Proof: Gromov's short basis, volume comparison

In summary, Gromov's short basis is a set of vectors that forms a basis for a Banach space and minimizes the length of the longest vector. It is closely related to volume comparison and has many practical applications in mathematics and science, particularly in geometry, topology, and functional analysis. Its key properties include minimizing the length of the longest vector, high degree of symmetry, and stability under small perturbations. It has been used to study the geometry of spaces, prove results about the volume of convex bodies, and in computer science for efficient algorithms.
  • #1
Sajet
48
0
Hi!

I'm having problems understanding the last step of a derivation for a version of a theorem of Gromov's we had in class:

Let [itex](M^n, g)[/itex] be complete with nonnegative sectional curvature. Then [itex]\pi_1(M, p)[/itex] can be generated by at most [itex]3^n[/itex] elements.

In short, the proof takes the Riemannian universal covering [itex](\tilde M, \tilde g, \tilde p)[/itex] of [itex](M, p)[/itex] and uses a short basis [itex](\gamma_1, \gamma_2, ...)[/itex] of the deck transformation group. I don't think there is any need to go into much detail about the construction.

Next it is shown that [itex]\alpha_{ij} \geq \pi/3[/itex], where [itex]\alpha_{ij}[/itex] is the angle between the minimal geodesics from the basis point [itex]\tilde p[/itex] to [itex]\gamma_i \tilde p[/itex] and [itex]\gamma_j \tilde p[/itex] respectively.

Now the desired estimate is acquired as follows:

Let [itex]v_i \in T_{\tilde p}^1\tilde M[/itex] be the starting velocity vector of a minimal unit speed geodesic from [itex]\tilde p[/itex] to [itex]\gamma_i\tilde p[/itex].

Because each angle between two such vectors is at least equal to [itex]\pi/3[/itex], we can draw pairwise disjoint open balls [itex]B_{\pi/6}(v_i) \subset T_{\tilde p}^1\tilde M \cong S^n[/itex] around each [itex]v_i[/itex]. (Note that these are (n-1)-dimensional neighborhoods within the n-Sphere of unit vectors.)

Now the desired result is acquired by applying Bishop-Gromov's Volume Comparison Theorem:

If [itex]h[/itex] is the number of these unit vectors [itex]v_i[/itex], then:

[itex]h\cdot vol(B_{pi/6}(e_1) \subset S^n) \leq vol(S^n) \Rightarrow h \leq 3^n[/itex].​

I don't understand this last step. It seems to me, the author goes:

[itex]h \leq \frac{vol(B_{pi/2}(e_1) \subset S^n)}{vol(B_{\pi/6}(e_1) \subset S^n)} \leq \frac{(\pi/2)^n}{(\pi/6)^n} = 3^n[/itex]​

where the second step follows by applying the volume comparison theorem and comparing to [itex]\mathbb R^n[/itex]. But in my opinion [itex]vol(S^n) = vol(B_\pi(e_1)\subset S^n)[/itex] (with a [itex]\pi[/itex] instead of [itex]\pi/2[/itex]), which would give an estimate of [itex]6^n[/itex].

Am I making a very elementary mistake or is there an error in the proof?
 
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  • #2


Hi there,

Thank you for sharing your question about the last step of the derivation for Gromov's theorem. I can understand why you are confused and I would like to provide some clarification.

From what I can see, there is indeed an error in the proof. The volume comparison theorem states that if a complete Riemannian manifold M has nonnegative sectional curvature, then the volume of any ball in M is less than or equal to the volume of the corresponding ball in Euclidean space with the same radius. In other words, vol(B_r(p) \subset M) \leq vol(B_r(q) \subset \mathbb{R}^n) for any two points p, q \in M and any radius r.

In this case, the author seems to have mistakenly compared the volume of the ball B_{\pi/2}(e_1) \subset S^n (which is the unit sphere in Euclidean space) to the volume of the ball B_{\pi/6}(e_1) \subset S^n (which is a small neighborhood of the unit vectors in the unit sphere). This comparison is incorrect and should instead be vol(B_{\pi/2}(e_1) \subset S^n) \leq vol(B_{\pi/6}(e_1) \subset S^n) since the latter is a smaller ball.

To summarize, the correct final step should be:

h \leq \frac{vol(B_{pi/6}(e_1) \subset S^n)}{vol(B_{pi/6}(e_1) \subset S^n)} \leq \frac{(\pi/6)^n}{(\pi/6)^n} = 1

I hope this helps clarify the confusion. If you have any further questions, please do not hesitate to ask.

 

Related to Proof: Gromov's short basis, volume comparison

1. What is Gromov's short basis?

Gromov's short basis is a mathematical concept developed by Russian mathematician Mikhael Gromov. It is a set of vectors that forms a basis for a Banach space, meaning that all other vectors in the space can be expressed as a linear combination of these basis vectors. The key property of Gromov's short basis is that it minimizes the length of the longest vector in the set.

2. How is Gromov's short basis related to volume comparison?

Gromov's short basis is closely related to volume comparison, which is a geometric concept used to compare the volumes of different spaces. In particular, the short basis for a Banach space can be used to define a notion of volume for that space, which can then be compared to the volumes of other spaces using volume comparison techniques.

3. Why is Gromov's short basis important?

Gromov's short basis is important because it has many applications in mathematics and science. It has been used to solve problems in areas such as geometry, topology, and functional analysis. It also has connections to other important mathematical concepts, such as the geometry of Banach spaces and the theory of convex bodies.

4. What are the key properties of Gromov's short basis?

There are several key properties of Gromov's short basis that make it useful in mathematics. Firstly, it minimizes the length of the longest vector in the set. Secondly, it has a high degree of symmetry, meaning that all the basis vectors are approximately the same length and point in different directions. Finally, it is stable under small perturbations, meaning that small changes to the vectors in the set do not significantly affect its properties.

5. How is Gromov's short basis used in practical applications?

Gromov's short basis has many practical applications, particularly in the fields of geometry and topology. For example, it has been used to study the geometry of spaces with negative curvature, and to prove results about the volume of convex bodies. It has also been applied in computer science, for example in the design of efficient algorithms for solving linear equations in high dimensional spaces.

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