检索结果-内蒙古大学图书馆

arXiv 2017年

作者： Fritz, Adrian Hellmuth, Marc Wieseke, Nicolas Stadler, Peter F. Computational Biology of Infection Research Helmholtz Centre for Infection Research Inhoffenstraße 7 BraunschweigD-38124 Germany University of Greifswald Dpt. of Mathematics and Computer Science Walther- Rathenau-Strasse 47 GreifswaldD-17487 Germany Saarland University Center for Bioinformatics Building e 2.1 P.O. Box 151150 SaarbrückenD-66041 Germany Parallel Computing and Complex Systems Group Department of Computer Science University of Leipzig Augustusplatz 10 LeipzigD-04109 Germany Bioinformatics Group Department of Computer Science Interdisciplinary Center of Bioinformatics University of Leipzig Härtelstraße 16-18 LeipzigD-04107 Germany Max-Planck-Institute for Mathematics in the Sciences Inselstraße 22 LeipzigD-04103 Germany Inst. F. Theoretical Chemistry University of Vienna Währingerstraße 17 WienA-1090 Austria Santa Fe Institute 1399 Hyde Park Rd. Santa FeNM87501 United States

The modular decomposition of a graph G = (V;E) does not contain prime modules if and only if G is a cograph, that is, if no quadruple of vertices induces a simple connected path P4. The cograph editing problem consists in inserting into and deleting from G a set F of edges so that H = (V,EΔF) is a cograph and |F| is minimum. This NP-hard combinatorial optimization problem has recently found applications, e.g., in the context of phylogenetics. Efficient heuristics are hence of practical importance. The simple characterization of cographs in terms of their modular decomposition suggests that inst.ad of editing G one could operate directly on the modular decomposition. We show here that editing the induced P4s is equivalent to resolving prime modules by means of a suitable defined merge operation on the submodules. Moreover, we characterize so-called module-preserving edit sets and demonstrate that optimal pairwise sequences of module-preserving edit sets exist for every non-cograph. This eventually leads to an exact algorithm for the cograph editing problem. In addition, we provide two heuristics with time complexity O(|V|3), resp., O(|V|2). Copyright © 2017, The Authors. All rights reserved.

关键词： Graph theory

来源：评论

学校读者我要写书评

暂无评论

DualRadviz: Preserving Context between Classification Evaluation and Data Exploration with RadViz

DualRadviz: Preserving Context between Classification Evalua...

引用

Brazilian Conference on Intelligent Systems (BRACIS)

作者： Igor Bueno Corrêa André Ponce de Leon Ferreira de Carvalho Institute of Mathematics and Computer Science University of São Paulo São Carlos Brazil Inst. of Math. & Comput. Sci. Univ. of Sao Paulo Sao Carlos Brazil

With today's flood of data coming from many types of sources, Machine Learning becomes increasingly important. Though, many times the use of Machine Learning is not enough to make sense of all this data. This makes visualization a very useful tool for Machine Learning practitioners and data analysts alike. Interactive visualization techniques can be very helpful by giving insight on the meaning of the output from classification tasks. This also applies to the data itself, as visualization can make some characteristics of the data become clear. Several bi-dimensional projection methods have been used to visualize data inst.nces based on their attribute values. This visualization is more difficult when the inst.nces have a large number of attributes. One of the visualization techniques that can deal with high dimensional data is Radial Coordinates Visualization (RadViz). RadViz can also be employed to visualize the performance of a probabilistic classifier, helping a user to find problematic inst.nces that might have been misclassified. In this study, a new approach to use RadViz is proposed and investigated. The proposed approach combines the two aforementioned uses of RadViz (attribute-based data exploration and result exploration based on the output of probabilistic classification). For such, it approach provides an easy transition between the two types of visualization. This allows the context to be preserved, since the user can visually track the same data inst.nce from one type of visualization to the other. In order to evaluate the proposed approach, a prototype, named DualRadviz, was implemented. On this prototype, in addition to RadViz, visualization by Parallel Coordinates is also provided, so that precise inst.nce inspection can be performed, since, different from RadViz, Parallel coordinates visualization does not suffer from ambiguity. To illustrate the usefulness of the proposed method, a case study is presented.

