Publication

Amplitude analysis of B+ -> J/psi phi K+ decays

Jian Wang, Olivier Schneider, Yiming Li, Yi Zhang, Aurelio Bay, Guido Haefeli, Christoph Frei, Frédéric Blanc, Tatsuya Nakada, Michel De Cian, Luca Pescatore, François Fleuret, Elena Graverini, Chitsanu Khurewathanakul, Renato Quagliani, Maria Vieites Diaz, Federico Betti, Aravindhan Venkateswaran, Zhirui Xu, Lei Zhang, Jessica Prisciandaro, Mark Tobin, Minh Tâm Tran, Niko Neufeld, Matthew Needham, Marc-Olivier Bettler, Greig Alan Cowan, Maurizio Martinelli, Donal Patrick Hill, Cédric Potterat, Liang Sun, Pietro Marino, Mirco Dorigo, Jean Wicht, Xiaoxue Han, Sebastiana Gianì, Liupan An, Federico Leo Redi, Ilya Komarov, Thibaud Humair, Maxime Schubiger, Hang Yin, Guido Andreassi, Violaine Bellée, Olivier Göran Girard, Axel Kuonen, Preema Rennee Pais, Pavol Stefko, Hans Dijkstra, Gerhard Raven, Peter Clarke, Frédéric Teubert, Giovanni Carboni, Victor Coco, Adam Davis, Paolo Durante, Yu Zheng, Anton Petrov, Maxim Borisyak, Luis Alberto Granado Cardoso
2017
Journal paper

Abstract

The first full amplitude analysis of B+ -> J/psi phi K+ with J/psi -> mu(+)mu(-), phi -> K+K- decays is performed with a data sample of 3 fb(-1) of pp collision data collected at root s = 7 and 8 TeV with the LHCb detector. The data cannot be described by a model that contains only excited kaon states decaying into phi K+, and four J/psi phi structures are observed, each with significance over 5 standard deviations. The quantum numbers of these structures are determined with significance of at least 4 standard deviations. The lightest has mass consistent with, but width much larger than, previous measurements of the claimed X(4140) state. The model includes significant contributions from a number of expected kaon excitations, including the first observation of the K*(1680)+ -> phi K+ transition.

Official source

https://infoscience.epfl.ch/record/225823?ln=en

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Ontological neighbourhood

Physics

Particle physics: Standard Model

Atomic physics: Topics in atomic physics

Statistics

Statistical inference: Mathematical statistics

Related concepts (33)

Standard deviation

In statistics, the standard deviation is a measure of the amount of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the values are spread out over a wider range. Standard deviation may be abbreviated SD, and is most commonly represented in mathematical texts and equations by the lower case Greek letter σ (sigma), for the population standard deviation, or the Latin letter s, for the sample standard deviation.

Average absolute deviation

The average absolute deviation (AAD) of a data set is the average of the absolute deviations from a central point. It is a summary statistic of statistical dispersion or variability. In the general form, the central point can be a mean, median, mode, or the result of any other measure of central tendency or any reference value related to the given data set. AAD includes the mean absolute deviation and the median absolute deviation (both abbreviated as MAD). Several measures of statistical dispersion are defined in terms of the absolute deviation.

Unbiased estimation of standard deviation

In statistics and in particular statistical theory, unbiased estimation of a standard deviation is the calculation from a statistical sample of an estimated value of the standard deviation (a measure of statistical dispersion) of a population of values, in such a way that the expected value of the calculation equals the true value. Except in some important situations, outlined later, the task has little relevance to applications of statistics since its need is avoided by standard procedures, such as the use of significance tests and confidence intervals, or by using Bayesian analysis.

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