## main370

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    // main370.cc is a part of the PYTHIA event generator.
    // Copyright (C) 2025 Torbjorn Sjostrand.
    // PYTHIA is licenced under the GNU GPL v2 or later, see COPYING for details.
    // Please respect the MCnet Guidelines, see GUIDELINES for details.

    // Authors:
    //            Torbjorn Sjostrand

    // Keywords:
    //            Top
    //            Toponium
    //            Openmp

    // Plot ttbar system properties contrasting six different scenarios:
    // 0 : pure Born baseline.
    // 1 : Coulomb enhancement.
    // 2 : Green's function purely for E > 0.
    // 3 : Green's function, only for the E < 0 part mirrored to E > 0.
    //     Scenario 2 can be added to 3 to give a "complete" scenario.
    // 4 : as 3, but in addition the top mass is reduced to give better <E>.
    // 5 : full Green's for E > and E < 0, the "best bet" scenario.
    // Plots all scenarios in one frame, which may be too much,
    // but also shows how to select and combine as desired.
    // This main is the same as main369, but demonstrates how the run
    // can be done with PythiaParallel rather than OpenMP.

    // Based on threshold factors according to
    // V. Fadin,  V. Khoze and T. Sjostrand, Z. Phys. C48 (1990) 613.

    #include "Pythia8/PythiaParallel.h"
    using namespace Pythia8;

    //============================================================================

    int main() {

      // Restrict to threshold region only or not.
      bool thresholdOnly = true;

      // Full event generation or only cross-section-oriented studies.
      bool fullEvents = false;

      // Number of events. Fewer in scenarios 3 and 4, since only mirrored part.
      int nEvent       = 1000000;
      int nEventMirror = 0.1 * nEvent;

      // LHC collision energy.
      double eCM = 13000.;

      // Example of possible setup values. Reduced top mass in scenario 4.
      double mt            = 172.5;
      double mtLow         = mt - 3.8;
      double thrWidth      = 10.;
      int    alphasOrder   = 2;
      double alphasValue   = 0.118;
      double ggSingletFrac = 2. / 7.;
      double qqSingletFrac = 0.;

      // Histograms. (Last slot used for E < 0 part of scenario 5.)
      bool separateFrames = true;
      Hist mThrOrig[7], mThrOrigZoom[7],  mHatLow[7];
      for (int scenario = 0; scenario < 7; ++scenario) {
        mThrOrig[scenario].book("original threshold", 100, -20., 80.);
        mThrOrigZoom[scenario].book("original threshold, zoom", 100, -10., 30.);
        mHatLow[scenario].book("ttbar invariant mass, low", 100, 300., 400.);
      }

      // Compare the six scenarios.
      for (int scenario = 0; scenario < 6; ++scenario) {

        // Generator.
        PythiaParallel pythia;

        // Feed in desired values.
        int topModel = (scenario < 4) ? scenario : scenario - 1;
        pythia.settings.mode("TopThreshold:model", topModel);
        double mtNow = (scenario == 4) ? mtLow :  mt;
        pythia.particleData.m0(6, mtNow);
        pythia.settings.parm("TopThreshold:width", thrWidth);
        pythia.settings.mode("TopThreshold:alphasOrder", alphasOrder);
        pythia.settings.parm("TopThreshold:alphasValue", alphasValue);
        pythia.settings.parm("TopThreshold:ggSingletFrac", ggSingletFrac);
        pythia.settings.parm("TopThreshold:qqSingletFrac", qqSingletFrac);

        // Process selection and collision energy.
        pythia.readString("Top:gg2ttbar = on");
        pythia.readString("Top:qqbar2ttbar = on");
        pythia.settings.parm("Beams:eCM", eCM);

        // Restrict to threshold region.
        if (thresholdOnly) {
          pythia.readString("PhaseSpace:mHatMin = 300.");
          pythia.readString("PhaseSpace:mHatMax = 400.");
        }
        else pythia.readString("PhaseSpace:mHatMin = 200.");