关键词： Data visualization Prototypes Probabilistic logic Context Inspection Springs Matrix converters

来源：评论

学校读者我要写书评

暂无评论

Embedded controlled language to facilitate information extraction from eGov policies 15

Embedded controlled language to facilitate information extra...

引用

17th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2015

作者： Safwat, Hazem Gruzitis, Normunds Enache, Ramona Davis, Brian Insight Centre for Data Analytics National University of Ireland Ireland Inst. of Mathematics and Computer Science University of Latvia Latvia Dept. of Computer Science and Engineering University of Gothenburg Sweden

ISBN: (纸本)9781450334914

The goal of this paper is to propose a system that can extract formal semantic knowledge representation from natural language eGov policies. We present an architecture that allows for extracting Controlled Natural Language (CNL) statements from heterogeneous natural language texts with the ability to support multilinguality. The approach is based on the concept of embedded CNLs. © 2015 ACM.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

A framework for reengineering Web applications into Linked Data based on MDA 15

A framework for reengineering Web applications into Linked D...

引用

International Conference on Intelligent Information Processing, Security and Advanced Communication, IPAC 2015

作者： Bouougada, Benamar Bouchiha, Djelloul Malki, Mimoun Univ Ctr of Naama Inst. Science and Technology Dept. Mathematics and Computer Science Algeria EEDIS Laboratory Djillali Liabes University of Sidi Bel Abbes Algeria

ISBN: (纸本)9781450334587

Currently, the Web became a very enormous resource of data, often hidden in documents. Most of the Web applications represent the data under a structured format, in particularly tables and lists. These data are automatically generated from databases, so they have a restricted access. RDF (Resource Description Framework) offers an effective mechanism, which allows structuring the data on the Web in a simple format, so it makes them directly accessible. In this paper we propose a framework that allows to transform the hidden data on the Web into Linked Data. The framework contains four layers according to MDA (Model Driven Architecture): (1) the layer M0 allows to build a source model from a Web application, (2) layer M1 contains the source model and mapping rules, (3) layer M2 enables to define meta-models of the models included in the layer M1, at the last, (4) layer M3 describes the meta-models using a language of metameta-model, such as MOF or ECORE of the framework EMF. At the end of this transformation process, we obtain a target RDF model, which represents data of the Web application. © 2015 ACM.

关键词： Linked data

来源：评论

学校读者我要写书评

暂无评论

Observation of seasonal variation of atmospheric multiple-muon events in the NOvA Near Detector

