diff --git a/include/Rivet/Tools/SmearingFunctions.hh b/include/Rivet/Tools/SmearingFunctions.hh
--- a/include/Rivet/Tools/SmearingFunctions.hh
+++ b/include/Rivet/Tools/SmearingFunctions.hh
@@ -1,838 +1,838 @@
// -*- C++ -*-
#ifndef RIVET_SmearingFunctions_HH
#define RIVET_SmearingFunctions_HH
#include "Rivet/Tools/MomentumSmearingFunctions.hh"
#include "Rivet/Tools/ParticleSmearingFunctions.hh"
#include "Rivet/Tools/JetSmearingFunctions.hh"
namespace Rivet {
/// @name Electron efficiency and smearing functions
//@{
/// ATLAS Run 1 electron reconstruction efficiency
/// @todo Include reco eff (but no e/y discrimination) in forward region
/// @todo How to use this in combination with tracking eff?
inline double ELECTRON_EFF_ATLAS_RUN1(const Particle& e) {
if (e.abseta() > 2.5) return 0;
if (e.pT() < 10*GeV) return 0;
return (e.abseta() < 1.5) ? 0.95 : 0.85;
}
/// ATLAS Run 2 electron reco efficiency
/// @todo Currently just a copy of Run 1: fix!
inline double ELECTRON_EFF_ATLAS_RUN2(const Particle& e) {
return ELECTRON_EFF_ATLAS_RUN1(e);
}
/// @brief ATLAS Run 2 'loose' electron identification/selection efficiency
///
/// Values read from Fig 3 of ATL-PHYS-PUB-2015-041
/// @todo What about faking by jets or non-electrons?
inline double ELECTRON_IDEFF_ATLAS_RUN2_LOOSE(const Particle& e) {
// Manually symmetrised eta eff histogram
const static vector<double> edges_eta = { 0.0, 0.1, 0.8, 1.37, 1.52, 2.01, 2.37, 2.47 };
const static vector<double> effs_eta = { 0.950, 0.965, 0.955, 0.885, 0.950, 0.935, 0.90 };
// Et eff histogram (10-20 is a guess)
const static vector<double> edges_et = { 0, 10, 20, 25, 30, 35, 40, 45, 50, 60, 80 };
const static vector<double> effs_et = { 0.0, 0.90, 0.91, 0.92, 0.94, 0.95, 0.955, 0.965, 0.97, 0.98 };
if (e.abseta() > 2.47) return 0.0; // no ID outside the tracker
const int i_eta = binIndex(e.abseta(), edges_eta);
const int i_et = binIndex(e.Et()/GeV, edges_et, true);
const double eff = effs_et[i_et] * effs_eta[i_eta] / 0.95; //< norm factor as approximate double differential
return min(eff, 1.0);
}
/// @brief ATLAS Run 1 'medium' electron identification/selection efficiency
inline double ELECTRON_IDEFF_ATLAS_RUN1_MEDIUM(const Particle& e) {
const static vector<double> eta_edges_10 = {0.000, 0.049, 0.454, 1.107, 1.46, 1.790, 2.277, 2.500};
const static vector<double> eta_vals_10 = {0.730, 0.757, 0.780, 0.771, 0.77, 0.777, 0.778};
const static vector<double> eta_edges_15 = {0.000, 0.053, 0.456, 1.102, 1.463, 1.783, 2.263, 2.500};
const static vector<double> eta_vals_15 = {0.780, 0.800, 0.819, 0.759, 0.749, 0.813, 0.829};
const static vector<double> eta_edges_20 = {0.000, 0.065, 0.362, 0.719, 0.980, 1.289, 1.455, 1.681, 1.942, 2.239, 2.452, 2.500};
const static vector<double> eta_vals_20 = {0.794, 0.806, 0.816, 0.806, 0.797, 0.774, 0.764, 0.788, 0.793, 0.806, 0.825};
const static vector<double> eta_edges_25 = {0.000, 0.077, 0.338, 0.742, 1.004, 1.265, 1.467, 1.692, 1.940, 2.227, 2.452, 2.500};
const static vector<double> eta_vals_25 = {0.833, 0.843, 0.853, 0.845, 0.839, 0.804, 0.790, 0.825, 0.830, 0.833, 0.839};
const static vector<double> eta_edges_30 = {0.000, 0.077, 0.350, 0.707, 0.980, 1.289, 1.479, 1.681, 1.942, 2.239, 2.441, 2.500};
const static vector<double> eta_vals_30 = {0.863, 0.872, 0.881, 0.874, 0.870, 0.824, 0.808, 0.847, 0.845, 0.840, 0.842};
const static vector<double> eta_edges_35 = {0.000, 0.058, 0.344, 0.700, 1.009, 1.270, 1.458, 1.685, 1.935, 2.231, 2.468, 2.500};
const static vector<double> eta_vals_35 = {0.878, 0.889, 0.901, 0.895, 0.893, 0.849, 0.835, 0.868, 0.863, 0.845, 0.832};
const static vector<double> eta_edges_40 = {0.000, 0.047, 0.355, 0.699, 0.983, 1.280, 1.446, 1.694, 1.943, 2.227, 2.441, 2.500};
const static vector<double> eta_vals_40 = {0.894, 0.901, 0.909, 0.905, 0.904, 0.875, 0.868, 0.889, 0.876, 0.848, 0.827};
const static vector<double> eta_edges_45 = {0.000, 0.058, 0.356, 0.712, 0.997, 1.282, 1.459, 1.686, 1.935, 2.220, 2.444, 2.500};
