susy_cross_section: Table-format cross-section data handler
A Python package for cross section tables and interpolation.
This package supports Python 2.7 and 3.5+.
Install simply via PyPI and use a script as:
$ pip install susy-cross-section
$ susy-xs get 13TeV.n2x1+.wino 500
(32.9 +2.7 -2.7) fb
$ susy-xs get 13TeV.n2x1+.wino 513.3
(29.4 +2.5 -2.5) fb
which gives the 13 TeV LHC cross section to wino-like neutralino-chargino pair-production (p p > n2 x1+
), etc.
The values are taken from LHC SUSY Cross Section Working Group with interpolation if needed.
To see more information, you will use show
sub-command, which displays the cross-section table with physical attributes.
$ susy-xs show 13TeV.n2x1+.wino
------------------------------------------------------------------------
TABLE "xsec" (unit: fb)
------------------------------------------------------------------------
value unc+ unc-
m_wino
100 13895.100000 485.572000 485.572000
125 6252.210000 222.508000 222.508000
150 3273.840000 127.175000 127.175000
... ... ... ...
475 41.023300 3.288370 3.288370
500 32.913500 2.734430 2.734430
525 26.602800 2.299570 2.299570
... ... ... ...
1950 0.005096 0.001769 0.001769
1975 0.004448 0.001679 0.001679
2000 0.003892 0.001551 0.001551
[77 rows x 3 columns]
collider: pp-collider, ECM=13TeV
calculation order: NLO+NLL
PDF: Envelope by LHC SUSY Cross Section Working Group
included processes:
p p > wino0 wino+
You may also notice that the above value for 513.3GeV is obtained by interpolating the grid data.
You can list all the available tables, or search for tables you want, by list
sub-command:
$ susy-xs list
13TeV.n2x1-.wino lhc_susy_xs_wg/13TeVn2x1wino_envelope_m.csv
13TeV.n2x1+.wino lhc_susy_xs_wg/13TeVn2x1wino_envelope_p.csv
13TeV.n2x1+-.wino lhc_susy_xs_wg/13TeVn2x1wino_envelope_pm.csv
13TeV.slepslep.ll lhc_susy_xs_wg/13TeVslepslep_ll.csv
13TeV.slepslep.maxmix lhc_susy_xs_wg/13TeVslepslep_maxmix.csv
13TeV.slepslep.rr lhc_susy_xs_wg/13TeVslepslep_rr.csv
...
$ susy-xs list 7TeV
7TeV.gg.decoup nllfast/7TeV/gdcpl_nllnlo_mstw2008.grid
7TeV.gg.high nllfast/7TeV/gg_nllnlo_hm_mstw2008.grid
7TeV.gg nllfast/7TeV/gg_nllnlo_mstw2008.grid
...
7TeV.ss10 nllfast/7TeV/ss_nllnlo_mstw2008.grid
7TeV.st nllfast/7TeV/st_nllnlo_mstw2008.grid
$ susy-xs list 8t decoup
8TeV.gg.decoup nllfast/8TeV/gdcpl_nllnlo_mstw2008.grid
8TeV.sb10.decoup nllfast/8TeV/sdcpl_nllnlo_mstw2008.grid
and run for it:
$ susy-xs get 8TeV.sb10.decoup 1120
(0.00122 +0.00019 -0.00019) pb
For more help, try to run with --help
option.
$ susy-xs --help
Usage: susy-xs [OPTIONS] COMMAND [ARGS]...
...
$ susy-xs get --help
Usage: susy-xs get [OPTIONS] TABLE [ARGS]...
...
You can uninstall this package as simple as
$ pip uninstall susy-cross-section
Uninstalling susy-cross-section-x.y.z:
...
Proceed (y/n)?
Production cross sections are the most important values for high-energy physics collider experiments. Many collaborations publish their cross-section tables, calculated in various tools or schemes, which are available on the WWW. For SUSY scenarios, the values provided by LHC SUSY Cross Section Working Group are the most famous source of the "nominal" cross section expectation for the LHC, while NNLL-fast collaboration publishes those for colored process at the very high precision.
However, these results are provided in various format; for example, some are in HTML with absolute combined symmetric uncertainties, and others are in CSV files with relative asymmetric uncertainties.
This package susy_cross_section
is provided to handle those data regardless of their format.
This package reads any table-like grid files with help of pandas DataFrame, and interpret any format of uncertainties once an annotation file (info
files) written in JSON format is provided, which allows one to interpolate the grid easily, e.g., by using scipy.interpolate package.
For simpler use-case, a command-line script susy-xs
is provided, with which one can get the cross section in several simple scenarios.
For more customization, you can use this package from your own code with more detailed interpolator options (linear-interpolation, loglog-spline-interpolation, etc.) or with your interpolator.
The document is provided on readthedocs.io, together with API references. A PDF file is also distributed with this package.
The program codes included in this repository are licensed by Sho Iwamoto / Misho under MIT License.
The non-program-code documents are licensed by Sho Iwamoto / Misho under CC BY-NC 4.0 International License.
Original cross-section data is distributed by other authors, including
Full list of references are shown in citations.pdf distributed with this package, where you will find the citation policy for this package.