EvtVubBLNPHybrid.cpp

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#include "EvtGenModels/EvtVubBLNPHybrid.hh"
 
#include "EvtGenBase/EvtGenKine.hh"
#include "EvtGenBase/EvtPDL.hh"
#include "EvtGenBase/EvtParticle.hh"
#include "EvtGenBase/EvtRandom.hh"
#include "EvtGenBase/EvtReport.hh"
#include "EvtGenBase/EvtVector4R.hh"
 
#include "EvtGenModels/EvtItgPtrFunction.hh"
#include "EvtGenModels/EvtItgSimpsonIntegrator.hh"
#include "EvtGenModels/EvtPFermi.hh"
 
#include <stdlib.h>
#include <string>
 
// For incomplete gamma function
#include "math.h"
#include "signal.h"
#define ITMAX 100
#define EPS 3.0e-7
#define FPMIN 1.0e-30
 
using std::cout;
using std::endl;
 
std::string EvtVubBLNPHybrid::getName() const
{
    return "VUB_BLNPHYBRID";
}
 
EvtDecayBase* EvtVubBLNPHybrid::clone() const
{
    return new EvtVubBLNPHybrid;
}
 
void EvtVubBLNPHybrid::init()
{
    // check number of arguments
    if ( getNArg() < EvtVubBLNPHybrid::nParameters ) {
        EvtGenReport( EVTGEN_ERROR, "EvtVubBLNPHybrid" )
            << "EvtVubBLNPHybrid generator expected "
            << "at least " << EvtVubBLNPHybrid::nParameters
            << " arguments but found: " << getNArg()
            << "\nWill terminate execution!" << endl;
        ::abort();
    } else if ( getNArg() == EvtVubBLNPHybrid::nParameters ) {
        EvtGenReport( EVTGEN_WARNING, "EvtVubBLNPHybrid" )
            << "EvtVubBLNPHybrid: generate B -> Xu l nu events "
            << "without using the hybrid reweighting." << endl;
        m_noHybrid = true;
    } else if ( getNArg() <
                EvtVubBLNPHybrid::nParameters + EvtVubBLNPHybrid::nVariables ) {
        EvtGenReport( EVTGEN_ERROR, "EvtVubBLNPHybrid" )
            << "EvtVubBLNPHybrid could not read number of bins for "
            << "all variables used in the reweighting\n"
            << "Will terminate execution!" << endl;
        ::abort();
    }
 
    // get parameters (declared in the header file)
 
    // Input parameters
    m_mBB = 5.2792;
    m_lambda2 = 0.12;
 
    // Shape function parameters
    m_b = getArg( 0 );
    m_Lambda = getArg( 1 );
    m_Ecut = 1.8;
    m_wzero = m_mBB - 2 * m_Ecut;
 
    // SF and SSF modes
    m_itype = (int)getArg( 5 );
    m_dtype = getArg( 5 );
    m_isubl = (int)getArg( 6 );
 
    // flags
    m_flag1 = (int)getArg( 7 );
    m_flag2 = (int)getArg( 8 );
    m_flag3 = (int)getArg( 9 );
 
    // Quark mass
    m_mb = 4.61;
 
    // hidden parameter what and SF stuff
    const double xlow = 0;
    const double xhigh = m_mBB;
    const int aSize = 10000;
    EvtPFermi pFermi( m_Lambda, m_b );
    // pf is the cumulative distribution normalized to 1.
    m_pf.resize( aSize );
    for ( int i = 0; i < aSize; i++ ) {
        double what = xlow + (double)( i + 0.5 ) / ( (double)aSize ) *
                                 ( xhigh - xlow );
        if ( i == 0 )
            m_pf[i] = pFermi.getSFBLNP( what );
        else
            m_pf[i] = m_pf[i - 1] + pFermi.getSFBLNP( what );
    }
    for ( size_t i = 0; i < m_pf.size(); i++ ) {
        m_pf[i] /= m_pf[m_pf.size() - 1];
    }
 
    // Matching scales
    m_muh = m_mBB * getArg( 2 );    // 0.5
    m_mui = getArg( 3 );            // 1.5
    m_mubar = getArg( 4 );          // 1.5
 
    // Perturbative quantities
    m_CF = 4.0 / 3.0;
    m_CA = 3.0;
    double nf = 4.0;
 
    m_beta0 = 11.0 / 3.0 * m_CA - 2.0 / 3.0 * nf;
    m_beta1 = 34.0 / 3.0 * m_CA * m_CA - 10.0 / 3.0 * m_CA * nf - 2.0 * m_CF * nf;
    m_beta2 = 2857.0 / 54.0 * m_CA * m_CA * m_CA +
              ( m_CF * m_CF - 205.0 / 18.0 * m_CF * m_CA -
                1415.0 / 54.0 * m_CA * m_CA ) *
                  nf +
              ( 11.0 / 9.0 * m_CF + 79.0 / 54.0 * m_CA ) * nf * nf;
 
    m_zeta3 = 1.0 + 1 / 8.0 + 1 / 27.0 + 1 / 64.0;
 
    m_Gamma0 = 4 * m_CF;
    m_Gamma1 = m_CF * ( ( 268.0 / 9.0 - 4.0 * M_PI * M_PI / 3.0 ) * m_CA -
                        40.0 / 9.0 * nf );
    m_Gamma2 = 16 * m_CF *
               ( ( 245.0 / 24.0 - 67.0 / 54.0 * M_PI * M_PI +
                   +11.0 / 180.0 * pow( M_PI, 4 ) + 11.0 / 6.0 * m_zeta3 ) *
                     m_CA * m_CA *
                     +( -209.0 / 108.0 + 5.0 / 27.0 * M_PI * M_PI -
                        7.0 / 3.0 * m_zeta3 ) *
                     m_CA * nf +
                 ( -55.0 / 24.0 + 2 * m_zeta3 ) * m_CF * nf - nf * nf / 27.0 );
 
    m_gp0 = -5.0 * m_CF;
    m_gp1 = -8.0 * m_CF *
            ( ( 3.0 / 16.0 - M_PI * M_PI / 4.0 + 3 * m_zeta3 ) * m_CF +
              ( 1549.0 / 432.0 + 7.0 / 48.0 * M_PI * M_PI - 11.0 / 4.0 * m_zeta3 ) *
                  m_CA -
              ( 125.0 / 216.0 + M_PI * M_PI / 24.0 ) * nf );
 