const static vector<double> eta_vals_45 = {0.900, 0.911, 0.923, 0.918, 0.917, 0.897, 0.891, 0.904, 0.894, 0.843, 0.796};
const static vector<double> eta_edges_50 = {0.000, 0.059, 0.355, 0.711, 0.983, 1.280, 1.469, 1.682, 1.919, 2.227, 2.441, 2.500};
const static vector<double> eta_vals_50 = {0.903, 0.913, 0.923, 0.922, 0.923, 0.903, 0.898, 0.908, 0.895, 0.831, 0.774};
const static vector<double> eta_edges_60 = {0.000, 0.053, 0.351, 0.720, 1.006, 1.291, 1.469, 1.696, 1.946, 2.243, 2.455, 2.500};
const static vector<double> eta_vals_60 = {0.903, 0.917, 0.928, 0.924, 0.927, 0.915, 0.911, 0.915, 0.899, 0.827, 0.760};
const static vector<double> eta_edges_80 = {0.000, 0.053, 0.351, 0.720, 0.994, 1.292, 1.482, 1.708, 1.934, 2.220, 2.458, 2.500};
const static vector<double> eta_vals_80 = {0.936, 0.942, 0.952, 0.956, 0.956, 0.934, 0.931, 0.944, 0.933, 0.940, 0.948};
const static vector<double> et_edges = { 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 80 };
const static vector< vector<double> > et_eta_edges = { eta_edges_10, eta_edges_15, eta_edges_20, eta_edges_25, eta_edges_30, eta_edges_35, eta_edges_40, eta_edges_45, eta_edges_50, eta_edges_60, eta_edges_80 };
const static vector< vector<double> > et_eta_vals = { eta_vals_10, eta_vals_15, eta_vals_20, eta_vals_25, eta_vals_30, eta_vals_35, eta_vals_40, eta_vals_45, eta_vals_50, eta_vals_60, eta_vals_80 };
if (e.abseta() > 2.5 || e.Et() < 10*GeV) return 0.0;
const int i_et = binIndex(e.Et()/GeV, et_edges, true);
const int i_eta = binIndex(e.abseta(), et_eta_edges[i_et]);
return et_eta_vals[i_et][i_eta];
}
/// @brief ATLAS Run 2 'medium' electron identification/selection efficiency
///
/// ~1% increase over Run 1 informed by Fig 1 in https://cds.cern.ch/record/2157687/files/ATLAS-CONF-2016-024.pdf
inline double ELECTRON_IDEFF_ATLAS_RUN2_MEDIUM(const Particle& e) {
- return 1.01 * ELECTRON_IDEFF_ATLAS_RUN2_MEDIUM(e);
+ return 1.01 * ELECTRON_IDEFF_ATLAS_RUN1_MEDIUM(e);
}
/// @brief ATLAS Run 1 'tight' electron identification/selection efficiency
inline double ELECTRON_IDEFF_ATLAS_RUN1_TIGHT(const Particle& e) {
const static vector<double> eta_edges_10 = {0.000, 0.049, 0.459, 1.100, 1.461, 1.789, 2.270, 2.500};
const static vector<double> eta_vals_10 = {0.581, 0.632, 0.668, 0.558, 0.548, 0.662, 0.690};
const static vector<double> eta_edges_15 = {0.000, 0.053, 0.450, 1.096, 1.463, 1.783, 2.269, 2.500};
const static vector<double> eta_vals_15 = {0.630, 0.678, 0.714, 0.633, 0.616, 0.700, 0.733};
const static vector<double> eta_edges_20 = {0.000, 0.065, 0.362, 0.719, 0.992, 1.277, 1.479, 1.692, 1.930, 2.227, 2.464, 2.500};
const static vector<double> eta_vals_20 = {0.653, 0.695, 0.735, 0.714, 0.688, 0.635, 0.625, 0.655, 0.680, 0.691, 0.674};
const static vector<double> eta_edges_25 = {0.000, 0.077, 0.362, 0.719, 0.992, 1.300, 1.479, 1.692, 1.942, 2.227, 2.464, 2.500};
const static vector<double> eta_vals_25 = {0.692, 0.732, 0.768, 0.750, 0.726, 0.677, 0.667, 0.692, 0.710, 0.706, 0.679};
const static vector<double> eta_edges_30 = {0.000, 0.053, 0.362, 0.719, 1.004, 1.277, 1.467, 1.681, 1.954, 2.239, 2.452, 2.500};
const static vector<double> eta_vals_30 = {0.724, 0.763, 0.804, 0.789, 0.762, 0.702, 0.690, 0.720, 0.731, 0.714, 0.681};
const static vector<double> eta_edges_35 = {0.000, 0.044, 0.342, 0.711, 0.971, 1.280, 1.456, 1.683, 1.944, 2.218, 2.442, 2.500};
const static vector<double> eta_vals_35 = {0.736, 0.778, 0.824, 0.811, 0.784, 0.730, 0.718, 0.739, 0.743, 0.718, 0.678};
const static vector<double> eta_edges_40 = {0.000, 0.047, 0.355, 0.699, 0.983, 1.268, 1.457, 1.671, 1.931, 2.204, 2.453, 2.500};
const static vector<double> eta_vals_40 = {0.741, 0.774, 0.823, 0.823, 0.802, 0.764, 0.756, 0.771, 0.771, 0.734, 0.684};
const static vector<double> eta_edges_45 = {0.000, 0.056, 0.354, 0.711, 0.984, 1.280, 1.458, 1.684, 1.945, 2.207, 2.442, 2.500};
const static vector<double> eta_vals_45 = {0.758, 0.792, 0.841, 0.841, 0.823, 0.792, 0.786, 0.796, 0.794, 0.734, 0.663};
