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Measurements of the temperature and E-mode polarization of the cosmic microwave background from the full 500-square-degree SPTpol dataset

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Physical Review D 2025年第12期111卷 123513-123513页

作者： T.-L. Chou P. A. R. Ade A. J. Anderson J. E. Austermann L. Balkenhol J. A. Beall A. N. Bender B. A. Benson F. Bianchini L. E. Bleem J. E. Carlstrom C. L. Chang P. Chaubal H. C. Chiang R. Citron C. Corbett Moran T. M. Crawford A. T. Crites T. de Haan M. A. Dobbs D. Dutcher W. Everett J. Gallicchio E. M. George N. Gupta N. W. Halverson G. P. Holder W. L. Holzapfel J. D. Hrubes N. Huang J. Hubmayr K. D. Irwin L. Knox A. T. Lee D. Li A. Lowitz J. J. McMahon J. Montgomery T. Natoli J. P. Nibarger G. I. Noble V. Novosad Y. Omori S. Padin S. Patil C. Pryke W. Quan C. L. Reichardt J. E. Ruhl B. R. Saliwanchik K. K. Schaffer C. Sievers G. Smecher A. A. Stark C. Tucker T. Veach J. D. Vieira G. Wang N. Whitehorn W. L. K. Wu V. Yefremenko J. A. Zebrowski Department of Astronomy and Astrophysics University of Chicago 5640 South Ellis Avenue Chicago Illinois 60637 USA Kavli Institute for Cosmological Physics University of Chicago 5640 South Ellis Avenue Chicago Illinois 60637 USA Cardiff University Cardiff CF10 3XQ United Kingdom Fermi National Accelerator Laboratory MS209 P.O. Box 500 Batavia Illinois 60510 USA NIST Quantum Devices Group 325 Broadway Mailcode 817.03 Boulder Colorado 80305 USA Department of Physics University of Colorado Boulder Colorado 80309 USA Sorbonne Universit’e CNRS UMR 7095 Institut d’Astrophysique de Paris 98 bis bd Arago 75014 Paris France High Energy Physics Division Argonne National Laboratory 9700 South Cass Avenue Argonne Illinois 60439 USA SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo Park California 94025 USA Department of Physics University of Chicago 5640 South Ellis Avenue Chicago Illinois 60637 USA Enrico Fermi Institute University of Chicago 5640 South Ellis Avenue Chicago Illinois 60637 USA School of Physics University of Melbourne Parkville Victoria 3010 Australia Department of Physics McGill University 3600 Rue University Montreal Quebec H3A 2T8 Canada School of Mathematics Statistics and Computer Science University of KwaZulu-Natal Durban South Africa University of Chicago 5640 South Ellis Avenue Chicago Illinois 60637 USA Jet Propulsion Laboratory Pasadena California 91109 USA Department of Physics Cornell University Ithaca New York USA Department of Astronomy Cornell University Ithaca New York USA Department of Physics University of California Berkeley California 94720 USA Physics Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA High Energy Accelerator Research Organization (KEK) Tsukuba Ibaraki 305-0801 Japan Canadian Institute for Advanced Research CIFAR Program in Gravity and the Extreme Universe Toronto Ontario M5G 1Z8 Canada Joseph Henry Laboratories of Physics Jadwin Hall Princ