    // Lbar and m_mupisq
 
    m_Lbar = m_Lambda;    // all models
    m_mupisq = 3 * m_Lambda * m_Lambda / m_b;
    if ( m_itype == 1 )
        m_mupisq = 3 * m_Lambda * m_Lambda / m_b;
    if ( m_itype == 2 )
        m_mupisq = 3 * m_Lambda * m_Lambda *
                   ( Gamma( 1 + 0.5 * m_b ) * Gamma( 0.5 * m_b ) /
                         pow( Gamma( 0.5 + 0.5 * m_b ), 2 ) -
                     1 );
 
    // m_moment2 for SSFs
    m_moment2 = pow( 0.3, 3 );
 
    // inputs for total rate (T for Total); use BLNP notebook defaults
    m_flagpower = 1;
    m_flag2loop = 1;
 
    // stuff for the integrator
    m_maxLoop = 20;
    //m_precision = 1.0e-3;
    m_precision = 2.0e-2;
 
    // vector of global variables, to pass to static functions (which can't access globals);
    m_gvars.push_back( 0.0 );         // 0
    m_gvars.push_back( 0.0 );         // 1
    m_gvars.push_back( m_mui );       // 2
    m_gvars.push_back( m_b );         // 3
    m_gvars.push_back( m_Lambda );    // 4
    m_gvars.push_back( m_mBB );       // 5
    m_gvars.push_back( m_mb );        // 6
    m_gvars.push_back( m_wzero );     // 7
    m_gvars.push_back( m_beta0 );     // 8
    m_gvars.push_back( m_beta1 );     // 9
    m_gvars.push_back( m_beta2 );     // 10
    m_gvars.push_back( m_dtype );     // 11
 
    // check that there are 3 daughters and 10 arguments
    checkNDaug( 3 );
    // A. Volk: check for number of arguments is not necessary
    //checkNArg(10);
 
    if ( m_noHybrid )
        return;    // Without hybrid weighting, nothing else to do
 
    m_bins_mX = std::vector<double>( abs( (int)getArg( 10 ) ) );
    m_bins_q2 = std::vector<double>( abs( (int)getArg( 11 ) ) );
    m_bins_El = std::vector<double>( abs( (int)getArg( 12 ) ) );
 
    int nextArg = EvtVubBLNPHybrid::nParameters + EvtVubBLNPHybrid::nVariables;
 
    m_nbins = m_bins_mX.size() * m_bins_q2.size() *
              m_bins_El.size();    // Binning of weight table
 
    int expectArgs = nextArg + m_bins_mX.size() + m_bins_q2.size() +
                     m_bins_El.size() + m_nbins;
 
    if ( getNArg() < expectArgs ) {
        EvtGenReport( EVTGEN_ERROR, "EvtVubBLNPHybrid" )
            << " finds " << getNArg() << " arguments, expected " << expectArgs
            << ".  Something is wrong with the tables of weights or thresholds."
            << "\nWill terminate execution!" << endl;
        ::abort();
    }
 
    // read bin boundaries from decay.dec
    for ( auto& b : m_bins_mX )
        b = getArg( nextArg++ );
    m_masscut = m_bins_mX[0];
    for ( auto& b : m_bins_q2 )
        b = getArg( nextArg++ );
    for ( auto& b : m_bins_El )
        b = getArg( nextArg++ );
 
    // read in weights (and rescale to range 0..1)
    readWeights( nextArg );
}
 
void EvtVubBLNPHybrid::initProbMax()
{
    noProbMax();
}
 
void EvtVubBLNPHybrid::decay( EvtParticle* Bmeson )
{
    int j;
 
    EvtParticle *xuhad( nullptr ), *lepton( nullptr ), *neutrino( nullptr );
    EvtVector4R p4;
    double EX( 0. ), sh( 0. ), El( 0. ), ml( 0. );
    double Pp, Pm, Pl, pdf, qsq, mpi, ratemax;
 
    double xhigh, xlow, what;
    double mX;
 
    bool rew( true );
    while ( rew ) {
        Bmeson->initializePhaseSpace( getNDaug(), getDaugs() );
 
        xuhad = Bmeson->getDaug( 0 );
        lepton = Bmeson->getDaug( 1 );
        neutrino = Bmeson->getDaug( 2 );
 
        m_mBB = Bmeson->mass();
        ml = lepton->mass();
 
        //  get SF value
        xlow = 0;
        xhigh = m_mBB;
        // the case for alphas = 0 is not considered
        what = 2 * xhigh;
        while ( what > xhigh || what < xlow ) {
            what = findBLNPWhat();
            what = xlow + what * ( xhigh - xlow );
        }
 
        bool tryit = true;
 
        while ( tryit ) {
            // generate pp between 0 and
            // Flat(min, max) gives R(max - min) + min, where R = random btwn 0 and 1
 
            Pp = EvtRandom::Flat( 0, m_mBB );    // P+ = EX - |PX|
            Pl = EvtRandom::Flat( 0, m_mBB );    // mBB - 2El
            Pm = EvtRandom::Flat( 0, m_mBB );    // P- = EX + |PX|
 
            sh = Pm * Pp;
            EX = 0.5 * ( Pm + Pp );
            qsq = ( m_mBB - Pp ) * ( m_mBB - Pm );
            El = 0.5 * ( m_mBB - Pl );
 
            // Need maximum rate.  Waiting for Mr. Paz to give it to me.
            // Meanwhile, use this.
            ratemax = 3.0;    // From trial and error - most events below 3.0
 
            // kinematic bounds (Eq. 2)
            mpi = 0.14;
            if ( ( Pp > 0 ) && ( Pp <= Pl ) && ( Pl <= Pm ) && ( Pm < m_mBB ) &&
                 ( El > ml ) && ( sh > 4 * mpi * mpi ) ) {
                // Probability of pass proportional to PDF
                pdf = rate3( Pp, Pl, Pm );
                double testRan = EvtRandom::Flat( 0., ratemax );
                if ( pdf >= testRan )
                    tryit = false;
            }
        }
 
        // compute all kinematic variables needed for reweighting
        mX = sqrt( sh );
 
        // Reweighting in bins of mX, q2, El
        if ( m_nbins > 0 ) {
            double xran1 = EvtRandom::Flat();
            double w = 1.0;
            if ( !m_noHybrid )
                w = getWeight( mX, qsq, El );
            if ( w >= xran1 )
                rew = false;
        } else {
            rew = false;
        }
    }
    // o.k. we have the three kineamtic variables
    // now calculate a flat cos Theta_H [-1,1] distribution of the
    // hadron flight direction w.r.t the B flight direction
    // because the B is a scalar and should decay isotropic.
    // Then chose a flat Phi_H [0,2Pi] w.r.t the B flight direction
    // and and a flat Phi_L [0,2Pi] in the W restframe w.r.t the
    // W flight direction.
 
