A $q$-analogue of delta-matroids

This post is based on joint work with Michela Ceria and Trygve Jonsen.

It was already four years ago that I wrote about the q-analogue of a matroid. Over these years, there have been a lot of developments in this area. A non-exhaustive list: a lot of cryptomorphisms of q-matroids have been proven [BCJ22], the direct sum has been defined (this is less trivial than it sounds!) [CJ24], there are hints of category theory [GJ23], and the representability of q-matroids has been translated to the finite geometry problem of finding certain linear sets [AJNZ24+].

In this post, I’ll talk about the q-analogue of delta-matroids. You might remember them from this choose-your-own-adventure post from Carolyn Chun. But first, let’s develop some intuition for the q-analogue of a matroid.

In combinatorics, when we talk about a q-analogue, we mean a generalisation from sets to finite dimensional vector spaces (often over a finite field). A straightforward definition of a q-matroid can be given in terms of its rank function:

Definition. A q-matroid is a pair $(E,r)$ of a finite dimensional vector space $E$ and an integer-valued function $r$ on the subspaces of $E$ such that for all $A,B\subseteq E$:
(r1) $0\leq r(A)\leq\dim(A)$.
(r2) If $A\subseteq B$ then $r(A)\leq r(B)$.
(r3) $r(A+B)+r(A\cap B)\leq r(A)+r(B)$ (semimodularity)

Here we see that the role of the cardinality of a set is replaced by that of a dimension of a space. Inclusion and intersection are defined as one would expect, and the role of elements of a set is played by 1-dimensional subspaces in the q-analogue. The q-analogue of the union of sets is the sum of vector spaces. Here we see the first difference between the world of sets and that of spaces: where the union of sets $A$ and $B$ contains only elements that are either in $A$ or in $B$, the sum $A+B$ of vector spaces $A$ and $B$ contains a lot of 1-dimensional spaces that were in neither $A$ nor $B$. Luckily, we have semimodularity of the rank function to keep control over all these new spaces.

Lemma. Loops come in spaces.

A loop is a 1-dimensional space of rank 0. If $x$ and $y$ are loops, then by semimodularity, all 1-dimensional subspaces of $x+y$ are loops. The opposite of this result is the following.

Corollary. Independent spaces never come alone.

Suppose a q-matroid $(E,r)$ has a 1-dimensional independent space $x$. Then this q-matroid might have loops, but we know that the space $L$ containing exactly all loops (let’s call it the loop space) can have dimension at most $\dim(E)-1$, since $x$ is not a loop. But if $L$ has dimension $\dim(E)-1$, it means that all 1-dimensional spaces that are not in $L$, are independent. And there are many of them!

This reasoning motivates the definition of a q-matroid in terms of its bases [CJ24a,CJ24b]. (This definition is cryptomorphic to the one above: define a basis as a subspace such that $r(B)=r(E)$, and for the other way around, let $r(A)$ be the dimension of the biggest intersection between $A$ and a basis.)

Definition. A q-matroid is a pair $(E,\mathcal{B})$ of a finite dimensional vector space $E$ and a family $\mathcal{B}$ of subspaces of $E$ such that:
(B1) $\mathcal{B}\neq\emptyset$.
(B2) For all $B_1,B_2\in\mathcal{B}$ we have $\dim B_1=\dim B_2$.
(B3) For all $B_1,B_2\in\mathcal{B}$, and for each subspace $A$ that has codimension 1 in $B_1$ there exists $X\subseteq E$ of codimension 1 in $E$ such that $X \supseteq A$, $X\not \supseteq B_2$ and $A+x \in \mathcal{B}$ for all 1-dimensional $x\subseteq E$, $x\not\subseteq X$.

(B1) and (B2) should not surprise you, but (B3) looks at first sight rather different from its classical counterpart. But let us translate the classical axiom a bit. We start with a basis and remove an element from it. This is the same as saying we take a subset of $B_1$ of size $|B_1|-1$. Then, we add an element from a basis $B_2$ that is not in $B_1$. In a convoluted way, this can be seen as first taking a subset $X$ of $E$ of size $n-1$ that does not contain $B_2$, and then adding the complement of $X$ in $E$ to $B_1$. However, this convoluted view does give us a statement of which the q-analogue is exactly (B3) above. Note as well that (B3) produces a lot of new bases, not just one: this is due to the fact that independent spaces never come alone.

