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Evidence for the decay $B_{s}^0 \rightarrow \overline{K}{}^{*0}\mu^+\mu^-$

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Abstract

A search for the decay $B_{s}^0 \rightarrow \overline{K}{}^{*0}\mu^+\mu^-$ is presented using data sets corresponding to 1.0, 2.0 and 1.6 $\text{fb}^{-1}$ of integrated luminosity collected during $pp$ collisions with the LHCb experiment at centre-of-mass energies of 7, 8 and 13 TeV, respectively. An excess is found over the background-only hypothesis with a significance of 3.4 standard deviations. The branching fraction of the $B_{s}^0 \rightarrow \overline{K}{}^{*0}\mu^+\mu^-$ decay is determined to be $\mathcal{B}(B_{s}^0 \rightarrow \overline{K}{}^{*0}\mu^+\mu^-) = [2.9 \pm 1.0 (\text{stat}) \pm 0.2 (\text{syst}) \pm 0.3 (\text{norm})] \times 10^{-8}$, where the first and second uncertainties are statistical and systematic, respectively. The third uncertainty is due to limited knowledge of external parameters used to normalise the branching fraction measurement.

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Distribution of reconstructed $ K ^- \pi ^+ \mu ^+\mu ^- $ invariant mass of candidates outside the $ { J \mskip -3mu/\mskip -2mu\psi \mskip 2mu}$ and $\psi {(2S)}$ mass regions, summing the three highest neural network response bins of each run condition. The candidates are shown (left) over the full range and (right) over a restricted vertical range to emphasise the $ B ^0_ s \!\rightarrow \overline{ K }{} {}^{*0} \mu ^+\mu ^- $ component. The solid line indicates a combination of the results of the fits to the individual bins. Components are detailed in the legend, where they are shown in the same order as they are stacked in the figure. The background from misidentified $ B ^0 \!\rightarrow K ^{*0} \mu ^+\mu ^- $ decays is included in the $\overline{ B }{} {}^0 \!\rightarrow \overline{ K }{} {}^{*0} \mu ^+\mu ^- $ component.

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Distribution of reconstructed $ { J \mskip -3mu/\mskip -2mu\psi \mskip 2mu} K ^- \pi ^+ $ invariant mass of the candidates in the $ { J \mskip -3mu/\mskip -2mu\psi \mskip 2mu}$ mass region summing the three highest neural network response bins of each run condition, shown (left) over the full range and (right) over a restricted vertical range to emphasise the $ B ^0_ s \!\rightarrow { J \mskip -3mu/\mskip -2mu\psi \mskip 2mu} \overline{ K }{} {}^{*0} $ component. The solid line indicates a combination of the results of the fits to the individual bins. Components are detailed in the legend, where they are shown in the same order as they are stacked in the figure. The background from misidentified $ B ^0 \!\rightarrow { J \mskip -3mu/\mskip -2mu\psi \mskip 2mu} K ^{*0} $ decays is included in the $\overline{ B }{} {}^0 \!\rightarrow { J \mskip -3mu/\mskip -2mu\psi \mskip 2mu} \overline{ K }{} {}^{*0} $ component.

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Change in log-likelihood from the simultaneous fit to the candidates in the two data-taking periods and the different bins of neural network response, as a function of the $ B ^0_ s \!\rightarrow \overline{ K }{} {}^{*0} \mu ^+\mu ^- $ yield. Systematic uncertainties on the yield have been included in the likelihood.

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Distribution of reconstructed $ K ^- \pi ^+ \mu ^+\mu ^- $ invariant mass of candidates in the $ { J \mskip -3mu/\mskip -2mu\psi \mskip 2mu}$ mass window in (top four figures) the Run 1 and (bottom four figures) Run 2 data sets. The candidates are divided into four independent bins of increasing neural network response per data taking period.

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Distribution of reconstructed $ K ^- \pi ^+ \mu ^+\mu ^- $ invariant mass of candidates outside of the $ { J \mskip -3mu/\mskip -2mu\psi \mskip 2mu}$ and $\psi {(2S)}$ mass regions in (top four figures) the Run 1 and (bottom four figures) Run 2 data sets. The candidates are divided into four independent bins of increasing neural network response per data taking period.

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Distribution of reconstructed $ { J \mskip -3mu/\mskip -2mu\psi \mskip 2mu} K ^- \pi ^+ $ invariant mass after application of a $ { J \mskip -3mu/\mskip -2mu\psi \mskip 2mu}$ mass constraint of candidates in (top four figures) the Run 1 and (bottom four figures) Run 2 data sets. The candidates are divided into four independent bins of increasing neural network response per data taking period.

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Tables and captions

Main sources of systematic uncertainty considered on the branching fraction measurements. The first uncertainty applies to the measurement of $\mathcal{B} ( B ^0_ s \!\rightarrow \overline{ K }{} {}^{*0} \mu ^+\mu ^- )$, the second to $\mathcal{B} ( B ^0_ s \!\rightarrow \overline{ K }{} {}^{*0} \mu ^+\mu ^- )/\mathcal{B} (\overline{ B }{} {}^0 \!\rightarrow \overline{ K }{} {}^{*0} \mu ^+\mu ^- )$ and the third to $\mathcal{B} ( B ^0_ s \!\rightarrow \overline{ K }{} {}^{*0} \mu ^+\mu ^- )/\mathcal{B} ( B ^0_ s \!\rightarrow { J \mskip -3mu/\mskip -2mu\psi \mskip 2mu} \overline{ K }{} {}^{*0} )$, respectively. A description of the different contributions can be found in the text. The first three sources of uncertainty affect the measured yield of the signal decay. The total uncertainty is the sum in quadrature of the individual sources. The final row indicates the additional uncertainty arising from the uncertainties on external parameters used in the measurements.

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Supplementary Material [file]

Supplementary material full pdf

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This ZIP file contains supplementary material for the publication LHCb-PAPER-2018-004. The files are: supplemantary.pdf : An overview of the extra text and figures *.pdf, *.png, *.eps, *.C : The additional figures in a variaty of file formats

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Created on 09 December 2018.Citation count from INSPIRE on 09 December 2018.