    double ctH = EvtRandom::Flat( -1, 1 );
    double phH = EvtRandom::Flat( 0, 2 * M_PI );
    double phL = EvtRandom::Flat( 0, 2 * M_PI );
 
    // now compute the four vectors in the B Meson restframe
 
    double ptmp, sttmp;
    // calculate the hadron 4 vector in the B Meson restframe
 
    sttmp = sqrt( 1 - ctH * ctH );
    ptmp = sqrt( EX * EX - sh );
    double pHB[4] = { EX, ptmp * sttmp * cos( phH ), ptmp * sttmp * sin( phH ),
                      ptmp * ctH };
    p4.set( pHB[0], pHB[1], pHB[2], pHB[3] );
    xuhad->init( getDaug( 0 ), p4 );
 
    if ( m_storeWhat ) {
        // cludge to store the hidden parameter what with the decay;
        // the lifetime of the Xu is abused for this purpose.
        // tau = 1 ps corresponds to ctau = 0.3 mm -> in order to
        // stay well below BaBars sensitivity we take what/(10000 GeV).
        // To extract what back from the StdHepTrk its necessary to get
        // delta_ctau = Xu->decayVtx()->point().distanceTo(XuDaughter->decayVtx()->point());
        //
        // what = delta_ctau * 100000 * Mass_Xu/Momentum_Xu
        //
        xuhad->setLifetime( what / 10000. );
    }
 
    // calculate the W 4 vector in the B Meson restrframe
 
    double apWB = ptmp;
    double pWB[4] = { m_mBB - EX, -pHB[1], -pHB[2], -pHB[3] };
 
    // first go in the W restframe and calculate the lepton and
    // the neutrino in the W frame
 
    double mW2 = m_mBB * m_mBB + sh - 2 * m_mBB * EX;
    double beta = ptmp / pWB[0];
    double gamma = pWB[0] / sqrt( mW2 );
 
    double pLW[4];
 
    ptmp = ( mW2 - ml * ml ) / 2 / sqrt( mW2 );
    pLW[0] = sqrt( ml * ml + ptmp * ptmp );
 
    double ctL = ( El - gamma * pLW[0] ) / beta / gamma / ptmp;
    if ( ctL < -1 )
        ctL = -1;
    if ( ctL > 1 )
        ctL = 1;
    sttmp = sqrt( 1 - ctL * ctL );
 
    // eX' = eZ x eW
    double xW[3] = { -pWB[2], pWB[1], 0 };
    // eZ' = eW
    double zW[3] = { pWB[1] / apWB, pWB[2] / apWB, pWB[3] / apWB };
 
    double lx = sqrt( xW[0] * xW[0] + xW[1] * xW[1] );
    for ( j = 0; j < 2; j++ )
        xW[j] /= lx;
 
    // eY' = eZ' x eX'
    double yW[3] = { -pWB[1] * pWB[3], -pWB[2] * pWB[3],
                     pWB[1] * pWB[1] + pWB[2] * pWB[2] };
    double ly = sqrt( yW[0] * yW[0] + yW[1] * yW[1] + yW[2] * yW[2] );
    for ( j = 0; j < 3; j++ )
        yW[j] /= ly;
 
    // p_lep = |p_lep| * (  sin(Theta) * cos(Phi) * eX'
    //                    + sin(Theta) * sin(Phi) * eY'
    //                    + cos(Theta) *            eZ')
    for ( j = 0; j < 3; j++ )
        pLW[j + 1] = sttmp * cos( phL ) * ptmp * xW[j] +
                     sttmp * sin( phL ) * ptmp * yW[j] + ctL * ptmp * zW[j];
 
    double apLW = ptmp;
 
    // boost them back in the B Meson restframe
 
    double appLB = beta * gamma * pLW[0] + gamma * ctL * apLW;
 
    ptmp = sqrt( El * El - ml * ml );
    double ctLL = appLB / ptmp;
 
    if ( ctLL > 1 )
        ctLL = 1;
    if ( ctLL < -1 )
        ctLL = -1;
 
    double pLB[4] = { El, 0, 0, 0 };
    double pNB[4] = { pWB[0] - El, 0, 0, 0 };
 
    for ( j = 1; j < 4; j++ ) {
        pLB[j] = pLW[j] + ( ctLL * ptmp - ctL * apLW ) / apWB * pWB[j];
        pNB[j] = pWB[j] - pLB[j];
    }
 
    p4.set( pLB[0], pLB[1], pLB[2], pLB[3] );
    lepton->init( getDaug( 1 ), p4 );
 
    p4.set( pNB[0], pNB[1], pNB[2], pNB[3] );
    neutrino->init( getDaug( 2 ), p4 );
}
 
double EvtVubBLNPHybrid::rate3( double Pp, double Pl, double Pm )
{
    // rate3 in units of GF^2*Vub^2/pi^3
 
    double factor = 1.0 / 16 * ( m_mBB - Pp ) * U1lo( m_muh, m_mui ) *
                    pow( ( Pm - Pp ) / ( m_mBB - Pp ), alo( m_muh, m_mui ) );
 
    double doneJS = DoneJS( Pp, Pm, m_mui );
    double done1 = Done1( Pp, Pm, m_mui );
    double done2 = Done2( Pp, Pm, m_mui );
    double done3 = Done3( Pp, Pm, m_mui );
 