const static vector<double> eta_edges_50 = {0.000, 0.059, 0.355, 0.699, 0.983, 1.268, 1.446, 1.682, 1.943, 2.216, 2.453, 2.500};
const static vector<double> eta_vals_50 = {0.771, 0.806, 0.855, 0.858, 0.843, 0.810, 0.800, 0.808, 0.802, 0.730, 0.653};
const static vector<double> eta_edges_60 = {0.000, 0.050, 0.350, 0.707, 0.981, 1.278, 1.468, 1.694, 1.944, 2.242, 2.453, 2.500};
const static vector<double> eta_vals_60 = {0.773, 0.816, 0.866, 0.865, 0.853, 0.820, 0.812, 0.817, 0.804, 0.726, 0.645};
const static vector<double> eta_edges_80 = {0.000, 0.051, 0.374, 0.720, 0.981, 1.279, 1.468, 1.707, 1.945, 2.207, 2.457, 2.500};
const static vector<double> eta_vals_80 = {0.819, 0.855, 0.899, 0.906, 0.900, 0.869, 0.865, 0.873, 0.869, 0.868, 0.859};
const static vector<double> et_edges = { 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 80 };
const static vector< vector<double> > et_eta_edges = { eta_edges_10, eta_edges_15, eta_edges_20, eta_edges_25, eta_edges_30, eta_edges_35, eta_edges_40, eta_edges_45, eta_edges_50, eta_edges_60, eta_edges_80 };
const static vector< vector<double> > et_eta_vals = { eta_vals_10, eta_vals_15, eta_vals_20, eta_vals_25, eta_vals_30, eta_vals_35, eta_vals_40, eta_vals_45, eta_vals_50, eta_vals_60, eta_vals_80 };
if (e.abseta() > 2.5 || e.Et() < 10*GeV) return 0.0;
const int i_et = binIndex(e.Et()/GeV, et_edges, true);
const int i_eta = binIndex(e.abseta(), et_eta_edges[i_et]);
return et_eta_vals[i_et][i_eta];
}
/// @brief ATLAS Run 2 'tight' electron identification/selection efficiency
///
/// ~1% increase over Run 1 informed by Fig 1 in https://cds.cern.ch/record/2157687/files/ATLAS-CONF-2016-024.pdf
inline double ELECTRON_IDEFF_ATLAS_RUN2_TIGHT(const Particle& e) {
const static vector<double> et_edges = { /* 10, 15, */ 20, 25, 30, 35, 40, 45, 50, 60, 80 };
const static vector<double> et_effs = { 0.785, 0.805, 0.820, 0.830, 0.840, 0.850, 0.875, 0.910 };
const static vector<double> eta_edges = {0.000, 0.051, 0.374, 0.720, 0.981, 1.279, 1.468, 1.707, 1.945, 2.207, 2.457, 2.500}; // from ET > 80 bin
const static vector<double> eta_refs = {0.819, 0.855, 0.899, 0.906, 0.900, 0.869, 0.865, 0.873, 0.869, 0.868, 0.859};
if (e.abseta() > 2.5 || e.Et() < 20*GeV) return 0.0;
const int i_et = binIndex(e.Et()/GeV, et_edges, true);
const int i_eta = binIndex(e.abseta(), eta_edges);
const eff_et = et_effs[i_et]; //< integral eff
// Scale to |eta| shape, following the ~85% efficient high-ET bin from Run 1
const eff = eff_et * (eta_refs[i_eta]/0.85);
//return ELECTRON_IDEFF_ATLAS_RUN1_TIGHT(e);
return eff;
}
/// ATLAS Run 1 electron reco smearing
inline Particle ELECTRON_SMEAR_ATLAS_RUN1(const Particle& e) {
static const vector<double> edges_eta = {0., 2.5, 3.};
static const vector<double> edges_pt = {0., 0.1, 25.};
static const vector<double> e2s = {0.000, 0.015, 0.005,
0.005, 0.005, 0.005,
0.107, 0.107, 0.107};
static const vector<double> es = {0.00, 0.00, 0.05,
0.05, 0.05, 0.05,
2.08, 2.08, 2.08};
static const vector<double> cs = {0.00, 0.00, 0.25,
0.25, 0.25, 0.25,
0.00, 0.00, 0.00};
const int i_eta = binIndex(e.abseta(), edges_eta, true);
const int i_pt = binIndex(e.pT()/GeV, edges_pt, true);
const int i = i_eta*edges_pt.size() + i_pt;
// Calculate absolute resolution in GeV
const double c1 = sqr(e2s[i]), c2 = sqr(es[i]), c3 = sqr(cs[i]);
const double resolution = sqrt(c1*e.E2() + c2*e.E() + c3) * GeV;
// normal_distribution<> d(e.E(), resolution);
// const double mass = e.mass2() > 0 ? e.mass() : 0; //< numerical carefulness...
// const double smeared_E = max(d(gen), mass); //< can't let the energy go below the mass!
// return Particle(e.pid(), FourMomentum::mkEtaPhiME(e.eta(), e.phi(), mass, smeared_E));
return Particle(e.pid(), P4_SMEAR_E_GAUSS(e, resolution));
}
/// ATLAS Run 2 electron reco smearing
/// @todo Currently just a copy of the Run 1 version: fix!
inline Particle ELECTRON_SMEAR_ATLAS_RUN2(const Particle& e) {
return ELECTRON_SMEAR_ATLAS_RUN1(e);
}
/// @todo Add charge flip efficiency?
