@@ -103,10 +103,10 @@ def PhaseShift(
103103 freq : :obj:`numpy.ndarray`
104104 Positive frequency axis
105105 kx : :obj:`int`, optional
106- Horizontal wavenumber axis (centered around 0) of size
106+ Horizontal spectroscopic wavenumber axis (centered around 0) of size
107107 :math:`[n_x \times 1]`.
108108 ky : :obj:`int`, optional
109- Second horizontal wavenumber axis for 3d phase shift
109+ Second horizontal spectroscopic wavenumber axis for 3d phase shift
110110 (centered around 0) of size :math:`[n_y \times 1]`.
111111 dtype : :obj:`str`, optional
112112 Type of elements in input array
@@ -130,9 +130,14 @@ def PhaseShift(
130130 d(f, k_x, k_y) = m(f, k_x, k_y)
131131 e^{-j \Delta z \sqrt{\omega^2/v^2 - k_x^2 - k_y^2}}
132132
133- where :math:`v` is the constant propagation velocity and
134- :math:`\Delta z` is the propagation depth. In adjoint mode, the data is
135- propagated backward using the following transformation:
133+ where :math:`v` is the constant propagation velocity,
134+ :math:`\Delta z` is the propagation depth, :math:`\omega=2\pi f` is the
135+ angular frequency axis (where :math:`f` is represented by ``freq``),
136+ :math:`k_x=2\pi \tilde{k}_x` is the horizontal wavenumber (where
137+ :math:`\tilde{k}_x` is represented by ``kx``), and :math:`k_y=2\pi \tilde{k}_y`
138+ is the second horizontal wavenumber (where :math:`\tilde{k}_y`
139+ is represented by ``ky``). In adjoint mode, the data is propagated backward
140+ using the following transformation:
136141
137142 .. math::
138143 m(f, k_x, k_y) = d(f, k_x, k_y)
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