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Frequentist Analysis of Rosenbluth Data: A Study of Proton Form Factor Measurements

These are the Python scripts and subsequent results from this reanalysis of electron-proton scattering data from the NE11 experiment at SLAC (see this paper). Ratio of electric proton form factor to standard dipole for 1.75 <= Q^2 <= 8.83 Ratio of magnetic proton form factor to standard dipole for 1.75 <= Q^2 <= 8.83 Ratio of electric proton form factor to magnetic proton form factor for 1.75 <= Q^2 <= 8.83

Dependencies

The scripts are written in Python 3.5.2, so Python 3.0 or greater is required. numpy, scipy, and matplotlib are required.

Contents

File/Path name Description
Form Factors/ Plots (PNG files) of form factors and their ratios versus Q^2 for three different analyses
chi_square.py Performs chi-squared analysis of scattering data as reduced cross sections versus epsilon. Generates chi-squared distribution histograms.
data.csv 8 GeV scattering data from SLAC NE11, reported by Andivahis et al. 1994
data2.csv Annotated 8 GeV and 1.6 GeV scattering data from SLAC NE11, reported by Andivahis et al. 1994
data3.csv (not in use) Annotated 8 GeV and 1.6 GeV scattering data from SLAC NE11, reported by Andivahis et al. 1994
1.6 GeV cross sections and errors are multiplied by a normalizing factor of 0.958.
data4.csv (not in use) Annotated 8 GeV and 1.6 GeV scattering data from SLAC NE11, reported by Andivahis et al. 1994
1.6 GeV cross sections and errors are multiplied by a normalizing factor of 0.958. Includes values of E'.
data5.csv Annotated 8 GeV and 1.6 GeV scattering data from SLAC NE11, reported by Andivahis et al. 1994. Rows where angle ~= 90 degrees are marked to be multiplied by a normalizing factor.
ff_plot.py Generates plots of form factors (seen above) based on results CSVs generated by rosenbluth.py
latexify.py (not in use) Converts results CSVs generated by rosenbluth.py to LaTeX syntax for tables
rosenbluth.py Main analysis. Computes form factors and their errors given an input file and normalization factor. Generates output CSV files and form factor distribution histograms.

How to Use

rosenbluth.py

Analysis without any normalization of scattering data.

python rosenbluth.py data2.csv

Analysis with normalization of 1.6 GeV cross sections by 0.958.

python rosenbluth.py data2.csv 0.958

Analysis with normalization of 8 GeV cross sections where angle ~= 90 degrees by 0.958.

python rosenbluth.py data5.csv 0.958

chi_square.py

Chi-squared analysis without any normalization of scattering data.

python chi_square.py data2.csv

Chi-squared analysis with normalization of 1.6 GeV cross sections by 0.958.

python chi_square.py data2.csv 0.958

Chi-squared analysis with normalization of 8 GeV cross sections where angle ~= 90 degrees by 0.958.

python chi_square.py data5.csv 0.958

ff_plot.py

Plot form factors from 1 or more output files located in a /Figures/ subdirectory (generated by rosenbluth.py)

python ff_plot.py {results 1} {results 2} {results 3} ...