#[test]
fn landau_damping() {
use crate::tooling::core::algos::lagrangian::SemiLagrangian;
use crate::tooling::core::algos::uniform::UniformGrid6D;
use crate::tooling::core::init::domain::{Domain, SpatialBoundType, VelocityBoundType};
use crate::tooling::core::integrator::TimeIntegrator as _;
use crate::tooling::core::phasespace::PhaseSpaceRepr as _;
use crate::tooling::core::poisson::fft::FftPoisson;
use crate::tooling::core::time::strang::StrangSplitting;
let lx = 1.0f64;
let lv = 4.0f64;
let sigma = 2.0f64;
let g = 1.0f64;
let epsilon = 0.05f64;
let k = std::f64::consts::PI / lx;
let domain = Domain::builder()
.spatial_extent(lx)
.velocity_extent(lv)
.spatial_resolution(8)
.velocity_resolution(8)
.t_final(1.0)
.spatial_bc(SpatialBoundType::Periodic)
.velocity_bc(VelocityBoundType::Open)
.build()
.unwrap();
let mut grid = UniformGrid6D::new(domain.clone());
let dx = domain.dx();
let dv = domain.dv();
let [nx1, nx2, nx3, nv1, nv2, nv3] = grid.sizes();
let mut s_norm = 0.0f64;
for iv1 in 0..nv1 {
let v1 = -lv + (iv1 as f64 + 0.5) * dv[0];
for iv2 in 0..nv2 {
let v2 = -lv + (iv2 as f64 + 0.5) * dv[1];
for iv3 in 0..nv3 {
let v3 = -lv + (iv3 as f64 + 0.5) * dv[2];
s_norm += (-(v1 * v1 + v2 * v2 + v3 * v3) / (2.0 * sigma * sigma)).exp()
* dv[0]
* dv[1]
* dv[2];
}
}
}
let c = 1.0 / s_norm;
for ix1 in 0..nx1 {
let x1 = -lx + (ix1 as f64 + 0.5) * dx[0];
let perturb = 1.0 + epsilon * (k * x1).cos();
for ix2 in 0..nx2 {
for ix3 in 0..nx3 {
for iv1 in 0..nv1 {
let v1 = -lv + (iv1 as f64 + 0.5) * dv[0];
for iv2 in 0..nv2 {
let v2 = -lv + (iv2 as f64 + 0.5) * dv[1];
for iv3 in 0..nv3 {
let v3 = -lv + (iv3 as f64 + 0.5) * dv[2];
let f = c
* (-(v1 * v1 + v2 * v2 + v3 * v3) / (2.0 * sigma * sigma)).exp()
* perturb;
let idx = grid.index([ix1, ix2, ix3], [iv1, iv2, iv3]);
grid.data[idx] = f.max(0.0);
}
}
}
}
}
}
let rho_init = grid.compute_density();
let rho_max_init = rho_init.data.iter().cloned().fold(0.0f64, f64::max);
let rho_min_init = rho_init.data.iter().cloned().fold(f64::MAX, f64::min);
let amp_init = (rho_max_init - rho_min_init).max(1e-30);
let poisson = FftPoisson::new(&domain);
let advector = SemiLagrangian::new();
let mut integrator = StrangSplitting::new(g);
let dt = 0.1f64;
for _ in 0..8 {
integrator
.advance(&mut grid, &poisson, &advector, dt)
.unwrap();
}
let rho_final = grid.compute_density();
assert!(
!rho_final.data.iter().any(|x| x.is_nan()),
"Density contains NaN"
);
let rho_max_final = rho_final.data.iter().cloned().fold(0.0f64, f64::max);
let rho_min_final = rho_final.data.iter().cloned().fold(f64::MAX, f64::min);
let amp_final = rho_max_final - rho_min_final;
assert!(
amp_final < 2.0 * amp_init,
"Landau damping: amplitude grew (unstable). amp_init={:.4e}, amp_final={:.4e}",
amp_init,
amp_final
);
println!(
"Landau damping: k={:.3}, k_J≈{:.3}, amp_init={:.4e}, amp_final={:.4e}",
k,
(4.0 * std::f64::consts::PI * g).sqrt() / sigma,
amp_init,
amp_final
);
}