Jeremy Kahn kindly sent me a more detailed overview of his argument with Vlad Markovic, that I blogged earlier about here (also see Jesse Johnson’s blog for other commentary). With his permission, this is reproduced below in its entirety.

Editorial note: I have latexified Jeremy’s email; hence “dhat-mu” becomes \hat{d}\mu, “boundary-hat” becomes \hat{d}, and “boundary-tilde” becomes \tilde{d}. I also linkified the link to Caroline Series’ paper.

 


Hi Danny,

 

I was busy with the conference on Thursday and Friday, and taking a break on Saturday, and now I’ve finally had a chance to read your blog, and reply to your message. I decided (especially as Jesse had requested it) to write out a complete outline of the theorem. I’m sending a copy of this message to you, Jesse Johnson, Ian Agol, and Francois Labourie: you are all welcome to reproduce it, as long as it is reproduced in its entirety, and states clearly that this is joint work with Vladimir Markovic. Of course, time and energy permitting, I’ll be happy to answer any questions.

Here is an outline of the argument, working backwards to make it clearer:

1. We want to construct a surface made out of skew pants, each of which has complex half-length close to R, and which are joined together so that the complex twist-bends are within o(1/R) of 1. Using a paper of Caroline
Series (published in the Pacific J. of Mathematics) we show that these surfaces are quasi-isometrically embedded in the universal cover of the three-manifold.

2. Consider the following two conditions on two Borel measures \mu and \nu on a metric space X with the same (finite) total measure:

A. For every Borel subset A of X, \mu(A) is less than or equal to the \nu-measure of an \epsilon neighborhood of A.

B. There is a measure space (Y, \eta) and functions f: Y \to X and g: Y \to X such that \mu and \nu are the push-forwards by f and g respectively of the measure \eta, and the distance in X between f(y) and g(y) is less than \epsilon for almost every y \in Y.

It is easy to show that B implies A (also that A is symmetric in \mu and \nu!). In the case where \mu and \nu are discrete and integral measures (the measure of every point is a non-negative integer), we can show that A implies B (and Y will be a finite set with the counting measure) using Hall’s marriage theorem. In fact, the statement that A implies B for discrete and integral measures is easily shown to be equivalent to Hall’s marriage theorem. I don’t know if A implies B in general because I don’t know how to replace the inductive algorithm for Hall’s marriage theorem with a method that works for a relation between two general measure spaces.

We call \mu and \nu \epsilon-equivalent if they satisfy condition A, and note that the condition is additively transitive: if \mu is \epsilon-equivalent to \nu, and \nu is \delta-equivalent to \rho, then \mu and \rho are (\epsilon+\delta)-equivalent.

3. Suppose that \gamma is one boundary component of a pair of skew pants P. We can form the common orthogonals in P from \gamma to each of other other two cuffs. For each common orthogonal, at the point where it meets \gamma, we can find a unit normal vector to \gamma that points along this common orthogonal. The two resulting normal vectors are related by a translation along the half-length of \gamma (the suitable square root of the loxodromic element for \gamma), so we will call them a pair of opposite unit normal vectors (or pounv for short) and they live in the live in the bundle of pounv’s which is conformally equivalent to the complex plane mod the lattice generated by the half-length of \gamma and 2\pi i. We give the bundle of pounv’s the Euclidean metric inherited from the complex plane, and also the Lebesgue measure.

4. Given a measure on pants we can produce a measure on the union pounv bundles of the boundary geodesics as follows: if the measure is a unit atom on one pair of skew pants, the resulting measure on pounv bundles is a unit atom on the pounv bundle of each the cuffs, at the pounv described in step 3. We extend to a general measure by linearity. This produces a linear operator we will call the \hat{d} operator.

If we are given a positive integral formal sum of pants (or a multi-set of pants) we can think of it as an integral measure on the space of pants.

5. On the pounv bundle for each closed geodesic we can apply a translation of 1 + i \pi; we will call this translation \tau. We can think of \tau as a map from the union of the pounv bundles to itself.