引用

Physical Review D 2019年第12期99卷 122004-122004页

作者： M. A. Acero P. Adamson L. Aliaga T. Alion V. Allakhverdian S. Altakarli N. Anfimov A. Antoshkin A. Aurisano A. Back C. Backhouse M. Baird N. Balashov P. Baldi B. A. Bambah S. Bashar K. Bays S. Bending R. Bernstein V. Bhatnagar B. Bhuyan J. Bian J. Blair A. C. Booth P. Bour C. Bromberg N. Buchanan A. Butkevich S. Calvez M. Campbell T. J. Carroll E. Catano-Mur A. Cedeno S. Childress B. C. Choudhary B. Chowdhury T. E. Coan M. Colo L. Corwin L. Cremonesi G. S. Davies P. F. Derwent P. Ding Z. Djurcic D. Doyle E. C. Dukes H. Duyang S. Edayath R. Ehrlich G. J. Feldman P. Filip W. Flanagan M. J. Frank H. R. Gallagher R. Gandrajula F. Gao S. Germani A. Giri R. A. Gomes M. C. Goodman V. Grichine M. Groh R. Group B. Guo A. Habig F. Hakl J. Hartnell R. Hatcher A. Hatzikoutelis K. Heller J. Hewes A. Himmel A. Holin B. Howard J. Huang J. Hylen F. Jediny C. Johnson M. Judah I. Kakorin D. Kalra D. M. Kaplan R. Keloth O. Klimov L. W. Koerner L. Kolupaeva S. Kotelnikov A. Kreymer Ch. Kulenberg A. Kumar C. D. Kuruppu V. Kus T. Lackey K. Lang S. Lin M. Lokajicek J. Lozier S. Luchuk S. Magill W. A. Mann M. L. Marshak V. Matveev D. P. Méndez M. D. Messier H. Meyer T. Miao W. H. Miller S. R. Mishra A. Mislivec R. Mohanta A. Moren L. Mualem M. Muether S. Mufson K. Mulder R. Murphy J. Musser D. Naples N. Nayak J. K. Nelson R. Nichol G. Nikseresht E. Niner A. Norman T. Nosek A. Olshevskiy T. Olson J. Paley R. B. Patterson G. Pawloski O. Petrova R. Petti D. D. Phan R. K. Plunkett B. Potukuchi C. Principato F. Psihas V. Raj R. A. Rameika B. Rebel P. Rojas V. Ryabov O. Samoylov M. C. Sanchez P. Schreiner I. S. Seong P. Shanahan A. Sheshukov P. Singh V. Singh E. Smith J. Smolik P. Snopok N. Solomey E. Song A. Sousa K. Soustruznik M. Strait L. Suter A. Sutton R. L. Talaga P. Tas R. B. Thayyullathil J. Thomas E. Tiras S. C. Tognini D. Torbunov J. Tripathi A. Tsaris Y. Torun J. Urheim P. Vahle J. Vasel L. Vinton P. Vokac T. Vrba M. Wallbank B. Wang T. K. Warburton M. Wetstein M. While D. Whittington S. G. Wojcicki J. Wolcott N. Yadav A. Yallappa Universidad del Atlantico Km. 7 antigua via a Puerto Colombia Barranquilla Colombia Fermi National Accelerator Laboratory Batavia Illinois 60510 USA Department of Physics and Astronomy University of Sussex Falmer Brighton BN1 9QH United Kingdom Joint Institute for Nuclear Research Dubna Moscow region 141980 Russia Department of Mathematics Statistics and Physics Wichita State University Wichita Kansas 67206 USA School of Physics and Astronomy University of Minnesota Twin Cities Minneapolis Minnesota 55455 USA Department of Physics University of Cincinnati Cincinnati Ohio 45221 USA Department of Physics and Astronomy Iowa State University Ames Iowa 50011 USA Physics and Astronomy Dept. University College London Gower Street London WC1E 6BT United Kingdom Indiana University Bloomington Indiana 47405 USA Department of Physics University of Virginia Charlottesville Virginia 22904 USA Department of Physics and Astronomy University of California at Irvine Irvine California 92697 USA School of Physics University of Hyderabad Hyderabad 500 046 India Department of Physics and Astronomy Tufts University Medford Massachusetts 02155 USA California Institute of Technology Pasadena California 91125 USA Department of Physics Illinois Institute of Technology Chicago Illinois 60616 USA Department of Physics Panjab University Chandigarh 160 014 India Department of Physics IIT Guwahati Guwahati 781 039 India Department of Physics University of Houston Houston Texas 77204 USA Czech Technical University in Prague Brehova 7 115 19 Prague 1 Czech Republic Department of Physics and Astronomy Michigan State University East Lansing Michigan 48824 USA Department of Physics Colorado State University Fort Collins Colorado 80523-1875 USA Inst. for Nuclear Research of Russia Academy of Sciences 7a 60th October Anniversary prospect Moscow 117312 Russia Department of Physics University of Texas at Austin Austin Texas 78712 USA Department of Physics Colle

Using two years of data from the NOvA Near Detector at Fermilab, we report a seasonal variation of cosmic ray induced multiple-muon (Nμ≥2) event rates which has an opposite phase to the seasonal variation in the atmospheric temperature. The strength of the seasonal multiple-muon variation is shown to increase as a function of the muon multiplicity. However, no significant dependence of the strength of the seasonal variation of the multiple-muon variation is seen as a function of the muon zenith angle, or the spatial or angular separation between the correlated muons.

