Kinematic Fitting for b 1 π Events

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Kinematic Fitting for b 1 π Events William Levine Carnegie Mellon University

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Kinematic Fitting for b 1 π Events. William Levine Carnegie Mellon University. Kinematic Fitting. Fit with constraints Constraints: Conservation of energy and momentum Mass constraint (i.e. π 0 → γγ ) Informally: wiggle the measured values (within errors) to satisfy constraints - PowerPoint PPT Presentation

Transcript of Kinematic Fitting for b 1 π Events

Page 1: 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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