matrix representation of relation composition
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composition
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\PMlinkescapephraserelational composition
\PMlinkescapephraseRelational composition
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We have it within our reach to pick up another way of representing 2-adic relations (http://planetmath.org/RelationTheory), namely, the representation as logical matrices, and also to grasp the analogy
between relational composition (http://planetmath.org/RelationComposition2) and ordinary matrix multiplication
as it appears in linear algebra.
First of all, while we still have the data of a very simple concrete case in mind, let us reflect on what we did in our last Example in order to find the composition G∘H of the 2-adic relations G and H.
Here is the setup that we had before:
X=Y=Z={1,2,3,4,5,6,7}
G=4:3+4:4+4:5⊆X×Y=X×XH=3:4+4:4+5:4⊆Y×Z=X×X
Let us recall the rule for finding the relational composition of a pair of 2-adic relations. Given the 2-adic relations P⊆X×Y and Q⊆Y×Z, the relational composition of P and Q, in that order, is written as P∘Q, or more simply as PQ, and obtained as follows:
To compute PQ, in general, where P and Q are 2-adic relations, simply multiply out the two sums in the ordinary distributive algebraic way, but subject to the following rule for finding the product of two elementary relations of shapes a:b and c:d.
(a:b)(c:d)=(a:d)ifb=c(a:b)(c:d)=0otherwise
To find the relational composition G∘H, one may begin by writing it as a quasi-algebraic product:
G∘H=(4:3+4:4+4:5)(3:4+4:4+5:4)
Multiplying this out in accord with the applicable form of distributive law one obtains the following expansion:
G∘H=(4:3)(3:4)+(4:3)(4:4)+(4:3)(5:4)+(4:4)(3:4)+(4:4)(4:4)+(4:4)(5:4)+(4:5)(3:4)+(4:5)(4:4)+(4:5)(5:4)
Applying the rule that determines the product of elementary relations produces the following array:
G∘H=(4:4)+0+0+0+(4:4)+0+0+0+(4:4)
Since the plus sign in this context represents an operation of logical disjunction or set-theoretic aggregation, all of the positive multiplicities count as one, and this gives the ultimate result:
G∘H=(4:4)
With an eye toward extracting a general formula for relation composition, viewed here on analogy with algebraic multiplication, let us examine what we did in multiplying the 2-adic relations G and H together to obtain their relational composite G∘H.
1 Arrangement
Given the space X={1,2,3,4,5,6,7}, whose cardinality |X| is 7, there are |X×X|=|X|⋅|X|=7⋅7=49 elementary relations of the form i:j, where i and j range over the space X. Although they might be organized in many different ways, it is convenient to regard the collection of elementary relations as being arranged in a lexicographic block of the following form:
1:11:21:31:41:51:61:72:12:22:32:42:52:62:73:13:23:33:43:53:63:74:14:24:34:44:54:64:75:15:25:35:45:55:65:76:16:26:36:46:56:66:77:17:27:37:47:57:67:7
2 Expansion
The relations G and H may then be regarded as logical sums of the following forms:
G=∑ijGij(i:j)
H=∑ijHij(i:j)
The notation ∑ij indicates a logical sum over the collection of elementary relations i:j, while the factors Gij and Hij are values in the boolean domain 𝔹={0,1} that are known as the coefficients of the relations G and H, respectively, with regard to the corresponding elementary relations i:j.
In general, for a 2-adic relation L, the coefficient Lij of the elementary relation i:j in the relation L will be 0 or 1, respectively, as i:j is excluded from or included in L.
With these conventions in place, the expansions of G and H may be written out as follows:
G=4:3+4:4+4:5=0(1:1)+0(1:2)+0(1:3)+0(1:4)+0(1:5)+0(1:6)+0(1:7)+0(2:1)+0(2:2)+0(2:3)+0(2:4)+0(2:5)+0(2:6)+0(2:7)+0(3:1)+0(3:2)+0(3:3)+0(3:4)+0(3:5)+0(3:6)+0(3:7)+0(4:1)+0(4:2)+1(4:3)+1(4:4)+1(4:5)+0(4:6)+0(4:7)+0(5:1)+0(5:2)+0(5:3)+0(5:4)+0(5:5)+0(5:6)+0(5:7)+0(6:1)+0(6:2)+0(6:3)+0(6:4)+0(6:5)+0(6:6)+0(6:7)+0(7:1)+0(7:2)+0(7:3)+0(7:4)+0(7:5)+0(7:6)+0(7:7)
H=3:4+4:4+5:4=0(1:1)+0(1:2)+0(1:3)+0(1:4)+0(1:5)+0(1:6)+0(1:7)+0(2:1)+0(2:2)+0(2:3)+0(2:4)+0(2:5)+0(2:6)+0(2:7)+0(3:1)+0(3:2)+0(3:3)+1(3:4)+0(3:5)+0(3:6)+0(3:7)+0(4:1)+0(4:2)+0(4:3)+1(4:4)+0(4:5)+0(4:6)+0(4:7)+0(5:1)+0(5:2)+0(5:3)+1(5:4)+0(5:5)+0(5:6)+0(5:7)+0(6:1)+0(6:2)+0(6:3)+0(6:4)+0(6:5)+0(6:6)+0(6:7)+0(7:1)+0(7:2)+0(7:3)+0(7:4)+0(7:5)+0(7:6)+0(7:7)
3 Extraction
Stripping down to the bare essentials, one obtains the following matrices of coefficients for the relations G and H.