        // Switch off (most) code parts not relevant here. Reduce printout.
        if (!fullEvents) {
          pythia.readString("PartonLevel:ISR = off");
          pythia.readString("PartonLevel:FSR = off");
          pythia.readString("PartonLevel:MPI = off");
          pythia.readString("HadronLevel:all = off");
        }
        pythia.readString("Next:numberCount = 100000");

        // If Pythia fails to initialize, abort this scenario.
        cout << " =============================================================="
          "=========\n Initializing PYTHIA for scenario " << scenario
             << " with topModel " << topModel << " and top mass " << mtNow
             << " GeV" << endl;
        bool ok = pythia.init();
        cout << " Completed initialization of PYTHIA for scenario " << scenario
             << "\n ============================================================"
          "===========\n";
        if (!ok) continue;

        // Run events in parallel.
        int nBelow = 0, nBelowgg = 0, nBelowqq = 0, nAbovegg = 0, nAboveqq = 0;
        double eBelow = 0.;
        int nEventNow = (scenario == 3 || scenario == 4) ? nEventMirror : nEvent;
        pythia.run(nEventNow, [&](Pythia* pythiaPtr) {

          // Original threshold value and other properties.
          double eThr = pythiaPtr->info.toponiumE;
          if (scenario == 4) eThr -= 2. * (mt - mtLow);
          double mHat = pythiaPtr->info.mHat();

          // Histogram threshold value and ttbar invariant mass.
          mThrOrig[scenario].fill( eThr);
          mThrOrigZoom[scenario].fill( eThr);
          mHatLow[scenario].fill( mHat);
          if (scenario == 5 && eThr < 0.) {
            mThrOrig[6].fill( eThr);
            mThrOrigZoom[6].fill( eThr);
            mHatLow[6].fill( mHat);
          }

          // Statistics for below threshold cross sections.
          if (scenario == 3 || scenario == 4 || (scenario == 5 && eThr < 0.)) {
            ++nBelow;
            if (pythiaPtr->info.code() == 601) ++nBelowgg;
            else ++nBelowqq;
            eBelow += eThr;
          } else {
            if (pythiaPtr->info.code() == 601) ++nAbovegg;
            else ++nAboveqq;
          }
        });

        // Normalization and statistics for this scenario.
        cout << "\n ===== End-of-run statistics for scenario " << scenario
             << " with topModel " << topModel << " and top mass " << mtNow
             << " GeV =====" << endl;

        // Normalize histogram to cross section, in pb/GeV.
        double sigmapb = 1e9 * pythia.sigmaGen() / nEventNow;
        mThrOrig[scenario]     *= sigmapb;
        mThrOrigZoom[scenario] *= 2.5 * sigmapb;
        mHatLow[scenario]      *= sigmapb;
        if (scenario == 5) {
          mThrOrig[6]          *= sigmapb;
          mThrOrigZoom[6]      *= 2.5 * sigmapb;
          mHatLow[6]           *= sigmapb;
        }

        // Statistics and cross sections.
        pythia.stat();
        double sigAbv   = sigmapb * (nEventNow - nBelow);
        double sigAbvgg = sigmapb * nAbovegg;
        double sigAbvqq = sigmapb * nAboveqq;
        double sigBel   = sigmapb * nBelow;
        double sigBelgg = sigmapb * nBelowgg;
        double sigBelqq = sigmapb * nBelowqq;
        cout << "\n sigma above threshold = " << fixed << setprecision(3)
             << sigAbv << " pb" << endl << "   whereof gg = " << sigAbvgg
             << " and qq = "<< sigAbvqq << endl << " sigma below threshold = "
             << sigBel << " pb" << endl << "   whereof gg = " << sigBelgg
             << " and qq = " << sigBelqq << endl;
        eBelow /= max(1, nBelow);
        cout << " average energy for below-threshold part = " << eBelow
             << " GeV" << endl;
        // End loop over threshold cases.
      }