6. Let \mu be an integral measure on pants with cuff half-lengths close to R. We can apply the \hat{d} operator described in step 4 to obtain a measure on the union of pounv bundles of all the boundary geodesics; we will call the measure \hat{d}\mu. If \hat{d}\mu and the translation of \hat{d}\mu by \tau are \epsilon/R equivalent, then we can take two oriented pants for each pair of pants in our multi-set (taking each of the two possible orientations) and then fit all of these oriented pants into an oriented surface of the type described in step 1. We use Hall’s marriage theorem as described in step 2, and a very small amount of combinatorics.

If the measure \hat{d}\mu, restricted to a given pounv bundle, is \epsilon/R equivalent to a rescaling of Lebesgue measure on that torus, then \hat{d}\mu and \tau of \hat{d}\mu are 2\epsilon/R-equivalent, which is what we wanted.

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This is as far as I got in the first talk at Utah, so it would be best to stop and take a breath for a moment. We haven’t really done anything, but we’ve reformulated the problem: the type of surface we want has been well-defined, and the problem of finding this surface has been reformulated as finding a measure on pairs of pants that satisfies a given criterion.

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7. A two-frame for M will comprise a tangent vector and a normal vector both at the same point, unit length and orthogonal. Given a two-frame we can rotate the tangent vector 120 degrees around the normal vector, using the right-hand rule; the orbit of this action is an ordered triple of two-frames, which will call a tripod. We can also rotate 120 degrees in the opposite direction, and obtain an anti-tripod.

8. A connected pair of two-frames is a pair of two frames along with a geodesic segment connecting them. Given \epsilon and r, with r large in terms of \epsilon, we can find a weighting function on connected two-frames such that the following properties hold whenever the weight is non-zero:

A. The length of the connecting segment is within \epsilon of r.

B. If the normal vector of one two-frame is parallel translated along the connecting segment, then it forms an angle of less then \epsilon with the normal vector of the other two-frame.

C. The angle between the the tangent vector of the two frame and (the tangent vector to) the connecting geodesic segment is exponentially small in r.

Moreover,

D. Given a pair of two-frames, the sum of the weights of the connecting geodesic segments is exponentially close (in r) to 1.

E. The weighting is geometrically natural, in that it depends only the length of the connecting segment, the angle between the parallel translated normal vectors, and the angles between the connecting segment and the tangent vectors.

We will describe the (relatively simple) weighting function in the end; we will use the exponential mixing of geodesic flow to obtain property D.

9. Given a tripod and an anti-tripod, we can form three pairs of two-frames by pairing the frames in order, and then we can measures (or weightings) on the connected pairs of two-frames, and then form the product measure (or weighting) by multiplying the weights of the three connections. This gives us a weighting on “connected pairs of tripods” (really a tripod and an anti-tripod) that is supported on connections that satisfy properties A, B, and C.

10. We call a perfect connection between two two-frames a geodesic segment that has a length of r, and angle of zero between the segment and the tangent vectors, and translates one normal vector to the other. If a tripod and an anti-tripod were connected by three perfect connection, then they would be a 1-dimensional retract of a flat pair of pants with three cuffs of equal length R, where R is approximately r + \log \cos \pi/6 when r is large. If the tripod and anti-tripod are connected by arcs that satisfy properties A and B, then the connected pair of tripods is still a retract of a skew pair of pants, whose cuffs have half-length within \epsilon (or 10\epsilon) of R. Thus there is a map from good connected pairs of tripods to good pairs of pants, which we will denote by \pi.

11. We can let \tilde{\mu} be the measure on connected pairs of tripods, given by integrating the weighting of steps 8 and 9 with respect to the Liouville measure on pairs of tripods (or pairs of two-frames). We then push this measure forward by \pi to obtain a measure \mu on pairs of pants; after finding a rational approximation and clearing denominators, it will be the \mu that was asked for in step 6. We will show that \hat{d}\mu (taking the original irrational \mu) is \epsilon/R-equivalent to a rescaling of Lebesgue measure on each pounv bundle and thereby complete the proof.