    // The EvtSimpsonIntegrator returns zero for bad integrals.
    // So if any of the integrals are zero (ie bad), return zero.
    // This will cause pdf = 0, so the event will not pass.
    // I hope this will not introduce a bias.
    if ( doneJS * done1 * done2 * done3 == 0.0 ) {
        //cout << "Integral failed: (Pp, Pm, Pl) = (" << Pp << ", " << Pm << ", " << Pl << ")" << endl;
        return 0.0;
    }
    //  if (doneJS*done1*done2*done3 != 0.0) {
    //    cout << "Integral OK: (Pp, Pm, Pl) = (" << Pp << ", " << Pm << ", " << Pl << ")" << endl;
    //}
 
    double f1 = F1( Pp, Pm, m_muh, m_mui, m_mubar, doneJS, done1 );
    double f2 = F2( Pp, Pm, m_muh, m_mui, m_mubar, done3 );
    double f3 = F3( Pp, Pm, m_muh, m_mui, m_mubar, done2 );
    double answer = factor * ( ( m_mBB + Pl - Pp - Pm ) * ( Pm - Pl ) * f1 +
                               2 * ( Pl - Pp ) * ( Pm - Pl ) * f2 +
                               ( m_mBB - Pm ) * ( Pm - Pp ) * f3 );
    return answer;
}
 
double EvtVubBLNPHybrid::F1( double Pp, double Pm, double muh, double mui,
                             double mubar, double doneJS, double done1 )
{
    std::vector<double> vars( 12 );
    vars[0] = Pp;
    vars[1] = Pm;
    for ( int j = 2; j < 12; j++ ) {
        vars[j] = m_gvars[j];
    }
 
    double y = ( Pm - Pp ) / ( m_mBB - Pp );
    double ah = m_CF * alphas( muh, vars ) / 4 / M_PI;
    double ai = m_CF * alphas( mui, vars ) / 4 / M_PI;
    double abar = m_CF * alphas( mubar, vars ) / 4 / M_PI;
    double lambda1 = -m_mupisq;
 
    double t1 = -4 * ai / ( Pp - m_Lbar ) *
                ( 2 * log( ( Pp - m_Lbar ) / mui ) + 1 );
    double t2 = 1 + dU1nlo( muh, mui ) + anlo( muh, mui ) * log( y );
    double t3 = -4.0 * pow( log( y * m_mb / muh ), 2 ) +
                10.0 * log( y * m_mb / muh ) - 4.0 * log( y ) -
                2.0 * log( y ) / ( 1 - y ) - 4.0 * PolyLog( 2, 1 - y ) -
                M_PI * M_PI / 6.0 - 12.0;
    double t4 = 2 * pow( log( y * m_mb * Pp / ( mui * mui ) ), 2 ) -
                3 * log( y * m_mb * Pp / ( mui * mui ) ) + 7 - M_PI * M_PI;
 
    double t5 = -wS( Pp ) + 2 * t( Pp ) +
                ( 1.0 / y - 1.0 ) * ( u( Pp ) - v( Pp ) );
    double t6 = -( lambda1 + 3.0 * m_lambda2 ) / 3.0 +
                1.0 / pow( y, 2 ) * ( 4.0 / 3.0 * lambda1 - 2.0 * m_lambda2 );
 
    double shapePp = Shat( Pp, vars );
 
    double answer = ( t2 + ah * t3 + ai * t4 ) * shapePp + ai * doneJS +
                    1 / ( m_mBB - Pp ) *
                        ( m_flag2 * abar * done1 + m_flag1 * t5 ) +
                    1 / pow( m_mBB - Pp, 2 ) * m_flag3 * shapePp * t6;
    if ( Pp > m_Lbar + mui / exp( 0.5 ) )
        answer = answer + t1;
    return answer;
}
 
double EvtVubBLNPHybrid::F2( double Pp, double Pm, double muh, double /* mui */,
                             double mubar, double done3 )
{
    std::vector<double> vars( 12 );
    vars[0] = Pp;
    vars[1] = Pm;
    for ( int j = 2; j < 12; j++ ) {
        vars[j] = m_gvars[j];
    }
 
    double y = ( Pm - Pp ) / ( m_mBB - Pp );
    double lambda1 = -m_mupisq;
    double ah = m_CF * alphas( muh, vars ) / 4 / M_PI;
    double abar = m_CF * alphas( mubar, vars ) / 4 / M_PI;
 
    double t6 = -wS( Pp ) - 2 * t( Pp ) + 1.0 / y * ( t( Pp ) + v( Pp ) );
    double t7 = 1 / pow( y, 2 ) * ( 2.0 / 3.0 * lambda1 + 4.0 * m_lambda2 ) -
                1 / y * ( 2.0 / 3.0 * lambda1 + 3.0 / 2.0 * m_lambda2 );
 
    double shapePp = Shat( Pp, vars );
 
    double answer = ah * log( y ) / ( 1 - y ) * shapePp +
                    1 / ( m_mBB - Pp ) *
                        ( m_flag2 * abar * 0.5 * done3 + m_flag1 / y * t6 ) +
                    1.0 / pow( m_mBB - Pp, 2 ) * m_flag3 * shapePp * t7;
    return answer;
}
 
double EvtVubBLNPHybrid::F3( double Pp, double Pm, double /*muh*/,
                             double /* mui */, double mubar, double done2 )
{
    std::vector<double> vars( 12 );
    vars[0] = Pp;
    vars[1] = Pm;
    for ( int j = 2; j < 12; j++ ) {
        vars[j] = m_gvars[j];
    }
 
    double y = ( Pm - Pp ) / ( m_mBB - Pp );
    double lambda1 = -m_mupisq;
    double abar = m_CF * alphas( mubar, vars ) / 4 / M_PI;
 
    double t7 = 1.0 / pow( y, 2 ) * ( -2.0 / 3.0 * lambda1 + m_lambda2 );
 
    double shapePp = Shat( Pp, vars );
 
    double answer = 1.0 / ( Pm - Pp ) * m_flag2 * 0.5 * y * abar * done2 +
                    1.0 / pow( m_mBB - Pp, 2 ) * m_flag3 * shapePp * t7;
    return answer;
}
 
double EvtVubBLNPHybrid::DoneJS( double Pp, double Pm, double /* mui */ )
{
    std::vector<double> vars( 12 );
    vars[0] = Pp;
    vars[1] = Pm;
    for ( int j = 2; j < 12; j++ ) {
        vars[j] = m_gvars[j];
    }
 
    double lowerlim = 0.001 * Pp;
    double upperlim = ( 1.0 - 0.001 ) * Pp;
 
    auto func = EvtItgPtrFunction{ &IntJS, lowerlim, upperlim, vars };
    auto integ = EvtItgSimpsonIntegrator{ func, m_precision, m_maxLoop };
    return integ.evaluate( lowerlim, upperlim );
}
 
double EvtVubBLNPHybrid::Done1( double Pp, double Pm, double /* mui */ )
{
    std::vector<double> vars( 12 );
    vars[0] = Pp;
    vars[1] = Pm;
    for ( int j = 2; j < 12; j++ ) {
        vars[j] = m_gvars[j];
    }
 
