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config.yaml
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config.yaml
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#################################
# 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, 0, 1, 0, 0, 0, 0, 0, 0, 0, # - db
0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, # - g
0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, # - d = ubar
0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, # - u
0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, # - s+
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: PI
# 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: "HERMES $\\pi^-$ deuteron", file: "HERMES_PI_MINUS_DEUTERON.yaml", cuts: [{name: Qcut, min: 2.0, max: 50}, {name: zcut, min: 0.2, max: 0.8}], training fraction: 0.5}
- {name: "HERMES $\\pi^-$ proton", file: "HERMES_PI_MINUS_PROTON.yaml", cuts: [{name: Qcut, min: 2.0, max: 50}, {name: zcut, min: 0.2, max: 0.8}], training fraction: 0.5}
- {name: "HERMES $\\pi^+$ deuteron", file: "HERMES_PI_PLUS_DEUTERON.yaml", cuts: [{name: Qcut, min: 2.0, max: 50}, {name: zcut, min: 0.2, max: 0.8}], training fraction: 0.5}
- {name: "HERMES $\\pi^+$ proton", file: "HERMES_PI_PLUS_PROTON.yaml", cuts: [{name: Qcut, min: 2.0, max: 50}, {name: zcut, min: 0.2, max: 0.8}], training fraction: 0.5}
- {name: "COMPASS $\\pi^-$", file: "COMPASS_PI_MINUS.yaml", cuts: [{name: Qcut, min: 2.0, max: 50}], training fraction: 0.5}
- {name: "COMPASS $\\pi^+$", file: "COMPASS_PI_PLUS.yaml", cuts: [{name: Qcut, min: 2.0, max: 50}], training fraction: 0.5}
- {name: "BELLE $\\pi^\\pm$", file: "BELLE_PI_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.075, max: 0.9}], training fraction: 0.5}
- {name: "BABAR prompt $\\pi^\\pm$", file: "BABAR_PI_PLUS_MINUS_PROMPT.yaml", cuts: [{name: zcut, min: 0.076, max: 0.9}], training fraction: 0.5}
- {name: "TASSO 12 GeV $\\pi^\\pm$", file: "TASSO_12_PI_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.075, max: 0.9}], training fraction: 0.5}
- {name: "TASSO 14 GeV $\\pi^\\pm$", file: "TASSO_14_PI_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.075, max: 0.9}], training fraction: 0.5}
- {name: "TASSO 22 GeV $\\pi^\\pm$", file: "TASSO_22_PI_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.075, max: 0.9}], training fraction: 0.5}
- {name: "TPC $\\pi^\\pm$", file: "TPC_PI_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.075, max: 0.9}], training fraction: 0.5}
- {name: "TASSO 30 GeV $\\pi^\\pm$", file: "TASSO_30_PI_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.075, max: 0.9}], training fraction: 0.5}
- {name: "TASSO 34 GeV $\\pi^\\pm$", file: "TASSO_34_PI_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.075, max: 0.9}], training fraction: 0.5}
- {name: "TASSO 44 GeV $\\pi^\\pm$", file: "TASSO_44_PI_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.075, max: 0.9}], training fraction: 0.5}
- {name: "TOPAZ $\\pi^\\pm$", file: "TOPAZ_PI_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.075, max: 0.9}], training fraction: 0.5}
- {name: "ALEPH $\\pi^\\pm$", file: "ALEPH_PI_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "DELPHI total $\\pi^\\pm$", file: "DELPHI_PI_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "DELPHI $uds$ $\\pi^\\pm$", file: "DELPHI_PI_PLUS_MINUS_UDS.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "DELPHI bottom $\\pi^\\pm$", file: "DELPHI_PI_PLUS_MINUS_B.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "OPAL $\\pi^\\pm$", file: "OPAL_PI_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "SLD total $\\pi^\\pm$", file: "SLD_PI_PLUS_MINUS.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "SLD $uds$ $\\pi^\\pm$", file: "SLD_PI_PLUS_MINUS_UDS.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
#- {name: "SLD charm $\\pi^\\pm$", file: "SLD_PI_PLUS_MINUS_C.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}
- {name: "SLD bottom $\\pi^\\pm$", file: "SLD_PI_PLUS_MINUS_B.yaml", cuts: [{name: zcut, min: 0.02, max: 0.9}], training fraction: 0.5}