorontoONM5S 3H8 Canada Faculty of Physics Ludwig-Maximilians-Universität Scheinerstr. 1 Munich81679 Germany Department of Astronomy and Astrophysics University of California Santa Cruz 1156 High Street Santa CruzCA95064 United States Berkeley Center for Cosmological Physics BerkeleyCA94720 United States Department of Physics University of California BerkeleyCA94720 United States Department of Physics Cornell University IthacaNY14853 United States Department of Astrophysical Sciences Princeton University PrincetonNJ08544 United States Department of Physics Princeton University PrincetonNJ08544 United States Department of Astronomy University of Michigan MI United States Lawrence Berkeley National Laboratory One Cyclotron Road BerkeleyCA94720 United States Department of Physics Columbia University New YorkNY10027 United States Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States Department of Physics and Astronomy Rutgers State University of New Jersey 136 Frelinghuyse

We measure the projected number density profiles of galaxies and the splashback feature in clusters selected by the Sunyaev–Zeldovich (SZ) effect from the Advanced Atacama Cosmology Telescope (AdvACT) survey using galaxies observed by the Dark Energy Survey (DES). The splashback radius for the complete galaxy sample is consistent with theoretical measurements from CDM-only simulations, and is located at 2.4+−0034 Mpc h−1. We split the sample based on galaxy color and find significant differences in the profile shapes. Red galaxies and those in the green valley show a splashback-like minimum in their slope profile consistent with theoretical predictions, while the bluest galaxies show a weak feature that appears at a smaller radius. We develop a mapping of galaxies to subhalos in N-body simulations by splitting subhalos based on infall time onto the cluster halos. We find that the location of the steepest slope and differences in the shapes of the profiles can be mapped to differences in the average time of infall of galaxies of different colors. The minima of the slope in the galaxy profiles trace a discontinuity in the phase space of dark matter halos. By relating spatial profiles to infall time for galaxies of different colours, we can use splashback as a clock to understand galaxy quenching. We find that red galaxies have on average been in their clusters for over 3.2 Gyrs, green galaxies about 2.2 Gyrs, while blue galaxies have been accreted most recently and have not reached apocenter. Using the information from the complete radial profiles, we fit a simple quenching model and find that the onset of galaxy quenching in clusters occurs after a delay of about a gigayear, and that galaxies quench rapidly thereafter with an exponential timescale of 0.6 Gyr. Copyright © 2020, The Authors. All rights reserved.

关键词： Galaxies

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Atacama Cosmology Telescope: Component-separated maps of CMB temperature and the thermal Sunyaev-Zel’dovich effect

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Physical Review D 2020年第2期102卷 023534-023534页

作者： Mathew S. Madhavacheril J. Colin Hill Sigurd Næss Graeme E. Addison Simone Aiola Taylor Baildon Nicholas Battaglia Rachel Bean J. Richard Bond Erminia Calabrese Victoria Calafut Steve K. Choi Omar Darwish Rahul Datta Mark J. Devlin Joanna Dunkley Rolando Dünner Simone Ferraro Patricio A. Gallardo Vera Gluscevic Mark Halpern Dongwon Han Matthew Hasselfield Matt Hilton Adam D. Hincks Renée Hložek Shuay-Pwu Patty Ho Kevin M. Huffenberger John P. Hughes Brian J. Koopman Arthur Kosowsky Martine Lokken Thibaut Louis Marius Lungu Amanda MacInnis Loïc Maurin Jeffrey J. McMahon Kavilan Moodley Federico Nati Michael D. Niemack Lyman A. Page Bruce Partridge Naomi Robertson Neelima Sehgal Emmanuel Schaan Alessandro Schillaci Blake D. Sherwin Cristóbal Sifón Sara M. Simon David N. Spergel Suzanne T. Staggs Emilie R. Storer Alexander van Engelen Eve M. Vavagiakis Edward J. Wollack Zhilei Xu Centre for the Universe Perimeter Institute for Theoretical Physics Waterloo Ontario Canada N2L 2Y5 Department of Astrophysical Sciences Princeton University 4 Ivy Lane Princeton New Jersey 08544 USA Department of Physics Columbia University 550 West 120th Street New York New York 10027 USA Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New York New York 10010 USA School of Natural Sciences Institute for Advanced Study Princeton New Jersey 08540 USA Department of Physics and Astronomy Johns Hopkins University Baltimore Maryland 21218 USA Department of Physics University of Michigan Ann Arbor Michigan 48103 USA Department of Astronomy Cornell University Ithaca New York 14853 USA Canadian Institute for Theoretical Astrophysics University of Toronto 60 St. George St. Toronto Ontario M5S 3H8 Canada School of Physics and Astronomy Cardiff University The Parade Cardiff CF24 3AA United Kingdom Department of Applied Mathematics and Theoretical Physics University of Cambridge Wilberforce Road Cambridge CB3 0WA United Kingdom Department of Physics and Astronomy University of Pennsylvania 209 South 33rd Street Philadelphia Pennsylvania 19104 USA Joseph Henry Laboratories of Physics Jadwin Hall Princeton University Princeton New Jersey 08544 USA Instituto de Astrofísica and Centro de Astro-Ingeniería Facultad de Física Pontificia Universidad Católica de Chile Av. Vicuña Mackenna 4860 7820436 Macul Santiago Chile Physics Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA Department of Physics Cornell University 109 Clark Hall Ithaca New York 14853 USA Department of Physics and Astronomy University of Southern California Los Angeles California 90089-0484 USA Department of Physics and Astronomy University of British Columbia Vancouver British Columbia Canada V6T 1Z1 Physics and Astronomy Department Stony Brook University Stony Brook New York 11794 USA Astrophysics & Cosmology Research Unit Sc

