Enumeration of Anti-Invariant Subspaces and Touchard’s
Formula for the Entries of the -Hermite Catalan Matrix
Amritanshu Prasad
The Institute of Mathematical Sciences, Chennai, India.
Homi Bhabha National Institute, Mumbai, India.
amri@imsc.res.in and Samrith Ram
Indraprastha Institute of Information Technology Delhi, New Delhi, India.
samrith@gmail.com
Abstract.
We express the number of anti-invariant subspaces for a linear operator on a finite vector space in terms of the number of its invariant subspaces.
When the operator is diagonalizable with distinct eigenvalues, our formula gives a finite-field interpretation for the entries of the -Hermite Catalan matrix.
We also obtain an interesting new proof of Touchard’s formula for these entries.
Let be a prime power, and let denote a finite field of order . For nonnegative integers and , let denote the -binomial coefficient, which is the number of -dimensional subspaces of . Recall that for a linear operator , a subspace is said to be -invariant if .
Definition 1.
For a linear operator , a subspace is said to be -anti-invariant if
Main Theorem.
For any , the number of -dimensional -anti-invariant subspaces of is given by
(1)
where is the number of -dimensional -invariant subspaces of .
The computation of from the similarity class of as a polynomial in is easy [13, Section 2] and has been implemented in SageMath [10]. The formula in Eq. (1) can be recast in the following form, which will be used in the proof.
(2)
Anti-invariant subspaces were introduced by Barría and Halmos [3].
A matrix is said to be -transitive if each matrix over appears as the upper left submatrix of some matrix similar to . Using the fact that is -transitive if and only if it admits an -dimensional anti-invariant subspace, they characterized -transitive matrices.
Sourour [14] determined the maximal dimension of an anti-invariant subspace.
Knüppel and Nielsen [8] defined a subspace to be -fold anti-invariant if
and determined the maximal dimension of a -fold anti-invariant subspace for a linear operator . They also showed [8, Thm. 2.1] that if denote the degrees of the invariant factors in the Smith normal form of where is the matrix with respect to some basis, then a -fold anti-invariant subspace of dimension exists if and only if .
Enumerative versions of such problems can be traced back to a paper of Bender, Coley, Robbins and Rumsey [4]. In the context of pseudorandom number generation, Niederreiter [9] made the following definition:
given , an -dimensional subspace is said to be a -splitting subspace of degree if
Niederreiter asked for the number of -dimensional -splitting subspaces of degree when the characteristic polynomial of is irreducible, unaware that the question had already been answered in [4]. The number of -splitting subspaces in this case is given by
Chen and Tseng [5] reproved this result by developing recurrence relations involving a larger class of combinatorial problems.
Their recurrence relations are independent of the matrix , and reduce the enumeration of splitting subspaces to the enumeration of flags of -invariant subspaces.
However, the recurrences are very difficult to solve in general.
Aggarwal and Ram [1] used the recurrences of Chen and Tseng to show that when is regular nilpotent, the number of -splitting subspaces of degree is given by .
For regular nilpotent , for , so (1) becomes
(3)
Setting and , we recover the formula of [1] in the case . Later, it came to light that these results in the regular nilpotent case follow from the results in [4].
Viennot’s combinatorial theory of orthogonal polynomials [16] places the moments of an orthogonal polynomial sequence in the first column of an infinite array known as the Catalan matrix. There is a connection between our main theorem and the Catalan matrix associated to the -Hermite orthogonal polynomial sequence as defined by Ismail, Stanton and Viennot [7]. This connection emerges from our work [11, 12] where a more general class of enumerative problems is considered.
Definition 2.
For a linear endomorphism and a partition of , a subspace is said to have -profile if
The number of subspaces with -profile is denoted .
When , a subspace has profile if is -dimensional, and .
Let denote the transpose of .
For a subspace , let denote its annihilator in the linear dual of .
When has profile , . Also if and only if . By using the identity
(4)
for and each subspace , it follows that
Therefore, has profile if and only if is an -dimensional -anti-invariant subspace.
Since is similar to , we have
(5)
Let denote the set consisting of the first positive integers. Denote by the set of partitions of whose block sizes are the parts of the integer partition conjugate to .
Suppose is a diagonalizable matrix with distinct eigenvalues in .
One of the main results of [12] is a combinatorial formula for in terms of a statistic on set partitions known as the interlacing number:
where , a sum is over partitions of with blocks of size and singleton blocks.
In Section 5, we show that coincides with polynomials defined recursively by Touchard [15] in the context of the stamp-folding problem.
Touchard [15, Eq. (28)] showed that
(8)
When is a diagonalizable matrix with distinct eigenvalues in , .
