codebase / stimlib

  #ifndef STIM_MIE_H
  #define STIM_MIE_H

  #include <boost/math/special_functions/bessel.hpp>

  
  #include "scalarwave.h"
  #include "../math/bessel.h"

  #include "../cuda/cudatools/devices.h"

  #include <cmath>
  
  namespace stim{
  
  
  /// Calculate the scattering coefficients for a spherical scatterer
  template<typename T>
  void B_coefficients(stim::complex<T>* B, T a, T k, stim::complex<T> n, int Nl){
  
  	//temporary variables
  	double vm;															//allocate space to store the return values for the bessel function calculation

  	double* j_ka = (double*) malloc( (Nl + 2) * sizeof(double) );
  	double* y_ka = (double*) malloc( (Nl + 2) * sizeof(double) );
  	double* dj_ka= (double*) malloc( (Nl + 2) * sizeof(double) );
  	double* dy_ka= (double*) malloc( (Nl + 2) * sizeof(double) );

  	stim::complex<double>* j_kna = (stim::complex<double>*) malloc( (Nl + 2) * sizeof(stim::complex<double>) );
  	stim::complex<double>* y_kna = (stim::complex<double>*) malloc( (Nl + 2) * sizeof(stim::complex<double>) );
  	stim::complex<double>* dj_kna= (stim::complex<double>*) malloc( (Nl + 2) * sizeof(stim::complex<double>) );
  	stim::complex<double>* dy_kna= (stim::complex<double>*) malloc( (Nl + 2) * sizeof(stim::complex<double>) );

  
  	double ka = k * a;													//store k*a (argument for spherical bessel and Hankel functions)
  	stim::complex<double> kna = k * n * a;								//store k*n*a (argument for spherical bessel functions and derivatives)
  
  	stim::bessjyv_sph<double>(Nl, ka, vm, j_ka, y_ka, dj_ka, dy_ka);			//calculate bessel functions and derivatives for k*a
  	stim::cbessjyva_sph<double>(Nl, kna, vm, j_kna, y_kna, dj_kna, dy_kna);		//calculate complex bessel functions for k*n*a
  
  	stim::complex<double> h_ka, dh_ka;
  	stim::complex<double> numerator, denominator;
  	stim::complex<double> i(0, 1);

  	for(int l = 0; l <= Nl; l++){

  		h_ka.r = j_ka[l];
  		h_ka.i = y_ka[l];
  		dh_ka.r = dj_ka[l];
  		dh_ka.i = dy_ka[l];
  
  		numerator = j_ka[l] * dj_kna[l] * (stim::complex<double>)n - j_kna[l] * dj_ka[l];
  		denominator = j_kna[l] * dh_ka - h_ka * dj_kna[l] * (stim::complex<double>)n;
  		B[l] = (2 * l + 1) * pow(i, l) * numerator / denominator;

  	}

  
  	//free memory
  	free(j_ka); free(y_ka);	free(dj_ka); free(dy_ka); free(j_kna); free(y_kna); free(dj_kna); free(dy_kna);

  }
  
  template<typename T>
  void A_coefficients(stim::complex<T>* A, T a, T k, stim::complex<T> n, int Nl){
  	//temporary variables
  	double vm;															//allocate space to store the return values for the bessel function calculation

  	double* j_ka = (double*) malloc( (Nl + 2) * sizeof(double) );
  	double* y_ka = (double*) malloc( (Nl + 2) * sizeof(double) );
  	double* dj_ka= (double*) malloc( (Nl + 2) * sizeof(double) );
  	double* dy_ka= (double*) malloc( (Nl + 2) * sizeof(double) );

  	stim::complex<double>* j_kna = (stim::complex<double>*) malloc( (Nl + 2) * sizeof(stim::complex<double>) );
  	stim::complex<double>* y_kna = (stim::complex<double>*) malloc( (Nl + 2) * sizeof(stim::complex<double>) );
  	stim::complex<double>* dj_kna= (stim::complex<double>*) malloc( (Nl + 2) * sizeof(stim::complex<double>) );
  	stim::complex<double>* dy_kna= (stim::complex<double>*) malloc( (Nl + 2) * sizeof(stim::complex<double>) );