Optimal analyses of many signals in the cosmic microwave background (CMB) require map-level extraction of individual components in the microwave sky, rather than measurements at the power spectrum level alone. To date, nearly all map-level component separation in CMB analyses has been performed exclusively using satellite data. In this paper, we implement a component separation method based on the internal linear combination (ILC) approach which we have designed to optimally account for the anisotropic noise (in the 2D Fourier domain) often found in ground-based CMB experiments. Using this method, we combine multifrequency data from the Planck satellite and the Atacama Cosmology Telescope Polarimeter (ACTPol) to construct the first wide-area (≈2100 sq. deg.), arcminute-resolution component-separated maps of the CMB temperature anisotropy and the thermal Sunyaev-Zel’dovich (tSZ) effect sourced by the inverse-Compton scattering of CMB photons off hot, ionized gas. Our ILC pipeline allows for explicit deprojection of various contaminating signals, including a modified blackbody approximation of the cosmic infrared background (CIB) spectral energy distribution. The cleaned CMB maps will be a useful resource for CMB lensing reconstruction, kinematic SZ cross-correlations, and primordial non-Gaussianity studies. The tSZ maps will be used to study the pressure profiles of galaxies, groups, and clusters through cross-correlations with halo catalogs, with dust contamination controlled via CIB deprojection. The data products described in this paper are available on LAMBDA.

关键词： Cosmic microwave background Cosmology

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Publisher Correction: Brain charts for the human lifespan

