Source code for struphy.propagators.poisson_adiabatic_gyrokinetic

from dataclasses import dataclass
from typing import Callable, Literal

from feectools.linalg.basic import IdentityOperator
from feectools.linalg.stencil import StencilVector

from struphy.feec.mass import AverageOperator
from struphy.io.options import LiteralOptions
from struphy.linear_algebra.solver import SolverParameters
from struphy.models.variables import FEECVariable, PICVariable, SPHVariable
from struphy.pic.accumulation.filter import FilterParameters
from struphy.pic.accumulation.particles_to_grid import ParticlesToGrid
from struphy.propagators.implicit_diffusion import ImplicitDiffusion
from struphy.utils.utils import check_option


[docs] class PoissonAdiabaticGyrokinetic(ImplicitDiffusion): r""" Weak discretization of the Poisson equation, with adabatic response of electrons. Find :math:`\phi \in H^1` such that .. math:: \frac{1}{Z\epsilon^2} \int_\Omega \frac{n_0}{T_0} \psi\, \phi\,\textrm d \mathbf x + \int_\Omega \frac{n_0}{|B_0|²} \nabla \psi^\top \,\mathbb D \nabla \phi \,\textrm d \mathbf x = \sum_i \int_\Omega \psi\, \rho_i(\mathbf x)\,\textrm d \mathbf x \qquad \forall \ \psi \in H^1\,, where :math:`\mathbb D` can be an anisotropic (gyrokinetic) diffusion operator (or the identity), :math:`\epsilon \in \mathbb R` is the gyrokinetic ratio defined in units, and Z the charge number of ions. Boundary terms from integration by parts are assumed to vanish. The equation is discretized as .. math:: \left( \frac{1}{Z\epsilon^2}\,\mathbb M^0_ad + \mathbb G^\top \mathbb M^1_\textnormal{gyro} \mathbb G \right)\, \boldsymbol\phi^{n+1} = \sum_i(\Lambda^0, \rho_i )_{L^2}\,, where :math:`\mathbb M^1_\textnormal{gyro}` is the gyrokinetic mass matrix and :math:`\mathbb S` is a stabilization matrix. Parameters ---------- phi : StencilVector FE coefficients of the solution as a discrete 0-form. stab_eps : float Stabilization parameter multiplied on stab_mat (default=0.0). stab_mat : str Name of the stabilizing matrix. rho : FEECVariable or Callable or ParticlesToGrid or list (List of) right-hand side source term(s) of the Poisson problem (optional, can be set with a setter later). See :class:`~struphy.propagators.implicit_diffusion.ImplicitDiffusion` for the accepted entries; particle sources are passed as :class:`~struphy.pic.accumulation.particles_to_grid.ParticlesToGrid`. x0 : StencilVector Initial guess for the iterative solver (optional, can be set with a setter later). solver : dict Parameters for the iterative solver (see ``__init__`` for details). """ def __init__( self, rho: FEECVariable | Callable | ParticlesToGrid | list = None, rho_coeffs: float | list = None, epsilon: float = 1.0, Z: int = 1, diagnostic: FEECVariable | None = None, ): """ Parameters ---------- see ImplicitDiffusion.__init__ docstring for other parameters. epsilon : float Gyrokinetic parameter, appears in gyrokinetic Poisson equation Z : int Charge number for ions, appears in gyrokinetic Poisson equation """ super().__init__(rho=rho, rho_coeffs=rho_coeffs, diagnostic=diagnostic) self.epsilon = epsilon self.Z = Z
