Complex Numbers, $\small \pi$, Fourier Transform, Eigenvectors
This video,
[Source: YouTube; discussion]
describes the mathematics behind one of Richard Feynman’s lectures on the elliptical orbits of planets.
- Feynman discusses the algebraic completeness of complex numbers here.
- See also Reflecting on complex numbers (again)
Interestingly, I later encountered the same (conceptual) description at about the 3-minute mark in this lecture, on the Fourier transform (“An animated introduction to the Fourier Transform, winding graphs around circles.”),
[Source: YouTube]
This page, Understanding the Fourier Transform [mirror] describes the Fourier transform very succinctly.
[Image source. Click image to open in new window.]That figure is explained in the accompanying blog posts.
Basically, whenever you see $\small i$ and $\small \pi$, think “circles and rotation.”
Euler’s formula ties in with $\small i$ and rotation and eigenvectors, as discussed in the really excellent blog post Intuitive Understanding of Euler's Formula:
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Euler's identity $\small e^{i \pi} = -1$ emerges from a more general formula, $\small e^{ix} = \cos(x) + i \sin(x)$ relating an imaginary exponent to sine and cosine (and, where plugging in $\small \pi$ gives -1).
[Aside: that formula formed the basis of the embeddings in RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space (Feb 2019).]
Euler’s formula also comes up in my background discussion on graph signal processing. These complex numbers manifest later in that discussion, when I use GNU Octave to determine some eigenvalues in my various examples: I get “complex” eigenvectors of the form $\small 0.14037 + 0.55581i$ (which is reminiscent of Euler’s formula, $e^{i\phi} = cos\phi + (i)sin \phi$):
octave:>> c = [5,8,16; 4,1,8; -4,-4,-11] c = 5 8 16 4 1 8 -4 -4 -11 octave:>> [eigenvectors, eigenvalues] = eig(c) eigenvectors = 0.81650 + 0.00000i 0.14037 - 0.55581i 0.14037 + 0.55581i 0.40825 + 0.00000i -0.71521 + 0.00000i -0.71521 - 0.00000i -0.40825 + 0.00000i 0.28742 + 0.27790i 0.28742 - 0.27790i eigenvalues = Diagonal Matrix 1.00000 + 0.00000i 0 0 0 -3.00000 + 0.00000i 0 0 0 -3.00000 - 0.00000i octave:>> eig(c) ans = 1.00000 + 0.00000i -3.00000 + 0.00000i -3.00000 - 0.00000i octave:>>
Stated in [Imaginary Numbers] Complex Eigenvalues,
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"Complex numbers are added like vectors:
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$\small x + iy + u + iv = (x + u) + i(y + v)$
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$\small z * w = (x + iy)(u + iv) = xu - yv + i(yu - xv)$.
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$\small 1/z = 1/(x + iy) = (x - iy)/(x^2 + y^2)$."
… hinting (as we already know) at the relationship between vectors (e.g. vector space, models) and imaginary numbers.
That same source includes these statements,
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"Geometric interpretation. If $\small z = x + iy$ is written as a vector $\small \begin{align} \begin{bmatrix}x \\ y\end{bmatrix} \end{align}$, then multiplication with an $\small y$ other complex number $\small w$ is a dilation-rotation: a scaling by $\small |w|$ and a rotation by $\small arg(w)$."
