Kinematic Fitting for b 1 π Events
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Transcript of Kinematic Fitting for b 1 π Events
Kinematic Fitting for b1π Events
William LevineCarnegie Mellon University
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Kinematic Fitting Fit with constraints Constraints:
Conservation of energy and momentum Mass constraint (i.e. π0 → γγ)
Informally: wiggle the measured values (within errors) to satisfy constraints
Formally: least-squares fit with constraints enforced by Lagrange multipliers
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What’s the point? Cut out bad events
Confidence level measures goodness of fit Cuts out a well-defined amount of signal
Better understand errors Confidence level and pull distribution show how
well errors are estimated Improve errors on measured quantities
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Hall D software & Procedure Generate signal (genr8)
Final state: pπ+π+π− π− γγ Several exotic quantum number mesons can
decay to b1π
γ p → X(2000) p↪ b1 π−
↪ ω π+ ↪ π0 π+ π−
↪ γ γ
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Hall D software & Procedure Generating background
bggen/pythia Simulation
hd_parsim Modified to get error matrices for each particle
Analysis DKinFit class takes particles’4-momenta & error
matrices and does the fit
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b1π results No background Only look at events with final state pπ− π−
π+π+γγ Eliminates events with lost particles
Plot ω mass (π+π-γγ) Cheating by only looking at “correct” π’s
Fits with and without π0 mass constraint
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b1π results: before fitting
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b1π results: after fitting
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b1π results
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b1π results: after fitting and confidence level cut
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b1π results
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Background results Again, only looking at final state pπ− π− π+π+γγ End up with events with missing particles
Confidence level cut removes about 45% of events Cannot isolate a specific channel
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Background results: before fitting
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Background results
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Background results: after
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Kinematic Fitting Cuts bad events Improves errors on measured quantities It works!
Only as well as you estimate your errors
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