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Update n3fit/src/n3fit with code from Bayesian_PDF/bPDF_dc
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‎n3fit/src/n3fit/Basic_runcard_normal/filter.yml‎

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#
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# Configuration file for n3fit: nnpdf40-like.yml
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#
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######################################################################################
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description: NNLO baseline fit, NNPDF4.0 dataset, compare to NNPDF40_nnlo_as_01180_qcd
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######################################################################################
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dataset_inputs:
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- {dataset: NMC_NC_NOTFIXED_EM-F2, frac: 0.75, variant: legacy_dw}
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- {dataset: NMC_NC_NOTFIXED_P_EM-SIGMARED, frac: 0.75, variant: legacy}
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- {dataset: SLAC_NC_NOTFIXED_P_EM-F2, frac: 0.75, variant: legacy_dw}
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- {dataset: SLAC_NC_NOTFIXED_D_EM-F2, frac: 0.75, variant: legacy_dw}
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- {dataset: BCDMS_NC_NOTFIXED_P_EM-F2, frac: 0.75, variant: legacy_dw}
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- {dataset: BCDMS_NC_NOTFIXED_D_EM-F2, frac: 0.75, variant: legacy_dw}
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- {dataset: CHORUS_CC_NOTFIXED_PB_NU-SIGMARED, frac: 0.75, variant: legacy_dw}
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- {dataset: CHORUS_CC_NOTFIXED_PB_NB-SIGMARED, frac: 0.75, variant: legacy_dw}
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- {dataset: NUTEV_CC_NOTFIXED_FE_NU-SIGMARED, cfac: [MAS], frac: 0.75, variant: legacy_dw}
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- {dataset: NUTEV_CC_NOTFIXED_FE_NB-SIGMARED, cfac: [MAS], frac: 0.75, variant: legacy_dw}
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- {dataset: HERA_NC_318GEV_EM-SIGMARED, frac: 0.75, variant: legacy}
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- {dataset: HERA_NC_225GEV_EP-SIGMARED, frac: 0.75, variant: legacy}
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- {dataset: HERA_NC_251GEV_EP-SIGMARED, frac: 0.75, variant: legacy}
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- {dataset: HERA_NC_300GEV_EP-SIGMARED, frac: 0.75, variant: legacy}
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- {dataset: HERA_NC_318GEV_EP-SIGMARED, frac: 0.75, variant: legacy}
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- {dataset: HERA_CC_318GEV_EM-SIGMARED, frac: 0.75, variant: legacy}
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- {dataset: HERA_CC_318GEV_EP-SIGMARED, frac: 0.75, variant: legacy}
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- {dataset: HERA_NC_318GEV_EAVG_CHARM-SIGMARED, frac: 0.75, variant: legacy}
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- {dataset: HERA_NC_318GEV_EAVG_BOTTOM-SIGMARED, frac: 0.75, variant: legacy}
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- {dataset: DYE866_Z0_800GEV_DW_RATIO_PDXSECRATIO, frac: 0.75, variant: legacy}
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- {dataset: DYE866_Z0_800GEV_PXSEC, frac: 0.75, variant: legacy}
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- {dataset: DYE605_Z0_38P8GEV_DW_PXSEC, frac: 0.75, variant: legacy}
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- {dataset: DYE906_Z0_120GEV_DW_PDXSECRATIO, frac: 0.75, cfac: [ACC], variant: legacy}
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- {dataset: CDF_Z0_1P96TEV_ZRAP, frac: 0.75, variant: legacy}
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- {dataset: D0_Z0_1P96TEV_ZRAP, frac: 0.75, variant: legacy}
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- {dataset: D0_WPWM_1P96TEV_ASY, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_WPWM_7TEV_36PB_ETA, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_Z0_7TEV_36PB_ETA, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_Z0_7TEV_49FB_HIMASS, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_Z0_7TEV_LOMASS_M, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_WPWM_7TEV_46FB_CC-ETA, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_Z0_7TEV_46FB_CC-Y, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_Z0_7TEV_46FB_CF-Y, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_Z0_8TEV_HIMASS_M-Y, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_Z0_8TEV_LOWMASS_M-Y, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_Z0_13TEV_TOT, frac: 0.75, cfac: [NRM], variant: legacy}
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- {dataset: ATLAS_WPWM_13TEV_TOT, frac: 0.75, cfac: [NRM], variant: legacy}
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- {dataset: ATLAS_WJ_8TEV_WP-PT, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_WJ_8TEV_WM-PT, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_Z0J_8TEV_PT-M, frac: 0.75, variant: legacy_10}
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- {dataset: ATLAS_Z0J_8TEV_PT-Y, frac: 0.75, variant: legacy_10}
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- {dataset: ATLAS_TTBAR_7TEV_TOT_X-SEC, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_TTBAR_8TEV_TOT_X-SEC, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_TTBAR_13TEV_TOT_X-SEC, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_TTBAR_8TEV_LJ_DIF_YT-NORM, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_TTBAR_8TEV_LJ_DIF_YTTBAR-NORM, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_TTBAR_8TEV_2L_DIF_YTTBAR-NORM, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_1JET_8TEV_R06_PTY, frac: 0.75, variant: legacy_decorrelated}
