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Acoustic3D

sweep.equations.Acoustic3D 

Acoustic3D(spatial_order=4, device='cpu', backend='torch', dim=3)

Bases: sweep.equations.base.SecondOrderEquation

Second-order 3-D acoustic wave equation with CPML auxiliary fields.

Three-dimensional generalisation of :class:Acoustic: a pressure-like field h1 is driven by vp**2 · Laplace(u) (assembled from separable 1-D Laplacians in z / y / x) and absorbed on every face by a split-step CPML formulation (cpmlr by default).

Models (constructor input order)

  • vp (m/s): 3D acoustic P-wave velocity model.

Wavefields

  • h1 (aliases: pressure, p): Primary 3D acoustic pressure-like wavefield; default source and receiver.
  • h2 (aliases: pressure_prev): Previous-step pressure-like wavefield (internal).
  • psix: CPML memory variable for the x-derivative term (internal).
  • psiy: CPML memory variable for the y-derivative term (internal).
  • psiz: CPML memory variable for the z-derivative term (internal).
  • zetax: CPML auxiliary wavefield for the x-direction update (internal).
  • zetay: CPML auxiliary wavefield for the y-direction update (internal).
  • zetaz: CPML auxiliary wavefield for the z-direction update (internal).

Defaults

  • source_type: ['h1']
  • receiver_type: ['h1']
  • pml_type: 'cpmlr'

Build the 3-D acoustic equation operator.

Parameters:

  • spatial_order –

    FD accuracy order of the spatial Laplacian — e.g. spatial_order=4 is fourth-order accurate. Internally the half-stencil width is M = spatial_order // 2 (used for loop bounds and PML padding). Must be an even integer (typical values 2, 4, 6, 8, 10, …). Higher orders cut grid dispersion at the cost of more compute per step and a wider PML halo. Performance note (impl='c' on CUDA): the compiled kernels ship template specialisations only for spatial_order ∈ {2, 4, 6, 8}. Above 8 the dispatcher drops to a generic runtime path (order = -1 in src/sweep/csrc/cuda/equations/acoustic3d/forward.cu) which uses more registers and runs noticeably slower. The PyTorch eager path is unaffected. Defaults to 4.

  • device –

    Device for the operator's static kernels (Laplace / gradient coefficients). Use 'cuda' / a torch.device when running on GPU so the propagator can follow without a host↔device copy. Defaults to 'cpu'.

  • backend –

    Array / programming backend, 'torch' or 'jax'. When you later want impl='c', leave this on 'torch' — the compiled CUDA kernels are dispatched through the Torch binding. Defaults to 'torch'.

  • dim –

    Stored dimensionality. Always 3 for this class; use :class:Acoustic for 2-D. Defaults to 3.

C_NAME class-attribute 

C_NAME = 'acoustic3d'

str(object='') -> str str(bytes_or_buffer[, encoding[, errors]]) -> str

Create a new string object from the given object. If encoding or errors is specified, then the object must expose a data buffer that will be decoded using the given encoding and error handler. Otherwise, returns the result of object.str() (if defined) or repr(object). encoding defaults to sys.getdefaultencoding(). errors defaults to 'strict'.

supports_image_topography class-attribute 

supports_image_topography = True

bool(x) -> bool

Returns True when the argument x is true, False otherwise. The builtins True and False are the only two instances of the class bool. The class bool is a subclass of the class int, and cannot be subclassed.

supports_image_topography_c class-attribute 

supports_image_topography_c = True

bool(x) -> bool

Returns True when the argument x is true, False otherwise. The builtins True and False are the only two instances of the class bool. The class bool is a subclass of the class int, and cannot be subclassed.