/// CMS Run 1 electron reconstruction efficiency
inline double ELECTRON_EFF_CMS_RUN1(const Particle& e) {
if (e.abseta() > 2.5) return 0;
if (e.pT() < 10*GeV) return 0;
return (e.abseta() < 1.5) ? 0.95 : 0.85;
}
/// CMS Run 2 electron reco efficiency
/// @todo Currently just a copy of Run 1: fix!
inline double ELECTRON_EFF_CMS_RUN2(const Particle& e) {
return ELECTRON_EFF_CMS_RUN1(e);
}
/// @brief CMS electron energy smearing, preserving direction
///
/// Calculate resolution
/// for pT > 0.1 GeV, E resolution = |eta| < 0.5 -> sqrt(0.06^2 + pt^2 * 1.3e-3^2)
/// |eta| < 1.5 -> sqrt(0.10^2 + pt^2 * 1.7e-3^2)
/// |eta| < 2.5 -> sqrt(0.25^2 + pt^2 * 3.1e-3^2)
inline Particle ELECTRON_SMEAR_CMS_RUN1(const Particle& e) {
// Calculate absolute resolution in GeV from functional form
double resolution = 0;
const double abseta = e.abseta();
if (e.pT() > 0.1*GeV && abseta < 2.5) { //< should be a given from efficiencies
if (abseta < 0.5) {
resolution = add_quad(0.06, 1.3e-3 * e.pT()/GeV) * GeV;
} else if (abseta < 1.5) {
resolution = add_quad(0.10, 1.7e-3 * e.pT()/GeV) * GeV;
} else { // still |eta| < 2.5
resolution = add_quad(0.25, 3.1e-3 * e.pT()/GeV) * GeV;
}
}
// normal_distribution<> d(e.E(), resolution);
// const double mass = e.mass2() > 0 ? e.mass() : 0; //< numerical carefulness...
// const double smeared_E = max(d(gen), mass); //< can't let the energy go below the mass!
// return Particle(e.pid(), FourMomentum::mkEtaPhiME(e.eta(), e.phi(), mass, smeared_E));
return Particle(e.pid(), P4_SMEAR_E_GAUSS(e, resolution));
}
/// CMS Run 2 electron reco smearing
/// @todo Currently just a copy of the Run 1 version: fix!
inline Particle ELECTRON_SMEAR_CMS_RUN2(const Particle& e) {
return ELECTRON_SMEAR_CMS_RUN1(e);
}
//@}
/// @name Photon efficiency and smearing functions
//@{
/// @brief ATLAS Run 2 photon reco efficiency
///
/// Taken from converted photons, Fig 8, in arXiv:1606.01813
inline double PHOTON_EFF_ATLAS_RUN1(const Particle& y) {
if (y.pT() < 10*GeV) return 0;
if (inRange(y.abseta(), 1.37, 1.52) || y.abseta() > 2.37) return 0;
static const vector<double> edges_eta = {0., 0.6, 1.37, 1.52, 1.81, 2.37};
static const vector<double> edges_pt = {10., 15., 20., 25., 30., 35., 40., 45.,
50., 60., 80., 100., 125., 150., 175., 250.};
static const vector<double> effs = {0.53, 0.65, 0.73, 0.83, 0.86, 0.93, 0.94, 0.96,
0.97, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98,//
0.45, 0.57, 0.67, 0.74, 0.84, 0.87, 0.93, 0.94,
0.95, 0.96, 0.97, 0.98, 0.98, 0.99, 0.99, 0.99,//
0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00,
0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00,//
0.48, 0.56, 0.68, 0.76, 0.86, 0.90, 0.93, 0.95,
0.96, 0.97, 0.98, 0.99, 0.99, 1.00, 1.00, 1.00,//
0.50, 0.61, 0.74, 0.82, 0.88, 0.92, 0.94, 0.95,
0.96, 0.97, 0.98, 0.98, 0.98, 0.98, 0.99, 0.99};
const int i_eta = binIndex(y.abseta(), edges_eta);
const int i_pt = binIndex(y.pT()/GeV, edges_pt, true);
const int i = i_eta*edges_pt.size() + i_pt;
const double eff = effs[i];
return eff;
}
/// @brief ATLAS Run 2 photon reco efficiency
///
/// Taken from converted photons, Fig 6, in ATL-PHYS-PUB-2016-014
inline double PHOTON_EFF_ATLAS_RUN2(const Particle& y) {
if (y.pT() < 10*GeV) return 0;
if (inRange(y.abseta(), 1.37, 1.52) || y.abseta() > 2.37) return 0;
static const vector<double> edges_eta = {0., 0.6, 1.37, 1.52, 1.81, 2.37};
static const vector<double> edges_pt = {10., 15., 20., 25., 30., 35., 40., 45.,
50., 60., 80., 100., 125., 150., 175., 250.};
static const vector<double> effs = {0.55, 0.70, 0.85, 0.89, 0.93, 0.95, 0.96, 0.96,
0.97, 0.97, 0.98, 0.97, 0.97, 0.97, 0.97, 0.97,//
0.47, 0.66, 0.79, 0.86, 0.89, 0.94, 0.96, 0.97,
0.97, 0.98, 0.97, 0.98, 0.98, 0.98, 0.98, 0.98,//
0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00,
0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00,//
0.54, 0.71, 0.84, 0.88, 0.92, 0.93, 0.94, 0.95,
0.96, 0.96, 0.96, 0.96, 0.96, 0.96, 0.96, 0.96,//
0.61, 0.74, 0.83, 0.88, 0.91, 0.94, 0.95, 0.96,
0.97, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98, 0.98};
const int i_eta = binIndex(y.abseta(), edges_eta);
const int i_pt = binIndex(y.pT()/GeV, edges_pt, true);
const int i = i_eta*edges_pt.size() + i_pt;
const double eff = effs[i];
return eff;
}
/// CMS Run 1 photon reco efficiency
/// @todo Currently from Delphes
inline double PHOTON_EFF_CMS_RUN1(const Particle& y) {
if (y.pT() < 10*GeV || y.abseta() > 2.5) return 0;
return (y.abseta() < 1.5) ? 0.95 : 0.85;
}
/// CMS Run 2 photon reco efficiency
/// @todo Currently just a copy of Run 1: fix!
