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Acoustic

sweep.equations.Acoustic 

Acoustic(spatial_order=4, device='cpu', backend='torch', dim=2)

Bases: sweep.equations.base.SecondOrderEquation

Second-order 2-D acoustic wave equation with CPML auxiliary fields.

The default scalar-wave solver: a pressure-like field h1 is driven by vp**2 · Laplace(u) and absorbed at every side by a split-step CPML formulation (cpmlr by default). This is the most common forward and inversion equation in the codebase.

Models (constructor input order)

  • vp (m/s): Acoustic P-wave velocity model.

Wavefields

  • h1 (aliases: pressure, p): Primary 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).
  • psiz: CPML memory variable for the z-derivative term (internal).
  • zetax: CPML auxiliary wavefield for the x-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 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/acoustic2d/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 2 for this class; use :class:Acoustic3D for 3-D. Defaults to 2.