12. A partially connected pair of tripods T is a pair of tripods where we have connected two out of the three pairs of two-frames. To a partially connected pair of tripods we can assign a single closed geodesic \gamma that is homotopic to the concatenation (at both ends) of the two connecting segments. If we connect the third pair of two-frames and apply \pi we obtain a pair of pants P, and we can then find a pair of opposite unit normal vectors for gamma pointing to the two cuffs of P (as described in step 3). We will describe a method for predicting the pounv for \gamma and P knowing only the partially connected tripod T: First, lift T to the solid torus cover of M determined by \gamma, and then follow geodesic segments from the tangent vectors of the two unconnected two frames of (the lift of) T to the ideal boundary of this \gamma-cover. We can connect these two points in the boundary by two geodesics, each of which goes about half-way around this solid torus cover. We can then find the common orthogonals from each of these geodesics to (the lift of) \gamma, and then obtain two normal vectors to \gamma pointing along these common orthogonals; it is easy to verify that these are half-way along \gamma from each other (in the complex sense) and hence form a pounv. Property C of the connections between two-frames (and hence tripods) implies that this predicted pounv will be exponentially close (in r) to the actually pounv of any pair of pants P.

To summarize: given a good connected pair of tripods, we get a good pair of pants P, and taking one cuff gamma of P, we get a pounv for \gamma as described in step 3. But we only need two out of the three connecting segments to get \gamma, and using the third pair of two frames, without even knowing the third connecting segment, we can predict the pounv for \gamma and P to very high accuracy.

13. We can then define the \tilde{d} operator from measures on partially connected pairs of tripods to measures on the pounv bundles for the associated geodesics; this operator is just the linear extension of the operation in step 12. Given a connected pair of tripods, we can get three partially connected pairs of tripods in the obvious way; we can thereby extend \tilde{d} to map measures on connected pairs of tripods to measures on the bundles of pounv’s; because the predicted pounv described in step 12 is exponentially close to the actual pounv described in step 3, the two measures \tilde{d} \tilde{\mu} and \hat{d}\mu are \exp(-\alpha r)-equivalent, by the B => A of step 2.

14. For each closed geodesic \gamma, we can lift all the partially connected tripods that give \gamma to the \gamma cover of M described in step 12. There is a natural torus action on the normal bundle of \gamma, and this extends to an action on all of the solid torus cover associated to \gamma. Moreover, it acts on the (lifts of) partially connected tripods, and it does not change the weightings of the two established connecting segments, because of property E of the weighting function.

This is the crucial point: the effective weighting on a partially connected pair of tripods is not just the product of the weights of the two established connections, but that product times the sum of the weights of all possible third connections. By property D of the weighting function, this sum, while not constant, is exponentially close to being constant, so the effective weighting is exponentially close to being invariant under the torus action. Because the predicted pounv for a partially connected pair of tripods is equivariant for the torus action, the measure \tilde{d} \tilde{\mu} is exponentially close to a torus invariant measure on the pounv bundle (which is necessary a rescaling of Lebesgue measure), in the sense that the Radon-Nikodym derivative is exponentially close to 1. It is then an easy lemma that the two measures are exponentially close in the sense of step 2. And then we’re finished: \hat{d}\mu is exponentially close to \tilde{d} \tilde{\mu}, which is exponentially close to a rescaling of Lebesgue measure, which is what we wanted (with
overkill) in step 6.

15. It remains only to define the weighting function described in step 8, which is surprisingly simple: We take some left-invariant metric on \text{PSL}_2(\bf{C}), and hence on the two-frame bundle for M and its universal cover. Given a connected pair of two-frames in M, we lift to the universal cover, to obtain two two-frames v and w. We then flow v and w forward by the frame flow for time r/4 to obtain v' and w'. We let V be the \epsilon neighborhood of v', and W be the \epsilon neighborhood of w', with the tangent vector of w' replaced by its negation. Then the weighting of the connection is the volume of the intersection of W with the image of V under the frame flow for time r/2.