    double lowerlim = 0.001 * Pp;
    double upperlim = ( 1.0 - 0.001 ) * Pp;
 
    auto func = EvtItgPtrFunction{ &Int1, lowerlim, upperlim, vars };
    auto integ = EvtItgSimpsonIntegrator{ func, m_precision, m_maxLoop };
    return integ.evaluate( lowerlim, upperlim );
}
 
double EvtVubBLNPHybrid::Done2( double Pp, double Pm, double /* mui */ )
{
    std::vector<double> vars( 12 );
    vars[0] = Pp;
    vars[1] = Pm;
    for ( int j = 2; j < 12; j++ ) {
        vars[j] = m_gvars[j];
    }
 
    double lowerlim = 0.001 * Pp;
    double upperlim = ( 1.0 - 0.001 ) * Pp;
 
    auto func = EvtItgPtrFunction{ &Int2, lowerlim, upperlim, vars };
    auto integ = EvtItgSimpsonIntegrator{ func, m_precision, m_maxLoop };
    return integ.evaluate( lowerlim, upperlim );
}
 
double EvtVubBLNPHybrid::Done3( double Pp, double Pm, double /* mui */ )
{
    std::vector<double> vars( 12 );
    vars[0] = Pp;
    vars[1] = Pm;
    for ( int j = 2; j < 12; j++ ) {
        vars[j] = m_gvars[j];
    }
 
    double lowerlim = 0.001 * Pp;
    double upperlim = ( 1.0 - 0.001 ) * Pp;
 
    auto func = EvtItgPtrFunction{ &Int3, lowerlim, upperlim, vars };
    auto integ = EvtItgSimpsonIntegrator{ func, m_precision, m_maxLoop };
    return integ.evaluate( lowerlim, upperlim );
}
 
double EvtVubBLNPHybrid::Int1( double what, const std::vector<double>& vars )
{
    return Shat( what, vars ) * g1( what, vars );
}
 
double EvtVubBLNPHybrid::Int2( double what, const std::vector<double>& vars )
{
    return Shat( what, vars ) * g2( what, vars );
}
 
double EvtVubBLNPHybrid::Int3( double what, const std::vector<double>& vars )
{
    return Shat( what, vars ) * g3( what, vars );
}
 
double EvtVubBLNPHybrid::IntJS( double what, const std::vector<double>& vars )
{
    double Pp = vars[0];
    double Pm = vars[1];
    double mui = vars[2];
    double mBB = vars[5];
    double mb = vars[6];
    double y = ( Pm - Pp ) / ( mBB - Pp );
 
    return 1 / ( Pp - what ) * ( Shat( what, vars ) - Shat( Pp, vars ) ) *
           ( 4 * log( y * mb * ( Pp - what ) / ( mui * mui ) ) - 3 );
}
 
double EvtVubBLNPHybrid::g1( double w, const std::vector<double>& vars )
{
    double Pp = vars[0];
    double Pm = vars[1];
    double mBB = vars[5];
    double y = ( Pm - Pp ) / ( mBB - Pp );
    double x = ( Pp - w ) / ( mBB - Pp );
 
    double q1 = ( 1 + x ) * ( 1 + x ) * y * ( x + y );
    double q2 = y * ( -9 + 10 * y ) + x * x * ( -12.0 + 13.0 * y ) +
                2 * x * ( -8.0 + 6 * y + 3 * y * y );
    double q3 = 4 / x * log( y + y / x );
    double q4 = 3.0 * pow( x, 4 ) * ( -2.0 + y ) - 2 * pow( y, 3 ) -
                4 * pow( x, 3 ) * ( 2.0 + y ) - 2 * x * y * y * ( 4 + y ) -
                x * x * y * ( 12 + 4 * y + y * y );
    double q5 = log( 1 + y / x );
 
    double answer = q2 / q1 - q3 - 2 * q4 * q5 / ( q1 * y * x );
    return answer;
}
 
double EvtVubBLNPHybrid::g2( double w, const std::vector<double>& vars )
{
    double Pp = vars[0];
    double Pm = vars[1];
    double mBB = vars[5];
    double y = ( Pm - Pp ) / ( mBB - Pp );
    double x = ( Pp - w ) / ( mBB - Pp );
 
    double q1 = ( 1 + x ) * ( 1 + x ) * pow( y, 3 ) * ( x + y );
    double q2 = 10.0 * pow( x, 4 ) + y * y +
                3.0 * pow( x, 2 ) * y * ( 10.0 + y ) +
                pow( x, 3 ) * ( 12.0 + 19.0 * y ) +
                x * y * ( 8.0 + 4.0 * y + y * y );
    double q3 = 5 * pow( x, 4 ) + 2.0 * y * y +
                6.0 * pow( x, 3 ) * ( 1.0 + 2.0 * y ) +
                4.0 * x * y * ( 1 + 2.0 * y ) + x * x * y * ( 18.0 + 5.0 * y );
    double q4 = log( 1 + y / x );
 
    double answer = 2.0 / q1 * ( y * q2 - 2 * x * q3 * q4 );
    return answer;
}
 
double EvtVubBLNPHybrid::g3( double w, const std::vector<double>& vars )
{
    double Pp = vars[0];
    double Pm = vars[1];
    double mBB = vars[5];
    double y = ( Pm - Pp ) / ( mBB - Pp );
    double x = ( Pp - w ) / ( mBB - Pp );
 
    double q1 = ( 1 + x ) * ( 1 + x ) * pow( y, 3 ) * ( x + y );
    double q2 = 2.0 * pow( y, 3 ) * ( -11.0 + 2.0 * y ) -
                10.0 * pow( x, 4 ) * ( 6 - 6 * y + y * y ) +
                x * y * y * ( -94.0 + 29.0 * y + 2.0 * y * y ) +
                2.0 * x * x * y * ( -72.0 + 18.0 * y + 13.0 * y * y ) -
                x * x * x * ( 72.0 + 42.0 * y - 70.0 * y * y + 3.0 * y * y * y );
    double q3 = -6.0 * x * ( -5.0 + y ) * pow( y, 3 ) + 4 * pow( y, 4 ) +
                5 * pow( x, 5 ) * ( 6 - 6 * y + y * y ) -
                4 * x * x * y * y * ( -20.0 + 6 * y + y * y ) +
                pow( x, 3 ) * y * ( 90.0 - 10.0 * y - 28.0 * y * y + y * y * y ) +
                pow( x, 4 ) * ( 36.0 + 36.0 * y - 50.0 * y * y + 4 * y * y * y );
    double q4 = log( 1 + y / x );
 