inline double PHOTON_EFF_CMS_RUN2(const Particle& y) {
return PHOTON_EFF_CMS_RUN1(y);
}
/// @todo Use real photon smearing
inline Particle PHOTON_SMEAR_ATLAS_RUN1(const Particle& y) { return y; }
inline Particle PHOTON_SMEAR_ATLAS_RUN2(const Particle& y) { return y; }
inline Particle PHOTON_SMEAR_CMS_RUN1(const Particle& y) { return y; }
inline Particle PHOTON_SMEAR_CMS_RUN2(const Particle& y) { return y; }
//@}
/// @name Muon efficiency and smearing functions
//@{
/// ATLAS Run 1 muon reco efficiency
inline double MUON_EFF_ATLAS_RUN1(const Particle& m) {
if (m.abseta() > 2.7) return 0;
if (m.pT() < 10*GeV) return 0;
return (m.abseta() < 1.5) ? 0.95 : 0.85;
}
/// @brief ATLAS Run 2 muon reco efficiency
///
/// For medium ID, from Fig 3 of
/// https://cds.cern.ch/record/2047831/files/ATL-PHYS-PUB-2015-037.pdf
inline double MUON_EFF_ATLAS_RUN2(const Particle& m) {
if (m.abseta() > 2.7) return 0;
static const vector<double> edges_pt = {0., 3.5, 4., 5., 6., 7., 8., 10.};
static const vector<double> effs = {0.00, 0.76, 0.94, 0.97, 0.98, 0.98, 0.98, 0.99};
const int i_pt = binIndex(m.pT()/GeV, edges_pt, true);
const double eff = effs[i_pt];
return eff;
}
/// @todo Add muon loose/medium/tight ID efficiencies? All around 95-98%... ignore?
/// ATLAS Run 1 muon reco smearing
inline Particle MUON_SMEAR_ATLAS_RUN1(const Particle& m) {
static const vector<double> edges_eta = {0, 1.5, 2.5};
static const vector<double> edges_pt = {0, 0.1, 1.0, 10., 200.};
static const vector<double> res = {0., 0.03, 0.02, 0.03, 0.05,
0., 0.04, 0.03, 0.04, 0.05};
const int i_eta = binIndex(m.abseta(), edges_eta);
const int i_pt = binIndex(m.pT()/GeV, edges_pt, true);
const int i = i_eta*edges_pt.size() + i_pt;
const double resolution = res[i];
// Smear by a Gaussian centered on the current pT, with width given by the resolution
// normal_distribution<> d(m.pT(), resolution*m.pT());
// const double smeared_pt = max(d(gen), 0.);
// const double mass = m.mass2() > 0 ? m.mass() : 0; //< numerical carefulness...
// return Particle(m.pid(), FourMomentum::mkEtaPhiMPt(m.eta(), m.phi(), mass, smeared_pt));
return Particle(m.pid(), P4_SMEAR_PT_GAUSS(m, resolution*m.pT()));
}
/// ATLAS Run 2 muon reco smearing
/// @todo Currently just a copy of the Run 1 version: fix!
inline Particle MUON_SMEAR_ATLAS_RUN2(const Particle& m) {
return MUON_SMEAR_ATLAS_RUN1(m);
}
/// CMS Run 1 muon reco efficiency
inline double MUON_EFF_CMS_RUN1(const Particle& m) {
if (m.abseta() > 2.4) return 0;
if (m.pT() < 10*GeV) return 0;
return 0.95 * (m.abseta() < 1.5 ? 1 : exp(0.5 - 5e-4*m.pT()/GeV));
}
/// CMS Run 2 muon reco efficiency
/// @todo Currently just a copy of Run 1: fix!
inline double MUON_EFF_CMS_RUN2(const Particle& m) {
return MUON_EFF_CMS_RUN1(m);
}
/// CMS Run 1 muon reco smearing
inline Particle MUON_SMEAR_CMS_RUN1(const Particle& m) {
// Calculate fractional resolution
// for pT > 0.1 GeV, mom resolution = |eta| < 0.5 -> sqrt(0.01^2 + pt^2 * 2.0e-4^2)
// |eta| < 1.5 -> sqrt(0.02^2 + pt^2 * 3.0e-4^2)
// |eta| < 2.5 -> sqrt(0.05^2 + pt^2 * 2.6e-4^2)
double resolution = 0;
const double abseta = m.abseta();
if (m.pT() > 0.1*GeV && abseta < 2.5) {
if (abseta < 0.5) {
resolution = add_quad(0.01, 2.0e-4 * m.pT()/GeV);
} else if (abseta < 1.5) {
resolution = add_quad(0.02, 3.0e-4 * m.pT()/GeV);
} else { // still |eta| < 2.5... but isn't CMS' mu acceptance < 2.4?
resolution = add_quad(0.05, 2.6e-4 * m.pT()/GeV);
}
}
// Smear by a Gaussian centered on the current pT, with width given by the resolution
// normal_distribution<> d(m.pT(), resolution*m.pT());
// const double smeared_pt = max(d(gen), 0.);
// const double mass = m.mass2() > 0 ? m.mass() : 0; //< numerical carefulness...