关键词： Cosmic ray & astroparticle detectors Cosmic rays & astroparticles

来源：评论

学校读者我要写书评

暂无评论

Attribute graph grammar method for research information collection and sharing

Attribute graph grammar method for research information coll...

引用

International Conference on Digital Information Management (ICDIM)

作者： Youzou Miyadera Chiaki Murakami Koichi Anada Shoichi Nakamura Takeo Yaku Facul. Education Tokyo Gakugei University Tokyo Koganei Japan Waseda Res. Inst. for Sci. and Eng. Waseda University Tokyo Nerima Japan Dept. Computer Science and Mathematics Fukushima University Fukushima Fukushima Japan Dept. Information Science Nihon University Tokyo Setagaya Japan

ISBN: (纸本)9781509026425

In sharing information for the research support at university laboratories, not only the research documents including references, seminar documents, research data, and articles but also the context information including the process of the research activities that have been conducted and the relations between the research documents are important. In this study, both research documents and context information are called “research information”. This research information can be effectively managed and shared in a visual manner on the system. In collecting research information, the members' workload must be reduced as much as possible. In addition, to better share research information, it should be able to be visualized quickly without stress. Therefore, this paper describes a research information collection and sharing method developed by introducing attribute graph grammar. Specifically, this paper presents a research information collection method that can deal with various research activities and reduce members' workload for collecting information by introducing a research information relations graph (RIRG) and generating RIRG based on the production of the attribute graph grammar. In addition, this paper describes a method for effectively drawing RIRG by using a semantic rule of the attribute graph grammar. Finally, this paper introduces a research information collection and sharing support system (ResearchView) using this method.

关键词： Grammar Production Information management Context Seminars Visualization Laboratories

来源：评论

学校读者我要写书评

暂无评论

Stochastic Models, Statistics and Their Applications: Wroclaw, Poland, February 2015

Stochastic Models, Statistics and Their Applications: Wrocla...

引用

12th Workshop on Stochastic Models, Statistics and their Applications, 2015

作者： Steland, Ansgar Szajowski, Krzysztof Rafajlowicz, Ewaryst Institute of Statistics RWTH Aachen University Aachen Germany Inst. of Mathematics and Computer Science Wroclaw University of Technology Wroclaw Poland Dept. of Computer Engineering Control and Robotics Wroclaw University of Technology Wroclaw Poland

来源：评论

学校读者我要写书评

暂无评论

Observation of seasonal variation of atmospheric multiple-muon events in the NOvA Near Detector