Let us now move to delta-matroids. The definition we are going to use to make a q-analogue, is the following.

Definition. A delta-matroid is a pair $(E,\mathcal{F})$ of a finite set $E$ and a nonempty family $\mathcal{F}$ of subsets of $E$ such that for all $X,Y\in\mathcal{F}$ and for all $x\in X\triangle Y$ there is a $y\in X\triangle Y$ such that $X\triangle\{x,y\}\in\mathcal{F}$.

This definition makes use of the symmetric difference and unfortunately, we have no clue how a well-defined q-analogue of the symmetric difference looks like. (Ideas are welcome!) However, we can split this definition in four cases, depending on whether $x$ and $y$ are in $X-Y$ or in $Y-X$.

We can now make a q-analogue of a delta-matroid by treating all these four cases separately [CJJ24+].

Definition. A q-delta-matroid is a pair $(E,\mathcal{F})$ of a finite space $E$ and a nonempty family $\mathcal{F}$ of subsets of $E$ such that:
(F1) For every two subspaces $X$ and $Y$ in $\mathcal{F}$, and for each subspace $A\subseteq E$ that has codimension 1 in $X$, there either exists:
    (i) a codimension 1 space $Z \subseteq E$ with $A \subseteq Z$ and $Y\not\subseteq Z$, such that for all 1-dimensional $z\subseteq E$, $z\not\subseteq Z$ it holds that $A+z\in \mathcal{F}$; or
    (ii) a codimension 1 space $Z\subseteq E$ such that $Z \cap A \in \mathcal{F}$.
(F2) For every two subspaces $X$ and $Y$ in $\mathcal{F}$, and for each subspace $A\subseteq E$ with $X$ of codimension 1 in $A$, there either exists:
    (iii) a 1-dimensional $z\subseteq E$ with $z \subseteq A$, $z\not\subseteq Y$, such that for each $Z\subseteq E$ of codimension 1, $z\not\subseteq Z$ it holds that $A \cap Z \in \mathcal{F}$; or
    (iv) a 1-dimensional $z\subseteq E$ such that $A+z \in \mathcal{F}$.

The four cases of this definition reflect the four cases in the picture above, respectively. Note also the similarity between part (i) and (iii) and the basis axiom (B3). Just as in the classical case, a q-delta-matroid can be viewed as “take a q-matroid and forget that all bases need to have the same dimension”.

Here is an example of a q-delta-matroid. One can verify that this is indeed a q-delta-matroid by checking the definition above for every combination of dimensions of feasible spaces.

Example. Let $E=\mathbb{F}^4$ and $\mathcal{S}$ a spread of 2-spaces in $E$. (That is: a family of trivially intersecting 2-spaces such that every element of $E$ is in exactly one member of the spread.) Let $\mathcal{F}=\mathcal{S}\cup\{0,E\}$. Then $(E,\mathcal{F})$ is a q-delta-matroid.

The definition of a q-delta-matroid has some nice properties. First off: duality.

Theorem (dual q-delta-matroid). Let $(E,\mathcal{F})$ be a q-delta-matroid and let $\mathcal{F}^\perp=\{F^\perp:F\in\mathcal{F}\}$. Then $(E,\mathcal{F}^\perp)$ is a q-delta-matroid.

This statement follows immediately from the definition, since taking orthogonal complements in (F1) gives (F2) and vice versa. For delta-matroids there is also a notion of partial duality, also known as twist duality. We did not manage to find a q-analogue of this, largely due to the lack of q-analogue for the symmetric difference. Another concept that annoyingly does not have a straightforward q-analogue, is taking minors (via restriction and contraction) of q-delta-matroids. But for some positive news: we can make q-matroids from q-delta-matroids, and the other way around. The proofs of this statement are by directly checking the axioms.