// return Particle(m.pid(), FourMomentum::mkEtaPhiMPt(m.eta(), m.phi(), mass, smeared_pt));
return Particle(m.pid(), P4_SMEAR_PT_GAUSS(m, resolution*m.pT()));
}
/// CMS Run 2 muon reco smearing
/// @todo Currently just a copy of the Run 1 version: fix!
inline Particle MUON_SMEAR_CMS_RUN2(const Particle& m) {
return MUON_SMEAR_CMS_RUN1(m);
}
//@}
/// @name Tau efficiency and smearing functions
//@{
/// @brief ATLAS Run 1 8 TeV tau efficiencies (medium working point)
///
/// Taken from http://arxiv.org/pdf/1412.7086.pdf
/// 20-40 GeV 1-prong LMT eff|mis = 0.66|1/10, 0.56|1/20, 0.36|1/80
/// 20-40 GeV 3-prong LMT eff|mis = 0.45|1/60, 0.38|1/100, 0.27|1/300
/// > 40 GeV 1-prong LMT eff|mis = 0.66|1/15, 0.56|1/25, 0.36|1/80
/// > 40 GeV 3-prong LMT eff|mis = 0.45|1/250, 0.38|1/400, 0.27|1/1300
inline double TAU_EFF_ATLAS_RUN1(const Particle& t) {
if (t.abseta() > 2.5) return 0; //< hmm... mostly
double pThadvis = 0;
Particles chargedhadrons;
for (const Particle& p : t.children()) {
if (p.isHadron()) {
pThadvis += p.pT(); //< right definition? Paper is unclear
if (p.charge3() != 0 && p.abseta() < 2.5 && p.pT() > 1*GeV) chargedhadrons += p;
}
}
if (chargedhadrons.empty()) return 0; //< leptonic tau
if (pThadvis < 20*GeV) return 0; //< below threshold
if (pThadvis < 40*GeV) {
if (chargedhadrons.size() == 1) return (t.abspid() == PID::TAU) ? 0.56 : 0; //1/20.;
if (chargedhadrons.size() == 3) return (t.abspid() == PID::TAU) ? 0.38 : 0; //1/100.;
} else {
if (chargedhadrons.size() == 1) return (t.abspid() == PID::TAU) ? 0.56 : 0; //1/25.;
if (chargedhadrons.size() == 3) return (t.abspid() == PID::TAU) ? 0.38 : 0; //1/400.;
}
return 0;
}
/// @brief ATLAS Run 1 8 TeV tau misID rates (medium working point)
///
/// Taken from http://arxiv.org/pdf/1412.7086.pdf
/// 20-40 GeV 1-prong LMT eff|mis = 0.66|1/10, 0.56|1/20, 0.36|1/80
/// 20-40 GeV 3-prong LMT eff|mis = 0.45|1/60, 0.38|1/100, 0.27|1/300
/// > 40 GeV 1-prong LMT eff|mis = 0.66|1/15, 0.56|1/25, 0.36|1/80
/// > 40 GeV 3-prong LMT eff|mis = 0.45|1/250, 0.38|1/400, 0.27|1/1300
inline double TAU_MISID_ATLAS_RUN1(const Jet& j) {
if (j.abseta() > 2.5) return 0; //< hmm... mostly
double pThadvis = 0;
Particles chargedhadrons;
for (const Particle& p : j.particles()) {
if (p.isHadron()) {
pThadvis += p.pT(); //< right definition? Paper is unclear
if (p.charge3() != 0 && p.abseta() < 2.5 && p.pT() > 1*GeV) chargedhadrons += p;
}
}
if (chargedhadrons.empty()) return 0;
if (pThadvis < 20*GeV) return 0;
/// @todo Add some "if jet is true tau" logic... how? tau among constituents' ancestors?
if (pThadvis < 40*GeV) {
if (chargedhadrons.size() == 1) return 1/20.;
if (chargedhadrons.size() == 3) return 1/100.;
} else {
if (chargedhadrons.size() == 1) return 1/25.;
if (chargedhadrons.size() == 3) return 1/400.;
}
return 0;
}
/// @brief ATLAS Run 2 13 TeV tau efficiencies (medium working point)
///
/// From https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2015-045/ATL-PHYS-PUB-2015-045.pdf
/// LMT 1 prong efficiency/mistag = 0.6|1/30, 0.55|1/50, 0.45|1/120
/// LMT 3 prong efficiency/mistag = 0.5|1/30, 0.4|1/110, 0.3|1/300
inline double TAU_EFF_ATLAS_RUN2(const Particle& t) {
if (t.abseta() > 2.5) return 0; //< hmm... mostly
double pThadvis = 0;
Particles chargedhadrons;
for (const Particle& p : t.children()) {
if (p.isHadron()) {
pThadvis += p.pT(); //< right definition? Paper is unclear
if (p.charge3() != 0 && p.abseta() < 2.5 && p.pT() > 1*GeV) chargedhadrons += p;
}
}
if (chargedhadrons.empty()) return 0; //< leptonic tau
if (pThadvis < 20*GeV) return 0; //< below threshold
if (chargedhadrons.size() == 1) return (t.abspid() == PID::TAU) ? 0.55 : 0; //1/50.;
if (chargedhadrons.size() == 3) return (t.abspid() == PID::TAU) ? 0.40 : 0; //1/110.;
return 0;
}
/// @brief ATLAS Run 2 13 TeV tau misID rate (medium working point)
///
/// From https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2015-045/ATL-PHYS-PUB-2015-045.pdf
/// LMT 1 prong efficiency/mistag = 0.6|1/30, 0.55|1/50, 0.45|1/120
/// LMT 3 prong efficiency/mistag = 0.5|1/30, 0.4|1/110, 0.3|1/300
inline double TAU_MISID_ATLAS_RUN2(const Jet& j) {
if (j.abseta() > 2.5) return 0; //< hmm... mostly
double pThadvis = 0;
Particles chargedhadrons;
for (const Particle& p : j.particles()) {
if (p.isHadron()) {
pThadvis += p.pT(); //< right definition? Paper is unclear
if (p.charge3() != 0 && p.abseta() < 2.5 && p.pT() > 1*GeV) chargedhadrons += p;
}
}
if (chargedhadrons.empty()) return 0;
if (pThadvis < 20*GeV) return 0; //< below threshold
if (chargedhadrons.size() == 1) return 1/50.;
if (chargedhadrons.size() == 3) return 1/110.;
return 0;
}
/// ATLAS Run 1 tau smearing
/// @todo Currently a copy of the crappy jet smearing that is probably wrong...
