matsubara.hh

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#pragma once
 
// DiFfRG
#include <DiFfRG/common/cuda_prefix.hh>
#include <DiFfRG/common/math.hh>
 
// C++ standard library
#include <cmath>
#include <vector>
 
namespace DiFfRG
{
  template <typename NT> class MatsubaraQuadrature
  {
  public:
    int predict_size(const NT T, const NT typical_E = 1., const int step = 2);
 
    MatsubaraQuadrature(const NT T, const NT typical_E = 1., const int step = 2, const int min_size = 0,
                        const int max_size = powr<10>(2), const int vacuum_quad_size = 48,
                        const int precision_factor = 1);
 
    MatsubaraQuadrature();
 
    void reinit(const NT T, const NT typical_E = 1., const int step = 2, const int min_size = 0,
                const int max_size = powr<10>(2), const int vacuum_quad_size = 48, const int precision_factor = 1);
 
    const std::vector<NT> &nodes() const;
 
    const std::vector<NT> &weights() const;
 
    int size() const;
 
    NT get_T() const;
 
    NT get_typical_E() const;
 
    template <typename F> auto sum(const F &f) const
    {
      auto sum = T * f(static_cast<NT>(0));
      for (int i = 0; i < m_size; ++i)
        sum += w[i] * (f(x[i]) + f(-x[i]));
      return sum;
    }
 
#ifdef USE_CUDA
    const NT *device_nodes();
 
    const NT *device_weights();
#endif
 
  private:
    NT T, typical_E;
    std::vector<NT> x;
 
    std::vector<NT> w;
 
    int m_size;
 
#ifdef __CUDACC__
    thrust::device_vector<NT> device_x;
 
    thrust::device_vector<NT> device_w;
#endif
 
    void move_device_data();
 
    void reinit_0();
 
    int vacuum_quad_size;
    int precision_factor;
  };
} // namespace DiFfRG