Theorem (q-matroids from q-delta-matroids). Let $D=(E,\mathcal{F})$ be a q-delta-matroid. Then all feasible spaces of maximal dimension, and all feasible spaces of minimum dimension, are the families of bases of q-matroids. We call these the upper- and lower q-matroid of $D$.

Theorem (q-delta-matroids from q-matroids). The families of bases, independent spaces, and spanning spaces of a q-matroid all form the family of feasible spaces of a q-delta-matroid.

A much more involved result on q-delta-matroids has to do with strong maps. As in the classical case, a strong map between q-matroids is a linear map between their ground spaces where the inverse image of a flat is a flat. This leads to the definition of a qg-matroid:

Definition. Let $\varphi:M_1\to M_2$ be a strong map between q-matroids. Then the family of all spaces contained in a basis of $M_1$ and containing a basis of $M_2$, are the feasible spaces of a q-g-matroid.

Theorem. Every qg-matroid is a q-delta-matroid.

The inverse of this statement is not true: see the example above that is a q-delta-matroid but not a qg-matroid, since no 1-space or 3-space is a feasible space. We do see in this example that there is a strong map between the upper q-matroid, which is $U_{4,4}$, and the lower q-matroid $U_{0,4}$. We expect this to hold in general.

Conjecture. There is a strong map between the upper- and lower q-matroid of a q-delta-matroid.

This statement was proven in the classical case via the theory of multimatroids, a concept that does not seem to have a clear q-analogue (yet). We have some hope that the birank of a q-delta-matroid (of which I’ll skip the definition) might help with this goal.

Of course, our dream is to make a q-analogue of every equivalent definition of delta-matroids. That will not be easy, because it is at the moment pie in the sky to consider a q-analogue of ribbon graphs, or embeddings of graphs — we don’t even understand yet what the q-analogue of a graph is! However, there are several more direct questions, as mentioned along the way in this post, that are waiting for interested researchers to tackle them.

References

[AJNZ24+] Gianira N. Alfarano, Relinde Jurrius, Alessandro Neri, Ferdinando Zullo, Representability of the direct sum of uniform q-matroids (2024). Preprint, arXiv:2408.00630.

[BCJ22] Eimear Byrne, Michela Ceria, Relinde Jurrius, Constructions of new q-cryptomorphisms, Journal of Combinatorial Theory, Series B, 153 (2022), pp. 149–194.

[CJ24] Michela Ceria, Relinde Jurrius, The direct sum of q-matroids. Journal of Algebraic Combinatorics, 59 (2024), pp. 291–330.

[CJ24a] Michela Ceria, Relinde Jurrius, Alternatives for the q-matroid axioms of independent spaces, bases, and spanning spaces, Advances in Applied Mathematics, 153 (2024), 102632.

[CJ24b] Michela Ceria, Relinde Jurrius, Corrigendum to Alternatives for the $q$-matroid axioms of independent spaces, bases, and spanning spaces [Adv. Appl. Math. 153 (2024) 102632] Advances in Applied Mathematics 158 (2024), 102708.

[CJJ24+] Michela Ceria, Relinde Jurrius, Trygve Johnsen, A q-analogue of $\Delta$-matroids and related concepts (2024). Preprint, arXiv:2406.14944.

[GJ23] Heide Gluesing-Luerssen, Benjamin Jany, Coproducts in categories of q-matroids, European Journal of Combinatorics, 112 (2023), 103733.

List-colouring matroid intersections

Colouring and list-colouring

Staying close in theme to last month’s post, this month I’m writing about decomposing matroids into independent sets.

The colouring number (or covering number), $\text{col}(M)$ of a matroid $M$ is defined as the smallest $t$ for which the ground set of $M$ can be partitioned into $t$ independent sets. I’ve written before about how I like the term colouring number since it highlights the analogy with the chromatic number of graphs (which is the smallest number of vertex-independent sets in which the graph can be partitioned). For this blog post, though, it is more illuminating to compare the colouring number to the edge-chromatic number of a graph.

