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 //----------------------------------*-C++-*----------------------------------//
 // Copyright 2022-2024 UT-Battelle, LLC, and other Celeritas developers.
 // See the top-level COPYRIGHT file for details.
 // SPDX-License-Identifier: (Apache-2.0 OR MIT)
 //---------------------------------------------------------------------------//
 //! \file celeritas/em/distribution/EnergyLossGaussianDistribution.hh
 //---------------------------------------------------------------------------//
 #pragma once
 
 #include <cmath>
 
 #include "corecel/Assert.hh"
 #include "corecel/Macros.hh"
 #include "corecel/Types.hh"
 #include "corecel/math/Algorithms.hh"
 #include "celeritas/random/distribution/NormalDistribution.hh"
 
 #include "EnergyLossHelper.hh"
 
 namespace celeritas
 {
 //---------------------------------------------------------------------------//
 /*!
  * Sample energy loss from a Gaussian distribution.
  *
  * In a thick absorber, the total energy transfer is a result of many small
  * energy losses from a large number of collisions. The central limit theorem
  * applies, and the energy loss fluctuations can be described by a Gaussian
  * distribution. See section 7.3.1 of the Geant4 Physics Reference Manual and
  * GEANT3 PHYS332 section 2.3.
  *
  * The Gaussian approximation is valid for heavy particles and in the
  * regime \f$ \kappa = \xi / T_\textrm{max} > 10 \f$.
  * Fluctuations of the unrestricted energy loss
  * follow a Gaussian distribution if \f$ \Delta E > \kappa T_{max} \f$,
  * where \f$ T_{max} \f$ is the maximum energy transfer (PHYS332 section
  * 2). For fluctuations of the \em restricted energy loss, the condition is
  * modified to \f$ \Delta E > \kappa T_{c} \f$ and \f$ T_{max} \le 2 T_c
  * \f$, where \f$ T_c \f$ is the delta ray cutoff energy (PRM Eq. 7.6-7.7).
  */
 class EnergyLossGaussianDistribution
 {
   public:
     //!@{
     //! \name Type aliases
     using Energy = units::MevEnergy;
     using EnergySq = Quantity<UnitProduct<units::Mev, units::Mev>>;
     //!@}
 
   public:
     // Construct from distribution parameters
     inline CELER_FUNCTION
     EnergyLossGaussianDistribution(Energy mean_loss, Energy bohr_stddev);
 
     // Construct from helper distribution parameters
     inline CELER_FUNCTION
     EnergyLossGaussianDistribution(Energy mean_loss, EnergySq bohr_var);
 
     // Construct from helper-calculated data
     explicit inline CELER_FUNCTION
     EnergyLossGaussianDistribution(EnergyLossHelper const& helper);
 
     // Sample energy loss according to the distribution
     template<class Generator>
     inline CELER_FUNCTION Energy operator()(Generator& rng);
 
   private:
     real_type const max_loss_;
     NormalDistribution<real_type> sample_normal_;
 };
 
 //---------------------------------------------------------------------------//
 // INLINE DEFINITIONS
 //---------------------------------------------------------------------------//
 /*!
  * Construct from mean/stddev.
  *
  * This formulation is used internally by the Urban distribution.
  */
 CELER_FUNCTION EnergyLossGaussianDistribution::EnergyLossGaussianDistribution(
     Energy mean_loss, Energy bohr_stddev)
     : max_loss_(2 * mean_loss.value())
     , sample_normal_(mean_loss.value(), bohr_stddev.value())
 
 {
     CELER_EXPECT(mean_loss > zero_quantity());
     CELER_EXPECT(bohr_stddev > zero_quantity());
 }
 
 //---------------------------------------------------------------------------//
 /*!
  * Construct from distribution parameters.
  *
  * The mean loss is the energy lost over the step, and the standard deviation
  * is the square root of Bohr's variance (PRM Eq. 7.8). For thick absorbers,
  * the straggling function approaches a Gaussian distribution with this
  * standard deviation.
  */
 CELER_FUNCTION EnergyLossGaussianDistribution::EnergyLossGaussianDistribution(
     Energy mean_loss, EnergySq bohr_var)
     : EnergyLossGaussianDistribution{mean_loss,
                                      Energy{std::sqrt(bohr_var.value())}}
 {
 }
 
 //---------------------------------------------------------------------------//
 /*!
  * Construct from helper-calculated data.
  */
 CELER_FUNCTION EnergyLossGaussianDistribution::EnergyLossGaussianDistribution(
     EnergyLossHelper const& helper)
     : EnergyLossGaussianDistribution{helper.mean_loss(), helper.bohr_variance()}
 {
 }
 
 //---------------------------------------------------------------------------//
 /*!
  * Sample energy loss according to the distribution.
  */
 template<class Generator>
 CELER_FUNCTION auto
 EnergyLossGaussianDistribution::operator()(Generator& rng) -> Energy
 {
     real_type result;
     do
     {
         result = sample_normal_(rng);
     } while (result <= 0 || result > max_loss_);
     return Energy{result};
 }
 
 //---------------------------------------------------------------------------//
 }  // namespace celeritas

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