1 / 15

Scaling methods

Scaling methods. Overall method:. Main idea of scaling methods is:. C(E) is obtained in 5 different ways:. From horn-off data, E cut < E < E high From horn-off data, E low < E < E cut From horn-off data, all energies From horn-on data, E > E high

suzy
Download Presentation

Scaling methods

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. Scaling methods • Overall method: • Main idea of scaling methods is: • C(E) is obtained in 5 different ways: • From horn-off data, Ecut < E < Ehigh • From horn-off data, Elow < E < Ecut • From horn-off data, all energies • From horn-on data, E > Ehigh • From horn-on data, all energies (since • for )

  2. n from m+, MC Scaling method 1: L010000 data/MC ratio, Ecut < E < Ehigh data Scaled MC, no m+ data/MC L010000 data-Scaled MC

  3. n from m+, MC Scaling method 2: L010000 data/MC ratio, 4 < E < Ecut data Scaled MC, no m+ data/MC L010000 data-Scaled MC

  4. n from m+, MC Scaling method 3: L010000 data/MC ratio, all E Pol 4th deg data Scaled MC, no m+ data/MC L010000 data-Scaled MC

  5. n from m+, MC Scaling method 4: L010185 data/MC ratio, E > Ecut constant Pol 3rd deg data Scaled MC, no m+ data/MC L010185 data-Scaled MC

  6. n from m+, MC Scaling method 5: L010185 data/MC ratio, all E’s Pol 4th deg data Scaled MC, no m+ data/MC L010185 data-Scaled MC

  7. Fit methods • Used same procedure as Zarko & Rustem showed in Boston, i.e. Mega Fit such that: • Parameterize fluka p- yields. • 6 parameters to distort pt-xf p- distributions. • 2 parameters for kaons. • No Zbeam parameters, except for POT • Difference lies in that only regions with no m+ contributions are fit. Three separate fits were performed: • le010z000i (all E) & le010z185i (with E>Ecut) • le010z185i (with E>Ecut) • le010z000i (all E)

  8. Fit 1: le010z185i (E>Ecut) & le010z000i (all E) le010z185i le010z000i

  9. Fit 2: le010z185i (E>Ecut) le010z185i

  10. Fit 3: le010z000i (all E) le010z000i

  11. Predicting from the three fits:

  12. n from m+, MC Fit 1: le010z185i (E>Ecut) & le010z000i (all E) data Fit MC, no m+ MC (no m+) Fit MC (no m+) data-Fit MC

  13. n from m+, MC Fit 2: le010z185i (E>Ecut) data Fit MC, no m+ MC (no m+) Fit MC (no m+) data-Fit MC

  14. n from m+, MC Fit 3: le010z000i (all E) MC (no m+) Fit MC (no m+) data Fit MC, no m+ data-Fit MC

  15. n from m+ decay candidates n from m+ decay candidates Summary of Results Expected to be negative Should be ~0 if data/MC from horn-off is trust worthy in this region Should be 0 by construction Should be real nubars from m+ all methods (except fit method 2) all methods

More Related