"Unit circle. Complex numbers of length $\small 1$ have the form $\small z = e^{i\phi}$ and are located on the unit circle. The characteristic polynomial $\small f_A(\lambda) = \lambda^5 - 1$ of the matrix
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$\small \begin{align} \begin{bmatrix}
0 & 1 & 0 & 0 & 0 \\\
0 & 0 & 1 & 0 & 0 \\\
0 & 0 & 0 & 1 & 0 \\\
0 & 0 & 0 & 0 & 1 \\\
1 & 0 & 0 & 0 & 0
\end{bmatrix} \end{align}$
These concepts are elaborated in Geometry of the Eigenvectors of Plane Rotation, which states the following. [A good background before reading this material is Intuitive Understanding of Euler's Formula,]
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"Rotation of a two-dimensional vector $\small (x,y)$ in the Cartesian plane can be expressed as a matrix multiplication, where the rotated vector $\small (x',y')$ is equal to the product of the rotation matrix $\small M$ and the original (column) vector $\small (x,y)$. For rotation by a counter-clockwise angle $\small A$, the antisymmetric $\small 2x2$ matrix $\small M$ has the cosine of $\small A$ in the diagonal elements, the sine of $\small A$ at lower left, and the negative of the sine of $\small A$ at upper right. ...
"For an arbitrary angle $\small A$, however, $\small M$ has the two complex-conjugate eigenvalues $\small c = e^{iA}$ and $\small c^* = e^{-iA}$. These complex eigenvalues have meaning only if the setting is generalized to allow $\small x$ and $\small y$ to be complex, so that the products of $\small c$ and $\small x$ and of $\small c$ and $\small y$ are again elements of the vector space. The product of $\small c$ and a complex number $\small z$ is itself equivalent to a rotation of $\small z$ in the complex plane by the angle $\small A$. To see this, represent $\small z$ in polar coordinates as magnitude times exponential of the product of $\small i$ and the angle; then multiplying by $\small c$ just adds $\small A$ to the angle. Thus, multiplication of the complex eigenvector $\small (x,y)$ by the eigenvalue $\small c$ or $\small c^*$ is equivalent to rotation of the complex $\small x$ and $\small y$ by the angle $\small A$ (for $\small c$) or the angle $\small -A$ (for $\small c^*$) in the respective complex $\small x$ and $\small y$ planes.
"The matrix $\small M$, however, is real. Thus, for complex $\small x$ and $\small y$, the product of $\small M$ and $\small x$ or $\small y$ can be viewed as the product of $\small M$ and the real vector $\small Re(x,y)$ plus $\small i$ times the product of $\small M$ and the real vector $\small Im(x,y)$, where $\small Re$ and $\small Im$ denote the real and imaginary parts, respectively. Each of these real products is a rotation by $\small A$ in a real two-dimensional plane: the first is the rotation by $\small A$ in the plane of the real parts of $\small x$ and $\small y$, and the second is the rotation by $\small A$ in the plane of the imaginary parts of $\small x$ and $\small y$. Each of these is equivalent in form to the original rotation of the original real vector $\small (x,y)$.
"The eigenvalue condition in the complex setting can therefore be viewed as a commutation relation: rotation by $\small A$ of the vector of real parts of $\small x$ and $\small y$ in the plane $\small Im(x,y)=(0,0)$, followed by rotation by $\small A$ of the vector of imaginary parts of $\small x$ and $\small y$ in the plane $\small Re(x,y)=0$, gives the same result as rotation of the complex $\small x$ by $\small A$ (or $\small -A$, for $\small c^*$) in the plane $\small y=0$, followed by rotation of the complex $\small y$ by $\small A$ (or $\small -A$, for $\small c^*$) in the plane $\small x=0$. ...
"The vector space in the complex setting is effectively four dimensional, with independent real and imaginary parts for each of $\small x$ and $\small y$. This makes the geometry of the rotations by $\small M$ and $\small c$ or $\small c^*$ difficult to depict or visualize. ..."

[Image source. Click image to open in new window.]
Sources and Additional Reading
- Rotation matrix
- Euler’s rotation theorem
- How to get the eigenvectors from eigenvalues in a rotation matrix?
- Vectors in Three Dimensions and Transformations
- [local copy] Eigendecomposition [Ch. 2 (Linear Algebra) excerpt, from Goodfellow, Bengio & Courville, Deep Learning (2016]
Imaginary Numbers
- Complex Eigenvalues
- Geometry of the Eigenvectors of Plane Rotation
- Intuitive Understanding of Euler's Formula