    double answer = q2 / q1 + 2 / q1 / y * q3 * q4;
    return answer;
}
 
double EvtVubBLNPHybrid::Shat( double w, const std::vector<double>& vars )
{
    double mui = vars[2];
    double b = vars[3];
    double Lambda = vars[4];
    double wzero = vars[7];
    int itype = (int)vars[11];
 
    double norm = 0.0;
    double shape = 0.0;
 
    if ( itype == 1 ) {
        double Lambar = ( Lambda / b ) *
                        ( Gamma( 1 + b ) - Gamma( 1 + b, b * wzero / Lambda ) ) /
                        ( Gamma( b ) - Gamma( b, b * wzero / Lambda ) );
        double muf = wzero - Lambar;
        double mupisq = 3 * pow( Lambda, 2 ) / pow( b, 2 ) *
                            ( Gamma( 2 + b ) -
                              Gamma( 2 + b, b * wzero / Lambda ) ) /
                            ( Gamma( b ) - Gamma( b, b * wzero / Lambda ) ) -
                        3 * Lambar * Lambar;
        norm = Mzero( muf, mui, mupisq, vars ) * Gamma( b ) /
               ( Gamma( b ) - Gamma( b, b * wzero / Lambda ) );
        shape = pow( b, b ) / Lambda / Gamma( b ) * pow( w / Lambda, b - 1 ) *
                exp( -b * w / Lambda );
    }
 
    if ( itype == 2 ) {
        double dcoef = pow( Gamma( 0.5 * ( 1 + b ) ) / Gamma( 0.5 * b ), 2 );
        double t1 = wzero * wzero * dcoef / ( Lambda * Lambda );
        double Lambar =
            Lambda * ( Gamma( 0.5 * ( 1 + b ) ) - Gamma( 0.5 * ( 1 + b ), t1 ) ) /
            pow( dcoef, 0.5 ) / ( Gamma( 0.5 * b ) - Gamma( 0.5 * b, t1 ) );
        double muf = wzero - Lambar;
        double mupisq = 3 * Lambda * Lambda *
                            ( Gamma( 1 + 0.5 * b ) - Gamma( 1 + 0.5 * b, t1 ) ) /
                            dcoef / ( Gamma( 0.5 * b ) - Gamma( 0.5 * b, t1 ) ) -
                        3 * Lambar * Lambar;
        norm = Mzero( muf, mui, mupisq, vars ) * Gamma( 0.5 * b ) /
               ( Gamma( 0.5 * b ) -
                 Gamma( 0.5 * b, wzero * wzero * dcoef / ( Lambda * Lambda ) ) );
        shape = 2 * pow( dcoef, 0.5 * b ) / Lambda / Gamma( 0.5 * b ) *
                pow( w / Lambda, b - 1 ) *
                exp( -dcoef * w * w / ( Lambda * Lambda ) );
    }
 
    double answer = norm * shape;
    return answer;
}
 
double EvtVubBLNPHybrid::Mzero( double muf, double mu, double mupisq,
                                const std::vector<double>& vars )
{
    double CF = 4.0 / 3.0;
    double amu = CF * alphas( mu, vars ) / M_PI;
    double answer = 1 -
                    amu * ( pow( log( muf / mu ), 2 ) + log( muf / mu ) +
                            M_PI * M_PI / 24.0 ) +
                    amu * ( log( muf / mu ) - 0.5 ) * mupisq / ( 3 * muf * muf );
    return answer;
}
 
double EvtVubBLNPHybrid::wS( double w )
{
    double answer = ( m_Lbar - w ) * Shat( w, m_gvars );
    return answer;
}
 
double EvtVubBLNPHybrid::t( double w )
{
    double t1 = -3 * m_lambda2 / m_mupisq * ( m_Lbar - w ) * Shat( w, m_gvars );
    double myf = myfunction( w, m_Lbar, m_moment2 );
    double myBIK = myfunctionBIK( w, m_Lbar, m_moment2 );
    double answer = t1;
 
    if ( m_isubl == 1 )
        answer = t1;
    if ( m_isubl == 3 )
        answer = t1 - myf;
    if ( m_isubl == 4 )
        answer = t1 + myf;
    if ( m_isubl == 5 )
        answer = t1 - myBIK;
    if ( m_isubl == 6 )
        answer = t1 + myBIK;
 
    return answer;
}
 
double EvtVubBLNPHybrid::u( double w )
{
    double u1 = -2 * ( m_Lbar - w ) * Shat( w, m_gvars );
    double myf = myfunction( w, m_Lbar, m_moment2 );
    double myBIK = myfunctionBIK( w, m_Lbar, m_moment2 );
    double answer = u1;
 
    if ( m_isubl == 1 )
        answer = u1;
    if ( m_isubl == 3 )
        answer = u1 + myf;
    if ( m_isubl == 4 )
        answer = u1 - myf;
    if ( m_isubl == 5 )
        answer = u1 + myBIK;
    if ( m_isubl == 6 )
        answer = u1 - myBIK;
 
    return answer;
}
 
double EvtVubBLNPHybrid::v( double w )
{
    double v1 = 3 * m_lambda2 / m_mupisq * ( m_Lbar - w ) * Shat( w, m_gvars );
    double myf = myfunction( w, m_Lbar, m_moment2 );
    double myBIK = myfunctionBIK( w, m_Lbar, m_moment2 );
    double answer = v1;
 
    if ( m_isubl == 1 )
        answer = v1;
    if ( m_isubl == 3 )
        answer = v1 - myf;
    if ( m_isubl == 4 )
        answer = v1 + myf;
    if ( m_isubl == 5 )
        answer = v1 - myBIK;
    if ( m_isubl == 6 )
        answer = v1 + myBIK;
 
    return answer;
}
 
double EvtVubBLNPHybrid::myfunction( double w, double Lbar, double mom2 )
{
    double bval = 5.0;
    double x = w / Lbar;
    double factor = 0.5 * mom2 * pow( bval / Lbar, 3 );
    double answer = factor * exp( -bval * x ) *
                    ( 1 - 2 * bval * x + 0.5 * bval * bval * x * x );
    return answer;
}
 
