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The SIA and SIDIS data sets to extract SHK22.h light charged hadron FFs and the corresponding config file #3

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The SIA and SIDIS data sets to extract SHK22.h light charged hadron FFs and the corresponding config file #3

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87feac0
Update README.md
hamzeh-khanpour Jul 6, 2022
0351417
Merge branch 'MapCollaboration:main' into main
hamzeh-khanpour Jul 6, 2022
2303a66
SIA and SIDIS data sets to extract SHK22.h light charged hadron FFs […
hamzeh-khanpour Jul 23, 2022
c38ab93
SIA and SIDIS data sets to extract SHK22.h light charged hadron FFs […
hamzeh-khanpour Jul 25, 2022
44fc45a
Config file for SHK22.h light charged hadron FFs [2202.10779 [hep-ph]]
hamzeh-khanpour Jul 25, 2022
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2 changes: 1 addition & 1 deletion README.md
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![alt text](resources/MontBlanc.jpg "Mont Blanc")
![alt text](resources/MontBlanc.jpg "Mont Blanc")

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.6264693.svg)](https://doi.org/10.5281/zenodo.6264693)

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122 changes: 122 additions & 0 deletions config/SHK22_h/SHK22_h_charged_hadron_FFs.yaml
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#
# SHK22.h: Neural network QCD analysis of charged hadron fragmentation functions in the presence of SIDIS data,
# Maryam Soleymaninia, Hadi Hashamipour, Hamzeh Khanpour,
# Published in: Phys.Rev.D 105 (2022) 11, 11;
# e-Print: 2202.10779 [hep-ph]
#
#################################
# Predictions
#################################
Predictions:
# Perturbative order, 0: LO, 1: NLO
perturbative order: 1

# Initial scale in GeV to be used for the DGLAP evolution of the FFs.
mu0: 5

# Quark thresholds
thresholds: [0, 0, 0, 1.51, 4.92]

# Strong coupling
alphas:
aref: 0.118
Qref: 91.1876

# Fine-structure constant
alphaem:
aref: 0.00776578395589
Qref: 91.1876

# APFEL++ grid
xgrid:
- [100, 1e-2, 3]
- [60, 2e-1, 3]
- [40, 8e-1, 3]

# PDF set
pdfset:
name: NNPDF31_nlo_pch_as_0118
member: -1 #N>=0 for a specific member (0 for central) ; N<0 for all members to be used randomly(flat dist)

#################################
# Optimiser
#################################
# Parameters of the optimiser managed by ceres-solver
Optimizer:
max_num_iterations: 3000
chi2_tolerance: 3

#################################
# NNAD
#################################
NNAD:
# Initialisation seed
seed: 0

# Architecture
architecture: [1, 20, 7]

# The output function can be either the activation function of the
# NN (0), or linear (1), or quadratic (2). If this entry is absent a
# linear function is assumed.
output function: 2

# The flavour map gives the the specific combinations of
# distributions in the physical-basis (d, u, s, ..) to be fitted to
# the data. The number of combinations has to match the number of
# nodes of the output layer of the NN given in the
# architecture. When defining the flavour map, one should keep in
# mind that the code computes predictions using the QCD-evolution
# basis (Sigma, V, T3, ...). Therefore, in general,
# QCD-evolution-like combinations should be preferred. Moreover, the
# distributions are assumed to be for the positive charge of the a
# given hadronic species. The negative distributions are derived
# using charge conjugation (q->qbar).

# tb bb cb sb ub db g d u s c b t # Combinations to be fitted (i.e. output of the NN):
flavour map: [0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, # - ub
0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, # - db + sb
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, # - g
0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, # - d+s
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, # - u
0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, # - c+
0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0] # - b+

#################################
# Data
#################################
Data:
# Seed used for the replica generation and the splitting between
# training and validation (do not use a too large number here in
# order to avoid correlation in the replica generation).
seed: 2

# Hadronic species being fitted. This is used to make sure that all
# data sets included in the fit actually refer to the correct
# species.
hadron: H