inline Particle TAU_SMEAR_ATLAS_RUN1(const Particle& t) {
// Const fractional resolution for now
static const double resolution = 0.03;
// Smear by a Gaussian centered on 1 with width given by the (fractional) resolution
/// @todo Is this the best way to smear? Should we preserve the energy, or pT, or direction?
const double fsmear = max(randnorm(1., resolution), 0.);
const double mass = t.mass2() > 0 ? t.mass() : 0; //< numerical carefulness...
return Particle(t.pid(), FourMomentum::mkXYZM(t.px()*fsmear, t.py()*fsmear, t.pz()*fsmear, mass));
}
/// ATLAS Run 2 tau smearing
/// @todo Currently a copy of the Run 1 version
inline Particle TAU_SMEAR_ATLAS_RUN2(const Particle& t) {
return TAU_SMEAR_ATLAS_RUN1(t);
}
/// CMS Run 2 tau efficiency
///
/// @todo Needs work; this is the dumb version from Delphes 3.3.2
inline double TAU_EFF_CMS_RUN2(const Particle& t) {
return (t.abspid() == PID::TAU) ? 0.6 : 0;
}
/// CMS Run 1 tau efficiency
///
/// @todo Needs work; this is just a copy of the Run 2 version in Delphes 3.3.2
inline double TAU_EFF_CMS_RUN1(const Particle& t) {
return TAU_EFF_CMS_RUN2(t);
}
/// CMS Run 1 tau smearing
/// @todo Currently a copy of the crappy ATLAS one
inline Particle TAU_SMEAR_CMS_RUN1(const Particle& t) {
return TAU_SMEAR_ATLAS_RUN1(t);
}
/// CMS Run 2 tau smearing
/// @todo Currently a copy of the Run 1 version
inline Particle TAU_SMEAR_CMS_RUN2(const Particle& t) {
return TAU_SMEAR_CMS_RUN1(t);
}
//@}
/// @name Jet efficiency and smearing functions
//@{
/// Return the ATLAS Run 1 jet flavour tagging efficiency for the given Jet
inline double JET_BTAG_ATLAS_RUN1(const Jet& j) {
/// @todo This form drops past ~100 GeV, asymptotically to zero efficiency... really?!
if (j.abseta() > 2.5) return 0;
const auto ftagsel = [&](const Particle& p){ return p.pT() > 5*GeV && deltaR(p,j) < 0.3; };
if (j.bTagged(ftagsel)) return 0.80*tanh(0.003*j.pT()/GeV)*(30/(1+0.0860*j.pT()/GeV));
if (j.cTagged(ftagsel)) return 0.20*tanh(0.020*j.pT()/GeV)*( 1/(1+0.0034*j.pT()/GeV));
return 0.002 + 7.3e-6*j.pT()/GeV;
}
/// Return the ATLAS Run 2 MC2c20 jet flavour tagging efficiency for the given Jet
inline double JET_BTAG_ATLAS_RUN2_MV2C20(const Jet& j) {
if (j.abseta() > 2.5) return 0;
if (j.bTagged(Cuts::pT > 5*GeV)) return 0.77;
if (j.cTagged(Cuts::pT > 5*GeV)) return 1/4.5;
return 1/140.;
}
/// Return the ATLAS Run 2 MC2c10 jet flavour tagging efficiency for the given Jet
inline double JET_BTAG_ATLAS_RUN2_MV2C10(const Jet& j) {
if (j.abseta() > 2.5) return 0;
if (j.bTagged(Cuts::pT > 5*GeV)) return 0.77;
if (j.cTagged(Cuts::pT > 5*GeV)) return 1/6.0;
return 1/134.;
}
/// ATLAS Run 1 jet smearing
inline Jet JET_SMEAR_ATLAS_RUN1(const Jet& j) {
// Jet energy resolution lookup
// Implemented by Matthias Danninger for GAMBIT, based roughly on
// https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/CONFNOTES/ATLAS-CONF-2015-017/
// Parameterisation can be still improved, but eta dependence is minimal
/// @todo Also need a JES uncertainty component?
static const vector<double> binedges_pt = {0., 50., 70., 100., 150., 200., 1000., 10000.};
static const vector<double> jer = {0.145, 0.115, 0.095, 0.075, 0.07, 0.05, 0.04, 0.04}; //< note overflow value
const int ipt = binIndex(j.pT()/GeV, binedges_pt, true);
if (ipt < 0) return j;
const double resolution = jer.at(ipt);
// Smear by a Gaussian centered on 1 with width given by the (fractional) resolution
/// @todo Is this the best way to smear? Should we preserve the energy, or pT, or direction?
const double fsmear = max(randnorm(1., resolution), 0.);
const double mass = j.mass2() > 0 ? j.mass() : 0; //< numerical carefulness...
Jet rtn(FourMomentum::mkXYZM(j.px()*fsmear, j.py()*fsmear, j.pz()*fsmear, mass));
//if (deltaPhi(j, rtn) > 0.01) cout << "jdphi: " << deltaPhi(j, rtn) << endl;
return rtn;
}
/// ATLAS Run 2 jet smearing
/// @todo Just a copy of the Run 1 one: improve!!
inline Jet JET_SMEAR_ATLAS_RUN2(const Jet& j) {
return JET_SMEAR_ATLAS_RUN1(j);
}
/// CMS Run 2 jet smearing
/// @todo Just a copy of the suboptimal ATLAS one: improve!!
inline Jet JET_SMEAR_CMS_RUN1(const Jet& j) {
return JET_SMEAR_ATLAS_RUN1(j);
}
/// CMS Run 2 jet smearing
/// @todo Just a copy of the suboptimal ATLAS one: improve!!