The chromatic number for graphs has many variations that are studied for their own sake, such as the list-chromatic number. Similarly, there is a list-colouring version of the colouring number, which is defined as follows.

Definition. Let $M$ be a loopless matroid, and suppose that for each element $e$ of $M$ we are given a list $L(e)$ of colours available to element $e$. An $L$-colouring of $M$ is a function $c$ that maps each element $e$ of $M$ to an element of $L(e)$, with the additional property that $c^{-1}(i)$ is an independent set of $M$ for all $i \in \bigcup_{e} L(e)$. The matroid $M$ is $k$-list-colourable if it has an $L$-colouring whenever $|L(e)| \ge k$ for each $e$. We write $\text{col}_\ell(M)$ for the smallest $k$ such that $M$ is $k$-list-colourable.

When $L(e) = \{1,2,\ldots,k\}$ for each $e$, $L$-colouring corresponds to colouring the matroid with $k$ colours. This implies that $\text{col}_\ell(M) \ge \text{col}(M)$. For graphs the gap between chromatic number and list-chromatic number can be arbitrarily large. Surprisingly, the colouring and list-colouring numbers for matroids are equal, as shown by Seymour (using an application of matroid union!).

Theorem (Seymour). $\text{col}_\ell(M) = \text{col}(M)$ for all loopless matroids $M$.

It is clear from this theorem that nothing is to be gained by considering the list-colouring problem for matroids instead of the colouring problem.

However, it is not known if an analogue of Seymour’s result holds for matroid intersections. Let $M_1$ and $M_2$ be two matroids on a common ground set $E$. The colouring number $\text{col}(M_1 \wedge M_2)$ is the smallest $t$ for which $E$ can be partitioned into $k$ sets that are independent in both $M_1$ and $M_2$ (here, $M_1 \wedge m_2$ refers to the matroid intersection of $M_1$ and $M_2$). The list-colouring number for $\chi_\ell(M_1 \wedge M_2)$ is similarly obtained as a generalisation of the list-colouring number for matroids.

As in the case of (list-)colouring matroids, a straightforward argument shows that $\text{col}_\ell(M_1 \wedge M_2) \ge \text{col}(M_1 \wedge M_2)$, but it is not known if equality holds for all matroid intersections.

1-partition matroids and Galvin’s theorem

A 1-partition matroid is a matroid whose ground set can be partitioned into subsets such that the independent sets of the matroid contain at most one element from each of the subsets. In other words, a loopless matroid $M$ is a 1-partition matroid if and only if it is the direct sum of $r(M)$ parallel classes.

Such matroids arise naturally in matching theory. A bipartite graph $G$ with bipartition $L \cup R$ comes with two 1-partition matroids on $E$: one in which the parallel classes are formed by the edges incident with each of the vertices in $L$, and one whose parallel classes similarly correspond to the vertices in $R$. In fact, the matchings of $G$ are precisely the common independent sets of these two matroids.

Galvin showed that the list-edge-chromatic number and the edge-chromatic number of bipartite graphs coincide, which is equivalent to the following result.

Theorem (Galvin). $\text{col}_\ell(M_1 \wedge M_2) = \text{col}(M_1 \wedge M_2)$ for all loopless 1-partition matroids.

It is natural to ask if the conclusion of the theorem still holds when the 1-partition matroids are replaced by matroids that are the direct sum of uniform matroids whose rank may be larger than 1 (such matroids are called partition matroids). It turns out that the answer is ‘yes’, a result that was proved only a few months ago by Guo.

Theorem (Guo). $\text{col}_\ell(M_1 \wedge M_2) = \text{col}(M_1 \wedge M_2)$ for all loopless partition matroids.

When is $\text{col}_\ell(M_1 \wedge M_2) = \text{col}(M_1 \wedge M_2)$?

In light of Seymour’s theorem for the list-colouring number of matroids and the above results by Galvin and Guo, it is tempting to ask whether the list-colouring number is always equal to the colouring number for matroid intersections – as Király did.

Question (Király). Is it always true that $\text{col}_\ell(M_1 \wedge M_2) = \text{col}(M_1 \wedge M_2)$?