Properties A, B, and C are not difficult to verify. Property D follows immediately from exponential mixing: If we have v and w downstairs without any connection, and similarly define v', w', V and W, then the sum of the weights of the possible connections will just be the volume of the intersection of the downstairs W with the frame flow of V. By exponential mixing, this converges at the rate \exp(-\alpha r) to the square of the volume of an \epsilon neighborhood, divided by the volume of M.

We can normalize the weights by dividing by this constant.

Jeremy

 


I will try to add comments as they occur to me.

 

One obvious comment to make is that the argument is remarkably short, and does not depend on any very delicate or complicated analytic estimates (maybe the argument that the glued up surfaces are quasi-geodesic is the most delicate part). It is fair to say that it defies the conventional wisdom in that respect — I was personally very surprised that the general method could be made to work, especially in light of the failure of Bowen’s program. Kudos to Jeremy and Vlad for their boldness and ingenuity.

Another comment to make is that the matching argument is surprisingly robust and general, and I expect it to have many broader applications. One thing I was confused about in my last post seems to be resolved by Jeremy’s sketch above — if I understand it correctly, one first (almost) pairs continuous measures, and only then approximates them by discrete integral measures (with a little bit of combinatorics at the end). And one really does need exponential mixing rather than just mixing.

Incidentally, apropos the matching argument, there are some interesting and well-known variations where things go haywire. For example, papers by Burago-Kleiner and (Curt) McMullen show that there are examples of separated nets in Euclidean space which are not bilipschitz to a lattice (though, interestingly, Curt shows that they are Holder equivalent). No such examples exist in hyperbolic space, because of — nonamenability and Hall’s marriage theorem! Roughly, when trying to match up points in two nets in hyperbolic space, one doesn’t need to look very far because the number of options grows exponentially. This is one reason why Kahn-Markovic need to control the matchings of their measures carefully, because it must be done on a very small scale (where the exponential growth does not kick in).

I thought I would also mention that in case my previous comments lead one to believe otherwise, exponential mixing of the geodesic flow on a hyperbolic manifold is somewhat delicate. Exponential mixing under a flow g_t on a space X preserving a probability measure \mu means that for all (sufficiently nice) functions f and h on X, the correlations \rho(h,f,t):= \int_X h(x)f(g_tx) d\mu - \int_X h(x) d\mu \int_X f(x) d\mu are bounded in absolute value by an expression of the form C_1e^{-tC_2} for suitable constants C_1,C_2 (which might depend on the analytic quality of f and h). For example, one takes X to be the unit tangent bundle of a hyperbolic manifold, and g_t the geodesic flow (i.e. the flow which pushes vectors along the geodesics they are tangent to, at constant speed). Exponential mixing should be contrasted with the much slower mixing of the horocycle flow on a hyperbolic surface, for which the correlation is bounded by an expression like C_1(\log t)^{C_2}t^{-1}. The geodesic flow on a hyperbolic manifold is an example of what is called an Anosov flow; i.e. the tangent bundle TM splits equivariantly under the flow into three subbundles E^0, E^s, E^u where E^0 is 1-dimensional and tangent to the flow, E^s is contracted uniformly exponentially by the flow, and E^u is expanded uniformly exponentially by the flow. The best one knows for (certain) Anosov flows (by Chernov) is that the flow is stretched exponentially mixing, i.e. with an estimate of the form C_1e^{-\sqrt{t}C_2}. One knows exponential mixing for the geodesic flow on variable negative curvature surfaces by Dolgopyat, and on certain locally symmetric spaces, using representation theory. See Pollicott’s lecture notes here for more details. I don’t know if exponential mixing for geodesic flows is known on manifolds of variable negative curvature in high dimensions. Also I’d appreciate it if any reader who knows some ergodic theory can confirm/deny/clarify this paragraph . . .

(Update 8/12): Jeremy tells me that he and Vladimir only need “sufficiently high degree polynomial” mixing, so perhaps there is a decent chance the methods can be extended to variable negative curvature.

(Update 10/29): The paper is now available from the arXiv.