Using the full four-year SPTpol 500 deg2 dataset in both the 95 and 150 GHz frequency bands, we present measurements of the temperature and E-mode polarization of the cosmic microwave background (CMB), as well as the E-mode polarization autopower spectrum (EE) and temperature-E-mode cross-power spectrum (TE) in the angular multipole range 50<ℓ<8000. We find the SPTpol dataset to be self-consistent, passing several internal consistency tests based on maps, frequency bands, bandpowers, and cosmological parameters. The full SPTpol dataset is well-fit by the ΛCDM model, for which we find H0=70.48±2.16 km s−1 Mpc−1 and Ωm=0.271±0.026, when using only the SPTpol data and a Planck-based prior on the optical depth to reionization. The ΛCDM parameter constraints are consistent across the 95 GHz-only, 150 GHz-only, TE-only, and EE-only data splits. Between the ℓ<1000 and ℓ>1000 data splits, the ΛCDM parameter constraints are borderline consistent at the ∼2σ level. This consistency improves when including a parameter AL, the degree of lensing of the CMB inferred from the smearing of acoustic peaks. When marginalized over AL, the ΛCDM parameter constraints from SPTpol are consistent with those from Planck. The power spectra presented here are the most sensitive measurements of the lensed CMB damping tail to date for roughly ℓ>1700 in TE and ℓ>2000 in EE.

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Optimal CMB lensing reconstruction and parameter estimation with SPTpol data

arXiv

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arXiv 2020年

作者： Millea, Marius Daley, C.M. Chou, T.-L. Anderes, E. Ade, P.A.R. Anderson, A.J. Austermann, J.E. Avva, J.S. Beall, J.A. Bender, A.N. Benson, B.A. Bianchini, F. Bleem, L.E. Carlstrom, J.E. Chang, C.L. Chaubal, P. Chiang, H.C. Citron, R. Corbett Moran, C. Crawford, T.M. Crites, A.T. de Haan, T. Dobbs, M.A. Everett, W. Gallicchio, J. George, E.M. Goeckner-Wald, N. Guns, S. Gupta, N. Halverson, N.W. Henning, J.W. Hilton, G.C. Holder, G.P. Holzapfel, W.L. Hrubes, J.D. Huang, N. Hubmayr, J. Irwin, K.D. Knox, L. Lee, A.T. Li, D. Lowitz, A. McMahon, J.J. Meyer, S.S. Mocanu, L.M. Montgomery, J. Natoli, T. Nibarger, J.P. Noble, G. Novosad, V. Omori, Y. Padin, S. Patil, S. Pryke, C. Reichardt, C.L. Ruhl, J.E. Saliwanchik, B.R. Schaffer, K.K. Sievers, C. Smecher, G. Stark, A.A. Thorne, B. Tucker, C. Veach, T. Vieira, J.D. Wang, G. Whitehorn, N. Wu, W.L.K. Yefremenko, V. Department of Physics University of California BerkeleyCA94720 United States Astronomy Department University of Illinois at Urbana-Champaign 1002 W. Green Street UrbanaIL61801 United States Kavli Institute for Cosmological Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Statistics University of California One Shields Avenue DavisCA95616 United States Cardiff University CardiffCF10 3XQ United Kingdom Fermi National Accelerator Laboratory MS209 P.O. Box 500 BataviaIL60510 United States NIST Quantum Devices Group 325 Broadway Mailcode 817.03 BoulderCO80305 United States Department of Physics University of Colorado BoulderCO80309 United States High Energy Physics Division Argonne National Laboratory 9700 S. Cass Avenue ArgonneIL60439 United States Department of Astronomy and Astrophysics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States School of Physics University of Melbourne ParkvilleVIC3010 Australia Enrico Fermi Institute University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Physics McGill University 3600 Rue University MontrealQCH3A 2T8 Canada School of Mathematics Statistics & Computer Science University of KwaZulu-Natal Durban South Africa University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Jet Propulsion Laboratory PasadenaCA91109 United States Dunlap Institute for Astronomy & Astrophysics University of Toronto 50 St George St TorontoONM5S 3H4 Canada Department of Astronomy & Astrophysics University of Toronto 50 St George St TorontoONM5S 3H4 Canada Physics Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Canadian Institute for Advanced Research CIFAR Program in Gravity Extreme Universe TorontoONM5G 1Z8 Canada Department of Astrophysical and Pla