  
  	double ka = k * a;													//store k*a (argument for spherical bessel and Hankel functions)
  	stim::complex<double> kna = k * n * a;								//store k*n*a (argument for spherical bessel functions and derivatives)
  
  	stim::bessjyv_sph<double>(Nl, ka, vm, j_ka, y_ka, dj_ka, dy_ka);			//calculate bessel functions and derivatives for k*a
  	stim::cbessjyva_sph<double>(Nl, kna, vm, j_kna, y_kna, dj_kna, dy_kna);		//calculate complex bessel functions for k*n*a
  
  	stim::complex<double> h_ka, dh_ka;
  	stim::complex<double> numerator, denominator;
  	stim::complex<double> i(0, 1);
  	for(size_t l = 0; l <= Nl; l++){
  		h_ka.r = j_ka[l];
  		h_ka.i = y_ka[l];
  		dh_ka.r = dj_ka[l];
  		dh_ka.i = dy_ka[l];
  
  		numerator = j_ka[l] * dh_ka - dj_ka[l] * h_ka;
  		denominator = j_kna[l] * dh_ka - h_ka * dj_kna[l] * (stim::complex<double>)n;
  		A[l] = (2 * l + 1) * pow(i, l) * numerator / denominator;
  	}

  	//free memory
  	free(j_ka);	free(y_ka);	free(dj_ka); free(dy_ka); free(j_kna); free(y_kna); free(dj_kna); free(dy_kna);

  }
  

  #define LOCAL_NL	16

  template<typename T>

  __global__ void cuda_scalar_mie_scatter(stim::complex<T>* E, size_t N, T* x, T* y, T* z, stim::scalarwave<T>* W, size_t nW, T a, stim::complex<T> n, stim::vec3<T> c, stim::complex<T>* hB, T r_min, T dr, size_t N_hB, int Nl){

  	extern __shared__ stim::complex<T> shared_hB[];		//declare the list of waves in shared memory

  
  	size_t i = blockIdx.x * blockDim.x + threadIdx.x;				//get the index into the array

  	if(i >= N) return;													//exit if this thread is outside the array

  	stim::vec3<T> p;
  	(x == NULL) ? p[0] = 0 : p[0] = x[i];								// test for NULL values and set positions
  	(y == NULL) ? p[1] = 0 : p[1] = y[i];
  	(z == NULL) ? p[2] = 0 : p[2] = z[i];

  	p = p - c;

  	T r = p.len();														//calculate the distance from the sphere
  	if(r < a) return;													//exit if the point is inside the sphere (we only calculate the internal field)

  	T fij = (r - r_min)/dr;											//FP index into the spherical bessel LUT

  	size_t ij = (size_t) fij;											//convert to an integral index
  	T alpha = fij - ij;													//calculate the fractional portion of the index

  	size_t n0j = ij * (Nl + 1);												//start of the first entry in the LUT
  	size_t n1j = (ij+1) * (Nl + 1);											//start of the second entry in the LUT

  
  	T cos_phi;	

  	T Pl_2, Pl_1, Pl;														//declare registers to store the previous two Legendre polynomials
  	
  	stim::complex<T> hBl;

  	stim::complex<T> Ei = 0;											//create a register to store the result
  	int l;

  	stim::complex<T> hlBl[LOCAL_NL+1];									//the first LOCAL_NL components are stored in registers for speed
  	int shared_start = threadIdx.x * (Nl - LOCAL_NL);					//wrap up some operations so that they aren't done in the main loops