Very little appears to be known about this problem, with the exception of the results by Galvin and Guo and the following result by Király and Pap.

Theorem (Király and Pap). $\text{col}_\ell(M_1 \wedge M_2) = \text{col}(M_1 \wedge M_2)$ in each of the following cases:

  • $M_1$ and $M_2$ are both transversal matroids; or
  • $M_1$ is the graphic matroid and $M_2$ is the 1-partition matroid whose parts are formed by the in-stars of the graph that is the union of two arborescences with the same root; or
  • $M_1$ and $M_2$ both have rank 2.

(The third case of of their result actually extends to the situation where $M_1$ is a rank-2 matroid and $M_2$ is an arbitrary matroid.)

As a step towards resolution of Király’s question, the following problem may be more accessible:

Question. Is it true that $\text{col}_\ell(M_1 \wedge M_2) = \text{col}(M_1 \wedge M_2)$ for all loopless rank-3 matroids $M_1$ and $M_2$?

Partitioning infinite matroids into circuits

Although this post is part of the ongoing series on infinite matroids, it begins with an old result about graphs. Suppose that you have a graph $G$, and you want to know whether you can partition it into an edge-disjoint union of cycles. If $G$ is finite then there is a straightforward necessary and sufficient condition for this; every vertex of $G$ should have even degree. Necessity is obvious, and to see sufficiency note that as long as $G$ has any edges it cannot be a tree so it must contain some cycle; after deleting the edges of that cycle, every vertex still has even degree and so we can keep doing the same again until we have exhausted all the edges of the graph. 

What if $G$ is infinite? In that case it is no longer sufficient that all degrees are even. Indeed, consider the two-way infinite ray; every vertex has degree 2, but there isn’t even a single cycle. So we need a stronger condition. Rather than considering individual vertices, we should consider cuts. Since any cycle meets any cut in an even number of edges, if $G$ is an edge-disjoint union of cycles then every cut of $G$ must be a disjoint union of finite sets of even size, so must itself be even or infinite. In 1960, Nash-Williams showed that this condition is sufficient [3].

Theorem 1: Let $G$ be any graph. Then $G$ is an edge-disjoint union of cycles if and only if $G$ has no finite cuts of odd size.

In this post we will examine various generalisations of this result, as well as some of the basic ideas used to prove them, and we will finish up by looking at some intriguing open problems which remain. However, we will not look at Nash-Williams’ original proof, since that was long and technical, and over the years more efficient proofs have emerged (see for example [4],[5]).

Roughly speaking, the modern proofs work in the following way. We want to prove the result by induction on the cardinality of $G$. As the base case, we suppose that $G$ is countable. In this case, we can use an argument like the one above to recursively pick a sequence of edge-disjoint cycles $C_1, C_2,\ldots$ covering all edges of $G$.

For the induction step, we want to break $G$ up into strictly smaller edge-disjoint subgraphs of smaller cardinality, which we will use to cover larger and larger chunks of $G$. We will make sure that each of these subgraphs $H$ has the following properties:

  1. Any finite cut of $H$ is also a cut of $G$
  2. Any finite cut of $G – E(H)$ is also a cut of $G$

The first of these properties is obviously useful, since it ensures in particular that $H$ has no finite odd cuts, so that we can apply the induction hypothesis to it. It is also easy to extend any infinite subgraph $X$ of $G$ to a subgraph $H$ of the same cardinality satisfying (1), by repeatedly taking each finite cut of $X$ which isn’t a cut of $G$ and either adding all edges of the corresponding cut of $G$ (if that cut is finite) or infinitely many edges of the corresponding cut of $G$ (if that cut is infinite). So by closing under this operation we can easily extend any subgraph of $G$ to one satisfying (1).

The second property is used in a recursive construction of our partition of $G$ into subgraphs, to ensure that after we have taken $H$ as a partition class we still have no odd-sized cuts in the remainder and so we can continue finding more partition classes in the same way. Rather surprisingly, there is another operation, akin to that in the previous paragraph but more technical, such that by closing under that operation we can turn any subgraph of $G$ into another of the same cardinality satisfying (2). Even more surprisingly, the exact details of that operation need not be specified for the proof. 