inline Jet JET_SMEAR_CMS_RUN2(const Jet& j) {
return JET_SMEAR_CMS_RUN1(j);
}
//@}
/// @name ETmiss smearing functions
//@{
inline Vector3 MET_SMEAR_IDENTITY(const Vector3& met, double) { return met; }
/// @brief ATLAS Run 1 ETmiss smearing
///
/// Based on https://arxiv.org/pdf/1108.5602v2.pdf, Figs 14 and 15
inline Vector3 MET_SMEAR_ATLAS_RUN1(const Vector3& met, double set) {
Vector3 smeared_met = met;
// Linearity offset (Fig 14)
if (met.mod() < 25*GeV) smeared_met *= 1.05;
else if (met.mod() < 40*GeV) smeared_met *= (1.05 - (0.04/15)*(met.mod()/GeV - 25)); //< linear decrease
else smeared_met *= 1.01;
// Smear by a Gaussian with width given by the resolution(sumEt) ~ 0.45 sqrt(sumEt) GeV
const double resolution = 0.45 * sqrt(set/GeV) * GeV;
const double metsmear = max(randnorm(smeared_met.mod(), resolution), 0.);
smeared_met = metsmear * smeared_met.unit();
return smeared_met;
}
/// ATLAS Run 2 ETmiss smearing
/// @todo Just a copy of the Run 1 one: improve!!
inline Vector3 MET_SMEAR_ATLAS_RUN2(const Vector3& met, double set) {
return MET_SMEAR_ATLAS_RUN1(met, set);
}
/// CMS Run 1 ETmiss smearing
/// From https://arxiv.org/pdf/1411.0511.pdf Table 2, p16 (Z channels)
inline Vector3 MET_SMEAR_CMS_RUN1(const Vector3& met, double set) {
Vector3 smeared_met = met;
// Calculate parallel and perpendicular resolutions and combine in quadrature (?)
const double resolution_x = (1.1 + 0.6*sqrt(set/GeV)) * GeV;
const double resolution_y = (1.4 + 0.6*sqrt(set/GeV)) * GeV;
const double resolution = sqrt(sqr(resolution_x) + sqr(resolution_y));
// Smear by a Gaussian with width given by the resolution
const double metsmear = max(randnorm(smeared_met.mod(), resolution), 0.);
smeared_met = metsmear * smeared_met.unit();
return smeared_met;
}
/// CMS Run 2 ETmiss smearing
/// From http://inspirehep.net/record/1681214/files/JME-17-001-pas.pdf Table 3, p20
inline Vector3 MET_SMEAR_CMS_RUN2(const Vector3& met, double set) {
Vector3 smeared_met = met;
// Calculate parallel and perpendicular resolutions and combine in quadrature (?)
const double resolution_para = ( 2.0 + 0.64*sqrt(set/GeV)) * GeV;
const double resolution_perp = (-1.5 + 0.68*sqrt(set/GeV)) * GeV;
const double resolution = sqrt(sqr(resolution_para) + sqr(resolution_perp));
// Smear by a Gaussian with width given by the resolution
const double metsmear = max(randnorm(smeared_met.mod(), resolution), 0.);
smeared_met = metsmear * smeared_met.unit();
return smeared_met;
}
//@}
/// @name Tracking efficiency and smearing functions
//@{
/// ATLAS Run 1 tracking efficiency
inline double TRK_EFF_ATLAS_RUN1(const Particle& p) {
if (p.charge3() == 0) return 0;
if (p.abseta() > 2.5) return 0;
if (p.pT() < 0.1*GeV) return 0;
if (p.abspid() == PID::ELECTRON) {
if (p.abseta() < 1.5) {
if (p.pT() < 1*GeV) return 0.73;
if (p.pT() < 100*GeV) return 0.95;
return 0.99;
} else {
if (p.pT() < 1*GeV) return 0.50;
if (p.pT() < 100*GeV) return 0.83;
else return 0.90;
}
} else if (p.abspid() == PID::MUON) {
if (p.abseta() < 1.5) {
return (p.pT() < 1*GeV) ? 0.75 : 0.99;
} else {
return (p.pT() < 1*GeV) ? 0.70 : 0.98;
}
} else { // charged hadrons
if (p.abseta() < 1.5) {
return (p.pT() < 1*GeV) ? 0.70 : 0.95;
} else {
return (p.pT() < 1*GeV) ? 0.60 : 0.85;
}
}
}
/// ATLAS Run 2 tracking efficiency
/// @todo Currently just a copy of Run 1: fix!
inline double TRK_EFF_ATLAS_RUN2(const Particle& p) {
return TRK_EFF_ATLAS_RUN1(p);
}
/// CMS Run 1 tracking efficiency
inline double TRK_EFF_CMS_RUN1(const Particle& p) {
if (p.charge3() == 0) return 0;
if (p.abseta() > 2.5) return 0;
if (p.pT() < 0.1*GeV) return 0;
if (p.abspid() == PID::ELECTRON) {
if (p.abseta() < 1.5) {
if (p.pT() < 1*GeV) return 0.73;
if (p.pT() < 100*GeV) return 0.95;
return 0.99;
} else {
if (p.pT() < 1*GeV) return 0.50;
if (p.pT() < 100*GeV) return 0.83;
else return 0.90;
}
} else if (p.abspid() == PID::MUON) {
if (p.abseta() < 1.5) {
return (p.pT() < 1*GeV) ? 0.75 : 0.99;
} else {
return (p.pT() < 1*GeV) ? 0.70 : 0.98;
}
} else { // charged hadrons
if (p.abseta() < 1.5) {
return (p.pT() < 1*GeV) ? 0.70 : 0.95;
} else {
return (p.pT() < 1*GeV) ? 0.60 : 0.85;
}
}
}
/// CMS Run 2 tracking efficiency
/// @todo Currently just a copy of Run 1: fix!
inline double TRK_EFF_CMS_RUN2(const Particle& p) {
return TRK_EFF_CMS_RUN1(p);
}
//@}
}
#endif