  	#pragma unroll LOCAL_NL+1											//copy the first LOCAL_NL+1 h_l * B_l components to registers

  	for(l = 0; l <= LOCAL_NL; l++)
  		hlBl[l] = clerp<T>( hB[n0j + l], hB[n1j + l], alpha );
  	

  	for(l = LOCAL_NL+1; l <= Nl; l++)									//copy any additional h_l * B_l components to shared memory

  		shared_hB[shared_start + (l - (LOCAL_NL+1))] = clerp<T>( hB[n0j + l], hB[n1j + l], alpha );
  

  	complex<T> e, Ew;

  	for(size_t w = 0; w < nW; w++){										//for each plane wave

  		cos_phi = p.norm().dot(W[w].kvec().norm());						//calculate the cosine of the angle between the k vector and the direction from the sphere

  		Pl_2 = 1;														//the Legendre polynomials will be calculated recursively, initialize the first two steps of the recursive relation

  		Pl_1 = cos_phi;

  		e = exp(complex<T>(0, W[w].kvec().dot(c)));
  		Ew = W[w].E() * e;
  		Ei += Ew * hlBl[0] * Pl_2;								//unroll the first two orders using the initial steps of the Legendre recursive relation
  		Ei += Ew * hlBl[1] * Pl_1;		

  		#pragma unroll LOCAL_NL-1										//unroll the next LOCAL_NL-1 loops for speed (iterating through the components in the register file)

  		for(l = 2; l <= LOCAL_NL; l++){

  			Pl = ( (2 * (l-1) + 1) * cos_phi * Pl_1 - (l-1) * Pl_2 ) / (l);	//calculate the next step in the Legendre polynomial recursive relation (this is where most of the computation occurs)

  			Ei += Ew * hlBl[l] * Pl;								//calculate and sum the current field order

  			Pl_2 = Pl_1;												//shift Pl_1 -> Pl_2 and Pl -> Pl_1

  			Pl_1 = Pl;

  		}

  		for(l = LOCAL_NL+1; l <= Nl; l++){											//do the same as above, except for any additional orders that are stored in shared memory (not registers)
  			Pl = ( (2 * (l-1) + 1) * cos_phi * Pl_1 - (l-1) * Pl_2 ) / (l);				//again, this is where most computation in the kernel occurs

  			Ei += Ew * shared_hB[shared_start + l - LOCAL_NL - 1] * Pl;

  			Pl_2 = Pl_1;															//shift Pl_1 -> Pl_2 and Pl -> Pl_1
  			Pl_1 = Pl;			

  		}

  	}

  	E[i] += Ei;															//copy the result to device memory

  }
  

  ///Calculate the scalar Mie scattered field on the GPU
  /// @param E (GPU) is the N x N destination scalar field
  /// @param N is the number fo elements of the scalar field in each direction
  /// @param x (GPU) is the grid of X coordinates for each point in E
  /// @param y (GPU) is the grid of Y coordinates for each point in E
  /// @param z (GPU) is the grid of Z coordinates for each point in E
  /// @param W (CPU) is an array of coherent scalar plane waves incident on the Mie scatterer
  /// @param a is the radius of the Mie scatterer
  /// @param n is the complex refractive index of the Mie scatterer
  /// @param r_spacing is the minimum distance between r values of the sample points in E (used to calculate look-up tables)

  template<typename T>

  void gpu_scalar_mie_scatter(stim::complex<T>* E, size_t N, T* x, T* y, T* z, stim::scalarwave<T>* W, size_t nW, T a, stim::complex<T> n, stim::vec3<T> c, stim::complex<T>* hB, T kr_min, T dkr, size_t N_hB, size_t Nl){

  	
  	size_t max_shared_mem = stim::sharedMemPerBlock();	

  	size_t hBl_array = sizeof(stim::complex<T>) * (Nl + 1);

  	//std::cout<<"hl*Bl array size:  "<<hBl_array<<std::endl;
  	//std::cout<<"shared memory:     "<<max_shared_mem<<std::endl;

  	int threads = (int)((max_shared_mem / hBl_array) / 32 * 32);