Why not? There is a very useful trick, often applicable in such situations, called the Elementary Submodel Method. It allows us to define a kind of universal closure operation, which when applied to a subgraph closes it under almost anything we might have wanted. That seems miraculous. How could it possibly work? The idea is to make use of a result from logic called the Löwenheim-Skolem Theorem, which states that if we have some theory expressed using first-order logic, some model $M$ of that theory and some infinite subset $X$ of $M$ then we can find a submodel $N$ of $M$ including $X$ and of the same cardinality as $X$, such that any first order statement which holds (in $N$) for some elements of $N$ still holds for those same elements in $M$. $N$ is then called an elementary submodel of $M$. 

A first idea about how to apply this might be to take $M$ to be the graph $G$, considered as a model of the theory of graphs, and define $H$ to be the subgraph corresponding to $N$. Then for any construction we can express in the language of graphs, $H$ will be closed as a subgraph of $G$ under that construction. This is already fairly powerful, but unfortunately the operations under which we want to close subgraphs are often too complicated to be expressible using first-order logic in the language of graphs. So we need a more powerful idea.

What we do instead is to take $M$ to be the whole set-theoretic mathematical universe (considered as a model of the axioms of set theory). Given an infinite subgraph $X$ of $G$ we can now find an elementary submodel $N$ of $M$ including $X$ and containing $G$. If we define $H$ to be the intersection of $N$ with $G$ then it will really be closed under any operation we might think of. Any readers who are logicians might now be worried about whether it is really ok to step outside the set-theoretic universe and treat that whole universe as a mathematical object in this way. Would it then be contained in itself? This is a valid worry, but it can be circumvented by instead taking $M$ to be a large enough fragment of the set-theoretic universe, rather than the whole thing. 

For those reading about the Elementary Submodel Method for the first time, I understand that it can be a little mind-blowing the first time you see it. I remember that it took me a while to wrap my head around it. For the purposes of this post, all you need to remember is that it gives you a kind of universal closure operation, which (with a little more work) lets us push through the proof outlined above.

However, if at some point in life you find yourself working with some recursive construction where you would like to close some infinite graphs (or indeed matroids) under some very technical operations, and perhaps it isn’t easy to see exactly what those operations should be, do consider whether the Elementary Submodel Method might be a helpful tool for you. A good introduction can be found in [4].

What we want to focus on for now is how the same method allows us to extend Nash-Williams’ results to infinite matroids. The obvious question to ask is when we can express the ground set of a matroid as a disjoint union of circuits. In the discussion above, we relied on the fact that every cycle in a graph meets every cut in an even number of edges. The corresponding property in the language of matroids would be that every circuit-cocircuit intersection is even, or to put it another way, that the matroids we are working with are binary. And indeed we do get a corresponding result for infinite binary matroids, with a very similar proof:

Theorem 2: Let $M$ be a finitary binary matroid such that no finite cocircuit of $M$ has odd size. Then the ground set of $M$ is a disjoint union of circuits.

Note that this theorem is only for finitary matroids, which means that all circuits are finite, not for infinite matroids in general. We will return to this point later. However, it turns out that the theorem above can be generalised slightly beyond binary matroids. It turns out that what we need to do is to make precise exactly what it is that is used about circuits in binary matroids for the base case of an argument of the kind outlined above. 

Remember that the base case was that in which $M$ is countable. Our plan there was to recursively define a sequence of disjoint circuits $C_1, C_2, \ldots$ covering the ground set. To define $C_n$, we need that even after we have deleted the circuits $C_1, \ldots, C_{n-1}$ there is still at least one more circuit to choose as $C_n$. To ensure that we ultimately cover the whole ground set, we also need that we can choose this new circuit to contain our favourite edge $e$ of $M$. We can formalise all of this as follows:

Definition: A matroid $M$ is finite matching extendable if for any finite list $C_1, \ldots C_{n-1}$ of disjoint circuits of $M$ and any edge $e$ of $M$ not in any $C_i$ there is some circuit $C_n$ of $M$ containing $e$ and disjoint from all the other $C_i$.