G=[0000000000000000000000011100000000000000000000000]
H=[0000000000000000010000001000000100000000000000000]
These are the logical matrix representations of the 2-adic relations G and H.
If the 2-adic relations G and H are viewed as logical sums, then their relational composition G∘H can be regarded as a product of sums, a fact that can be indicated as follows:
G∘H=(∑ijGij(i:j))(∑ijHij(i:j)).
The composite relation G∘H is itself a 2-adic relation over the same space X, in other words, G∘H⊆X×X, and this means that G∘H must be amenable to being written as a logical sum of the following form:
G∘H=∑ij(G∘H)ij(i:j).
In this formula, (G∘H)ij is the coefficient of G∘H with respect to the elementary relation i:j.
One of the best ways to reason out what G∘H should be is to ask oneself what its coefficient (G∘H)ij should be for each of the elementary relations i:j in turn.
So let us pose the question:
(G∘H)ij=What?
In order to answer this question, it helps to realize that the indicated product given above can be written in the following equivalent form:
G∘H=(∑ikGik(i:k))(∑kjHkj(k:j)).
A moment’s thought will tell us that (G∘H)ij=1 if and only if there is an element k in X such that Gik=1 and Hkj=1.
Consequently, we have the result:
(G∘H)ij=∑kGikHkj.
This follows from the properties of logical products and sums, specifically, from the fact that the product GikHkj is 1 if and only if both Gik and Hkj are 1, and from the fact that ∑kFk is equal to 1 just in case some Fk is 1.
All that remains in order to obtain a computational formula for the relational composite G∘H of the 2-adic relations G and H is to collect the coefficients (G∘H)ij over the appropriate basis of elementary relations i:j, as i and j range through X.
G∘H=∑ij(G∘H)ij(i:j)=∑ij(∑kGikHkj)(i:j).
This is the logical analogue of matrix multiplication in linear algebra, the difference in the logical setting being that all of the operations performed on coefficients take place in a system of logical arithmetic where summation corresponds to logical disjunction and multiplication corresponds to logical conjunction.
By way of disentangling this formula, one may notice that the form ∑kGikHkj is what is usually called a scalar product. In this case it is the scalar product of the ith row of G with the jth column of H.
To make this statement more concrete, let us go back to the particular examples of G and H that we came in with:
G=[0000000000000000000000011100000000000000000000000]
H=[0000000000000000010000001000000100000000000000000]
The formula for computing G∘H says the following:
(G∘H)ij=theijthentry in the matrix representation forG∘H=the entry in theithrow and thejthcolumn ofG∘H=the scalar product of theithrow ofGwith the jthcolumn ofH=∑kGikHkj
As it happens, it is possible to make exceedingly light work of this example, since there is only one row of G and one column of H that are not all zeroes. Taking the scalar product, in a logical way, of the fourth row of G with the fourth column of H produces the sole non-zero entry for the matrix of G∘H.
G∘H=[0000000000000000000000001000000000000000000000000]
Title | matrix representation of relation composition |
Canonical name | MatrixRepresentationOfRelationComposition |
Date of creation | 2013-03-22 17:50:28 |
Last modified on | 2013-03-22 17:50:28 |
Owner | Jon Awbrey (15246) |
Last modified by | Jon Awbrey (15246) |
Numerical id | 21 |
Author | Jon Awbrey (15246) |
Entry type | Example |
Classification | msc 68R01 |
Classification | msc 68P15 |
Classification | msc 08A02 |
Classification | msc 05C65 |
Classification | msc 05B30 |
Classification | msc 05B20 |
Classification | msc 03E20 |
Classification | msc 03B10 |
Related topic | RelationTheory |
Related topic | AlgebraicRepresentationOfRelationComposition |
Related topic | GeometricRepresentationOfRelationComposition |
Related topic | GraphTheoreticRepresentationOfRelationComposition |
Related topic | LogicalMatrix |