  	//std::cout<<"threads per block: "<<threads<<std::endl;

  	dim3 blocks((unsigned)(N / threads + 1));										//calculate the optimal number of blocks
  
  	size_t shared_mem;
  	if(Nl <= LOCAL_NL) shared_mem = 0;
  	else shared_mem = threads * sizeof(stim::complex<T>) * (Nl - LOCAL_NL);				//amount of shared memory to allocate

  	//std::cout<<"shared memory allocated: "<<shared_mem<<std::endl;

  	cuda_scalar_mie_scatter<T><<< blocks, threads, shared_mem >>>(E, N, x, y, z, W, nW, a, n, c, hB, kr_min, dkr, N_hB, (int)Nl);	//call the kernel

  }
  
  template<typename T>

  __global__ void cuda_dist(T* r, T* x, T* y, T* z, size_t N, stim::vec3<T> c = stim::vec3<T>(0, 0, 0)){

  	size_t i = blockIdx.x * blockDim.x + threadIdx.x;				//get the index into the array
  	if(i >= N) return;													//exit if this thread is outside the array
  
  	stim::vec3<T> p;
  	(x == NULL) ? p[0] = 0 : p[0] = x[i];								// test for NULL values and set positions
  	(y == NULL) ? p[1] = 0 : p[1] = y[i];
  	(z == NULL) ? p[2] = 0 : p[2] = z[i];
  

  	r[i] = (p - c).len();

  }

  
  ///Calculate the scalar Mie scattered field on the GPU
  /// @param E (GPU) is the N x N destination scalar field
  /// @param N is the number fo elements of the scalar field in each direction
  /// @param x (GPU) is the grid of X coordinates for each point in E
  /// @param y (GPU) is the grid of Y coordinates for each point in E
  /// @param z (GPU) is the grid of Z coordinates for each point in E
  /// @param W (CPU) is an array of coherent scalar plane waves incident on the Mie scatterer
  /// @param a is the radius of the Mie scatterer
  /// @param n is the complex refractive index of the Mie scatterer
  /// @param r_spacing is the minimum distance between r values of the sample points in E (used to calculate look-up tables)

  template<typename T>

  void gpu_scalar_mie_scatter(stim::complex<T>* E, size_t N, T* x, T* y, T* z, std::vector<stim::scalarwave<T>> W, T a, stim::complex<T> n, stim::vec3<T> c = stim::vec3<T>(0, 0, 0), T r_spacing = 0.1){

  	//calculate the necessary number of orders required to represent the scattered field
  	T k = W[0].kmag();
  

  	int Nl = (int)ceil(k*a + 4 * cbrt( k * a ) + 2);
  	if(Nl < LOCAL_NL) Nl = LOCAL_NL;							//always do at least the minimum number of local operations (kernel optimization)

  	//std::cout<<"Nl: "<<Nl<<std::endl;

  
  	//calculate the scattering coefficients for the sphere
  	stim::complex<T>* B = (stim::complex<T>*) malloc( sizeof(stim::complex<T>) * (Nl + 1) );	//allocate space for the scattering coefficients

  	B_coefficients(B, a, k, n, Nl);	
  	

  	//	PLANE WAVES
  	stim::scalarwave<T>* dev_W;																//allocate space and copy plane waves
  	HANDLE_ERROR( cudaMalloc(&dev_W, sizeof(stim::scalarwave<T>) * W.size()) );
  	HANDLE_ERROR( cudaMemcpy(dev_W, &W[0], sizeof(stim::scalarwave<T>) * W.size(), cudaMemcpyHostToDevice) );
  

  	// BESSEL FUNCTION LOOK-UP TABLE

  	//calculate the distance from the sphere center
  	T* dev_r;
  	HANDLE_ERROR( cudaMalloc(&dev_r, sizeof(T) * N) );
  		
  	int threads = stim::maxThreadsPerBlock();
  	dim3 blocks((unsigned)(N / threads + 1));

  	cuda_dist<T> <<< blocks, threads >>>(dev_r, x, y, z, N, c);

