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Study of B-c(+) decays to the K+K-pi(+) final state and evidence for the decay B-c(+) -> chi(c0)pi(+)

Abstract

A study of B-c(+) -> K+K-pi(+) decays is performed for the first time using data corresponding to an integrated luminosity of 3.0 fb(-1) collected by the LHCb experiment in pp collisions at center-of-mass energies of 7 and 8 TeV. Evidence for the decay B-c(+) -> chi(c0)(K+K-)pi(+) is reported with a significance of 4.0 standard deviations, giving sigma(B-c(+))/sigma(B+) x B(B-c(+) -> chi(c0)pi+) = (9.8(-3.0)(+3.4)(stat) +/- 0.8(stat)) x 10(-6). Here B denotes a branching fraction while sigma(B-c(+)) and sigma(B+) are the production cross sections for B-c(+) and B+ mesons. An indication of (b) over barc weak annihilation is found for the region m(K-pi(+)) < 1.834 GeV/c(2), with a significance of 2.4 standard deviations.

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Abstract

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Related concepts (25)

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.

Median absolute deviation

In statistics, the median absolute deviation (MAD) is a robust measure of the variability of a univariate sample of quantitative data. It can also refer to the population parameter that is estimated by the MAD calculated from a sample. For a univariate data set X1, X2, ..., Xn, the MAD is defined as the median of the absolute deviations from the data's median : that is, starting with the residuals (deviations) from the data's median, the MAD is the median of their absolute values. Consider the data (1, 1, 2, 2, 4, 6, 9).

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