# Datasets to be included in the fit along with specific cuts and
# traning fraction. Each single dataset can implement an arbitrary
# number of cuts determined by the name of the appropriate function
# (e.g. zcut) and the allowed range.
sets:
- {name: "COMPASS $H^-$", file: "COMPASS_H_MINUS.yaml", cuts: [{name: Qcut, min: 2.0, max: 50}], training fraction: 0.5}
- {name: "COMPASS $H^+$", file: "COMPASS_H_PLUS.yaml", cuts: [{name: Qcut, min: 2.0, max: 50}], training fraction: 0.5}
- {name: "TASSO 14 GeV $H^\\pm$", file: "TASSO_14_H_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.075, max: 0.9}], training fraction: 0.5}
- {name: "TASSO 22 GeV $H^\\pm$", file: "TASSO_22_H_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.075, max: 0.9}], training fraction: 0.5}
#- {name: "TASSO 35 GeV $H^\\pm$", file: "TASSO_35_H_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.075, max: 0.9}], training fraction: 0.5}
- {name: "TASSO 44 GeV $H^\\pm$", file: "TASSO_44_H_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.075, max: 0.9}], training fraction: 0.5}
- {name: "TPC $H^\\pm$", file: "TPC_H_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.075, max: 0.9}], training fraction: 0.5}
- {name: "ALEPH $H^\\pm$", file: "ALEPH_H_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "DELPHI total $H^\\pm$", file: "DELPHI_H_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "DELPHI $uds$ $H^\\pm$", file: "DELPHI_H_PLUS_MINUS_UDS.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "DELPHI bottom $H^\\pm$", file: "DELPHI_H_PLUS_MINUS_B.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "OPAL total $H^\\pm$", file: "OPAL_H_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "OPAL $uds$ $H^\\pm$", file: "OPAL_H_PLUS_MINUS_UDS.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "OPAL charm $H^\\pm$", file: "OPAL_H_PLUS_MINUS_C.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "OPAL bottom $H^\\pm$", file: "OPAL_H_PLUS_MINUS_B.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "SLD total $H^\\pm$", file: "SLD_H_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "SLD $uds$ $H^\\pm$", file: "SLD_H_PLUS_MINUS_UDS.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "SLD charm $H^\\pm$", file: "SLD_H_PLUS_MINUS_C.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "SLD bottom $H^\\pm$", file: "SLD_H_PLUS_MINUS_B.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
188 changes: 188 additions & 0 deletions data/ALEPH_H_PLUS_MINUS.yaml
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dependent_variables:
- header: {title: "ALEPH $1/\\sigma_{tot}d\\sigma/dz_h^{H^\\pm}$"}
qualifiers:
- {name: process, value: SIA}
- {name: Vs, value: 91.20}
- {name: prefactor, value: 1}
- {name: z, low: 0.008, high: 1.00, integrate: false}
- {name: hadron, value: H}
- {name: charge, value: 0}
values:
- errors:
- {label: unc, value: 9.2806}
- {label: mult, value: 0.01}
value: 501.3
- errors:
- {label: unc, value: 4.0520}
- {label: mult, value: 0.01}
value: 392.69
- errors:
- {label: unc, value: 2.9265}
- {label: mult, value: 0.01}
value: 274.81
- errors:
- {label: unc, value: 1.9756}
- {label: mult, value: 0.01}
value: 191.05
- errors:
- {label: unc, value: 1.4727}
- {label: mult, value: 0.01}
value: 139.94
- errors:
- {label: unc, value: 1.1198}
- {label: mult, value: 0.01}
value: 107.33
- errors:
- {label: unc, value: 0.8735}
- {label: mult, value: 0.01}
value: 85.09
- errors:
- {label: unc, value: 0.7209}
- {label: mult, value: 0.01}
value: 68.96
- errors:
- {label: unc, value: 0.5881}
- {label: mult, value: 0.01}
value: 56.8
- errors:
- {label: unc, value: 0.4938}