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Nature 2022年第7931期610卷 E6页

作者： R A I Bethlehem J Seidlitz S R White J W Vogel K M Anderson C Adamson S Adler G S Alexopoulos E Anagnostou A Areces-Gonzalez D E Astle B Auyeung M Ayub J Bae G Ball S Baron-Cohen R Beare S A Bedford V Benegal F Beyer J Blangero M Blesa Cábez J P Boardman M Borzage J F Bosch-Bayard N Bourke V D Calhoun M M Chakravarty C Chen C Chertavian G Chetelat Y S Chong J H Cole A Corvin M Costantino E Courchesne F Crivello V L Cropley J Crosbie N Crossley M Delarue R Delorme S Desrivieres G A Devenyi M A Di Biase R Dolan K A Donald G Donohoe K Dunlop A D Edwards J T Elison C T Ellis J A Elman L Eyler D A Fair E Feczko P C Fletcher P Fonagy C E Franz L Galan-Garcia A Gholipour J Giedd J H Gilmore D C Glahn I M Goodyer P E Grant N A Groenewold F M Gunning R E Gur R C Gur C F Hammill O Hansson T Hedden A Heinz R N Henson K Heuer J Hoare B Holla A J Holmes R Holt H Huang K Im J Ipser C R Jack A P Jackowski T Jia K A Johnson P B Jones D T Jones R S Kahn H Karlsson L Karlsson R Kawashima E A Kelley S Kern K W Kim M G Kitzbichler W S Kremen F Lalonde B Landeau S Lee J Lerch J D Lewis J Li W Liao C Liston M V Lombardo J Lv C Lynch T T Mallard M Marcelis R D Markello S R Mathias B Mazoyer P McGuire M J Meaney A Mechelli N Medic B Misic S E Morgan D Mothersill J Nigg M Q W Ong C Ortinau R Ossenkoppele M Ouyang L Palaniyappan L Paly P M Pan C Pantelis M M Park T Paus Z Pausova D Paz-Linares A Pichet Binette K Pierce X Qian J Qiu A Qiu A Raznahan T Rittman A Rodrigue C K Rollins R Romero-Garcia L Ronan M D Rosenberg D H Rowitch G A Salum T D Satterthwaite H L Schaare R J Schachar A P Schultz G Schumann M Schöll D Sharp R T Shinohara I Skoog C D Smyser R A Sperling D J Stein A Stolicyn J Suckling G Sullivan Y Taki B Thyreau R Toro N Traut K A Tsvetanov N B Turk-Browne J J Tuulari C Tzourio É Vachon-Presseau M J Valdes-Sosa P A Valdes-Sosa S L Valk T van Amelsvoort S N Vandekar L Vasung L W Victoria S Villeneuve A Villringer P E Vértes K Wagstyl Y S Wang S K Warfield V Warrier E Westman M L Westwater H C Whalley A V Witte N Yang B Yeo H Y Autism Research Centre Department of Psychiatry University of Cambridge Cambridge UK. rb643@medschl.cam.ac.uk. Brain Mapping Unit Department of Psychiatry University of Cambridge Cambridge UK. rb643@medschl.cam.ac.uk. Department of Psychiatry University of Pennsylvania Philadelphia PA USA. jakob.seidlitz@pennmedicine.upenn.edu. Department of Child and Adolescent Psychiatry and Behavioral Science The Children's Hospital of Philadelphia Philadelphia PA USA. jakob.seidlitz@pennmedicine.upenn.edu. Lifespan Brain Institute The Children's Hospital of Philadelphia and Penn Medicine Philadelphia PA USA. jakob.seidlitz@pennmedicine.upenn.edu. Department of Psychiatry University of Cambridge Cambridge UK. MRC Biostatistics Unit University of Cambridge Cambridge UK. Department of Psychiatry University of Pennsylvania Philadelphia PA USA. Lifespan Informatics & Neuroimaging Center University of Pennsylvania Philadelphia PA USA. Department of Psychology Yale University New Haven CT USA. Developmental Imaging Murdoch Children's Research Institute Melbourne Victoria Australia. Department of Medicine Monash University Melbourne Victoria Australia. UCL Great Ormond Street Institute for Child Health London UK. Weill Cornell Institute of Geriatric Psychiatry Department of Psychiatry Weill Cornell Medicine New York USA. Department of Pediatrics University of Toronto Toronto Canada. Holland Bloorview Kids Rehabilitation Hospital Toronto Canada. The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for NeuroInformation University of Electronic Science and Technology of China Chengdu China. University of Pinar del Río "Hermanos Saiz Montes de Oca" Pinar del Río Cuba. MRC Cognition and Brain Sciences Unit University of Cambridge Cambridge UK. Autism Research Centre Department of Psychiatry University of Cambridge Cambridge UK. Department of Psychology School of Philosophy Psychology and Language Sciences University of Edinburgh Edinburgh UK. Queen's

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A separability-entanglement classifier via machine learning

arXiv

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arXiv 2017年

作者： Lu, Sirui Huang, Shilin Li, Keren Li, Jun Chen, Jianxin Lu, Dawei Ji, Zhengfeng Shen, Yi Zhou, Duanlu Zeng, Bei Department of Physics Tsinghua University Beijing100084 China Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Beijing Computational Science Research Center Beijing100193 China Department of Mathematics & Statistics University of Guelph GuelphONN1G 2W1 Canada Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD United States Department of Physics Southern University of Science and Technology Shenzhen518055 China Centre for Quantum Computation & Intelligent Systems School of Software Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Department of Statistics and Actuarial Science University of Waterloo WaterlooONN2L 3G1 Canada Institute of Physics Chinese Academy of Sciences Beijing100190 China

The problem of determining whether a given quantum state is entangled lies at the heart of quantum information processing, which is known to be an NP-hard problem in general. Despite the proposed many methods such as the positive partial transpose (PPT) criterion and the k-symmetric extendibility criterion to tackle this problem in practice, none of them enables a general, effective solution to the problem even for small dimensions. Explicitly, separable states form a high-dimensional convex set, which exhibits a vastly complicated structure. In this work, we build a new separability-entanglement classifier underpinned by machine learning techniques. Our method outperforms the existing methods in generic cases in terms of both speed and accuracy, opening up the avenues to explore quantum entanglement via the machine learning approach. Copyright © 2017, The Authors. All rights reserved.