  
  	//Find the minimum and maximum values of r
      cublasStatus_t stat;
      cublasHandle_t handle;
  
  	stat = cublasCreate(&handle);							//create a cuBLAS handle
  	if (stat != CUBLAS_STATUS_SUCCESS){						//test for failure
          printf ("CUBLAS initialization failed\n");
  		exit(1);
  	}
  
  	int i_min, i_max;
  	stat = cublasIsamin(handle, (int)N, dev_r, 1, &i_min);
  	if (stat != CUBLAS_STATUS_SUCCESS){						//test for failure
          printf ("CUBLAS Error: failed to calculate minimum r value.\n");
  		exit(1);
  	}
  	stat = cublasIsamax(handle, (int)N, dev_r, 1, &i_max);
  	if (stat != CUBLAS_STATUS_SUCCESS){						//test for failure
          printf ("CUBLAS Error: failed to calculate maximum r value.\n");
  		exit(1);
  	}
  

  	i_min--;				//cuBLAS uses 1-based indexing for Fortran compatibility
  	i_max--;

  	T r_min, r_max;											//allocate space to store the minimum and maximum values
  	HANDLE_ERROR( cudaMemcpy(&r_min, dev_r + i_min, sizeof(T), cudaMemcpyDeviceToHost) );		//copy the min and max values from the device to the CPU
  	HANDLE_ERROR( cudaMemcpy(&r_max, dev_r + i_max, sizeof(T), cudaMemcpyDeviceToHost) );
  

  	r_min = max(r_min, a);									//if the radius of the sphere is larger than r_min, change r_min to a (the scattered field doesn't exist inside the sphere)

  	//size_t Nlut_j = (size_t)((r_max - r_min) / r_spacing + 1);			//number of values in the look-up table based on the user-specified spacing along r

  	size_t N_hB_lut = (size_t)((r_max - r_min) / r_spacing + 1);

  	//T kr_min = k * r_min;
  	//T kr_max = k * r_max;

  
  	//temporary variables
  	double vm;															//allocate space to store the return values for the bessel function calculation
  	double* jv = (double*) malloc( (Nl + 1) * sizeof(double) );
  	double* yv = (double*) malloc( (Nl + 1) * sizeof(double) );
  	double* djv= (double*) malloc( (Nl + 1) * sizeof(double) );
  	double* dyv= (double*) malloc( (Nl + 1) * sizeof(double) );
  

  	size_t hB_bytes = sizeof(stim::complex<T>) * (Nl+1) * N_hB_lut;
  	stim::complex<T>* hB_lut = (stim::complex<T>*) malloc(hB_bytes);													//pointer to the look-up table

  	T dr = (r_max - r_min) / (N_hB_lut-1);												//distance between values in the LUT

  	//std::cout<<"LUT jl bytes:  "<<hB_bytes<<std::endl;

  	stim::complex<T> hl;

  	for(size_t ri = 0; ri < N_hB_lut; ri++){													//for each value in the LUT
  		stim::bessjyv_sph<double>(Nl, k * (r_min + ri * dr), vm, jv, yv, djv, dyv);		//compute the list of spherical bessel functions from [0 Nl]

  		for(size_t l = 0; l <= Nl; l++){													//for each order

  			hl.r = (T)jv[l];
  			hl.i = (T)yv[l];
  

  			hB_lut[ri * (Nl + 1) + l] = hl * B[l];										//store the bessel function result
  			//std::cout<<hB_lut[ri * (Nl + 1) + l]<<std::endl;

  		}
  	}

  	//T* real_lut = (T*) malloc(hB_bytes/2);
  	//stim::real(real_lut, hB_lut, N_hB_lut);
  	//stim::cpu2image<T>(real_lut, "hankel_B.bmp", Nl+1, N_hB_lut, stim::cmBrewer);