[docs] @dataclass class Options: r"""Configuration options for :class:`PoissonAdiabaticGyrokinetic`. Parameters ---------- epsilon : float, default=1.0 Gyrokinetic parameter Z : float, default=1.0 Charge number of ions stab_mat : {"M0", "M0ad", "Id"}, default="Id" Stabilization matrix multiplied by ``stab_eps``. - ``"M0"``: standard weighted 0-form mass operator. - ``"M0ad"``: adiabatic-electron weighted 0-form mass operator. - ``"Id"``: identity operator. which_geometry: {"cylindrical", "toroidal"}, default="cylindrical" Geometry of the problem, determines the meaning of `<\phi>` in the stabilization term. diffusion_mat : {"M1", "M1perp", "M1gyro"}, defaults="M1gyro" Diffusion matrix. rho : FEECVariable or Callable or ParticlesToGrid or list, default=None Right-hand side source term(s) of the Poisson problem. Accepted entries are: - ``None``: zero source. - ``FEECVariable`` in ``H1``. - ``Callable`` to be projected to ``H1`` via ``L2Projector``. - :class:`~struphy.pic.accumulation.particles_to_grid.ParticlesToGrid`, describing a particle-to-grid (charge/current) deposition. - a ``list`` containing any mix of the entries above. rho_coeffs : float or list, default=None Multiplicative coefficient(s) applied to ``rho``. If ``None``, coefficients default to ``1.0`` for all sources. x0 : StencilVector, default=None Initial guess for the iterative linear solver. solver : LiteralOptions.OptsSymmSolver, default="pcg" Name of the symmetric iterative solver passed to :func:`psydac.linalg.solvers.inverse`. precond : LiteralOptions.OptsMassPrecond, default="MassMatrixPreconditioner" Name of the preconditioner configuration. Currently this class inherits the same behavior as :class:`ImplicitDiffusion`, where ``pc=None`` is used internally. solver_params : SolverParameters, default=None Iterative-solver controls (for example ``tol``, ``maxiter``, ``verbose``, ``info``, ``recycle``). If ``None``, defaults to ``SolverParameters()``. filter_params : dict[PICVariable | SPHVariable, FilterParameters], default=None If not None, specifies a filter to the accumulation of a specific variable. Notes ----- ``Poisson.Options`` reuses :class:`ImplicitDiffusion` internals by enforcing ``sigma_2 = 0.0``, ``sigma_3 = 1.0``, ``divide_by_dt = False`` and ``diffusion_mat = "M1"`` in ``__post_init__``. """ # specific literals OptsStabMat = Literal["M0", "M0ad", "Id", "M0ad_withT"] OptsDiffusionMat = Literal["M1", "M1perp", "M1gyro"] OptsGeometry = Literal["cylindrical", "toroidal"] # propagator options stab_mat: OptsStabMat = "M0ad_withT" diffusion_mat: OptsDiffusionMat = "M1gyro" which_geometry: OptsGeometry = "cylindrical" x0: StencilVector = None solver: LiteralOptions.OptsSymmSolver = "pcg" precond: LiteralOptions.OptsMassPrecond = "MassMatrixPreconditioner" solver_params: SolverParameters = None filter_params: dict[PICVariable | SPHVariable, FilterParameters] = None def __post_init__(self): # checks check_option(self.stab_mat, self.OptsStabMat) check_option(self.solver, LiteralOptions.OptsSymmSolver) check_option(self.precond, LiteralOptions.OptsMassPrecond) # defaults if self.solver_params is None: self.solver_params = SolverParameters()
def allocate(self): epsilon = self.epsilon Z = self.Z self.options.sigma_1 = 1 / epsilon**2 / self.Z self.options.sigma_2 = 0.0 self.options.sigma_3 = 1 / epsilon self.options.divide_by_dt = False super().allocate() if self.options.which_geometry == "cylindrical": average_mat = AverageOperator(self.derham, "H1", 2) self._stab_mat = self._stab_mat @ ( IdentityOperator(self._stab_mat.domain, self._stab_mat.codomain) - average_mat ) elif self.options.which_geometry == "toroidal": average_mat1 = AverageOperator(self.derham, "H1", 1) average_mat2 = AverageOperator(self.derham, "H1", 2) self._stab_mat = self._stab_mat @ ( IdentityOperator(self._stab_mat.domain, self._stab_mat.codomain) - (average_mat1 @ average_mat2) ) @property def options(self) -> Options: if not hasattr(self, "_options"): self._options = self.Options() return self._options @options.setter def options(self, new): assert isinstance(new, self.Options) self._options = new