Skip to main content

Authors in a Markov matrix: Which author do people find most inspiring? (11)

Let's consider a case in which we have three people. The number of elements becomes \(3^2 = 9\), means there are nine relationships. Let me show you this with the example of Figure 10.
Figure 10: Examples graphs for relationships among three nodes.
A set of three-node relationships is represented by the following 3x3 adjacency matrix:
 \begin{eqnarray*} \left[ \begin{array}{ccc} a_{11} & a_{12} & a_{13} \\ a_{21} & a_{22} & a_{23} \\ a_{31} & a_{32} & a_{33} \\ \end{array} \right] \end{eqnarray*}
Figure 10 (a) has an edge from node 1 to node 2. According to the definition of an adjacency matrix, the element \(a_{12}\) is 1. The adjacency matrix is the following: \begin{eqnarray*} M_{(a)} = \left[ \begin{array}{ccc} 0 & 1 & 0 \\ 0 & 0 & 0 \\ 0 & 0 & 0 \\ \end{array} \right] \end{eqnarray*} The adjacency matrices of Figures 10 (b), (c) are the following: \begin{eqnarray*} M_{(b)} = \left[ \begin{array}{ccc} 1 & 0 & 0 \\ 0 & 0 & 0 \\ 0 & 0 & 0 \\ \end{array} \right] \end{eqnarray*} \begin{eqnarray*} M_{(c)} = \left[ \begin{array}{ccc} 0 & 1 & 0 \\ 0 & 0 & 0 \\ 0 & 1 & 0 \\ \end{array} \right] \end{eqnarray*} Figures 10 (d), (e), (f) are undirected graphs. There are no arrows since these relationships are mutual. The adjacency matrices are the following: \begin{eqnarray*} M_{(d)} = \left[ \begin{array}{ccc} 0 & 1 & 0 \\ 1 & 0 & 0 \\ 0 & 0 & 0 \\ \end{array} \right] \end{eqnarray*} \begin{eqnarray*} M_{(e)} = \left[ \begin{array}{ccc} 1 & 0 & 0 \\ 0 & 0 & 0 \\ 0 & 0 & 0 \\ \end{array} \right] \end{eqnarray*} \begin{eqnarray*} M_{(f)} = \left[ \begin{array}{ccc} 0 & 1 & 0 \\ 1 & 0 & 1 \\ 0 & 1 & 0 \\ \end{array} \right] \end{eqnarray*} In an undirected graph (a graph that only has undirected edges), all the relationships are mutual, therefore, the matrix has symmetry. As we saw with the symmetric matrix of Alice and Cheshire Cat, if you treat the diagonal (the elements from top left to bottom right) as a mirror, the matching elements are the same on either side of this line. Let me explain a bit more about a symmetric matrix. The main diagonal of matrix is all diagonal elements from top left to bottom right. The main diagonal of 3x3 matrix is formed by the ``d'' elements in the following: \begin{eqnarray*} \left[ \begin{array}{ccc} d & & \\ & d & \\ & & d \\ \end{array} \right] \end{eqnarray*} A symmetric matrix has symmetry with respect to the main diagonal. No matter what kind of elements a matrix contains, it will be symmetrical if the corresponding elements across the diagonal are equal. For example, the following matrix has three pairs (`a'-pair, `b'-pair, and `c'-pair) in the matrix. When each pair is the same number, the matrix is called symmetric. \begin{eqnarray*} \left[ \begin{array}{ccc} & \mbox{a} & \mbox{b} \\ \mbox{a} & & \mbox{c} \\ \mbox{b} & \mbox{c} & \\ \end{array} \right] \end{eqnarray*} For example, you can see the symmetry in \(M_{(f)}\) as the following: \begin{eqnarray*} M_{(f)} = \left[ \begin{array}{ccc} & 1 & 0 \\ 1 & & 1 \\ 0 & 1 & \\ \end{array} \right] \end{eqnarray*} Another symmetric matrix example is the following: \begin{eqnarray*} \left[ \begin{array}{ccc} 1 & 6 & 7 \\ 6 & 2 & 8 \\ 7 & 8 & 3 \\ \end{array} \right] \end{eqnarray*}

Comments

Shitohichi said…
Note: A reader pointed out the
self reference cannot be directional. He is correct. Because a directional relationship is only either ``A likes B'' or ``B likes A.'' If both are true, this is non directional. But the self link is A = B. It cannot be both ``Alice like Alice'' and ``Alice doesn't like Alice'' are true at once.

Thanks for the feedback.

2013-1-23(Wed)

Popular posts from this blog

Geometric Multiplicity: eignvectors (2)

If eigenvectors of a matrix A are independent, it is a happy property. Because the matrix A can be diagonalized with a matrix S that column vectors are eigenvectors of A . For example, Why this is a happy property of A? Because I can find A's power easily. A^{10} is not a big deal. Because Λ is a diagonal matrix and power of a diagonal matrix is quite simple. A^{10} = SΛ^{10} S^{-1} Then, why if I want to compute power of A ? That is the same reason to find eigenvectors. Eigenvectors are a basis of a matrix. A matrix can be represented by a single scalar. I repeat this again. This is the happy point, a matrix becomes a scalar. What can be simpler than a scalar value. But, this is only possible when the matrix S's columns are independent. Because S^{-1} must be exist. Now I come back to my first question. Is the λ's multiplicity related with the number of eigenvectors? This time I found this has the name. Geometric multiplicity (GM): the number of in...

Gauss's quote for positive, negative, and imaginary number

Recently I watched the following great videos about imaginary numbers by Welch Labs. https://youtu.be/T647CGsuOVU?list=PLiaHhY2iBX9g6KIvZ_703G3KJXapKkNaF I like this article about naming of math by Kalid Azad. https://betterexplained.com/articles/learning-tip-idea-name/ Both articles mentioned about Gauss, who suggested to use other names of positive, negative, and imaginary numbers. Gauss wrote these names are wrong and that is one of the reason people didn't get why negative times negative is positive, or, pure positive imaginary times pure positive imaginary is negative real number. I made a few videos about explaining why -1 * -1 = +1, too. Explanation: why -1 * -1 = +1 by pattern https://youtu.be/uD7JRdAzKP8 Explanation: why -1 * -1 = +1 by climbing a mountain https://youtu.be/uD7JRdAzKP8 But actually Gauss's insight is much powerful. The original is in the Gauß, Werke, Bd. 2, S. 178 . Hätte man +1, -1, √-1) nicht positiv, negative, imaginäre (oder gar um...

Tezuka Osamu's Black Jack, "Shrinking"

I like several novel authors. My first favorite author is probably Teduka, Osamu. I still love him. The list grows by adding Hoshi, Shinichi, Agatha Christie, Hermann Hesse, and so forth. My first favorite article of Tezuka was Atom as most of the (boy's) Tezuka fans did. But my favorite is Black Jack. I try to summarize one story, it is still quite vivid in my memory. I first read this story when I was 13 - 15 years old. I re-read it at least several times since Black Jack is composed of many short episodes. The title should be "ちぢむ (SHRINKING)" or it might be "縮む(Shrinking)". (It is not so convenient to translate this to English, since English does not have a system to say the exact same word in several ways. So I just simulate it with capital letters.) Black Jack is a genius surgeon, but he does not have the license. In short, his medical activity is illegal. His skill is top level in the world, but, the fee is also out-of-law expensive. In the story ...