We perform the first simultaneous Bayesian parameter inference and optimal reconstruction of the gravitational lensing of the cosmic microwave background (CMB), using 100 deg2 of polarization observations from the SPTpol receiver on the South Pole Telescope. These data reach noise levels as low as 5.8 µK-arcmin in polarization, which are low enough that the typically used quadratic estimator (QE) technique for analyzing CMB lensing is significantly sub-optimal. Conversely, the Bayesian procedure extracts all lensing information from the data and is optimal at any noise level. We infer the amplitude of the gravitational lensing potential to be Aφ = 0.949 ±0.122 using the Bayesian pipeline, consistent with our QE pipeline result, but with 17% smaller error bars. The Bayesian analysis also provides a simple way to account for systematic uncertainties, performing a similar job as frequentist "bias hardening," and reducing the systematic uncertainty on Aφ due to polarization calibration from almost half of the statistical error to effectively zero. Finally, we jointly constrain Aφ along with AL, the amplitude of lensing-like effects on the CMB power spectra, demonstrating that the Bayesian method can be used to easily infer parameters both from an optimal lensing reconstruction and from the delensed CMB, while exactly accounting for the correlation between the two. These results demonstrate the feasibility of the Bayesian approach on real data, and pave the way for future analysis of deep CMB polarization measurements with SPT-3G, Simons Observatory, and CMB-S4, where improvements relative to the QE can reach 1.5 times tighter constraints on Aφ and 7 times lower effective lensing reconstruction noise. Copyright © 2020, The Authors. All rights reserved.

关键词： Cosmology

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A demonstration of improved constraints on primordial gravitational waves with delensing

arXiv

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arXiv 2020年

作者： Ade, P.A.R. Ahmed, Z. Amiri, M. Anderson, A.J. Austermann, J.E. Avva, J.S. Barkats, D. Thakur, R. Basu Beall, J.A. Bender, A.N. Benson, B.A. Bianchini, F. Bischoff, C.A. Bleem, L.E. Bock, J.J. Boenish, H. Bullock, E. Buza, V. Carlstrom, J.E. Chang, C.L. Cheshire, J.R. Chiang, H.C. Chou, T.-L. Citron, R. Connors, J. Moran, C. Corbett Cornelison, J. Crawford, T.M. Crites, A.T. Crumrine, M. Cukierman, A. de Haan, T. Dierickx, M. Dobbs, M.A. Duband, L. Everett, W. Fatigoni, S. Filippini, J.P. Fliescher, S. Gallicchio, J. George, E.M. Germaine, T.St. Goeckner-Wald, N. Goldfinger, D.C. Grayson, J. Gupta, N. Hall, G. Halpern, M. Halverson, N.W. Harrison, S. Henderson, S. Henning, J.W. Hildebrandt, S.R. Hilton, G.C. Holder, G.P. Holzapfel, W.L. Hrubes, J.D. Huang, N. Hubmayr, J. Hui, H. Irwin, K.D. Kang, J. Karkare, K.S. Karpel, E. Kefeli, S. Kernasovskiy, S.A. Knox, L. Kovac, J.M. Kuo, C.L. Lau, K. Lee, A.T. Leitch, E.M. Li, D. Lowitz, A. Manzotti, A. McMahon, J.J. Megerian, K.G. Meyer, S.S. Millea, M. Mocanu, L.M. Moncelsi, L. Montgomery, J. Nadolski, A. Namikawa, T. Natoli, T. Netterfield, C.B. Nguyen, H.T. Nibarger, J.P. Noble, G. Novosad, V. O’Brient, R. Ogburn, R.W. Omori, Y. Padin, S. Palladino, S. Patil, S. Prouve, T. Pryke, C. Racine, B. Reichardt, C.L. Reintsema, C.D. Richter, S. Ruhl, J.E. Saliwanchik, B.R. Schaffer, K.K. Schillaci, A. Schmitt, B.L. Schwarz, R. Sheehy, C.D. Sievers, C. Smecher, G. Soliman, A. Stark, A.A. Steinbach, B. Sudiwala, R.V. Teply, G.P. Thompson, K.L. Tolan, J.E. Tucker, C. Turner, A.D. Umiltà, C. Veach, T. Vieira, J.D. Vieregg, A.G. Wandui, A. Wang, G. Weber, A.C. Whitehorn, N. Wiebe, D.V. Willmert, J. Wong, C.L. Wu, W.L. Kimmy Yang, H. Yefremenko, V. Yoon, K.W. Young, E. Yu, C. Zeng, L. Zhang, C. Cardiff University CardiffCF10 3XQ United Kingdom SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo ParkCA94025 United States Kavli Institute for Particle Astrophysics and Cosmology Stanford University 452 Lomita Mall StanfordCA94305 United States Department of Physics and Astronomy University of British Columbia VancouverBCV6T 1Z1 Canada Fermi National Accelerator Laboratory MS209 P.O. Box 500 BataviaIL60510 United States NIST Quantum Devices Group 325 Broadway Mailcode 817.03 BoulderCO80305 United States Department of Physics University of Colorado BoulderCO80309 United States Department of Physics University of California BerkeleyCA94720 United States Harvard-Smithsonian Center for Astrophysics 60 Garden Street CambridgeMA02138 United States California Institute of Technology MS 249-17 1216 E. California Blvd. PasadenaCA91125 United States High Energy Physics Division Argonne National Laboratory 9700 S. Cass Avenue ArgonneIL60439 United States Kavli Institute for Cosmological Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Astronomy and Astrophysics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States School of Physics University of Melbourne ParkvilleVIC3010 Australia Department of Physics University of Cincinnati CincinnatiOH45221 United States Jet Propulsion Laboratory PasadenaCA91109 United States Department of Physics Harvard University CambridgeMA02138 United States Minnesota Institute for Astrophysics University of Minnesota MinneapolisMN55455 United States Department of Physics University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Enrico Fermi Institute University of Chicago 5640 South Ellis Avenue ChicagoIL60637 United States Department of Physics McGill University 3600 Rue University MontrealQCH3A 2T8 Canada School of Mathematics Statistics & Computer Science University of KwaZulu-Natal