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- {dataset: ATLAS_2JET_7TEV_R06_M12Y, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_PH_13TEV_XSEC, frac: 0.75, cfac: [EWK], variant: legacy}
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- {dataset: ATLAS_SINGLETOP_7TEV_TCHANNEL-XSEC, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_SINGLETOP_13TEV_TCHANNEL-XSEC, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_SINGLETOP_7TEV_T-Y-NORM, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_SINGLETOP_7TEV_TBAR-Y-NORM, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_SINGLETOP_8TEV_T-RAP-NORM, frac: 0.75, variant: legacy}
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- {dataset: ATLAS_SINGLETOP_8TEV_TBAR-RAP-NORM, frac: 0.75, variant: legacy}
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- {dataset: CMS_WPWM_7TEV_ELECTRON_ASY, frac: 0.75}
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- {dataset: CMS_WPWM_7TEV_MUON_ASY, frac: 0.75, variant: legacy}
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- {dataset: CMS_Z0_7TEV_DIMUON_2D, frac: 0.75}
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- {dataset: CMS_WPWM_8TEV_MUON_Y, frac: 0.75, variant: legacy}
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- {dataset: CMS_Z0J_8TEV_PT-Y, frac: 0.75, cfac: [NRM], variant: legacy_10}
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- {dataset: CMS_2JET_7TEV_M12-Y, frac: 0.75, variant: legacy}
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- {dataset: CMS_1JET_8TEV_PTY, frac: 0.75, variant: legacy}
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- {dataset: CMS_TTBAR_7TEV_TOT_X-SEC, frac: 0.75, variant: legacy}
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- {dataset: CMS_TTBAR_8TEV_TOT_X-SEC, frac: 0.75, variant: legacy}
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- {dataset: CMS_TTBAR_13TEV_TOT_X-SEC, frac: 0.75, variant: legacy}
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- {dataset: CMS_TTBAR_8TEV_LJ_DIF_YTTBAR-NORM, frac: 0.75, variant: legacy}
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- {dataset: CMS_TTBAR_5TEV_TOT_X-SEC, frac: 0.75, variant: legacy}
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- {dataset: CMS_TTBAR_8TEV_2L_DIF_MTTBAR-YT-NORM, frac: 0.75, variant: legacy}
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- {dataset: CMS_TTBAR_13TEV_2L_DIF_YT, frac: 0.75, variant: legacy}
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- {dataset: CMS_TTBAR_13TEV_LJ_2016_DIF_YT, frac: 0.75, variant: legacy}
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- {dataset: CMS_SINGLETOP_7TEV_TCHANNEL-XSEC, frac: 0.75, variant: legacy}
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- {dataset: CMS_SINGLETOP_8TEV_TCHANNEL-XSEC, frac: 0.75, variant: legacy}
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- {dataset: CMS_SINGLETOP_13TEV_TCHANNEL-XSEC, frac: 0.75, variant: legacy}
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- {dataset: LHCB_Z0_7TEV_DIELECTRON_Y, frac: 0.75}
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- {dataset: LHCB_Z0_8TEV_DIELECTRON_Y, frac: 0.75}
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- {dataset: LHCB_WPWM_7TEV_MUON_Y, frac: 0.75, cfac: [NRM]}
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- {dataset: LHCB_Z0_7TEV_MUON_Y, frac: 0.75, cfac: [NRM]}
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- {dataset: LHCB_WPWM_8TEV_MUON_Y, frac: 0.75, cfac: [NRM]}
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- {dataset: LHCB_Z0_8TEV_MUON_Y, frac: 0.75, cfac: [NRM]}
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- {dataset: LHCB_Z0_13TEV_DIMUON-Y, frac: 0.75}
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- {dataset: LHCB_Z0_13TEV_DIELECTRON-Y, frac: 0.75}
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################################################################################
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datacuts:
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t0pdfset: 240701-02-rs-nnpdf40-baseline
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q2min: 3.49
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w2min: 12.5
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################################################################################
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# NNLO QCD TRN evolution
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theory:
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theoryid: 40_000_000
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################################################################################
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trvlseed: 591866982
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nnseed: 945709987
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mcseed: 519562661
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genrep: true
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diagonal_basis: false
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################################################################################
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parameters: # This defines the parameter dictionary that is passed to the Model Trainer
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nodes_per_layer: [25, 20, 8]
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activation_per_layer: [tanh, tanh, linear]
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initializer: glorot_normal
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optimizer:
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clipnorm: 6.073e-6
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learning_rate: 2.621e-3
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optimizer_name: Nadam
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epochs: 17000
