“251 Mercer street” I said, “it is in the village,” “I know that” said the driver “are you going to NYU?” “Yes” I said. I was going to give a lecture at Ricky and Eli’s Tuesday evening’s Geometry Seminar and came earlier to have a chance to chat with the guys. “Let me tell you something” the driver said, “I did not finish elementary school, I left in the 6th grade and started working, and everyday I come home and have sex. My friends who finished elementary school have sex 2-3 times a week, tops. And , you know,” continued the driver “those who went on to finish high school, they have sex maybe once a week, no more.” “I see,” I said. Continue reading

# Monthly Archives: November 2008

# The Simplified Pill Algorithm

Ok so I had to take one pill every day, and fortunately the pill package was marked, it contained 14 pills with labels Sunday, Monday and so on. It started with Sunday, which was the mark for the leftmost pill. The pharmacy gave me 30 pills every month, two packages and 2 separately, which meant that taking the pills would be out of synchronization.

However, I had it all figured out: All I need is to remember a single number between -3 and 3 for the entire four weeks. Say the starting day is Tuesday. Then I had to remember the number -2. On Tuesday I take the leftmost pill for Sunday, on Wednesday I take the pill for Monday, on Thursday I take the pill for Tuesday, and so on. If, for example, the starting date is Thursday, then I have to remember +3. The pill for Sunday I take on Thursday, and then the pill for Monday I take on Friday etc. Easy. (I tried to write this number of the package but this didn’t work.)

I can remember several 7 digit phone numbers so, in theory, I did not see any difficulty in remembering one small integer number for an entire month. The math itself was not too challenging.

In practice it did not work so well. Sometimes I could not remember: either I already took the pill and the magic number is 2 or I did not and it is 3. Other times, I wondered if the magic number +2 or -2.

After several months Continue reading

# Sarkaria’s Proof of Tverberg’s Theorem 2

Karanbir Sarkaria

## 4. Sarkaria’s proof:

**Tverberg’s theorem (1965):** Let be points in , . Then there is a partition of such that .

**Proof:** We can assume that . First suppose that the points belong to the -dimensional affine space in of points with the property that the sum of all coordinates is 1. Next consider another -dimensional vector space and vectors in , such that is the only linear relation among the s. (So we can take as the standard basis in and . )

Now we consider the tensor product .

Nothing to be scared of: can be regarded just as the -dimensional vector space of *d+1* by matrices. We can define the tensor product of two vectors and , as the (rank-one) matrix .

Consider in U the following sets of points:

…

…

Note that 0 is in the convex hull of every . Indeed it is the sum of the elements in . (And thus . )

By the Colorful Caratheodory Theorem we can Continue reading

# Sarkaria’s Proof of Tverberg’s Theorem 1

Helge Tverberg

Ladies and gentlemen, this is an excellent time to tell you about the beautiful theorem of Tverberg and the startling proof of Sarkaria to Tverberg’s theorem (two parts). A good place to start is Radon’s theorem.

## 1. The theorems of Radon, Helly, and Caratheodory.

### Radon’s theorem

**Radon’s theorem: **Let be points in , . Then there is a partition of such that . (Such a partition is called a **Radon partition**.)

**Proof: **Since the points are affinely dependent. Namely, there are coefficients, not all zero, such that and . Now we can write and , and note that

(*) ,

and also . This last sum is positive because not all the s are equal to zero. We call it .

To exhibit a convex combination of which is equal to a convex combination in just divide relation (*) by . **Walla.**

This trick of basing a partition on the signs of the coefficients repeats in other proofs. Take note!

Radon used his theorem to prove Helly’s theorem.

### Helly’s theorem

**Helly’s theorem**: For a family , , of convex sets in , if every of the sets have a point in common then all of the sets have a point in common.

**Proof:** It is enough to show that when if every of the sets have a point in common then there is a point in common to them all. Let . In words, is a point that belongs to all the s except perhaps to . We assumed that such a point exists for every .

Now we can apply Radon’s theorem: Consider the Radon partition of the points, namely a partition of such that . Let . Since belongs to the convex hull of and every for belongs to every for every not in we obtain that belongs to every for not in . By the same argument belongs to every for not in . Since and are disjoint, the point belongs to all s. **Ahla.**

The proof of Helly’s theorem from Radon’s theorem as described on the cover of a book by Steven R. Lay

### Caratheodory’s theorem

**Caratheodory’s theorem: **For , if then for some , .

Like for Radon’s theorem, there is a simple linear algebra proof. We can assume that is finite; we start with a presentation of as a convex combination of vectors in , and if we can use an affine dependency among the vectors in to change the convex combination, forcing one coefficient to vanish.

Without further ado here is Tverberg’s theorem.

## 2. Tverberg’s Theorem

**Tverberg Theorem (1965):**Let be points in , . Then there is a partition of such that .

So Tverberg’s theorem is very similar to Radon’s theorem except that we want more than two parts! Continue reading

# Bad Advice; An Answer to an Old Trivia Question

A transparency and a lecture using transparencies. (No relation to the advice.)

## Our bad, worse and worst advice corner

### Bad – When you give a talk with transparencies or computer presentations, don’t go over the content of the transparencies but rather assume that the audience reads and digests them while you develop the matter even further and make comments about their content.

