combinatorial representations
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Combinatorial representations Peter J. Cameron December 2011 Joint - PowerPoint PPT Presentation

Combinatorial representations Peter J. Cameron December 2011 Joint work with Max Gadouleau and Sren Riis see arXiv 1109.1216 Matroids As we have heard several times in the last week or so, a matroid is a structure for describing the linear


  1. Combinatorial representations Peter J. Cameron December 2011 Joint work with Max Gadouleau and Søren Riis see arXiv 1109.1216

  2. Matroids As we have heard several times in the last week or so, a matroid is a structure for describing the linear independence and dependence of sets of vectors in a vector space.

  3. Matroids As we have heard several times in the last week or so, a matroid is a structure for describing the linear independence and dependence of sets of vectors in a vector space. Think of the elements of a matroid as being a family ( v i : i ∈ E ) of vectors in a vector space V . (It is a family rather than a set since we don’t mind if vectors are repeated.)

  4. Matroids As we have heard several times in the last week or so, a matroid is a structure for describing the linear independence and dependence of sets of vectors in a vector space. Think of the elements of a matroid as being a family ( v i : i ∈ E ) of vectors in a vector space V . (It is a family rather than a set since we don’t mind if vectors are repeated.) A matroid can be described in many different ways: by the independent sets, the bases, the minimal dependent sets, the rank function . . .

  5. Matroid representations I will present a matroid by means of its bases.

  6. Matroid representations I will present a matroid by means of its bases. Let E be the ground set and B the family of bases of a matroid M of rank r . A vector representation of M is an assignment of a vector v i ∈ F r to each i ∈ E , such that, for i 1 , . . . , i r ∈ E , ( v i 1 , . . . , v i r ) is a basis for F r ⇔ { i 1 , . . . , i r } ∈ B .

  7. . . . in dual form Now regard the representing vectors v 1 , . . . , v r as lying in the dual space of F r . To emphasise this I will write f i instead of v i ; thus f i is a function from F r to F .

  8. . . . in dual form Now regard the representing vectors v 1 , . . . , v r as lying in the dual space of F r . To emphasise this I will write f i instead of v i ; thus f i is a function from F r to F . Notation: if f i 1 , . . . , f i r : F r → F , then we regard the r -tuple ( f i 1 , . . . , f i r ) as being a function from F r to F r .

  9. . . . in dual form Now regard the representing vectors v 1 , . . . , v r as lying in the dual space of F r . To emphasise this I will write f i instead of v i ; thus f i is a function from F r to F . Notation: if f i 1 , . . . , f i r : F r → F , then we regard the r -tuple ( f i 1 , . . . , f i r ) as being a function from F r to F r . Now a vector representation of the matroid M is an assignment of a linear map f i : F r → F to each i ∈ E , so that ( f i 1 , . . . , f i r ) : F r → F r is a bijection ⇔ { i 1 , . . . , i r } ∈ B .

  10. . . . generalised Let B be any family of r -subsets of a ground set E , and let A be an alphabet of size q . A combinatorial representation of ( E , B ) over A is an assignment of a function f i : A r → A to each point i ∈ E so that ( f i 1 , . . . , f i r ) : A r → A r is a bijection ⇔ { i 1 , . . . , i r } ∈ B .

  11. . . . generalised Let B be any family of r -subsets of a ground set E , and let A be an alphabet of size q . A combinatorial representation of ( E , B ) over A is an assignment of a function f i : A r → A to each point i ∈ E so that ( f i 1 , . . . , f i r ) : A r → A r is a bijection ⇔ { i 1 , . . . , i r } ∈ B . Thus any vector representation of a matroid, dualised, is a combinatorial representation.

  12. . . . generalised Let B be any family of r -subsets of a ground set E , and let A be an alphabet of size q . A combinatorial representation of ( E , B ) over A is an assignment of a function f i : A r → A to each point i ∈ E so that ( f i 1 , . . . , f i r ) : A r → A r is a bijection ⇔ { i 1 , . . . , i r } ∈ B . Thus any vector representation of a matroid, dualised, is a combinatorial representation. If X = { i 1 , . . . , i r } , we denote ( f i 1 , . . . , f i r ) by f X .

  13. An example Let n = 4 and B = {{ 1, 2 } , { 3, 4 }} . A combinatorial representation over a 3-element set { a , b , c } is given by taking f 1 and f 2 to be the two coordinate functions (that is, f 1 ( x , y ) = x and f 2 ( x , y ) = y ), and f 3 and f 4 by the tables b a a b b c b c b and a c c . c c a a b a Note that ( E , B ) is not a matroid.

