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Enhancing Analysis Frameworks for Atmospheric Muon and Neutrino Flux with New Macros

This thesis presents new scripts designed to plot and track parameter distributions in atmospheric muon and neutrino fluxes, addressing associated uncertainties. It details the computation of ratio errors using quadrature methods and integrates systematic errors through Gaussian smearing. A novel command structure enables users to execute multiple discovery-related macros simultaneously, generating plots, histograms, and threshold evaluations swiftly. The document also compares the effectiveness of clustering methods (Emfit, Cfit) and includes updates on data processing tools like AntDST and nTuple generation.

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Enhancing Analysis Frameworks for Atmospheric Muon and Neutrino Flux with New Macros

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  1. Group meeting J. P. Gómez-González 26/07/2012

  2. Tesis

  3. Macros New scripts to plot track parameters distributions including atm. muon&neutrino flux uncertainties:

  4. Macros Hot are the ratio errors computed? They are added in quadrature, so in each bin we put: ->SetBinError(bin,err) where: err = sqrt(pow(hmu_binerr,2)+hnu_binerr,2)) / cont being cont = hmu_content + hnu_content

  5. Detector effsystematic Now, integer number of fake signal events (during pex simulation) are injected. To correctly compute limits and stuff TS distribution have to be reweighted according to Poisson statistics. Systematic errors on the detector efficiency are included by means of a Gaussian smearing:

  6. Macros New code to run all discovery potential related macros at once. With one simple command plots, histograms, TS_thresholds, etc are produced. User can define cut variables and other inputs in the main script.

  7. Macros Test on new clustering code… Discovery power comparison between methods (Emfit, Cfit) for two different source extensions (0.5º left, 2.5º right) wrt the detector PSG

  8. Analysis • Compiled new version of AntDST (v1r2p5) • Revised code to produce nTuples • Run on rbr mc v2.0 files … • Compare: time residuals, ang. error estimate pull distribution…

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