关键词： Quantum entanglement

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A second update on mapping the human genetic architecture of COVID-19

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Nature 2023年第7977期621卷 E7-E26页

作者： Masahiro Kanai Christine Stevens Benjamin M. Neale Mark Daly Andrea Ganna Amy Trankiem Mary K. Balaconis Samuli Ripatti Lindo Nkambul Mark J. Daly Sam Bryant Matthew Solomonson Shea J. Andrews Mattia Cordioli Juha Karjalainen Juha Mehtonen Matti Pirinen Andrea Corbetta Bradley Jermy Kati Donner Katja Kivinen Aarno Palotie Mari Kaunisto Kumar Veerapen Konrad J. Karczewski Alicia R. Martin Elizabeth G. Atkinson Kristin Tsuo Nikolas Baya Rahul Gupta Raymond K. Walters Duncan S. Palmer Gopal Sarma Nathan Cheng Wenhan Lu Claire Churchhouse Jacqueline I. Goldstein Daniel King Wei Zhou Cotton Seed Hilary Finucane F. Kyle Satterstrom Gita A. Pathak Akiko Iwasaki Karolina Chwialkowska Karolina Chwiałkowska Brooke N. Wolford Hajar Fauzan Ahmad Shea Andrews Kathrin Aprile von Hohenstaufen Puoti Palwende R. Boua Guillaume Butler-Laporte Celia M. T. Greenwood Bartha M. Knoppers Mark Lathrop Carmen L. Cadilla Francesca Colombo Nicole Dueker Chloe Kirk Atanu Kumar Dutta Yasser M. El-Sherbiny Jehan J. El-Jawhari Doaa Shahin Ahmed Elzeiny Tamer A. Mansour Madonna M. Eltoukhy Attia A. S. Mohamed Sahar Esmaeeli Annika Faucon Israel Fernández Cadenas Israel Fernandez-Cadenas Laia Llucià-Carol Natalia Cullell Elena Muiño Jara Cárcel-Márquez Margherita Francescatto Laurent Francioli Lindokuhle Nkambule Jatin Arora Soumya Raychaudhuri Caroline Cusick Lude Franke Macarena Fuentes Macarena Fuentes-Guajardo David Gómez Cabrero Emi N. Harry Philip Jansen József L. Szentpéteri Réka Várnai Elżbieta Kaja Athanasios Kousathanas Dorote Pasko Mark J. Caulfield Alex Stuckey Christopher A. Odhams Susan Walker Daniel Rhodes Richard H. Scott Loukas Moutsianas Afshan Siddiq Peter Goddard Sally Donovan Tala Zainy Fiona Maleady-Crowe Linda Todd Shahla Salehi Greg Elgar Georgia Chan Prabhu Arumugam Christine Patch Augusto Rendon Tom A. Fowler Jose E. Krieger Sanjay K. Patel Audrey Lemaçon Sophie Limou Pietro Lió Eirini Marouli Charles Hinds Minttu M. Marttila Carolina Medina-Gómez Isabelle Migeotte Soumyajit Mondal Andrés Moreno-Estrada Leire Moya Tomok Broad Institute of MIT and Harvard Cambridge MA USA Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Program in Bioinformatics and Integrative Genomics Harvard Medical School Boston MA USA Institute for Molecular Medicine Finland (FIMM) University of Helsinki Helsinki Finland Institute for Molecular Medicine Finland University of Helsinki Helsinki Finland Institute for Molecular Medicine Finland (FIMM) HiLIFE University of Helsinki Helsinki Finland Public Health Faculty of Medicine University of Helsinki Helsinki Finland Analytic & Translational Genetics Unit Massachusetts General Hospital Boston MA USA Stanley Center for Psychiatric Research & Program in Medical and Population Genetics Cambridge UK Institute for Molecular Medicine Finland (FIMM) Univerisity of Helsinki Helsinki Finland University of California San Francisco San Francisco CA USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Program in Biological and Biomedical Sciences Harvard Medical School Boston MA USA Department of Psychiatry School of Medicine Yale University New Haven CT USA Veteran Affairs Connecticut Healthcare System West Haven CT USA Yale University New Haven CT USA Centre for Bioinformatics and Data Analysis Medical University of Bialystok Bialystok Poland Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA Faculty of Industrial Sciences and Technology Universiti Malaysia Pahang Pahang Malaysia Icahn School of Medicine at Mount Sinai New York NY USA Genolier Innovation Network and Hub Swiss Medical Network Genolier Healthcare Campus Genolier Switzerland Immediate Independent Multidisciplinary Med & Biotech Research Association Milan Italy Clinical Research Unit of Nanor