We present a constraint on the tensor-to-scalar ratio, r, derived from measurements of cosmic microwave background (CMB) polarization B-modes with "delensing," whereby the uncertainty on r contributed by the sample variance of the gravitational lensing B-modes is reduced by cross-correlating against a lensing B-mode template. This template is constructed by combining an estimate of the polarized CMB with a tracer of the projected large-scale structure. The large-scale-structure tracer used is a map of the cosmic infrared background derived from Planck satellite data, while the polarized CMB map comes from a combination of South Pole Telescope, Bicep/Keck, and Planck data. We expand the Bicep/Keck likelihood analysis framework to accept a lensing template and apply it to the Bicep/Keck data set collected through 2014 using the same parametric foreground modelling as in the previous analysis. From simulations, we find that the uncertainty on r is reduced by ∼ 10%, from σ(r)= 0.024 to 0.022, which can be compared with a ∼ 26% reduction obtained when using a perfect lensing template or if there were zero lensing B-modes. Applying the technique to the real data, the constraint on r is improved from r0.05 Copyright © 2020, The Authors. All rights reserved.

关键词： Cosmology

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26th Annual computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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26th Annual computational Neuroscience Meeting (CNS*2017) of the Organization for computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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25th Annual computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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K, T and D-like fuzzy Kripke models

K, T and D-like fuzzy Kripke models

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Annual Meeting of The North American Fuzzy Information Processing Society

作者： Bedregal, Benjamin Santiago, Regivan H. N. Benevides, Mario Viana, Petrucio Group of Logic Language Information Theory and Applications - LoLITA Department of Informatics and Applied Mathematics Federal University of Rio Grande Do Norte 59072-970 Natal-RN Brazil Program of Engineering of Systems and Computing - PESC Department of Computer Science Federal University of Rio de Janeiro 21941-972 Rio de Janeiro-RJ Brazil Department of Analysis Fluminense Federal University 24020-140 Niterói-RJ Brazil

