Search for new physics in rare B decays

TLDR: In this article, a search for the decay B±→K±K±π∓ was performed using data collected by the OPAL detector at LEP. No evidence for a signal was observed and a 90% confidence level upper limit of 1.29×10−4 was set for the branching ratio.

About: This article is published in Physics Letters B.The article was published on 2000-03-16 and is currently open access. It has received 10 citations till now. The article focuses on the topics: Branching fraction.

Figures

Fig. 3. Invariant mass distribution of the Ky Ky pq candidates Ž . wafter all selection criteria were applied a via intermediate K Ž .resonance and b with direct production. The dots represent the data, the solid line shows the expected signal shape from Monte Carlo events after all the selection criteria were applied with arbitrary normalisation, and the dashed line is the expected background.

Table 1 Summary of d Erd x selection criteria: d Erd x is the differ-p ŽK . ence between the measured value of the ionisation energy loss in Ž .the jet chamber and the expected value for p K and s represents the expected standard deviation of the distribution. Nd Er d x is the number of jet chamber hits used for d Erd x. The d Erd x cuts were chosen based on probability values.

Fig. 4. Comparison of ANN input variables for Dwq candidates. The solid line represents the qq Monte Carlo and the dots are the data.

Frequently asked questions

Q1. What contributions have the authors mentioned in the paper "Search for new physics in rare b decays" ?

In this paper, a search for the decay BTMK K p was performed using data collected by the OPAL detector at LEP. No evidence for a signal was observed and a 90 % confidence level upper limit of 1.29=10 was set for the branching ratio. 

Q2. What was the b-tagging algorithm used to select vertices with a?

An artificial neural network with inputs based on decay length significance, vertex multiplicity and invariant mass w xinformation 19 was used to select vertices with a high probability of coming from b hadron decays. 

Q3. What was the b-tagging algorithm used to suppress the background events?

Since the hadronic data sample consisted mostly of non-bb events, the authors suppressed these events by means of a b-tagging algorithm, based on reconstructed displaced secondary vertices. 

Q4. How is the efficiency of the d Erd x cut calculated?

If one assumes resonance production, then the lowest efficiency, 8.11"0.19%, is obtained when assuming the signal decay channel w 0Ž .is via K 892 . 

Q5. What is the mass of the K p system?

y qnance , then the mass of the K p system can be exploited to further reduce background where the pion and one of the kaons are from the decay of a Kw resonance. 

Q6. How did the authors determine the signal to background ratio?

To enhance the signal to background ratio the authors required the momentum of the Dwq candidate to be larger than 15 GeVrc; the Dwq decay vertex to be at least 50 mm away from the interaction point; and the helicity angle, u ) , between the kaon momentum in the D rest frame and the D direction in the laboratory frame to satisfy cosu ) - 0.7. Background estimation, after applying these sew xlection criteria, was done as in 23 . 

Q7. What is the way to estimate the efficiency of the Dwq mesons?

The authors took advantage of the abundance and relative ease of reconstruction of Dwq mesons, and exploited them for testing the systematic uncertainties associated with the d Erd x selection criteria. 

Q8. What was the b-tagging algorithm used to select the vertices?

The neural network used seven input parameŽ .ters: the momenta of the three tracks p , p ; thep K Ž .B candidate momentum p ; the ratio of B candi-B Ž .date energy to the jet energy X ; the decay length;jet and the vertex probability, the probability of the three tracks to originate from a common vertex which is calculated using the track parameters. 

Q9. How did the background to the process ByTMKyKypq be estimated?

The background to the process By™KyKypqwas estimated by fitting a second-order polynomial to the invariant mass of a combinatorial background, obtained by releasing the ANN cut, and then normalŽising the shape to the mass side-bands of Fig. 3 4–5 2 2 .GeVrc and 5.6–6 GeVrc . 

Q10. What is the decay ByTM KyKypq 10?

However the decay By™ KyKypq 10, either as a direct three-body decay or through a Kw-like resonance, is a clear signature of this process. 

Q11. How was the heavy quark fragmentation performed?

The heavy quark fragmentation was pa-rameterised by the fragmentation function of Peterw xson et al. 15 , and all samples were processed with w xthe OPAL detector simulation package 16 . 

Q12. How did the authors assign the efficiency of the ANN to the qq Monte Carlo?

In order to assign a systematic uncertainty to the efficiency of the ANN, the authors took the difference between the fraction of Dwq events passing the ANN cut in the data to that in the qq Monte Carlo.