Substituting this into the formula (1) of our main theorem gives
(9)
Comparing the expressions in (7) and (9) gives a new, linear-algebraic proof of Touchard’s formula (8).
A road map
The proof of the main theorem consists of three parts which take up the next three sections of this article.
In the first part (Section 2) we establish the existence of a formula of the form (12) for the number of anti-invariant subspaces of a given dimension as a linear combination of the numbers of invariant subspaces, whose coefficients are independent of .
It remains to show that the coefficients of these linear combinations are as in Eq. (2).
In the second part (Section 3) we consider a family of matrices for which the number of anti-invariant subspaces is known.
Each matrix in this family gives rise to an equation in the coefficients of (12).
Theorem 6 establishes that this system of equations has a unique solution.
Thus in order to show that the coefficients are exactly the ones given in (2), it suffices to show that the identity (1) holds for each matrix in the family.
This can be be expressed as the family (17) of identities.
In the third part (Section 4) we prove the identities (17) by reducing them to Heine’s transformations for -hypergeometric functions.
The proof strategy in this article closely follows ideas in [13]; the main distinction is that the more general identity (17) needed here requires a very different approach.
The final section (Section 5) of this article is devoted to the case where is a diagonal matrix with distinct diagonal entries, and the connection to the Catalan matrix of -Hermite orthogonal polynomials.
2. Existence of a Universal Formula
In this section we prove the existence of a universal formula for the number of anti-invariant subspaces of a given dimension for an arbitrary operator . The main step is Lemma 3, which is a special case of the recurrence of Chen and Tseng [5, Lemma 2.7]. We begin by introducing some notation.
Given and sets and of subspaces of , define
For integers , we also write for the set of -dimensional subspaces of such that has dimension . The quantity is defined analogously.
For example, using identity (4), denotes the set of -dimensional -invariant subspaces, whereas denotes the set of -dimensional -anti-invariant subspaces. To explicitly specify the linear operator , we also write and .
Lemma 3.
For each and ,
Proof.
Since the collection of all -dimensional subspaces of is the disjoint union , we have
To count pairs of subspaces , first choose and then choose to be an arbitrary -dimensional subspace of It follows that
(10)
Similarly, the set of all -dimensional subspaces of equals the disjoint union . Therefore
Given , a pair belongs to if and only if is an -dimensional subspace that contains . Therefore, the number of choices for is .
Consequently,
(11)
The lemma now follows from Eqs. (10) and (11), and the fact that .
∎
Proposition 4.
Given integers , , , there exist polynomials , such that, for every prime power and every ,
Proof.
Lemma 3 expands in terms of , , and where either , or and .
The coefficients are polynomials in that are independent of .
Thus repeated application of Lemma 3 results in an expression of the stated form in finitely many steps.
∎
The following corollary shows the existence of a universal formula for the number of anti-invariant subspaces of a given dimension.
Corollary 5.
For all integers , there exist polynomials such that, for every prime power and every ,
3. Determination of Coefficients in the Universal Formula
We set up a system of linear equations which completely determine the polynomials in Corollary 5 by constructing, for each prime power , a sequence of matrices such that the following conditions are satisfied.
(1)
For each , there exists a polynomial such that for all prime powers .
(2)
The determinant of the matrix is a non-zero element of .
(3)
The identity (1) holds for for and all prime powers .
In effect, we have the following result.
Theorem 6.
For each prime power , the system of linear equations
(13)
in the variables has a solution given by
(14)
This solution is unique for sufficiently large prime powers and hence uniquely determines the polynomials for .
We now proceed with the construction of the matrices above. For each , let be any matrix in with irreducible characteristic polynomial.
For , take to be the matrix with block decomposition
where is a nonsingular matrix with irreducible characteristic polynomial.
We have
Therefore we can take
(15)
Lemma 7.
If has irreducible characteristic polynomial, then
It remains to show that the values of given by (14) are solutions to (13) for . We begin by showing that the left hand side of (13) vanishes in these cases.
Lemma 9.
For , we have .
Proof.
The -module , where acts by is of the form
Here denotes the characteristic polynomial of for .
Since none of the modules can be generated by or fewer generators, does not admit a subspace with profile .
In other words, for .
∎
In view of Lemma 9, in order to establish (13) for , it suffices to prove the identity
The proof uses techniques from the theory of -hypergeometric series, and appears in Section 4.
The non-singularity of is proved by using inequalities satisfied by the degrees of its entries.
We recall [13, Lemma 4.4].
Lemma 10.
Let be a real matrix such that whenever and ,
Then the sum attains its maximum value precisely when is the identity permutation.