So what we are using to prove the base case in our argument for finitary binary matroids is the fact that they are finite matching extendable. Komjáth, Milner and Polat showed [2] that this property also suffices for the general case.

Theorem 3: Let $M$ be any finitary matroid which is finite matching extendable. Then the ground set of $M$ is a disjoint union of circuits.

Once again, Komjáth, Milner and Polat’s proof was tricky and technical. However, using the Elementary Submodel Method, Attila Joó and I were able to give a much shorter alternative proof. 

Instead of generalising Theorem 1 to matroids, a natural question to ask is what happens for directed graphs. More precisely, a natural question to ask in this context is which directed graphs can be expressed as a disjoint union of directed cycles. After a little thought, it is clear that the following statement is the analog of Theorem 1 for directed graphs:

Theorem 4: Let $D$ be any directed graph such that every for every cut $K$ of $D$ the sets of edges crossing $K$ in each direction have the same cardinality. Then $D$ is a disjoint union of directed cycles. 

The history of this statement is a little peculiar. After proving Theorem 1 in 1960, Nash-Williams claimed that his methods could also be extended to give Theorem 4. However, he did not explain how to do so, and over the decades nobody else was able to reconstruct such a proof. Finally, in 2017 Thomassen gave Theorem 4 as a conjecture in [5], and a few years later this conjecture was finally proved by Attila Joó [1] using the Elementary Submodel Method.

Since we could generalise Theorem 1 to matroids, it is natural to ask whether we can also generalise Theorem 4 to matroids. And indeed we can, namely to regular matroids. To understand the statement, we need to understand what the analog of a directed cycle in a regular matroid might be. A quick way to express the concept we need is by using an alternative characterisation of regular matroids due to White [6].

Definition: A signing of a matroid $M$ consists of a choice, for each circuit $C$ of $M$, of a function $f_C \colon C \to \{-1, 1\}$ and a choice, for each cocircuit $D$ of $M$, of a function $g_D \colon D \to \{-1, 1\}$, such that for any circuit $C$ and cocircuit $D$ we have $$\sum_{e \in C \cap D} f_C(e)g_D(e) = 0\,.$$ A signed matroid is a matroid together with a signing of that matroid.

Fact: A matroid $M$ is regular if and only if it has a signing.

For example we can find a signing of the matroid associated to any graph $G$ by directing the edges of $G$ arbitrarily, defining each $f_C$ to be 1 on the edges directed in one sense around $C$ and -1 for the edges directed in the opposite sense, and defining each $g_D$ to be 1 on the edges crosssing $D$ in one direction and -1 on the edges crossing $D$ in the opposite direction. The desired equation holds since each cycle crosses each cut the same number of times in each direction.

In this context, it is clear what the analog of a directed cycle should be. We say that a circuit $C$ (or cocircuit $D$) of a signed matroid is directed if $f_C$ (or $g_D$) is constant. Attila and I were able to extend Theorem 4 to regular matroids as follows:

Theorem 5: Let $M$ be a finitary signed matroid such that for any cocircuit $D$ of $M$ the sets $g_D^{-1}(-1)$ and $g_D^{-1}(1)$ have the same cardinality. Then the ground set of $M$ is a disjoint union of directed circuits. 

All of the matroidal statements we have considered here were for finitary matroids. The reason for this, however, is not that they are known to be false for infinitary matroids. Indeed, there are no known counterexamples even for general infinite matroids. I would be very interested in any ideas for how to prove or refute the corresponding statements for arbitrary infinite matroids.

However there is an even more basic statement from which the countable case of Theorem 5 quickly follows, which is also open for general infinite matroids. It is an analog of the Farkas Lemma for signed matroids. It would probably be needed for any proof of Theorem 5 for general infinite matroids. So I would be extremely interested in any ideas on how to approach this problem.

Conjecture: Let $M$ be a (possibly infinite) signed matroid and $e$ an edge of $M$. Then $e$ is either contained in a directed circuit or a directed cocircuit. 

