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Evaluation of Mistagging and Resolution Systematics in Data Analysis

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allanpratt
12 diapositives · 160 Views · Jan 07, 2020

This study assesses the impact of mistagging and resolution differences between data and Monte Carlo simulations on measurement accuracy using smearing techniques. Results suggest that resolution effects are minimal, while mistagging can influence measurements, dependent on statistics.

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Evaluation of Mistagging and Resolution Systematics in Data Analysis
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  1. Resolutions and mistaggingsystematics Mauro Raggi29/06/2006

  2. Mistagging and resolution situation Less than 1/5 the bin size except for the very last bins Mistagging 400 cm 1.2 per mille The measurement is sensitive only to differences in resolutions and mistagging between Data and MC Mauro Raggi

  3. Resolution difference data MC sMK(data)=2.218 MeV sMK(MC)=2.265 MeV Difference(data-mc) = 2.1% Mauro Raggi

  4. Trying to evaulate the effect of smearing • I use the sample of MC IB DE INT from SS123 • I produce fake data merging IB+DE MC • I fit them using themself as MC • To produce smeared fake data samples • I use the Wtrue from MC and produce a Wsmeared as: • Wsmeared has only resolutions effects no reconstructions one Mauro Raggi

  5. Parametrization of the resolution Bin 0,1-0,15Resolution:0.0033Bin size:0.05worst case bin 0,85-0,9Resolution:0.0128Bin size:0.05 • The resolution as a function of the W value has been measured in 20 bins in W • In the smearing procedure for each event the smearing is applied according to the W value Mauro Raggi

  6. Notation • WTRUE= W with generated MC variables • WREC = W with the reconstructed MC variables • WSMEA= WTRUE smeared with the resolution only WSMEA(0%) is very similar to WREC but does’nt include the mistagging effect Mauro Raggi

  7. Evaluating mistagging effect • Fitting fake data distribution made with WREC with MCWREC we get a mesurement that is not affected by mistagging. In fact the data fake and MC have exactly the same mistagged events. • When we fit fake data distribution made with WSMEA using as MC distributions made with WREC we will see the effect of mistagging. In this case MC(REC) contains mistagging but fake data(SMEARED) did not. Mauro Raggi

  8. Smearing and mistagging 1M events Mauro Raggi

  9. Comments • A difference of 100% in mistagging induces a <2s fake interference • 50% resolution difference could induce a <1s effect of fake interference • The above results obviuosly depend on the statistics that in the previous sample is 5 times what we have in data. • Now I try redo the fits with a statistic that is comparable with the one we get in data Mauro Raggi

  10. Smearing and mistagging 0.2M events Mauro Raggi

  11. Comments • A difference of 100% in mistagging induces a <1s fake interference term • 50% resolution difference induces only a <0.5s effect of fake interference • The DE seems to be very stable with respect of both the effects Mauro Raggi

  12. Conclusions • The effect of resolutions seems to be absolutely negligible for both INT and DE terms • The result can be sensitive to 100% difference in mistagging between data and MC but with the present statistic and the present mistagging probability it is lower than the statistical uncertainties Mauro Raggi