HOPPET: A Higher Order Perturbative Parton Evolution Toolkit
Project description
HOPPET: A Higher Order Perturbative Parton Evolution Toolkit
HOPPET is a package for carrying out DGLAP evolution and other common manipulations of parton distribution functions (PDFs) in particle physics. The core package is written in Fortran. This Python interface provides access to a key subset of the functionality, the part known in the documentation as the "streamlined" interface.
The full underlying code and documentation can be found at https://github.com/hoppet-code/hoppet.
Example usage
import hoppet as hp
import numpy as np
def main():
# choose the underlying spacing in y=log(1/x):
# smaller spacing gives higher accuracy but slower evolution
dy = 0.1
# choose NNLO evolution
nloop = 3
# Start hoppet
hp.Start(dy, nloop)
asQ0 = 0.35
Q0 = np.sqrt(2.0)
# Do the evolution starting from a standard benchmark initial condition
hp.Evolve(asQ0, Q0, nloop, 1.0, hp.BenchmarkPDFunpol, Q0)
# Evaluate the PDFs at some x values and print them
xvals = [1e-5,1e-4,1e-3,1e-2,0.1,0.3,0.5,0.7,0.9]
Q = 100.0
print('')
print(' Evaluating PDFs at Q =',Q, ' GeV')
print(' x u-ubar d-dbar 2(ubr+dbr) c+cbar gluon')
for ix in range(9):
pdf_array = hp.Eval(xvals[ix], Q)
print('{:7.1E} {:11.4E} {:11.4E} {:11.4E} {:11.4E} {:11.4E}'.format(
xvals[ix],
pdf_array[6 + 2] - pdf_array[6 - 2],
pdf_array[6 + 1] - pdf_array[6 - 1],
2 * (pdf_array[6 - 1] + pdf_array[6 - 2]),
pdf_array[6 - 4] + pdf_array[6 + 4],
pdf_array[6 + 0]
))
hp.DeleteAll()
For more examples take a look at example_py. The above example is essentially identical to tabulation_example.py and prints the output of a typical benchmark PDF.
Citation policy
If you use this program in a scientific publication we ask that you cite
G.P. Salam, J. Rojo, 'A Higher Order Perturbative Parton Evolution Toolkit (HOPPET)', Comput. Phys. Commun. 180 (2009) 120-156, arXiv:0804.3755
and
A. Karlberg, P. Nason, G.P. Salam, G. Zanderighi & F. Dreyer arXiv:2510.09310.
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