arXiv

引用

arXiv 2019年

作者： Acero, M.A. Adamson, P. Aliaga, L. Alion, T. Allakhverdian, V. Altakarli, S. Anfimov, N. Antoshkin, A. Aurisano, A. Back, A. Backhouse, C. Baird, M. Balashov, N. Baldi, P. Bambah, B.A. Bashar, S. Bays, K. Bending, S. Bernstein, R. Bhatnagar, V. Bhuyan, B. Bian, J. Blair, J. Booth, A.C. Bour, P. Bromberg, C. Buchanan, N. Butkevich, A. Calvez, S. Campbell, M. Carroll, T.J. Catano-Mur, E. Cedeno, A. Childress, S. Choudhary, B.C. Chowdhury, B. Coan, T.E. Colo, M. Corwin, L. Cremonesi, L. Davies, G.S. Derwent, P.F. Ding, P. Djurcic, Z. Doyle, D. Dukes, E.C. Duyang, H. Edayath, S. Ehrlich, R. Feldman, G.J. Filip, P. Flanagan, W. Frank, M.J. Gallagher, H.R. Gandrajula, R. Gao, F. Germani, S. Giri, A. Gomes, R.A. Goodman, M.C. Grichine, V. Groh, M. Group, R. Guo, B. Habig, A. Hakl, F. Hartnell, J. Hatcher, R. Hatzikoutelis, A. Heller, K. Hewes, V. Himmel, A. Holin, A. Howard, B. Huang, J. Hylen, J. Jediny, F. Johnson, C. Judah, M. Kakorin, I. Kalra, D. Kaplan, D.M. Keloth, R. Klimov, O. Koerner, L.W. Kolupaeva, L. Kotelnikov, S. Kreymer, A. Kulenberg, Ch. Kumar, A. Kuruppu, C.D. Kus, V. Lackey, T. Lang, K. Lin, S. Lokajicek, M. Lozier, J. Luchuk, S. Magill, S. Mann, W.A. Marshak, M.L. Matveev, V. Méndez, D.P. Messier, M.D. Meyer, H. Miao, T. Miller, W.H. Mishra, S.R. Mislivec, A. Mohanta, R. Moren, A. Mualem, L. Muether, M. Mufson, S. Mulder, K. Murphy, R. Musser, J. Naples, D. Nayak, N. Nelson, J.K. Nichol, R. Nikseresht, G. Niner, E. Norman, A. Nosek, T. Olshevskiy, A. Olson, T. Paley, J. Patterson, R.B. Pawloski, G. Petrova, O. Petti, R. Phan, D.D. Plunkett, R.K. Potukuchi, B. Principato, C. Psihas, F. Raj, V. Rameika, R.A. Rebel, B. Rojas, P. Ryabov, V. Samoylov, O. Sanchez, M.C. Schreiner, P. Seong, I.S. Shanahan, P. Sheshukov, A. Singh, P. Singh, V. Smith, E. Smolik, J. Snopok, P. Solomey, N. Song, E. Sousa, A. Soustruznik, K. Strait, M. Suter, L. Sutton, A. Talaga, R.L. Tas, P. Argonne National Laboratory ArgonneIL60439 United States Universidad del Atlantico Km. 7 antigua via a Puerto Colombia Barranquilla Colombia Department of Physics Institute of Science Banaras Hindu University Varanasi221 005 India California Institute of Technology PasadenaCA91125 United States Charles University Faculty of Mathematics and Physics Institute of Particle and Nuclear Physics Prague Czech Republic Department of Physics University of Cincinnati CincinnatiOH45221 United States Department of Physics Cochin University of Science and Technology Kochi682 022 India Department of Physics Colorado State University Fort CollinsCO80523-1875 United States Czech Technical University in Prague Brehova 7 Prague 1115 19 Czech Republic University of Dallas 1845 E Northgate Drive IrvingTX75062 United States Department of Physics and Astrophysics University of Delhi Delhi110007 India Fermi National Accelerator Laboratory BataviaIL60510 United States Instituto de Física Universidade Federal de Goiás Goiás Goiânia74690-900 Brazil Department of Physics IIT Guwahati Guwahati781 039 India Department of Physics Harvard University CambridgeMA02138 United States Department of Physics University of Houston HoustonTX77204 United States School of Physics University of Hyderabad Hyderabad500 046 India Department of Physics IIT Hyderabad Hyderabad502 205 India Indiana University BloomingtonIN47405 United States Institute of Computer Science The Czech Academy of Sciences Prague182 07 Czech Republic Department of Physics Illinois Institute of Technology ChicagoIL60616 United States Inst. for Nuclear Research of Russia Academy of Sciences 7a 60th October Anniversary prospect Moscow117312 Russia Institute of Physics The Czech Academy of Sciences Prague182 21 Czech Republic Department of Physics and Astronomy Iowa State University AmesIA50011 United States Department of Physics and Astronomy University of California at Irvine Irvin

Using two years of data from the NOvA Near Detector at Fermilab, we report a seasonal variation of cosmic ray induced multiple-muon (Nµ ≥ 2) event rates which has an opposite phase to the seasonal variation in the atmospheric temperature. The strength of the seasonal multiple-muon variation is shown to increase as a function of the muon multiplicity. However, no significant dependence of the strength of the seasonal variation of the multiple-muon variation is seen as a function of the muon zenith angle, or the spatial or angular separation between the correlated muons. Copyright © 2019, The Authors. All rights reserved.