- {label: mult, value: 0.01}
value: 47.875
- errors:
- {label: unc, value: 0.3866}
- {label: mult, value: 0.01}
value: 37.655
- errors:
- {label: unc, value: 0.2873}
- {label: mult, value: 0.01}
value: 28.061
- errors:
- {label: unc, value: 0.2234}
- {label: mult, value: 0.01}
value: 21.389
- errors:
- {label: unc, value: 0.1746}
- {label: mult, value: 0.01}
value: 16.661
- errors:
- {label: unc, value: 0.1379}
- {label: mult, value: 0.01}
value: 13.233
- errors:
- {label: unc, value: 0.1085}
- {label: mult, value: 0.01}
value: 10.376
- errors:
- {label: unc, value: 0.0839}
- {label: mult, value: 0.01}
value: 7.928
- errors:
- {label: unc, value: 0.0662}
- {label: mult, value: 0.01}
value: 6.197
- errors:
- {label: unc, value: 0.0524}
- {label: mult, value: 0.01}
value: 4.874
- errors:
- {label: unc, value: 0.0431}
- {label: mult, value: 0.01}
value: 3.862
- errors:
- {label: unc, value: 0.0374}
- {label: mult, value: 0.01}
value: 3.055
- errors:
- {label: unc, value: 0.0284}
- {label: mult, value: 0.01}
value: 2.461
- errors:
- {label: unc, value: 0.0249}
- {label: mult, value: 0.01}
value: 1.995
- errors:
- {label: unc, value: 0.0184}
- {label: mult, value: 0.01}
value: 1.5555
- errors:
- {label: unc, value: 0.0162}
- {label: mult, value: 0.01}
value: 1.2122
- errors:
- {label: unc, value: 0.0123}
- {label: mult, value: 0.01}
value: 0.9401
- errors:
- {label: unc, value: 0.0129}
- {label: mult, value: 0.01}
value: 0.7346
- errors:
- {label: unc, value: 0.0088}
- {label: mult, value: 0.01}
value: 0.5634
- errors:
- {label: unc, value: 0.0057}
- {label: mult, value: 0.01}
value: 0.41
- errors:
- {label: unc, value: 0.0049}
- {label: mult, value: 0.01}
value: 0.2574
- errors:
- {label: unc, value: 0.0038}
- {label: mult, value: 0.01}
value: 0.172
- errors:
- {label: unc, value: 0.0032}
- {label: mult, value: 0.01}
value: 0.1042
- errors:
- {label: unc, value: 0.0030}
- {label: mult, value: 0.01}
value: 0.0608
- errors:
- {label: unc, value: 0.0032}
- {label: mult, value: 0.01}
value: 0.0263
- errors:
- {label: unc, value: 0.0020}
- {label: mult, value: 0.01}
value: 0.0049
independent_variables:
- header: {name: z}
values:
- {high: 0.012, low: 0.008, value: 0.01}
- {high: 0.02, low: 0.012, value: 0.016}
- {high: 0.03, low: 0.02, value: 0.025}
- {high: 0.04, low: 0.03, value: 0.035}
- {high: 0.05, low: 0.04, value: 0.045}
- {high: 0.06, low: 0.05, value: 0.055}
- {high: 0.07, low: 0.06, value: 0.065}
- {high: 0.08, low: 0.07, value: 0.075}
- {high: 0.09, low: 0.08, value: 0.085}
- {high: 0.1, low: 0.09, value: 0.095}
- {high: 0.12, low: 0.1, value: 0.11}
- {high: 0.14, low: 0.12, value: 0.13}
- {high: 0.16, low: 0.14, value: 0.15}
- {high: 0.18, low: 0.16, value: 0.17}
- {high: 0.2, low: 0.18, value: 0.19}
- {high: 0.225, low: 0.2, value: 0.2125}
- {high: 0.25, low: 0.225, value: 0.2375}
- {high: 0.275, low: 0.25, value: 0.2625}
- {high: 0.3, low: 0.275, value: 0.2875}
- {high: 0.325, low: 0.3, value: 0.3125}
- {high: 0.35, low: 0.325, value: 0.3375}
- {high: 0.375, low: 0.35, value: 0.3625}
- {high: 0.4, low: 0.375, value: 0.3875}
- {high: 0.43, low: 0.4, value: 0.415}
- {high: 0.46, low: 0.43, value: 0.445}
- {high: 0.49, low: 0.46, value: 0.475}
- {high: 0.52, low: 0.49, value: 0.505}
- {high: 0.55, low: 0.52, value: 0.535}
- {high: 0.6, low: 0.55, value: 0.575}
- {high: 0.65, low: 0.6, value: 0.625}
- {high: 0.7, low: 0.65, value: 0.675}
- {high: 0.75, low: 0.7, value: 0.725}
- {high: 0.8, low: 0.75, value: 0.775}
- {high: 0.9, low: 0.8, value: 0.85}
- {high: 1.0, low: 0.9, value: 0.95}
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