Proposition 11.
For all , the determinant of the matrix is non-zero.
Therefore, for sufficiently large prime powers , .
Proof.
By Eq. (15), the first row of is the unit vector .
Therefore it suffices to show that the determinant of the submatrix is non-zero.
Let .
Since , it follows from (15) that, for ,
since
If and , then
Now Lemma 10 implies that has degree and is thus non-zero.
∎
This completes all steps in the proof of Theorem 6 except for the identity (17).
4. Reduction to Heine’s Transformations
In this section, we prove the identity (17) encountered in the proof of Theorem 6 by using a Heine transformation for -hypergeometric series.
Accordingly, define
Let denote the sum obtained in (17) by replacing by .
We need to show that .
We will show that while by expressing the sums as -hypergeometric series.
Define, as usual, the -Pochhammer symbols
For convenience, we will also use the notation
Heine (see Gasper and Rahman [6]) defined the -hypergeometric series
Lemma 12.
Let .
For all , we have
()
()
()
()
We will see that Heine’s transformation formula [6, Eq. (III.2)]
transforms into and into ; therefore (17) will follow from the lemma.
Proof of the lemma.
We will use the following identities (equation numbers refer to Gasper and Rahman [6, Appendix I])
In this section, we discuss the connection between our main theorem and Touchard’s formula for the entries of the -Hermite Catalan matrix.
An extended chord diagram is a visual representation of an involution on .
Arrange nodes labelled along the -axis.
To their right, add a node labelled .
A circular arc lying above the -axis is used to connect the elements of each -cycle of .
Each fixed point of is connected to the node .
The extended chord diagram of the involution on the set is shown below:
A crossing is a pair of arcs such that .
The extended chord diagram above has four crossings, namely , , , and .
Let denote the number of crossings of the extended chord diagram of an involution .
Let denote the set of involutions in with fixed points.
Define
(23)
If is odd then , so .
If is even, then an element of has cycles of length two.
For each non-negative integer , let denote the -integer .
Lemma 13.
We have
Proof.
Each involution can be extended to an element of by adding as a fixed point.
Furthermore, each can be extended to an element of in different ways: any one of its fixed points can be paired with .
Pairing the -th fixed point from right to left with results in new crossings.
Taken together, these choices contribute to .
Since every element of can be obtained uniquely by one of these methods, the identity of the lemma follows.
∎
known as the Touchard-Riordan formula.
The polynomials are precisely the entries of the Catalan matrix associated to the normalized -Hermite orthogonal polynomials of Ismail, Stanton and Viennot [7].
See Aigner [2, Chapter 7] for a comprehensive exposition.
The combinatorial theory of orthogonal polynomials [16] places the moments of an orthogonal polynomial sequence in the first column of a Catalan matrix: if an orthogonal polynomial sequence satisfies the three-term recurrence relation
for some and , with , the entries of the Catalan matrix are given by
The moments of the orthogonal polynomial sequence are
Lemma 13 implies that the polynomials of (23) are the entries of the Catalan matrix with and , which correspond to the combinatorial version of the -Hermite orthogonal polynomial sequence [7, Eq. (2.11)].
Thus Touchard’s polynomials are the even moments of the -Hermite orthogonal polynomial sequence (the odd moments being ).
This is well-known and plays a role in the proof of the Touchard-Riordan formula [2, Chapter 7].
Let be an diagonalizable matrix with distinct eigenvalues in .
By (5), the number of -dimensional -anti-invariant subspaces is equal to the number of subspaces with -profile , where .
The conjugate of the partition is the partition .
Set partitions with blocks of size and blocks of size can be identified with involutions on with fixed points.
The interlacing number [12, Defn. 3.3] of such a set partition reduces to the number of crossings of the extended chord diagram on the corresponding involution.
Therefore, the formula (6) can be rephrased as follows.
Theorem 14.
For all integers ,
Since all -invariant subspaces are direct sums of eigenspaces, is just the binomial coefficient .
Combining Theorem 14 with our formula (1) for gives a new proof of Touchard’s formula [15, Eq. (28)] for .
Theorem 15(Touchard’s formula).
For all integers ,
Specializing to recovers the Touchard-Riordan formula (24).
6. Acknowledgements
We are indebted to an anonymous referee for several comments and suggestions that helped improve the overall presentation of this paper. We thank Divya Aggarwal for her comments on an earlier draft of this manuscript.
We thank Michael Schlosser for suggesting the method used in the proof of the main identity (17).
The second author was partially supported by a MATRICS grant MTR/2017/000794 awarded by the Science and Engineering Research Board and an Indo-Russian project DST/INT/RUS/RSF/P41/2021.
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