  14. A normalisation Suppose that b = { i 1 , . . . , i r } ∈ B . Define functions g i , for i ∈ E , by g i ( x 1 , . . . , x r ) = f i ( y 1 , . . . , y r ) , where ( y 1 , . . . , y r ) is the inverse image of ( x 1 , . . . , x r ) under the bijection f b . These functions also define a combinatorial representation, with the property that g i j is the j th coordinate function. So, where necessary, we may suppose that the first r elements of E form a basis and the first r functions are the coordinate functions. This transformation can be viewed as a change of variables.

  15. Linear representations Before going to the general case, we observe the following:

  16. Linear representations Before going to the general case, we observe the following: Theorem A set family has a combinatorial representation by linear functions over a field F if and only if it consists of the bases of a matroid (representable over F).

  17. Linear representations Before going to the general case, we observe the following: Theorem A set family has a combinatorial representation by linear functions over a field F if and only if it consists of the bases of a matroid (representable over F). Proof. We verify the exchange axiom. Let B 1 , B 2 ∈ B ; we may assume that the elements of B 1 are the coordinate functions. Now consider the r − 1 functions f i for i ∈ B 2 , i � = k , for some fixed k ∈ B 2 . These define a surjective function from F r to F r − 1 . Take any non-zero vector in the kernel, and suppose that its l th coordinate is non-zero. Then it is readily checked that the functions with indices in B 2 \ { k } ∪ { l } give a bijection from F r to F r ; so this set is a basis.

  18. Which families are representable? After the last result, the answer is a bit surprising:

  19. Which families are representable? After the last result, the answer is a bit surprising: Theorem Every uniform set family has a combinatorial representation over some alphabet.

  20. Which families are representable? After the last result, the answer is a bit surprising: Theorem Every uniform set family has a combinatorial representation over some alphabet. This depends on the following result:

  21. Which families are representable? After the last result, the answer is a bit surprising: Theorem Every uniform set family has a combinatorial representation over some alphabet. This depends on the following result: Theorem Let ( E , B 1 ) and ( E , B 2 ) be families of r-sets, which have representations over alphabets of cardinalities q 1 and q 2 respectively. Then ( E , B 1 ∩ B 2 ) has a representation over an alphabet of size q 1 q 2 .

  22. Now, to prove the theorem, we observe that �� E � � � B = \ { C } r C / ∈B so it is enough to represent the family consisting of all but one of the r -sets; and it is straightforward to show that this family is indeed a representable matroid.

  23. Now, to prove the theorem, we observe that �� E � � � B = \ { C } r C / ∈B so it is enough to represent the family consisting of all but one of the r -sets; and it is straightforward to show that this family is indeed a representable matroid. Note that our proof shows that in fact every set family has a representation by “matrix functions”. More on this later.

  24. Now, to prove the theorem, we observe that �� E � � � B = \ { C } r C / ∈B so it is enough to represent the family consisting of all but one of the r -sets; and it is straightforward to show that this family is indeed a representable matroid. Note that our proof shows that in fact every set family has a representation by “matrix functions”. More on this later. Question Given a set family, what are the cardinalities of alphabets over which it has a combinatorial representation?

  25. Graphs In the case r = 2, our family is just the edge set of a graph.

  26. Graphs In the case r = 2, our family is just the edge set of a graph. Theorem A graph is representable over all sufficiently large alphabets.

  27. Graphs In the case r = 2, our family is just the edge set of a graph. Theorem A graph is representable over all sufficiently large alphabets. As a warm-up, let us consider the complete graph. It is readily checked from the definitions that a representation of K n over an alphabet of size q is the same thing as a set of n − 2 mutually orthogonal Latin squares of order q ; these are known to exist for all sufficiently large q .

  28. Pairwise balanced designs A pairwise balanced design, or PBD, consists of a set X and a collection L of subsets of X (each of size greater than 1) such that every two points of X are contained in a unique “line” in L . If the line sizes all belong to the set K of positive integers, we call it a PBD ( K ) .

  29. Pairwise balanced designs A pairwise balanced design, or PBD, consists of a set X and a collection L of subsets of X (each of size greater than 1) such that every two points of X are contained in a unique “line” in L . If the line sizes all belong to the set K of positive integers, we call it a PBD ( K ) . A set K of positive integers is PBD-closed if, whenever there exists a PBD ( K ) on a set of size v , then v ∈ K .

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