Boolean squaring of adjacency matrix

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Homework Help Overview

The discussion revolves around the concept of boolean squaring of an adjacency matrix, specifically the notation ##M^{(2)}##, which signifies the square using boolean algebra. The original poster expresses confusion regarding the computation of ##M^{(2)}## and its distinction from the standard matrix squaring ##M^2##.

Discussion Character

  • Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • Participants explore the meaning of boolean algebra in the context of adjacency matrices and question the significance of the notation ##M^{(2)}## versus ##M^2##. There is a discussion about the implications of these notations on the interpretation of paths in a graph.

Discussion Status

Some participants have provided clarifications regarding the definitions of boolean operations and the implications of the notation used. There is an ongoing exploration of the differences between the two notations, and the original poster has indicated that the discussion has helped them gain a better understanding.

Contextual Notes

The original poster is seeking clarification on a specific mathematical notation and its application in the context of graph theory, particularly regarding adjacency matrices and boolean algebra. There is an acknowledgment of potential confusion surrounding the definitions and interpretations involved.

s3a
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Homework Statement


I have come across the following statement which I've written for myself a long time ago, and I don't remember what is going on.:
The adjacency matrix of R ◦ R is ##M^{(2)}##, where (2) signifies the square using boolean algebra.

Homework Equations


Boolean Squaring.

The Attempt at a Solution


Sorry for the potentially stupid question, but I've been researching how to compute ##M^{(2)}##, and the best I found was how to get an adjacency matrix from a graph, and computing ##M^2## (instead of ##M^{(2)}##).

If someone could either explain to me the ##M^{(2)}## part or point me to something that explains that, I would very much appreciate it!
 
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"Boolean algebra" is essentially algebra on "true", "false" or, equivalently "1", "0" with the addition rules that 0+ 0= 0, 1+ 0= 0+ 1= 1, and 1+ 1= 0 and multiplication rules 0*0= 0*1= 1*0= 0 and 1*1= 1.
 
For 1 + 1, I think you meant 1 + 1 = 1, but that's not my problem; my problem is the parentheses around the 2 . . . what's the difference between a power within parentheses and a power that's not within parentheses (in this context)?
 
s3a said:
For 1 + 1, I think you meant 1 + 1 = 1, but that's not my problem; my problem is the parentheses around the 2 . . . what's the difference between a power within parentheses and a power that's not within parentheses (in this context)?

The matrix ##M^k## has entries which specify the number of paths of length k; that is, the element ##M^k(i,j)## is the number of length-k paths from i to j. The matrix ##M^{(k)}## just says whether there are length-k paths; that is, ##M^{(k)}(i,j)## is 0 if there are no length-k paths from i to j and is equal to 1 if there is at least one length-k path from i to j.
 
So does it not make sense to ask:

Given that the matrix M is the adjacency matrix of the graph of some relation R.

What is the adjacency matrix of R◦R?"

to which the answer is

The adjacency matrix of R◦R is ##M^{(2)}##, where (2) signifies the square using boolean algebra.
?
 
Edit: I accidentally double-posted.
 
Actually, Ray Vickson, what you said gave me the ammunition to better understand what someone else explained to me.

Thank you both.
 

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