### Worse – The same as above, except that the transparencies are very dense and technical and hard to understand.

### Worst – The same as above except that the transparencies are handwritten in an unreadable way.

## Answer to Trivia question:

**Q**: What do Yehuda Agnon, Michael Ben-Or, Ehud Lehrer, Uzi Segal (whose calibration theorem was mentioned in the post on the controversy around expected utility theory), Mike Werman, myself, and quite a few others, all have in common?

Hint:

**Answer**: We all, (and altogether more than 20 students) took part in Continue reading

# Thomas Bayes and Probability

How can we assign probabilities in cases of uncertainty? And what is the nature of probabilities, to start with? And what is the rational mechanism for making a choice under uncertainty?

Thomas Bayes lived in the eighteenth century. Bayes’ famous formula shows how to update probabilities given some new evidence. Following is an example for an application of Bayes’ rule:

Suppose that ninety percent of pedestrians cross a certain crosswalk when the light is green, and ten percent cross it when the light is red. Suppose also that the probability of being hit by a car is 0.1% for a pedestrian who crosses on a green light, but the probability of being hit by a car is 2% for a pedestrian who crosses on a red light. A pedestrian is hit by a car at this particular crossing and brought to the hospital. How likely is it that he crossed on a red light?

Well, to start with (or *a priori*), only ten percent of the people who cross the crosswalk cross it on a red light, but now that we are told that this person was hit by a car it makes the probability that he crossed illegally higher. But by how much? Bayes’ rule allows us to compute this (*a posteriori*) probability. I will not describe the mathematical formula, but I will tell you the outcome: the probability that this person crossed on a red light is 2/3.

The Bayesian approach can be described as follows. We start by assigning probabilities to certain events of interest and, as more evidence is gathered, we update these probabilities. This approach is applied to mundane decision-making and also to the evaluation of scientific claims and theories in philosophy of science.

Bayes’ rule tells us how to update probabilities but we are left with the question of how to assign probabilities in cases of uncertainty to begin with. What is the probability of success in a medical operation? What is the chance of your team winning the next baseball game? How likely is it that war will break out in the Middle East in the next decade? How risky are your stock-market investments? Continue reading

# About Conjectures: Shmuel Weinberger

The following paragraph is taken from the original “too personal for publication draft” of an article entitled ” ‘Final values’ of functors” by Shmuel Weinberger for a volume in honor of Guido Mislin’s retirement from ETH. (L’enseignement Mathematique 54(2008), 180-182.) Shmuel’s remarks about making conjectures and the different types of conjectures appear here for the first time.

**“Final Values” of Functors**

** **

Shmuel Weinberger

A personal letter for, and to, Guido Mislin, a mathematician who always epitomized for me elegance, taste, and precision.

Guido Mislin

I have, on very rare occasions, conjectured things I really believe with evidence by analogy and the religious belief in the essential simplicity of the mathematical universe (looked at correctly)[1]. Besides beauty, such a conjecture[2] pragmatically serves as a guide through unknown landscape. And even an unreliable guide helps to point in the right direction. In fact, an unreliable guide known to be unreliable can be useful indeed. Sometimes one makes conjectures knowing them to be false, but feeling that their falsity is a deep phenomenon and most of the predictions made with the conjecture as guide will be true[3]. On other times, I have conjectured to lay down the gauntlet: “See, you can’t even disprove this ridiculous idea.” [4] On yet other times, the conjectures come from daydreams: it would be so nice if this were true[5]. And, yet on others one makes a conjecture hoping to probe the landscape that other conjectures have already illuminated[6].

The conjecture (and speculations) that I would like to present to you, Guido, is motivated by ideas I learnt from Goodwillie and Weiss, but I think it is also much in the spirit of the way you sometimes approach mathematics and it is somewhere between the last two kinds…

[1] These include the package of conjectures about homology manifolds made in [BFMW], which incidentally flatly contradict other standard conjectures like the Bing-Borsuk conjecture.

[2] Here I have in mind things like the Riemann hypothesis, indeed huge swaths of number theory; in topology and geometry, Thurston’s geometricization conjecture, Baum-Connes conjecture and Novikov conjectures, and so on are examples.

[3] Here I am thinking of the equivariant version of the Borel conjecture, or the stratified version. See [W, Chapter 13].

[4] I think this is what Lott had in mind (although he was usually careful to call it a question) — but I have less concern for my reputation, and am willing to conjecture the opposite of what I believe -when he formulated the zero-in-the-spectrum problem for all complete manifolds. And it was disproved in [FW]. On the other hand, my dear friend and mentor Donald Newman made a conjecture of this same sort once in rational approximation, only to have it proven by V.A.Popov.

[5] This must be the case for, say, Gromov’s questions about large Riemannian manifolds [G] or the Weinberger conjecture discussed first in print in [D]

[6] The zero in the spectrum problem for universal covers of aspherical manifolds or even uniformly contractible manifolds, also discussed by Lott, is of this sort. The conjecture of rationality of the difference of twisted APS invariants for homotopy equivalent manifolds was made after realizing that it would follow from the Borel conjecture for torsion free groups. By now, it’s been proven three times. [FLW][K][GHW] and [HR].

As further afterthoughts Shmuel writes: Continue reading