1 / 8

NuMI Data-MC Comparisons: Overview of Betancourt-Minnesota Meeting 11-02-2011

Explore the comparison of data and Monte Carlo using POT normalization, Kalman Track with specified cuts, FHC data track length comparison, and more. Discover the discrepancies and adjustments made during the analysis process.

sari
Télécharger la présentation

NuMI Data-MC Comparisons: Overview of Betancourt-Minnesota Meeting 11-02-2011

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. NuMI Data-MC comparisons Minerba Betancourt Minnesota Offline meeting 11-02-2011

  2. Overview • Trying to compare Data and MC using POT normalization • Using Kalman Track with the following cuts: • Files passing DataCheck quality cuts • Files with more than 6 DCMs • Events in the fiducial region, CosNuMI>0.7 and events in the spill window t>217us and t<227us • Comparison for FHC Data

  3. Track Length (cm) MC Scaled by POT Data after background subtraction Applying Random mask from Data to MC

  4. Some masks from MC look like this example, but a fraction of the data was taken with the X view installed and the muon catcher for both view. This is why the discrepancy In the track length plot about 3m.

  5. Number of planes and cells MC Scaled by POT

  6. CosNuMI MC Scaled by POT

  7. PE around the vertex MC Scaled by POT Using a function in the slicer to remove noise Without the noise

  8. Total PE Using a function in the slicer to remove noise Without the noise

More Related