Struct TensorPoisson 

pub struct TensorPoisson {
    pub shape: [usize; 3],
    pub dx: [f64; 3],
    /* private fields */
}

Tensor-format Poisson solver with isolated (vacuum) boundary conditions.

The Green’s function FFT is precomputed during construction, so repeated solves only require the convolution pipeline. FFT plans are cached for reuse across solve() calls.

Fields

shape: [usize; 3]

Spatial grid dimensions [N0, N1, N2] of the original (unpadded) domain.

dx: [f64; 3]

Grid spacing [dx0, dx1, dx2] in each spatial direction.

Implementations

impl TensorPoisson

pub fn new( shape: [usize; 3], dx: [f64; 3], exp_sum_accuracy: f64, _tolerance: f64, _max_rank: usize, ) -> Self

Create a new TensorPoisson solver.

Builds the Braess-Hackbusch exponential sum approximation for 1/r, constructs the Green’s function on a (2N)^3 zero-padded grid, and precomputes its 3D FFT plus cached forward/inverse FFT plans.

• shape: spatial grid dimensions [N0, N1, N2].
• dx: grid spacing in each direction.
• exp_sum_accuracy: target accuracy for the exponential sum decomposition.
• _tolerance, _max_rank: reserved for future rank-adaptive modes.

pub fn from_domain( domain: &Domain, exp_sum_accuracy: f64, tolerance: f64, max_rank: usize, ) -> Self

Create from a Domain, extracting shape and dx automatically.

pub fn with_near_field_enabled(self, enabled: bool) -> Self

Enable or disable the near-field correction (builder pattern).

pub fn last_near_field_magnitude(&self) -> f64

Return the L2 norm of the most recent near-field correction.

Returns 0.0 if no solve has been performed yet or if the correction is disabled.

Trait Implementations

impl PoissonSolver for TensorPoisson

fn solve(&self, density: &DensityField, g: f64) -> PotentialField

Solve the Poisson equation using dense FFT convolution with the precomputed Green’s function.

Pipeline: zero-pad rho to (2N)^3 -> 3D FFT -> pointwise multiply by Green’s FFT -> 3D IFFT -> extract N^3 subgrid -> apply near-field corrections.

fn compute_acceleration(&self, potential: &PotentialField) -> AccelerationField

Compute acceleration g = -grad(Phi) via second-order centered finite differences.

fn set_progress(&mut self, p: Arc<StepProgress>)

Attach shared progress state for intra-phase cell-level reporting.