  
  	//Allocate device memory and copy everything to the GPU

  	stim::complex<T>* dev_hB_lut;
  	HANDLE_ERROR( cudaMalloc(&dev_hB_lut, hB_bytes) );
  	HANDLE_ERROR( cudaMemcpy(dev_hB_lut, hB_lut, hB_bytes, cudaMemcpyHostToDevice) );

  	//std::cout << "r_min: " << r_min << std::endl;
  	//std::cout << "dr: " << dr << std::endl;
  	gpu_scalar_mie_scatter<T>(E, N, x, y, z, dev_W, W.size(), a, n, c, dev_hB_lut, r_min, dr, N_hB_lut, Nl);

  	HANDLE_ERROR(cudaMemcpy(E, E, N * sizeof(stim::complex<T>), cudaMemcpyDeviceToHost));			//copy the field from device memory
  
  	HANDLE_ERROR(cudaFree(dev_hB_lut));
  	HANDLE_ERROR(cudaFree(dev_r));
  	HANDLE_ERROR(cudaFree(dev_W));

  }
  /// Calculate the scalar Mie solution for the scattered field produced by a single plane wave
  
  /// @param E is a pointer to the destination field values
  /// @param N is the number of points used to calculate the field
  /// @param x is an array of x coordinates for each point, specified relative to the sphere (x = NULL assumes all zeros)
  /// @param y is an array of y coordinates for each point, specified relative to the sphere (y = NULL assumes all zeros)
  /// @param z is an array of z coordinates for each point, specified relative to the sphere (z = NULL assumes all zeros)
  /// @param W is an array of planewaves that will be scattered
  /// @param a is the radius of the sphere
  /// @param n is the complex refractive index of the sphere
  template<typename T>

  void cpu_scalar_mie_scatter(stim::complex<T>* E, size_t N, T* x, T* y, T* z, std::vector<stim::scalarwave<T>> W, T a, stim::complex<T> n, stim::vec3<T> c = stim::vec3<T>(0, 0, 0)){

  /*#ifdef CUDA_FOUND

  	stim::complex<T>* dev_E;										//allocate space for the field
  	cudaMalloc(&dev_E, N * sizeof(stim::complex<T>));
  	cudaMemcpy(dev_E, E, N * sizeof(stim::complex<T>), cudaMemcpyHostToDevice);
  	//cudaMemset(dev_F, 0, N * sizeof(stim::complex<T>));				//set the field to zero (necessary because a sum is used)
  
  	//	COORDINATES
  	T* dev_x = NULL;												//allocate space and copy the X coordinate (if specified)
  	if(x != NULL){
  		HANDLE_ERROR(cudaMalloc(&dev_x, N * sizeof(T)));
  		HANDLE_ERROR(cudaMemcpy(dev_x, x, N * sizeof(T), cudaMemcpyHostToDevice));
  	}
  	T* dev_y = NULL;												//allocate space and copy the Y coordinate (if specified)
  	if(y != NULL){
  		HANDLE_ERROR(cudaMalloc(&dev_y, N * sizeof(T)));
  		HANDLE_ERROR(cudaMemcpy(dev_y, y, N * sizeof(T), cudaMemcpyHostToDevice));
  	}
  	T* dev_z = NULL;												//allocate space and copy the Z coordinate (if specified)
  	if(z != NULL){
  		HANDLE_ERROR(cudaMalloc(&dev_z, N * sizeof(T)));
  		HANDLE_ERROR(cudaMemcpy(dev_z, z, N * sizeof(T), cudaMemcpyHostToDevice));
  	}
  

  	gpu_scalar_mie_scatter(dev_E, N, dev_x, dev_y, dev_z, W, a, n, c, r_spacing);

  
  	if(x != NULL) cudaFree(dev_x);														//free everything
  	if(y != NULL) cudaFree(dev_y);
  	if(z != NULL) cudaFree(dev_z);
  	cudaFree(dev_E);
  #else