References:

[1] Attila Joó. “On partitioning the edges of an infinite digraph into directed cycles”. In: Advances in Combinatorics 2.8 (2021)
[2] Péter Komjáth, Eric Charles Milner, and Norbert Polat. “A compactness theorem for perfect matchings in matroids”. In: Journal of Combinatorial Theory, Series B 44.3 (1988), pp. 253–262.
[3] C. St. J. A. Nash-Williams. “Decomposition of graphs into closed and endless chains”. In: Proceedings of the London Mathematical Society 3.1 (1960), pp. 221–238.
[4] Lajos Soukup. “Elementary submodels in infinite combinatorics”. In: Discrete Math- ematics 311.15 (2011), pp. 1585–1598.
[5] Carsten Thomassen. “Nash-Williams’ cycle-decomposition theorem”. In: Combina- torica 37.5 (2017), pp. 1027–1037.
[6] Neil White. Matroid applications. 40. Cambridge University Press, 1992.

Sparse representations of binary matroids

Let us call the sparsity of a binary matroid $M$ the minimum number of $1$’s in a binary matrix representation of $M$. There are many practical reasons to desire such a representation – matrices with few non-zero entries can be encoded and manipulated much more efficiently. So it would be really nice to have an algorithm which can efficiently perform row reductions in order to sparsify a binary matrix, even to within a very rough approximation of the optimal value.

Given the importance of this problem, I’m surprised that I haven’t seen more work on it from the matroid theory community. So this blog post aims to publicize the area, share some questions I have been wondering about, and ask the community for pointers to more work in this direction.

We consider classes of binary matroids which are closed under minors. For which such classes is the sparsity at most linear in the rank? Parallel edges cause silly problems, so we only consider the simple matroids in the class. If the number of elements is not linear in the rank, then neither is the sparsity. So a necessary condition is that the class forbids the cycle matroid of some clique. Is this obvious necessary condition also sufficient? Surely not, right?!

Problem 1: Is it true that for each integer $t$, there exists an integer $c=c(t)$ so that if $M$ is a simple rank-$r$ binary matroid without a minor isomorphic to the cycle matroid of a $t$-vertex clique, then $M$ has a representation with at most $c r$ many $1$’s?

Such a matroid $M$ has at most linearly many elements by the Growth Rate Theorem. Problem 1 asks if we can additionally bound the average number of $1$’s per column. This is possible for graphic classes since we can just take the incidence matrix. However, I would guess that the answer is no in general, even for matroids of bounded branch-width.

What if we only consider representations which are in reduced row echelon form? This added restriction probably makes it much harder to sparsify. For a graph $G$ from a minor-closed class, this means that we want to bound the minimum, over all spanning trees $T$, of the average length of a fundamental cycle. (For each edge $e \in E(G) \setminus E(T)$ , its fundamental cycle is the unique cycle of $T+e$.) The best candidate I have found for a graph that is not sparsifiable in this sense is a big grid.

Problem 2: Is it true that for each integer $k$, there exists an integer $n=n(k)$ so that if $T$ is any spanning tree of the $n \times n$ grid, then the average length of a fundamental cycle with respect to $T$ is at least $k$?

Pablo Blanco’s undergraduate thesis [1] at Princeton considered another notion of sparsity which is typically harder to obtain. From the matrix perspective, we want to find a matrix which is in reduced row echelon form and, additionally, avoids an all $1$’s submatrix of fixed size. He proposed a conjecture about graphs which suggests that the main obstructions are the following (planar) graph and its dual. The $k$-banana is the graph which is obtained from $k$ paths of length $k$ by identifying all of their starting vertices into one vertex $s$, and all of their ending vertices into one vertex $t$.

Let me also point out that Kristýna Pekárková has a really nice master’s thesis [2] which takes care of the bounded branch-depth case of sparsification quite nicely.

[1] Pablo Blanco, Graphs with Large Overlap in Their Spanning Trees, click here for info

[2] Kristýna Pekárková, Matroid Based Approach to Matrix Sparsification, click here for pdf