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Planck intermediate results. LVII. Joint Planck LFI and HFI data processing

arXiv

引用

arXiv 2020年

作者： Akrami, Y. Andersen, K.J. Ashdown, M. Baccigalupi, C. Ballardini, M. Banday, A.J. Barreiro, R.B. Bartolo, N. Basak, S. Benabed, K. Bernard, J.-P. Bersanelli, M. Bielewicz, P. Bond, J.R. Borrill, J. Burigana, C. Butler, R.C. Calabrese, E. Casaponsa, B. Chiang, H.C. Colombo, L.P.L. Combet, C. Crill, B.P. Cuttaia, F. de Bernardis, P. de Rosa, A. de Zotti, G. Delabrouille, J. Di Valentino, E. Diego, J.M. Doré, O. Douspis, M. Dupac, X. Eriksen, H.K. Fernandez-Cobos, R. Finelli, F. Frailis, M. Fraisse, A.A. Franceschi, E. Frolov, A. Galeotta, S. Galli, S. Ganga, K. Gerbino, M. Ghosh, T. González-Nuevo, J. Górski, K.M. Gruppuso, A. Gudmundsson, J.E. Handley, W. Helou, G. Herranz, D. Hildebrandt, S.R. Hivon, E. Huang, Z. Jaffe, A.H. Jones, W.C. Keihänen, E. Keskitalo, R. Kiiveri, K. Kim, J. Kisner, T.S. Krachmalnicoff, N. Kunz, M. Kurki-Suonio, H. Lasenby, A. Lattanzi, M. Lawrence, C.R. Le Jeune, M. Levrier, F. Liguori, M. Lilje, P.B. Lilley, M. Lindholm, V. López-Caniego, M. Lubin, P.M. Macías-Pérez, J.F. Maino, D. Mandolesi, N. Marcos-Caballero, A. Maris, M. Martin, P.G. Martínez-González, E. Matarrese, S. Mauri, N. McEwen, J.D. Meinhold, P.R. Mennella, A. Migliaccio, M. Mitra, S. Molinari, D. Montier, L. Morgante, G. Moss, A. Natoli, P. Paoletti, D. Partridge, B. Patanchon, G. Pearson, D. Pearson, T.J. Perrotta, F. Piacentini, F. Polenta, G. Rachen, J.P. Reinecke, M. Remazeilles, M. Renzi, A. Rocha, G. Rosset, C. Roudier, G. Rubiño-Martín, J.A. Ruiz-Granados, B. Salvati, L. Savelainen, M. Scott, D. Sirignano, C. Sirri, G. Spencer, L.D. Suur-Uski, A.-S. Svalheim, T.L. Tauber, J.A. Tavagnacco, D. Tenti, M. Terenzi, L. Thommesen, H. Toffolatti, L. Tomasi, M. Tristram, M. Trombetti, T. Valiviita, J. van Tent, B. Vielva, P. Villa, F. Vittorio, N. Wandelt, B.D. Wehus, I.K. Zacchei, A. Zonca, A. APC AstroParticule et Cosmologie Université Paris Diderot CNRS/IN2P3 CEA/lrfu Observatoire de Paris Sorbonne Paris Cité 10 rue Alice Domon et Léonie Duquet Paris Cedex 1375205 France African Institute for Mathematical Sciences 6-8 Melrose Road Muizenberg Cape Town South Africa Astrophysics Group Cavendish Laboratory University of Cambridge J J Thomson Avenue CambridgeCB3 0HE United Kingdom Astrophysics & Cosmology Research Unit School of Mathematics Statistics & Computer Science University of KwaZulu-Natal Westville Campus Private Bag X54001 Durban4000 South Africa CITA University of Toronto 60 St. George St. TorontoONM5S 3H8 Canada CNRS IRAP 9 Av. colonel Roche BP 44346 Toulouse cedex 4F-31028 France Cahill Center for Astronomy and Astrophysics California Institute of Technology PasadenaCA91125 United States California Institute of Technology PasadenaCA United States Computational Cosmology Center Lawrence Berkeley National Laboratory BerkeleyCA United States Département de Physique Théorique Université de Genève 24 Quai E. Ansermet Genève 41211 Switzerland Département de Physique École normale supérieure PSL Research University CNRS 24 rue Lhomond Paris75005 France La Laguna TenerifeE-38206 Spain Departamento de Física Universidad de Oviedo C/ Federico García Lorca 18 Oviedo Spain Department of Astrophysics IMAPP Radboud University P.O. Box 9010 Nijmegen6500 GL Netherlands Department of Physics & Astronomy University of British Columbia 6224 Agricultural Road VancouverBC Canada Department of Physics & Astronomy University of the Western Cape Cape Town7535 South Africa Department of Physics Gustaf Hällströmin katu 2a University of Helsinki Helsinki Finland Department of Physics Princeton University PrincetonNJ United States Department of Physics University of California Santa BarbaraCA United States Dipartimento di Fisica e Astronomia G. Galilei Università degli Studi di Padova via Marzolo 8 Padova35131 It

