Tag Archives: configuration spaces

Metric chromatic numbers

Idle thought.  Let G be a (loopless) graph, let M be a metric space, and let b be a nonnegative real number.  Then let Conf(G,M,b) be the space of maps from the vertices of the graph to M such that no two adjacent vertices are within b of each other.

When b=0 and G is the complete graph K_n, this is the usual ordered configuration space of n points on M.  When G is the empty graph on n vertices, it’s just M^n.  When M is a set of N points with the discrete metric, Conf(G,M,b) is the same thing for every b;  a set of points whose cardinality is χ_G(N), the chromatic polynomial of G evaluated at N.  When M is a box, Conf(G,M,b) is the “discs in a box” space I blogged about here.  If M is (Z/2Z)^k with Hamming distance, you are asking about how many ways you can supply G with k 2-colorings so that no edge is monochromatic in more than k-b-1 of them.

Update:  Ian Agol links in the comments to this paper about Conf(G,M,0) by Eastwood and Huggett; the paper points out that the Euler characteristic of Conf(G,M,0) computes χ_G(N) whenever M has Euler characteristic N; so M being N points works, but so does M = CP^{N-1}, and that’s the case they study.

When b=0 and G is the complex plane, Conf(G,C,0) is the complement of the graphic arrangement of G; its Poincare polynomial is  t^-{|G|} χ_G(-1/t).  Lots of graphs have the same chromatic polynomial (e.g. all trees do) but do they have homeomorphic Conf(G,C,0)?

This is fun to think about!  Is Conf(G,M,0), for various manifolds other than discrete sets of points, an interesting invariant of a graph?

You can think of

vol(Conf(G,M,b)) vol(M)^{-n}

as a sort of analogue of the chromatic polynomial, especially when b is small; when M = C, for instance, Conf(G,M,b) is just the complement of tubular neighborhoods around the hyperplanes in the graphical arrangement, and its volume should be roughly b^|G|χ_G(1/b) I think.  When b gets big, this function deviates from the chromatic polynomial, and in particular you can ask when it hits 0.

In other words:  you could define an M-chromatic number χ(G,M) to be the smallest B such that Conf(G,M,1/B) is nonempty.  When M is a circle S^1 with circumference 1, you can check that χ(G,M) is at least the clique number of G and at most the chromatic number.  If G is a (2n+1)-cycle, the clique number is 2, the chromatic number is 3, and the S^1-chromatic number is 2+1/n, if I did this right.  Does it have anything to do with the Lovasz number, which is also wedged between clique number and chromatic number?  Relevant here:  the vector chromatic number, which is determined by χ(G,S^{v(G)-1}), and which is in fact a lower bound for the Lovasz number.





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FI-modules over Noetherian rings

New paper on the arXiv, joint with Tom Church, Benson Farb, and UW grad student Rohit Nagpal.  In our first paper on FI-modules (which I blogged about earlier this year) a crucial tool was the fact that the category of FI-modules over a field of characteristic 0 is Noetherian; that is, a submodule of a finitely generated FI-module is again finitely generated.  But we didn’t know how to prove this over a more general ring, which limited the application of some of our results.

In the new paper, we show that the category of FI-modules is Noetherian over an arbitrary Noetherian ring.  Sample consequence:  if M is a manifold and Conf^n M is the configuration space of ordered n-tuples of distinct points on M, then we show that

dim_k H_i(Conf^n M, k)

is a polynomial function of n, for all n greater than some threshold.  In our previous paper, we could prove this only when k had characteristic 0; now it works for mod p cohomology as well.  We also discuss some of the results of Andy Putman’s paper on stable cohomology of congruence subgroups — it is a bad thing that I somehow haven’t blogged about this awesome paper! — showing how, at the expense of losing stable ranges, you can remove from his results some of the restrictions on the characteristic of the coefficient field.

Philosophically, this paper makes me happy because it brings me closer to what I wanted to do in the first place — talk about the representation theory of symmetric groups “for general n” without giving names to representations.  In characteristic 0, this desire might seem a bit perverse, given the rich and beautiful story of the bijection between irreducible representations and partitions.  But in characteristic p, the representation theory of S_n is much harder to describe.  So it is pleasing to be able to talk, in a principled way, about what one might call “representation stability” in this context; I think that when V is a finitely generated FI-module over a finite field k it makes sense to say that the representations V_n of k[S_n] are “the same” for n large enough, even though I don’t have as nice a description of the isomorphism classes of such representations.





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The hardest Rush Hour position

It takes 93 moves to solve, per this paper by Collette, Raskin, and Servais.  I tried it and got nowhere.

You can think of the space of all possible configurations of vehicles as, well, a configuration space, not unlike the configuration spaces of disks in a box.  But here there is a bit less topology; the space is just a graph, with two configurations made adjacent if one can be reached from the other by making a single move.  The connected component of configuration space containing the “hardest case” shown here has 24,132 vertices.






I wonder what this graph looks like?   What does the path of the cars look like as you traverse the 93-step path; do most of the cars traverse most of their range?  How many of the possible configurations of the 13 vehicles (constrained to stay in the given rows and columns, and in the same linear order when two share a row or column) are actually contained in this component?  Maybe Matt Kahle knows.  By the way, another Matt Kahle-like fact is that among the list of the hardest configurations are some which are not so dense at all, like this one with only 9 cars.  It looks like it should be easy, but apparently it takes 83 moves to solve!


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Rush Hour, Jr.

OK, so a black toddler and a Chinese toddler stumble on an international drug-trafficking ring — no, actually, this is a game I just bought for CJ, a kid’s version of Nob Yoshigahara‘s classic game Rush Hour.  The object here is to get the small white truck to the edge of the board (the top edge, in the image here.)  The trucks in your way can’t move sideways or turn; they just go forward and back.

You play a captivating game like this and naturally you start abstracting out the underlying math problem.  Play Set enough and you can’t avoid thinking about affine capsRush Hour has more to do with the geometry of configuration spaces; it reminds me of the “disk in a box” problems that people like Persi Diaconis and Matt Kahle work on.

So here’s a question — it doesn’t capture all the features of Rush Hour, but let’s start here.  Let X be the unit square, and let c be a parameter between 0 and 1, and let N be a large integer.  Let L be the set of line segments in X which are either horizontal of the form y = i/N or vertical of the form x = i/N.  A traffic jam is a choice of a length-c interval in each of the 2N +2 line segments in L, where we require that these intervals be pairwise disjoint.  The traffic jams naturally form a topological space, which we call T(N,c).  We say an interval (x,i/n),(x+c,i/n) in a traffic jam t is trapped if no traffic jam in the connected component of t contains the interval (0,i/n),(c,i/n).

Questions: For which values of (N,c) is T(N,c) connected?  In particular, is it connected almost always once it’s nonempty?  If not, when does T(N,c) have a “giant component”?  If there’s an interesting range of parameters where T(N,c) is not connected, what proportion of intervals do we expect to be trapped?

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