关键词： Cosmic rays

来源：评论

学校读者我要写书评

暂无评论

Measurement of neutrino-induced neutral-current coherent π0 production in the NOvA near detector

arXiv

引用

arXiv 2019年

作者： Acero, M.A. Adamson, P. Aliaga, L. Alion, T. Allakhverdian, V. Anfimov, N. Antoshkin, A. Arrieta-Diaz, E. Aurisano, A. Back, A. Backhouse, C. Baird, M. Balashov, N. Baldi, P. Bambah, B.A. Basher, S. Bays, K. Behera, B. Bending, S. Bernstein, R. Bhatnagar, V. Bhuyan, B. Bian, J. Blair, J. Booth, A.C. Bolshakova, A. Bour, P. Bromberg, C. Buchanan, N. Butkevich, A. Campbell, M. Carroll, T.J. Catano-Mur, E. Childress, S. Choudhary, B.C. Chowdhury, B. Coan, T.E. Colo, M. Corwin, L. Cremonesi, L. Cronin-Hennessy, D. Davies, G.S. Derwent, P.F. Ding, P. Djurcic, Z. Doyle, D. Dukes, E.C. Dung, P. Duyang, H. Edayath, S. Ehrlich, R. Feldman, G.J. Flanagan, W. Frank, M.J. Gallagher, H.R. Gandrajula, R. Gao, F. Germani, S. Giri, A. Gomes, R.A. Goodman, M.C. Grichine, V. Groh, M. Group, R. Guo, B. Habig, A. Hakl, F. Hartnell, J. Hatcher, R. Hatzikoutelis, A. Heller, K. Himmel, A. Holin, A. Howard, B. Huang, J. Hylen, J. Jediny, F. Johnson, C. Judah, M. Kakorin, I. Kalra, D. Kaplan, D.M. Keloth, R. Klimov, O. Koerner, L.W. Kolupaeva, L. Kotelnikov, S. Kreymer, A. Kulenberg, Ch. Kumar, A. Kuruppu, C.D. Kus, V. Lackey, T. Lang, K. Lin, S. Lokajicek, M. Lozier, J. Luchuk, S. Maan, K. Magill, S. Mann, W.A. Marshak, M.L. Matveev, V. Méndez, D.P. Messier, M.D. Meyer, H. Miao, T. Miller, W.H. Mishra, S.R. Mislivec, A. Mohanta, R. Moren, A. Mualem, L. Muether, M. Mulder, K. Mufson, S. Murphy, R. Musser, J. Naples, D. Nayak, N. Nelson, J.K. Nichol, R. Niner, E. Norman, A. Nosek, T. Oksuzian, Y. Olshevskiy, A. Olson, T. Paley, J. Patterson, R.B. Pawloski, G. Pershey, D. Petrova, O. Petti, R. Plunkett, R.K. Potukuchi, B. Principato, C. Psihas, F. Raj, V. Radovic, A. Rameika, R.A. Rebel, B. Rojas, P. Ryabov, V. Sachdev, K. Samoylov, O. Sanchez, M.C. Seong, I.S. Shanahan, P. Sheshukov, A. Singh, P. Singh, V. Smith, E. Smolik, J. Snopok, P. Solomey, N. Song, E. Sousa, A. Soustruznik, K. Strait, M. Suter, L. Talaga, R.L. Argonne National Laboratory ArgonneIL60439 United States Universidad del Atlantico Km. 7 antigua via a Puerto Colombia Barranquilla Colombia Department of Physics Institute of Science Banaras Hindu University Varanasi221 005 India California Institute of Technology PasadenaCA91125 United States Charles University Faculty of Mathematics and Physics Institute of Particle and Nuclear Physics Prague Czech Republic Department of Physics University of Cincinnati CincinnatiOH45221 United States Department of Physics Cochin University of Science and Technology Kochi682 022 India Department of Physics Colorado State University Fort CollinsCO80523-1875 United States Czech Technical University in Prague Brehova 7 Prague 1115 19 Czech Republic University of Dallas 1845 E Northgate Drive IrvingTX75062 United States Department of Physics and Astrophysics University of Delhi Delhi110007 India Fermi National Accelerator Laboratory BataviaIL60510 United States Instituto de Física Universidade Federal de Goiás Goiânia Goiás74690-900 Brazil Department of Physics IIT Guwahati Guwahati781 039 India Department of Physics Harvard University CambridgeMA02138 United States Department of Physics University of Houston HoustonTX77204 United States School of Physics University of Hyderabad Hyderabad500 046 India Department of Physics IIT Hyderabad Hyderabad502 205 India Indiana University BloomingtonIN47405 United States Institute of Computer Science Czech Academy of Sciences Prague182 07 Czech Republic Department of Physics Illinois Institute of Technology ChicagoIL60616 United States Inst. for Nuclear Research of Russia Academy of Sciences 7a 60th October Anniversary prospect Moscow117312 Russia Institute of Physics Czech Academy of Sciences Prague182 21 Czech Republic Department of Physics and Astronomy Iowa State University AmesIA50011 United States Department of Physics and Astronomy University of California at Irvine IrvineCA926

