# MWOperators¶

The MW operators discussed in this chapter is available to the application program by including:

#include "MRCPP/MWOperators"


## Operator application¶

The following is added to the list of functions for defining MW coefficients in a FunctionTree:

apply
Apply a MW operator to an input function, adaptive grid.

The MW operator can be any of those listed below, and the input function must be a well defined (projected) function, while the output function must be in an undefined state.

## Operator construction¶

The following operators are currently implemented in MRCPP:

### Convolution operators¶

IdentityConvolution
Convolution with a narrow Gaussian kernel, close to Dirac’s delta function.
DerivativeConvolution
Convolution with differentiated narrow Gaussian kernel.
PoissonOperator
Convolution with the Poisson Green’s function kernel.
HelmholtzOperator
Convolution with the complex Helmholtz Green’s function kernel.

The convolution operators will adaptively build the output tree based on the chosen precision (note that there are separate precision parameters for the construction and application of convolution operators).

### Derivative operators¶

ABGVOperator
The Alpert, Beylkin, Gines, Vozovoi derivative operator.
PHOperator
Based on Pavel Holoborodko’s smoothing derivative.
BSOperator
Derivative based on projectrion onto B-splines. This is a smoothing derivative operator.

The derivatives operator have clearly defined requirements on the output grid structure, based on the grid of the input function. This means that there is no real grid adaptivity, and thus no precision parameter is needed for the application of such an operator.

## Examples¶

### PoissonOperator¶

The electrostatic potential $$g$$ arising from a charge distribution $$f$$ are related through the Poisson equation

$-\nabla^2 g(r) = f(r)$

This equation can be solved with respect to the potential by inverting the differential operator into the Green’s function integral convolution operator

$g(r) = \int \frac{1}{4\pi\|r-r'\|} f(r') dr'$

This operator is available in the MW representation, and can be solved with arbitrary (finite) precision in linear complexity with respect to system size. Given an arbitrary charge dirtribution f_tree in the MW representation, the potential is computed in the following way:

double apply_prec;                              // Precision defining the operator application
double build_prec;                              // Precision defining the operator construction

mrcpp::PoissonOperator P(MRA, build_prec);      // MW representation of Poisson operator
mrcpp::FunctionTree<3> f_tree(MRA);             // Input function
mrcpp::FunctionTree<3> g_tree(MRA);             // Output function

mrcpp::apply(apply_prec, g_tree, P, f_tree);    // Apply operator adaptively


The Coulomb self-interaction energy can now be computed as the dot product:

double E = mrcpp::dot(g_tree, f_tree);


### HelmholtzOperator¶

The Helmholtz operator is a generalization of the Poisson operator and is given as the integral convolution

$g(r) = \int \frac{e^{-\mu\|r-r'\|}}{4\pi\|r-r'\|} f(r') dr'$

The operator is the inverse of the shifted Laplacian

$\big[-\nabla^2 + \mu^2 \big] g(r) = f(r)$

and appears e.g. when solving the SCF equations. The construction and application is similar to the Poisson operator, with an extra argument for the $$\mu$$ parameter

double apply_prec;                              // Precision defining the operator application
double build_prec;                              // Precision defining the operator construction
double mu;                                      // Must be a positive real number

mrcpp::HelmholtzOperator H(MRA, mu, build_prec);// MW representation of Helmholtz operator
mrcpp::FunctionTree<3> f_tree(MRA);             // Input function
mrcpp::FunctionTree<3> g_tree(MRA);             // Output function

mrcpp::apply(apply_prec, g_tree, H, f_tree);    // Apply operator adaptively


### ABGVOperator¶

The ABGV (Alpert, Beylkin, Gines, Vozovoi) derivative operator is initialized with two parameters $$a$$ and $$b$$ accounting for the boundary conditions between adjacent nodes, see Alpert etal..

double a = 0.0, b = 0.0;                        // Boundary conditions for operator
mrcpp::ABGVOperator<3> D(MRA, a, b);            // MW derivative operator
mrcpp::FunctionTree<3> f(MRA);                  // Input function
mrcpp::FunctionTree<3> f_x(MRA);                // Output function
mrcpp::FunctionTree<3> f_y(MRA);                // Output function
mrcpp::FunctionTree<3> f_z(MRA);                // Output function

mrcpp::apply(f_x, D, f, 0);                     // Operator application in x direction
mrcpp::apply(f_y, D, f, 1);                     // Operator application in y direction
mrcpp::apply(f_z, D, f, 2);                     // Operator application in z direction


The tree structure of the output function will depend on the choice of parameters $$a$$ and $$b$$: if both are zero, the output grid will be identical to the input grid; otherwise the grid will be widened by one node (on each side) in the direction of application.

### PHOperator¶

The PH derivative operator is based on the noise reducing derivative of Pavel Holoborodko. This operator is also available as a direct second derivative.

mrcpp::PHOperator<3> D1(MRA, 1);                // MW 1st derivative operator
mrcpp::PHOperator<3> D2(MRA, 2);                // MW 2nd derivative operator
mrcpp::FunctionTree<3> f(MRA);                  // Input function
mrcpp::FunctionTree<3> f_x(MRA);                // Output function
mrcpp::FunctionTree<3> f_xx(MRA);               // Output function

mrcpp::apply(f_x, D1, f, 0);                    // Operator application in x direction
mrcpp::apply(f_xx, D2, f, 0);                   // Operator application in x direction


Special thanks to Prof. Robert J. Harrison (Stony Brook University) for sharing the operator coefficients.

### BSOperator¶

The BS derivative operator is based on a pre-projection onto B-splines in order to remove the discontinuities in the MW basis. This operator is also available as a direct second and third derivative.

mrcpp::BSOperator<3> D1(MRA, 1);                // MW 1st derivative operator
mrcpp::BSOperator<3> D2(MRA, 2);                // MW 2nd derivative operator
mrcpp::BSOperator<3> D3(MRA, 3);                // MW 3nd derivative operator
mrcpp::FunctionTree<3> f(MRA);                  // Input function
mrcpp::FunctionTree<3> f_x(MRA);                // Output function
mrcpp::FunctionTree<3> f_yy(MRA);               // Output function
mrcpp::FunctionTree<3> f_zzz(MRA);              // Output function

mrcpp::apply(f_x, D1, f, 0);                    // Operator application in x direction
mrcpp::apply(f_yy, D2, f, 1);                   // Operator application in x direction
mrcpp::apply(f_zzz, D3, f, 2);                  // Operator application in x direction