      // Histograms with pyplot. Common notation.
      HistPlot hpl("plot370");
      string symbol[6] = {"h,black", "h,olive", "h,blue", "h,orange", "h,magenta",
                          "h,red"};
      string legend[6] = {"Born", "Coulomb", "Green's, $E > 0$",
          "Green's, $E < 0$ mirrored", "Green's, $E < 0$ mirrored + shifted",
          "Green's, all $E$"};

      // The formal E_thr value above/below threshold, key for reweighting.
      hpl.frame("fig370", "Energy above or below threshold",
        "$E$ (GeV)", "$\\mathrm{d}\\sigma/\\mathrm{d}m$ (pb/GeV)");
      for (int scenario = 0; scenario < 6; ++scenario)
        hpl.add( mThrOrig[scenario], symbol[scenario], legend[scenario]);
      hpl.plot();
      hpl.frame("", "Energy above or below threshold",
        "$E$ (GeV)", "$\\mathrm{d}\\sigma/\\mathrm{d}m$ (pb/GeV)");
      for (int scenario = 0; scenario < 6; ++scenario)
        hpl.add( mThrOrigZoom[scenario], symbol[scenario], legend[scenario]);
      hpl.plot();

      // Invariant mass of the ttbar pair.
      hpl.frame("", "invariant mass of ttbar pair, near threshold",
        "$m(t+tbar) (GeV)$", "$\\mathrm{d}\\sigma/\\mathrm{d}m$ (pb/GeV)");
      for (int scenario = 0; scenario < 6; ++scenario)
        hpl.add( mHatLow[scenario], symbol[scenario], legend[scenario]);
      hpl.plot();

      // Zooming in on three specific threshold scenarios (plots for talk).
      string legMirror = (separateFrames) ? "fig370mirror" : "";
      hpl.frame(legMirror, "", "$E$ (GeV)",
        "$\\mathrm{d}\\sigma/\\mathrm{d}m$ (pb/GeV)", 4.8, 4.8);
      hpl.add( mThrOrigZoom[0], "h,black", "Born cross section");
      hpl.add( mThrOrigZoom[2], "h,blue", "Green's above threshold");
      hpl.add( mThrOrigZoom[3], "h,magenta", "Green's below threshold mirrored");
      hpl.add( mThrOrigZoom[2] + mThrOrigZoom[3], "h,red", "Green's in total");
      hpl.plot(-10., 30., 0., 3.5);
      string legShift = (separateFrames) ? "fig370shift" : "";
      hpl.frame(legShift, "", "$E$ (GeV)",
        "$\\mathrm{d}\\sigma/\\mathrm{d}m$ (pb/GeV)", 4.8, 4.8);
      hpl.add( mThrOrigZoom[0], "h,black", "Born cross section");
      hpl.add( mThrOrigZoom[2], "h,blue", "Green's above threshold");
      hpl.add( mThrOrigZoom[4], "h,magenta",
        "Green's below threshold shifted + mirrored");
      hpl.add( mThrOrigZoom[2] + mThrOrigZoom[4], "h,red", "Green's in total");
      hpl.plot(-10., 30., 0., 3.5);
      string legFull = (separateFrames) ? "fig370full" : "";
      hpl.frame(legFull, "", "$E$ (GeV)",
        "$\\mathrm{d}\\sigma/\\mathrm{d}m$ (pb/GeV)", 4.8, 4.8);
      hpl.add( mThrOrigZoom[0], "h,black", "Born cross section");
      hpl.add( mThrOrigZoom[5] - mThrOrigZoom[6], "h,blue",
        "Green's above threshold");
      hpl.add( mThrOrigZoom[6], "h,magenta", "Green's below threshold");
      hpl.plot(-10., 30., 0., 3.5);

      // Done.
      return 0;
    }