  */

  	//calculate the necessary number of orders required to represent the scattered field
  	T k = W[0].kmag();
  
  	int Nl = (int)ceil(k*a + 4 * cbrt( k * a ) + 2);
  	if(Nl < LOCAL_NL) Nl = LOCAL_NL;							//always do at least the minimum number of local operations (kernel optimization)
  	//std::cout<<"Nl: "<<Nl<<std::endl;
  
  	//calculate the scattering coefficients for the sphere
  	stim::complex<T>* B = (stim::complex<T>*) malloc( sizeof(stim::complex<T>) * (Nl + 1) );	//allocate space for the scattering coefficients
  	B_coefficients(B, a, k, n, Nl);

  
  	//allocate space to store the bessel function call results
  	double vm;										
  	double* j_kr = (double*) malloc( (Nl + 1) * sizeof(double) );
  	double* y_kr = (double*) malloc( (Nl + 1) * sizeof(double) );
  	double* dj_kr= (double*) malloc( (Nl + 1) * sizeof(double) );
  	double* dy_kr= (double*) malloc( (Nl + 1) * sizeof(double) );
  
  	T* P = (T*) malloc( (Nl + 1) * sizeof(T) );
  
  	T r, kr, cos_phi;
  	stim::complex<T> h;

  	stim::complex<T> Ew;

  	for(size_t i = 0; i < N; i++){
  		stim::vec3<T> p;															//declare a 3D point
  	
  		(x == NULL) ? p[0] = 0 : p[0] = x[i];										// test for NULL values and set positions
  		(y == NULL) ? p[1] = 0 : p[1] = y[i];
  		(z == NULL) ? p[2] = 0 : p[2] = z[i];

  		p = p - c;

  		r = p.len();
  		if(r >= a){
  			for(size_t w = 0; w < W.size(); w++){

  				Ew = W[w].E() * exp(stim::complex<double>(0, W[w].kvec().dot(c)));

  				kr = p.len() * W[w].kmag();											//calculate k*r
  				stim::bessjyv_sph<double>(Nl, kr, vm, j_kr, y_kr, dj_kr, dy_kr);
  				cos_phi = p.norm().dot(W[w].kvec().norm());							//calculate the cosine of the angle from the propagating direction
  				stim::legendre<T>(Nl, cos_phi, P);
  
  				for(size_t l = 0; l <= Nl; l++){
  					h.r = j_kr[l];
  					h.i = y_kr[l];

  					E[i] += Ew * B[l] * h * P[l];

  				}
  			}
  		}
  	}

  //#endif

  }
  
  template<typename T>

  void cpu_scalar_mie_scatter(stim::complex<T>* E, size_t N, T* x, T* y, T* z, stim::scalarwave<T> w, T a, stim::complex<T> n, stim::vec3<T> c = stim::vec3<T>(0, 0, 0), T r_spacing = 0.1){

  	std::vector< stim::scalarwave<T> > W(1, w);

  	cpu_scalar_mie_scatter(E, N, x, y, z, W, a, n, c, r_spacing);

  }
  
  template<typename T>
  __global__ void cuda_scalar_mie_internal(stim::complex<T>* E, size_t N, T* x, T* y, T* z, stim::scalarwave<T>* W, size_t nW, T a, stim::complex<T> n, stim::complex<T>* jA, T r_min, T dr, size_t N_jA, int Nl){
  	extern __shared__ stim::complex<T> shared_jA[];		//declare the list of waves in shared memory
  
  	size_t i = blockIdx.x * blockDim.x + threadIdx.x;				//get the index into the array
  	if(i >= N) return;													//exit if this thread is outside the array
  	stim::vec3<T> p;
  	(x == NULL) ? p[0] = 0 : p[0] = x[i];								// test for NULL values and set positions
  	(y == NULL) ? p[1] = 0 : p[1] = y[i];
  	(z == NULL) ? p[2] = 0 : p[2] = z[i];
  	
  	T r = p.len();														//calculate the distance from the sphere

  	if(r >= a) return;													//exit if the point is inside the sphere (we only calculate the internal field)

  	T fij = (r - r_min)/dr;												//FP index into the spherical bessel LUT