ISBN: (纸本)9781612849676

The idea of a Kripke semantics endowed with possibility/plausibility information is not new;in fact there are different approaches for that;see: [6], [13], [16], [19]. This paper follows the approach found in [6], but whereas [6] provides a fixed interpretation for connectives into [0,1] here we provide a characterization of a fuzzy semantics for connectives in such a way that the resulting fuzzy frames: K, T and D, are described precisely by the set of statements which also describes, respectively, the usual modal systems K, T and D. © 2011 IEEE.

关键词： Semantics

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Generalizations in mathematical epidemiology: Using computer algebra and intuitive mechanized reasoning

Generalizations in mathematical epidemiology: Using computer...

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International Conference on Advances in Machine Learning and Systems engineering

作者： Cano, Davinson Castaño Logic and Computation Group Engineering Physics Program EAFIT University Carrera 49 N 7 Sur 50 Medellín Suramérica Colombia

ISBN: (纸本)9789048194186

We are concerned by imminent future problems caused by biological dangers, here we think of a way to solve them. One of them is analyzing endemic models, for this we make a study supported by Computer Algebra Systems (CAS) and Mechanized Reasoning (MR). Also we show the advantages of the use of "CAS" and "MR" to obtain in that case, an epidemic threshold theorem. We prove a previously obtained theorem for SnIR endemic model. Moreover using "CAS+MR" we obtain a new epidemic threshold theorem for the SnImR epidemic model and for the staged progressive SImR model. Finally we discuss the relevance of the theorems and some future applications. © 2010 Springer Science+Business Media B.V.

关键词： Algebra

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K, T and D-like fuzzy Kripke models

K, T and D-like fuzzy Kripke models

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Conference of the North American Fuzzy Information Processing Society - NAFIPS

作者： Benjamin Bedregal Regivan H. N. Santiago Mario Benevides Petrúcio Viana Group of Logic Language Information Theory and Applications-LoLITA Department of Informatics and Applied Mathematics Federal University of Rio Grande do Norte Natal Rio Grande do Norte Brazil Program of Engineering of Systems and Computing-PESC Department of Computer Science Federal University of Rio de Janeiro Rio de Janeiro Rio de Janeiro Brazil Department of Analysis Fluminense Federal University (UFF) Niteroi Rio de Janeiro Brazil

The idea of a Kripke semantics endowed with possibility/plausibility information is not new; in fact there are different approaches for that; see: [6], [13], [16], [19]. This paper follows the approach found in [6], but whereas [6] provides a fixed interpretation for connectives into [0,1] here we provide a characterization of a fuzzy semantics for connectives in such a way that the resulting fuzzy frames: K, T and D, are described precisely by the set of statements which also describes, respectively, the usual modal systems K, T and D.

关键词： Semantics Fuzzy sets Fuzzy logic Bismuth Electronic mail Uncertainty Reliability

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LQR control for a multi - inverted pendulum using maple

LQR control for a multi - inverted pendulum using maple

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2008 International Conference on Scientific Computing, CSC 2008

作者： Castaño, Leidy Marcela Giraldo Logic and Computation Group Program of Physical Engineering EAFIT University Medellín Colombia

ISBN: (纸本)1601320590

This article will describe a system for obtaining a LQR controller for a multi-inverted pendulum. The theoretical model of that, it will implement using Maple. The equations are constructed with the Euler-Lagrange mechanical and from them are possible to analyze the stability, controllability and observability matrixes of that system. Finally, this paper presents the LQR controller which is obtained as linear combination of dynamics variables, so that system will be implemented in analogue and computational form to achieve that the system remains stable.

关键词： Inverted pendulum

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