double EvtVubBLNPHybrid::myfunctionBIK( double w, double Lbar, double /* mom2 */ )
{
    double aval = 10.0;
    double normBIK = ( 4 - M_PI ) * M_PI * M_PI / 8 / ( 2 - M_PI ) / aval + 1;
    double z = 3 * M_PI * w / 8 / Lbar;
    double q = M_PI * M_PI * 2 * pow( M_PI * aval, 0.5 ) * exp( -aval * z * z ) /
                   ( 4 * M_PI - 8 ) * ( 1 - 2 * pow( aval / M_PI, 0.5 ) * z ) +
               8 / pow( 1 + z * z, 4 ) *
                   ( z * log( z ) + 0.5 * z * ( 1 + z * z ) -
                     M_PI / 4 * ( 1 - z * z ) );
    double answer = q / normBIK;
    return answer;
}
 
double EvtVubBLNPHybrid::dU1nlo( double muh, double mui )
{
    double ai = alphas( mui, m_gvars );
    double ah = alphas( muh, m_gvars );
 
    double q1 = ( ah - ai ) / ( 4 * M_PI * m_beta0 );
    double q2 = log( m_mb / muh ) * m_Gamma1 + m_gp1;
    double q3 = 4 * m_beta1 * ( log( m_mb / muh ) * m_Gamma0 + m_gp0 ) +
                m_Gamma2 * ( 1 - ai / ah );
    double q4 = m_beta1 * m_beta1 * m_Gamma0 * ( -1.0 + ai / ah ) /
                ( 4 * pow( m_beta0, 3 ) );
    double q5 = -m_beta2 * m_Gamma0 * ( 1.0 + ai / ah ) +
                m_beta1 * m_Gamma1 * ( 3 - ai / ah );
    double q6 = m_beta1 * m_beta1 * m_Gamma0 * ( ah - ai ) / m_beta0 -
                m_beta2 * m_Gamma0 * ah + m_beta1 * m_Gamma1 * ai;
 
    double answer =
        q1 * ( q2 - q3 / 4 / m_beta0 + q4 + q5 / ( 4 * m_beta0 * m_beta0 ) ) +
        1 / ( 8 * M_PI * m_beta0 * m_beta0 * m_beta0 ) * log( ai / ah ) * q6;
    return answer;
}
 
double EvtVubBLNPHybrid::U1lo( double muh, double mui )
{
    double epsilon = 0.0;
    double answer = pow( m_mb / muh, -2 * aGamma( muh, mui, epsilon ) ) *
                    exp( 2 * Sfun( muh, mui, epsilon ) -
                         2 * agp( muh, mui, epsilon ) );
    return answer;
}
 
double EvtVubBLNPHybrid::Sfun( double mu1, double mu2, double epsilon )
{
    double a1 = alphas( mu1, m_gvars ) / 4 / M_PI;
    double a2 = alphas( mu2, m_gvars ) / alphas( mu1, m_gvars );
 
    double answer = S0( a1, a2 ) + S1( a1, a2 ) + epsilon * S2( a1, a2 );
    return answer;
}
 
double EvtVubBLNPHybrid::S0( double a1, double r )
{
    double answer = -m_Gamma0 / ( 4.0 * m_beta0 * m_beta0 * a1 ) *
                    ( -1.0 + 1.0 / r + log( r ) );
    return answer;
}
 
double EvtVubBLNPHybrid::S1( double /* a1 */, double r )
{
    double answer = m_Gamma0 / ( 4 * m_beta0 * m_beta0 ) *
                    ( 0.5 * log( r ) * log( r ) * m_beta1 / m_beta0 +
                      ( m_Gamma1 / m_Gamma0 - m_beta1 / m_beta0 ) *
                          ( 1 - r + log( r ) ) );
    return answer;
}
 
double EvtVubBLNPHybrid::S2( double a1, double r )
{
    double w1 = pow( m_beta1, 2 ) / pow( m_beta0, 2 ) - m_beta2 / m_beta0 -
                m_beta1 * m_Gamma1 / ( m_beta0 * m_Gamma0 ) + m_Gamma2 / m_Gamma0;
    double w2 = pow( m_beta1, 2 ) / pow( m_beta0, 2 ) - m_beta2 / m_beta0;
    double w3 = m_beta1 * m_Gamma1 / ( m_beta0 * m_Gamma0 ) - m_beta2 / m_beta0;
    double w4 = a1 * m_Gamma0 / ( 4 * m_beta0 * m_beta0 );
 
    double answer = w4 *
                    ( -0.5 * pow( 1 - r, 2 ) * w1 + w2 * ( 1 - r ) * log( r ) +
                      w3 * ( 1 - r + r * log( r ) ) );
    return answer;
}
 
double EvtVubBLNPHybrid::aGamma( double mu1, double mu2, double epsilon )
{
    double a1 = alphas( mu1, m_gvars );
    double a2 = alphas( mu2, m_gvars );
    double answer = m_Gamma0 / ( 2 * m_beta0 ) * log( a2 / a1 ) +
                    epsilon * ( a2 - a1 ) / ( 8.0 * M_PI ) *
                        ( m_Gamma1 / m_beta0 -
                          m_beta1 * m_Gamma0 / ( m_beta0 * m_beta0 ) );
    return answer;
}
 
double EvtVubBLNPHybrid::agp( double mu1, double mu2, double epsilon )
{
    double a1 = alphas( mu1, m_gvars );
    double a2 = alphas( mu2, m_gvars );
    double answer = m_gp0 / ( 2 * m_beta0 ) * log( a2 / a1 ) +
                    epsilon * ( a2 - a1 ) / ( 8.0 * M_PI ) *
                        ( m_gp1 / m_beta0 -
                          m_beta1 * m_gp0 / ( m_beta0 * m_beta0 ) );
    return answer;
}
 
double EvtVubBLNPHybrid::alo( double muh, double mui )
{
    return -2.0 * aGamma( muh, mui, 0 );
}
 
double EvtVubBLNPHybrid::anlo( double muh, double mui )
{    // d/depsilon of aGamma
 
    double ah = alphas( muh, m_gvars );
    double ai = alphas( mui, m_gvars );
    double answer = ( ah - ai ) / ( 8.0 * M_PI ) *
                    ( m_Gamma1 / m_beta0 -
                      m_beta1 * m_Gamma0 / ( m_beta0 * m_beta0 ) );
    return answer;
}
 
double EvtVubBLNPHybrid::alphas( double mu, const std::vector<double>& vars )
{
    // Note: Lambda4 and Lambda5 depend on mbMS = 4.25
    // So if you change mbMS, then you will have to recalculate them.
 