The cross section of neutrino-induced neutral-current coherent π0 production on a carbon-dominated target is measured in the NOvA near detector. This measurement uses a narrow-band neutrino beam with the average neutrino energy of 2.7 GeV, which is of interest to the ongoing and future long-baseline neutrino oscillation experiments. The measured, flux-averaged cross section is σ = 14.0 ± 0.9 (stat.)±2.1 (syst.)×10−40 cm2/nucleus, consistent with model prediction. This result is the most precise measurement of neutral-current coherent π0 production in the few-GeV neutrino energy region. Copyright © 2019, The Authors. All rights reserved.

关键词： Germanium alloys

来源：评论

学校读者我要写书评

暂无评论

First measurement of neutrino oscillation parameters using neutrinos and antineutrinos by NOvA

arXiv

引用

arXiv 2019年

作者： Acero, M.A. Adamson, P. Aliaga, L. Alion, T. Allakhverdian, V. Altakarli, S. Anfimov, N. Antoshkin, A. Aurisano, A. Back, A. Backhouse, C. Baird, M. Balashov, N. Baldi, P. Bambah, B.A. Bashar, S. Bays, K. Bending, S. Bernstein, R. Bhatnagar, V. Bhuyan, B. Bian, J. Blackburn, T. Blair, J. Booth, A.C. Bour, P. Bromberg, C. Buchanan, N. Butkevich, A. Calvez, S. Campbell, M. Carroll, T.J. Catano-Mur, E. Cedeno, A. Childress, S. Choudhary, B.C. Chowdhury, B. Coan, T.E. Colo, M. Cooper, J. Corwin, L. Cremonesi, L. Davies, G.S. Derwent, P.F. Ding, P. Djurcic, Z. Doyle, D. Dukes, E.C. Duyang, H. Edayath, S. Ehrlich, R. Elkins, M. Feldman, G.J. Filip, P. Flanagan, W. Frank, M.J. Gallagher, H.R. Gandrajula, R. Gao, F. Germani, S. Giri, A. Gomes, R.A. Goodman, M.C. Grichine, V. Groh, M. Group, R. Guo, B. Habig, A. Hakl, F. Hartnell, J. Hatcher, R. Hatzikoutelis, A. Heller, K. Hewes, V. Himmel, A. Holin, A. Howard, B. Huang, J. Hylen, J. Jediny, F. Johnson, C. Judah, M. Kakorin, I. Kalra, D. Kaplan, D.M. Keloth, R. Klimov, O. Koerner, L.W. Kolupaeva, L. Kotelnikov, S. Kreymer, A. Kulenberg, Ch. Kumar, A. Kuruppu, C.D. Kus, V. Lackey, T. Lang, K. Lin, S. Lokajicek, M. Lozier, J. Luchuk, S. Maan, K. Magill, S. Mann, W.A. Marshak, M.L. Martinez-Casales, M. Matveev, V. Méndez, D.P. Messier, M.D. Meyer, H. Miao, T. Miller, W.H. Mishra, S.R. Mislivec, A. Mohanta, R. Moren, A. Mualem, L. Muether, M. Mufson, S. Mulder, K. Murphy, R. Musser, J. Naples, D. Nayak, N. Nelson, J.K. Nichol, R. Nikseresht, G. Niner, E. Norman, A. Nosek, T. Olshevskiy, A. Olson, T. Paley, J. Patterson, R.B. Pawloski, G. Pershey, D. Petrova, O. Petti, R. Phan, D.D. Plunkett, R.K. Potukuchi, B. Principato, C. Psihas, F. Radovic, A. Raj, V. Rameika, R.A. Rebel, B. Rojas, P. Ryabov, V. Samoylov, O. Sanchez, M.C. Falero, S. Sánchez Seong, I.S. Shanahan, P. Sheshukov, A. Singh, P. Singh, V. Smith, E. Smolik, J. Snopok, P. Solomey, N. Argonne National Laboratory