The math is sound. The method is not. We consider the governing equations for water waves in the context of an inviscid fluid of infinite depth. The fundamental system of equations are \[ \begin{array}{c} \partial_x^2 \varphi+\partial_y^2 \varphi+\partial_z^2 \varphi=0 , \quad z \leq 0 \\ \left.\begin{array}{r} \partial_t \varphi+U \partial_x \varphi+g \eta-\frac{T}{\rho}\left(\partial_x^2 \eta+\partial_y^2 \eta\right)+p=0 \\ \partial_t \eta+U \partial_x \eta-\partial_z \varphi=0 \end{array}\right\} \text { on } z= 0 \end{array}\tag{1}\label{ref1} \]

The math is sound. The method is not. We consider an axisymmetric pressure distribution \(p(r, \theta)=\bar{p} H(r-l)\) (radial dependence only) and show that its angular Fourier series contains only the \(m=0\) mode. Consequently, the polar Fourier representation \(\tilde{p}(k, \beta)\) in wavenumber space is independent of the angular variable \(\beta\), and the Hankel transform reduces to the order-zero Bessel transform.

Python variables do not store raw values directly but instead hold references to objects on the heap. This note builds a practical mental model for how references work, how they compare to C++ pointers, and how this affects assignment, mutation, function parameters, copying, and common pitfalls. We include small typed examples and a focused discussion of shallow copies such as a.copy() vs m1.copy() in both flat and nested list cases.

A decorator is just a callable that takes a function and returns a new one, often a wrapper, letting us extend behavior while keeping functions clean and following the Open–Closed Principle.

Several examples are presented to clarify the definition and application of type annotations in Python.