    double beta0 = vars[8];
    double beta1 = vars[9];
    double beta2 = vars[10];
 
    double Lambda4 = 0.298791;
    double lg = 2 * log( mu / Lambda4 );
    double answer = 4 * M_PI / ( beta0 * lg ) *
                    ( 1 - beta1 * log( lg ) / ( beta0 * beta0 * lg ) +
                      beta1 * beta1 / ( beta0 * beta0 * beta0 * beta0 * lg * lg ) *
                          ( ( log( lg ) - 0.5 ) * ( log( lg ) - 0.5 ) -
                            5.0 / 4.0 + beta2 * beta0 / ( beta1 * beta1 ) ) );
    return answer;
}
 
double EvtVubBLNPHybrid::PolyLog( double v, double z )
{
    if ( z >= 1 )
        cout << "Error in EvtVubBLNPHybrid: 2nd argument to PolyLog is >= 1."
             << endl;
 
    double sum = 0.0;
    for ( int k = 1; k < 101; k++ ) {
        sum = sum + pow( z, k ) / pow( k, v );
    }
    return sum;
}
 
double EvtVubBLNPHybrid::Gamma( double z )
{
    if ( z <= 0 )
        return 0;
 
    double v = lgamma( z );
    return exp( v );
}
 
double EvtVubBLNPHybrid::Gamma( double a, double x )
{
    double LogGamma;
    /*    if (x<0.0 || a<= 0.0) raise(SIGFPE);*/
    if ( x < 0.0 )
        x = 0.0;
    if ( a <= 0.0 )
        a = 1.e-50;
    LogGamma = lgamma( a );
    if ( x < ( a + 1.0 ) )
        return gamser( a, x, LogGamma );
    else
        return 1.0 - gammcf( a, x, LogGamma );
}
 
/* ------------------Incomplete gamma function-----------------*/
/* ------------------via its series representation-------------*/
 
double EvtVubBLNPHybrid::gamser( double a, double x, double LogGamma )
{
    double n;
    double ap, del, sum;
 
    ap = a;
    del = sum = 1.0 / a;
    for ( n = 1; n < ITMAX; n++ ) {
        ++ap;
        del *= x / ap;
        sum += del;
        if ( fabs( del ) < fabs( sum ) * EPS )
            return sum * exp( -x + a * log( x ) - LogGamma );
    }
    raise( SIGFPE );
 
    return 0.0;
}
 
/* ------------------Incomplete gamma function complement------*/
/* ------------------via its continued fraction representation-*/
 
double EvtVubBLNPHybrid::gammcf( double a, double x, double LogGamma )
{
    double an, b, c, d, del, h;
    int i;
 
    b = x + 1.0 - a;
    c = 1.0 / FPMIN;
    d = 1.0 / b;
    h = d;
    for ( i = 1; i < ITMAX; i++ ) {
        an = -i * ( i - a );
        b += 2.0;
        d = an * d + b;
        if ( fabs( d ) < FPMIN )
            d = FPMIN;
        c = b + an / c;
        if ( fabs( c ) < FPMIN )
            c = FPMIN;
        d = 1.0 / d;
        del = d * c;
        h *= del;
        if ( fabs( del - 1.0 ) < EPS )
            return exp( -x + a * log( x ) - LogGamma ) * h;
    }
    raise( SIGFPE );
 
    return 0.0;
}
 
double EvtVubBLNPHybrid::findBLNPWhat()
{
    double ranNum = EvtRandom::Flat();
    double oOverBins = 1.0 / ( float( m_pf.size() ) );
    int nBinsBelow = 0;    // largest k such that I[k] is known to be <= rand
    int nBinsAbove = m_pf.size();    // largest k such that I[k] is known to be >  rand
    int middle;
 
    while ( nBinsAbove > nBinsBelow + 1 ) {
        middle = ( nBinsAbove + nBinsBelow + 1 ) >> 1;
        if ( ranNum >= m_pf[middle] ) {
            nBinsBelow = middle;
        } else {
            nBinsAbove = middle;
        }
    }
 
    double bSize = m_pf[nBinsAbove] - m_pf[nBinsBelow];
    // binMeasure is always aProbFunc[nBinsBelow],
 
    if ( bSize == 0 ) {
        // rand lies right in a bin of measure 0.  Simply return the center
        // of the range of that bin.  (Any value between k/N and (k+1)/N is
        // equally good, in this rare case.)
        return ( nBinsBelow + .5 ) * oOverBins;
    }
 
    double bFract = ( ranNum - m_pf[nBinsBelow] ) / bSize;
 
    return ( nBinsBelow + bFract ) * oOverBins;
}
 
double EvtVubBLNPHybrid::getWeight( double mX, double q2, double El )
{
    int ibin_mX = -1;
    int ibin_q2 = -1;
    int ibin_El = -1;
 
    for ( unsigned i = 0; i < m_bins_mX.size(); i++ ) {
        if ( mX >= m_bins_mX[i] )
            ibin_mX = i;
    }
    for ( unsigned i = 0; i < m_bins_q2.size(); i++ ) {
        if ( q2 >= m_bins_q2[i] )
            ibin_q2 = i;
    }
    for ( unsigned i = 0; i < m_bins_El.size(); i++ ) {
        if ( El >= m_bins_El[i] )
            ibin_El = i;
    }
    int ibin = ibin_mX + ibin_q2 * m_bins_mX.size() +
               ibin_El * m_bins_mX.size() * m_bins_q2.size();
 
    if ( ( ibin_mX < 0 ) || ( ibin_q2 < 0 ) || ( ibin_El < 0 ) ) {
        EvtGenReport( EVTGEN_ERROR, "EvtVubHybrid" )
            << "Cannot determine hybrid weight "
            << "for this event "
            << "-> assign weight = 0" << endl;
        return 0.0;
    }
 
    return m_weights[ibin];
}
 
void EvtVubBLNPHybrid::readWeights( int startArg )
{
    m_weights.resize( m_nbins );
 
    double maxw = 0.0;
    for ( auto& w : m_weights ) {
        w = getArg( startArg++ );
        if ( w > maxw )
            maxw = w;
    }
 
    if ( maxw == 0 ) {
        EvtGenReport( EVTGEN_ERROR, "EvtVubBLNPHybrid" )
            << "EvtVub generator expected at least one "
            << " weight > 0, but found none! "
            << "Will terminate execution!" << endl;
        ::abort();
    }
 
    // rescale weights (to be in range 0..1)
    for ( auto& w : m_weights )
        w /= maxw;
}