ArgonneIL60439 United States Universidad del Atlantico Km. 7 antigua via a Puerto Colombia Barranquilla Colombia Department of Physics Institute of Science Banaras Hindu University Varanasi221 005 India California Institute of Technology PasadenaCA91125 United States Charles University Faculty of Mathematics and Physics Institute of Particle and Nuclear Physics Prague Czech Republic Department of Physics University of Cincinnati CincinnatiOH45221 United States Department of Physics Cochin University of Science and Technology Kochi682 022 India Department of Physics Colorado State University Fort CollinsCO80523-1875 United States Czech Technical University in Prague Brehova 7 Prague 1115 19 Czech Republic University of Dallas 1845 E Northgate Drive IrvingTX75062 United States Department of Physics and Astrophysics University of Delhi Delhi110007 India Fermi National Accelerator Laboratory BataviaIL60510 United States Instituto de Física Universidade Federal de Goiás Goiás Goiânia74690-900 Brazil Department of Physics IIT Guwahati Guwahati781 039 India Department of Physics Harvard University CambridgeMA02138 United States Department of Physics University of Houston HoustonTX77204 United States School of Physics University of Hyderabad Hyderabad500 046 India Department of Physics IIT Hyderabad Hyderabad502 205 India Indiana University BloomingtonIN47405 United States Institute of Computer Science The Czech Academy of Sciences Prague182 07 Czech Republic Department of Physics Illinois Institute of Technology ChicagoIL60616 United States Inst. for Nuclear Research of Russia Academy of Sciences 7a 60th October Anniversary prospect Moscow117312 Russia Institute of Physics The Czech Academy of Sciences Prague182 21 Czech Republic Department of Physics and Astronomy Iowa State University AmesIA50011 United States Department of Physics and Astronomy University of California at Irvine Irvin

The NOvA experiment has made a 4.4σ-significant observation of ν¯e appearance in a 2 GeV ν¯µ beam at a distance of 810 km. Using 12.33×1020 protons on target delivered to the Fermilab NuMI neutrino beamline, the experiment recorded 27 ν¯µ → ν¯e candidates with a background of 10.3 and 102 ν¯µ → ν¯µ candidates. This new antineutrino data is combined with neutrino data to measure the oscillation parameters |∆m232| = 2.48+0.11−0.06 × 10−3 eV2/c4, sin2 θ23 = 0.56+0.04−0.03 in the normal neutrino mass hierarchy and upper octant and excludes most values near δCP = π/2 for the inverted mass hierarchy by more than 3σ. The data favor the normal neutrino mass hierarchy by 1.9σ and θ23 values in the upper octant by 1.6σ. Copyright © 2019, The Authors. All rights reserved.

关键词： Germanium alloys

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：