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positivity:
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initial: 184.8
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multiplier:
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integrability:
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initial: 10
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multiplier:
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stopping_patience: 0.1
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layer_type: ['dense', 'dense', 'dense']
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dropout: 0.0
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threshold_chi2: 3.5
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prior_prec: 0.001
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std_init: -9
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kl_weight_factor: 0.001
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fitting:
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fitbasis: EVOL
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savepseudodata: True
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basis:
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- {fl: sng, trainable: false, smallx: [1.089, 1.119], largex: [1.475, 3.119]}
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- {fl: g, trainable: false, smallx: [0.7504, 1.098], largex: [2.814, 5.669]}
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- {fl: v, trainable: false, smallx: [0.479, 0.7384], largex: [1.549, 3.532]}
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- {fl: v3, trainable: false, smallx: [0.1073, 0.4397], largex: [1.733, 3.458]}
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- {fl: v8, trainable: false, smallx: [0.5507, 0.7837], largex: [1.516, 3.356]}
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- {fl: t3, trainable: false, smallx: [-0.4506, 0.9305], largex: [1.745, 3.424]}
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- {fl: t8, trainable: false, smallx: [0.5877, 0.8687], largex: [1.522, 3.515]}
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- {fl: t15, trainable: false, smallx: [1.089, 1.141], largex: [1.492, 3.222]}
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################################################################################
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positivity:
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posdatasets:
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# Positivity Lagrange Multiplier
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- {dataset: NNPDF_POS_2P24GEV_F2U, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_F2D, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_F2S, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_FLL, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_DYU, maxlambda: 1e10}
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- {dataset: NNPDF_POS_2P24GEV_DYD, maxlambda: 1e10}
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- {dataset: NNPDF_POS_2P24GEV_DYS, maxlambda: 1e10}
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- {dataset: NNPDF_POS_2P24GEV_F2C, maxlambda: 1e6}
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# Positivity of MSbar PDFs
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- {dataset: NNPDF_POS_2P24GEV_XUQ, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_XUB, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_XDQ, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_XDB, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_XSQ, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_XSB, maxlambda: 1e6}
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- {dataset: NNPDF_POS_2P24GEV_XGL, maxlambda: 1e6}
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added_filter_rules:
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- dataset: NNPDF_POS_2P24GEV_FLL
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rule: "x > 5.0e-7"
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- dataset: NNPDF_POS_2P24GEV_F2C
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rule: "x < 0.74"
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- dataset: NNPDF_POS_2P24GEV_XGL
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rule: "x > 0.1"
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- dataset: NNPDF_POS_2P24GEV_XUQ
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rule: "x > 0.1"
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- dataset: NNPDF_POS_2P24GEV_XUB
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rule: "x > 0.1"
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- dataset: NNPDF_POS_2P24GEV_XDQ
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rule: "x > 0.1"
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- dataset: NNPDF_POS_2P24GEV_XDB
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rule: "x > 0.1"
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- dataset: NNPDF_POS_2P24GEV_XSQ
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rule: "x > 0.1"
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- dataset: NNPDF_POS_2P24GEV_XSB
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rule: "x > 0.1"
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integrability:
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integdatasets:
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- {dataset: NNPDF_INTEG_3GEV_XT8, maxlambda: 1e2}
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- {dataset: NNPDF_INTEG_3GEV_XT3, maxlambda: 1e2}
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################################################################################
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debug: false
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maxcores: 8

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