We present the NPIPE processing pipeline, which produces calibrated frequency maps in temperature and polarization from data from the Planck Low Frequency Instrument (LFI) and High Frequency Instrument (HFI) using high-performance computers. NPIPE represents a natural evolution of previous Planck analysis efforts, and combines some of the most powerful features of the separate LFI and HFI analysis pipelines. For example, following the LFI 2018 processing procedure, NPIPE uses foreground polarization priors during the calibration stage in order to break scanning-induced degeneracies. Similarly, NPIPE employs the HFI 2018 time-domain processing methodology to correct for bandpass mismatch at all frequencies. In addition, NPIPE introduces several improvements, including, but not limited to: inclusion of the 8 % of data collected during repointing manoeuvres;smoothing of the LFI reference load data streams;in-flight estimation of detector polarization parameters;and construction of maximally independent detector-set split maps. For component-separation purposes, important improvements include: maps that retain the CMB Solar dipole, allowing for high-precision relative calibration in higher-level analyses;well-defined single-detector maps, allowing for robust CO extraction;and HFI temperature maps between 217 and 857 GHz that are binned into 0.09 pixels (Nside = 4096), ensuring that the full angular information in the data is represented in the maps even at the highest Planck resolutions. The net effect of these improvements is lower levels of noise and systematics in both frequency and component maps at essentially all angular scales, as well as notably improved internal consistency between the various frequency channels. Based on the NPIPE maps, we present the first estimate of the Solar dipole determined through component separation across all nine Planck frequencies. The amplitude is (3366.6 ± 2.7) µK, consistent with, albeit slightly higher than, earlier estimates.

关键词： Cosmology

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Enhancing quantum control by bootstrapping a quantum processor of 12 qubits

arXiv

引用

arXiv 2017年

作者： Lu, Dawei Li, Keren Li, Jun Katiyar, Hemant Park, Annie Jihyun Feng, Guanru Xin, Tao Li, Hang Long, Guilu Brodutch, Aharon Baugh, Jonathan Zeng, Bei Laflamme, Raymond Department of Physics Southern University of Science and Technology Shenzhen518055 China Institute for Quantum Computing Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada State Key Laboratory of Low-Dimensional Quantum Physics Department of Physics Tsinghua University Beijing100084 China Beijing Computational Science Research Center Beijing100193 China Max-Planck-Institutfür Quantenoptik GarchingD-85748 Germany Center for Quantum Information and Quantum Control Department of Physics Department of Electrical and Computer Engineering University of Toronto TorontoONM5S 3H6 Canada Department of Mathematics and Statistics University of Guelph GuelphONN1G 2W1 Canada Perimeter Institute for Theoretical Physics Waterloo ONN2L 2Y5 Canada

Accurate and efficient control of quantum systems is one of the central challenges for quantum information processing. Current state-of-the-art experiments rarely go beyond 10 qubits and in most cases demonstrate only limited control. Here we demonstrate control of a 12-qubit system, and show that the system can be employed as a quantum processor to optimize its own control sequence by using measurement-based feedback control (MQFC). The final product is a control sequence for a complex 12-qubit task: preparation of a 12-coherent state. The control sequence is about 10% more accurate than the one generated by the standard (classical) technique, showing that MQFC can correct for unknown imperfections. Apart from demonstrating a high level of control over a relatively large system, our results show that even at the 12-qubit level, a quantum processor can be a useful lab instrument. As an extension of our work, we propose a method for combining the MQFC technique with a twirling protocol, to optimize the control sequence that produces a desired Clifford gate. Copyright © 2017, The Authors. All rights reserved.

关键词： Quantum optics

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