b-dependent solution of the Balitsky-Kovchegov equation

In this work we solved the impact-parameter dependent Balitsky-Kovchegov equation with the recently proposed collinearly improved kernel. We find that the solutions do not present the Coulomb tails that have affected previous studies. We also show that once choosing an adequate initial condition it is possible to obtain a reasonable description of HERA data on the structure function of the proton, as well as on the cross section for the exclusive production of a J/ψ vector meson off proton targets. Here you can find the data sets associated with this work.

If you want to use this data set, please cite the following:
J.Cepila, J.G.Contreras and M.Matas, Collinearly improved kernel suppresses Coulomb tails in the impact-parameter dependent Balitsky-Kovchegov evolution, Phys.Rev. D99 (2019) no.5, 051502; arXiv:1812.02548 [hep-ph].

You can download the computed dat sets and an example in Python here: ciBK_data_files.zip.

Contact person: Marek Matas, marek.matas@fjfi.cvut.cz

README.txt:

Hi, welcome to the page with the data files regarding the scattering amplitude computed with the BK equation with the collinearly improved kernel. The computation was carried out as described in paper #insertArXiVHere. ########################## DATA FORMAT ############################# The scattering amplitude is stored in "data/N(r,b,Y).txt" The grids, that have been used for r and b are stored in "data/grid_in_r_and_b.txt" The grid for the values of Y are stored in "data/grid_in_Y.txt" ##### N(r,b,Y) ##### Each line in this file is the scattering amplitude N for all values of the impact parameter b for a fixed r and Y. The next line is again N for all values in b but for the next r and the same rapidity Y. After 226 lines, once the final value of r is reached, the next step in rapidity starts. Formaly, the format can be written as: N(r[0], b[0], Y[0]) N(r[0], b[1], Y[0]) ........... N(r[0], b[225], Y[0]) N(r[1], b[0], Y[0]) N(r[1], b[1], Y[0]) ........... N(r[1], b[225], Y[0]) . . . . N(r[225], b[0], Y[0]) N(r[225], b[1], Y[0]) ........... N(r[225], b[225], Y[0]) N(r[0], b[0], Y[1]) N(r[0], b[1], Y[1]) ........... N(r[0], b[225], Y[1]) N(r[1], b[0], Y[1]) N(r[1], b[1], Y[1]) ........... N(r[1], b[225], Y[1]) . . . . N(r[225], b[0], Y[1]) N(r[225], b[1], Y[1]) ........... N(r[225], b[225], Y[1]) N(r[0], b[0], Y[2]) N(r[0], b[1], Y[2]) ........... N(r[0], b[225], Y[2]) . . . ##### r, b ##### The grid for r and b was chosen to be identical, logarithmic from 10**-7 to 10**2 [1/GeV] The grid has 226 points in total, making it exactly 25 point per order of magnitude. ##### Y ##### Rapidity is computed in linear steps from 0 to 8 with the step lenght 0.1. ########################## PLOTTING ############################# All produced plots are saved in "plots/png" and "plots/eps" depending on the format. The plotting macro is called "plot.py" and it is a Python script. After installing packages "numpy" and "matplotlib", you can run it with python plot.py or python3 plot.py You can change the variables deciding which value of r/b to plot and which rapidity at the bottom of the script in . plot_vsb(r_index=10, Y=0.1) plot_vsr(b_index=10, Y=1.6) Further instructions for plotting are discussed in the script.