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reconstruct_B2Kpi.jl
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reconstruct_B2Kpi.jl
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using UnROOT
using BelleAnalysis.Converter
f = ROOTFile("samples/B2Kpi_100.root")
data, offsets = UnROOT.array(f, "tree/TrackFitResults/TrackFitResults.m_tau[5]", raw=true)
events = UnROOT.splitup(data, offsets, TrackFitResult)
using Plots
using Combinatorics
using LaTeXStrings
histogram([begin
if t1.omega * t2.omega > 0.; return missing; end
px1 = 0.004355344375 / abs(t1.omega) * cos(t1.phi0)
px2 = 0.004355344375 / abs(t2.omega) * cos(t2.phi0)
py1 = 0.004355344375 / abs(t1.omega) * sin(t1.phi0)
py2 = 0.004355344375 / abs(t2.omega) * sin(t2.phi0)
pz1 = 0.004355344375 / abs(t1.omega) * t1.tanlambda
pz2 = 0.004355344375 / abs(t2.omega) * t2.tanlambda
E1 = sqrt(0.140^2 + px1^2 + py1^2 + pz1^2)
E2 = sqrt(0.495^2 + px2^2 + py2^2 + pz2^2)
M = sqrt((E1 + E2)^2 - ((px1+px2)^2 + (py1+py2)^2 + (pz1 + pz2)^2))
M
end for event in events for (t1, t2) in combinations(event, 2)],
bins=5.0:0.005:5.5,
xlabel=L"$M_{K^\pm\pi^\mp}$ (GeV$/c^2$)"
)