Rivet analyses

// -*- C++ -*-
#include "Rivet/Analysis.hh"
#include "Rivet/Projections/FinalState.hh"

namespace Rivet {


  /// @brief e+ e- > n nbar
  class BESIII_2023_I2614192 : public Analysis {
  public:

    /// Constructor
    RIVET_DEFAULT_ANALYSIS_CTOR(BESIII_2023_I2614192);


    /// @name Analysis methods
    /// @{

    /// Book histograms and initialise projections before the run
    void init() {

      // Initialise and register projections
      declare(FinalState(), "FS");

      for (unsigned int ix = 0; ix < 2; ++ix) {
        book(_c[ix], "/TMP/c_" + toString(ix));
      }
    }


    /// Perform the per-event analysis
    void analyze(const Event& event) {
      const FinalState& fs = apply<FinalState>(event, "FS");
      if (fs.particles().size() != 2) vetoEvent;
      double cTheta(0.);
      for (const Particle& p : fs.particles()) {
        if (abs(p.pid()) != PID::NEUTRON) vetoEvent;
        if (p.pid() == PID::NEUTRON) cTheta = p.mom().z() / p.mom().p3().mod();
      }
      _c[0]->fill();
      _c[1]->fill(2. - 5. * sqr(cTheta));
    }


    /// Normalise histograms etc., after the run
    void finalize() {
      // storage of the values to fill histos
      const double mn = 0.93956542052;
      const double tau = 4. * sqr(mn / sqrtS());
      const double beta = sqrt(1. - tau);
      const double alpha = 7.2973525693e-3;
      const double GeV2nb = 0.3893793721e6;
      const double fact = 4. / 3. * M_PI * sqr(alpha) * beta / 2 / sqr(sqrtS()) * GeV2nb;
      scale(_c, crossSection() / sumOfWeights() / nanobarn / fact);

      double val[3], err[3];
      val[0] = sqrt(2. * _c[1]->val() / (_c[0]->val() - _c[1]->val()) / tau);
      err[0] = 0.5 / _c[1]->val() / tau
          * (sqr(_c[0]->err() * _c[1]->val()) + sqr(_c[1]->err() * _c[0]->val()))
          / pow(_c[0]->val() - _c[1]->val(), 3);
      val[1] = 1e2 * sqrt(0.5 * (_c[0]->val() - _c[1]->val()));
      err[1] = 1e2 * 0.125 * (sqr(_c[0]->err()) + sqr(_c[1]->err())) / (_c[0]->val() - _c[1]->val());
      val[2] = 1e2 * sqrt(_c[1]->val() / tau);
      err[2] = 1e2 * 0.25 * sqr(_c[1]->err()) / _c[1]->val() / tau;
      // fill histos
      for (unsigned int ix = 0; ix < 3; ++ix) {
        Estimate1DPtr mult;
        book(mult, 1, 1, 1 + ix);
        for (auto& b : mult->bins()) {
          if (inRange(sqrtS() / GeV, b.xMin(), b.xMax())) {
            b.set(val[ix], err[ix]);
          }
        }
      }
    }

    /// @}


    /// @name Histograms
    /// @{
    CounterPtr _c[2];
    /// @}
  };


  RIVET_DECLARE_PLUGIN(BESIII_2023_I2614192);

}