How to work out proofs in Analysis I

Now that we’ve had several results about sequences and series, it seems like a good time to step back a little and discuss how you should go about memorizing their proofs. And the very first thing to say about that is that you should attempt to do this while making as little use of your memory as you possibly can.

Suppose I were to ask you to memorize the sequence 5432187654321. Would you have to learn a string of 13 symbols? No, because after studying the sequence you would see that it is just counting down from 5 and then counting down from 8. What you want is for your memory of a proof to be like that too: you just keep doing the obvious thing except that from time to time the next step isn’t obvious, so you need to remember it. Even then, the better you can understand why the non-obvious step was in fact sensible, the easier it will be to memorize it, and as you get more experienced you may find that steps that previously seemed clever and nonobvious start to seem like the natural thing to do.

For some reason, Analysis I contains a number of proofs that experienced mathematicians find easy but many beginners find very hard. I want to try in this post to explain why the experienced mathematicians are right: in a rather precise sense many of these proofs really are easy, in the sense that if you just repeatedly do the obvious thing you will solve them. Others are mostly like that, with perhaps one smallish idea needed when the obvious steps run out. And even the hardest ones have easy parts to them.

I feel so strongly about this that a few years ago I teamed up with a colleague of mine, Mohan Ganesalingam, to write a computer program to solve easy problems. And after a lot of effort, we produced one that can solve several (but not yet all — there are still difficulties to sort out) problems of the kind I am talking about: easy for the experienced mathematician, but hard for the novice. Now you have some huge advantages over a computer. For example, you understand the English language. Also, you can be presented with a vague instruction such as “Do any obvious simplifications to the expression and then see whether it reminds you of anything,” and you will be able to follow it. (In principle, so could the program, but only if we spent a long time agonizing about what exactly constitutes an “obvious” simplification, what kind of similarity should be sufficient for one mathematical expression to trigger the program to call up another, and so on.) So if a mere computer can solve these problems, you should definitely be able to solve them.

What I plan to do in this post is basically explain how the program would go about proving some of the theorems we’ve proved in the course. To explain exactly how it works would be complicated. However, because you are humans, there are lots of technical details that I don’t need to worry about, and what remains of the algorithm when you ignore those details is really pretty simple.

The rough idea is that you should equip yourself with a small set of “moves” and simply apply these moves when the opportunity arises. That is an oversimplification, since sometimes one can do the moves in “silly” ways, but merely being consciously aware of the moves is very useful. (Incidentally, the notion of “silliness” is hard to define formally but is something that humans find easy to recognise when they see examples of it. So that’s another example of the kind of advantage you have over the computer.)

Subsequences of Cauchy sequences

I’m going to describe a way of keeping track of where you have got to in your discovery of a proof. It’s not something I suggest you do for the rest of your mathematical lives. Rather, it is something that you might like to consider doing if you find it hard to come up with typical Analysis I proofs. If you use this technique a few times, then it should get easier, and after a while you will find that you don’t need to use the technique any more.

The technique is simply to record what statements you are likely to want to use, and what statement you are trying to prove. Both of these can change during the course of your proof discovery, as we shall see.

I think the easiest way to explain this and the moves is to begin by giving an example of the whole process in action. Then I’ll talk about the moves in a more abstract way. Let’s take as an example the proof that if a Cauchy sequence has a convergent subsequence then the sequence itself is convergent.

To begin with, we have nothing we obviously need to use, and a statement that we want to prove. That statement is the following.

—————————————————-
Every Cauchy sequence with a convergent subsequence converges

Let us begin by writing that very slightly more formally, to bring out the fact that it starts with \forall.

—————————————————-
\forall (a_n)\ (a_n) is Cauchy and (a_n) has a convergent subsequence
\implies (a_n) converges

The next step is to apply the “let” move, which I’ve talked about several times in lectures. If you ever have a statement to prove of the form “For every x such that P(x) holds, Q(x) also holds,” then you can just automatically write “Let x be such that P(x) holds,” and change your target to that of establishing that Q(x) holds.

In our case, we write, “Let (a_n) be a Cauchy sequence that has a convergent subsequence,” and modify our target to that of proving that (a_n) converges. So now we represent where we’ve got to as follows.

(a_n) is a Cauchy sequence
(a_n) has a convergent subsequence
——————————————-
(a_n) converges

Maybe the purpose of those strange horizontal lines is becoming clearer at this point. I am listing statements that we can assume above the line and ones that we are trying to prove below the line.

At this point it seems natural to give a name to the convergent subsequence that we are given. Let us call it (a_{n_k}). This again is just one instance of a very general move: if you are told you’ve got something, then give it a name. This sequence has two properties: it is a subsequence of (a_n) and it converges. I’ll list those two properties separately.

(a_n) is a Cauchy sequence
(a_{n_k}) is a subsequence of (a_n)
(a_{n_k}) converges
——————————————-
(a_n) converges

Having done that, I think I’ll remove the second hypothesis, since the fact that (a_{n_k}) is a subsequence of (a_n) is implicit in the notation.

(a_n) is a Cauchy sequence
(a_{n_k}) converges
——————————————-
(a_n) converges

The second hypothesis here is again telling us we’ve got something: a limit of the subsequence. So let’s apply the naming move again, calling this limit a.

(a_n) is a Cauchy sequence
(a_{n_k})\to a
——————————————-
(a_n) converges

That’s enough reformulation of our assumptions. It’s time to think about what we are trying to prove. To do that, we use a process called expansion. That means taking a definition and writing it out in more detail. It tends to be good to avoid expanding definitions unless you are genuinely stuck: that way you won’t miss opportunities to use results from the course rather than proving everything from first principles. However, here a proof from first principles is what is required. I’m going to do a partial expansion to start with: a sequence converges if there exists a real number that it converges to.

(a_n) is a Cauchy sequence
a_{n_k}\to a
——————————————-
\exists x\ (a_n) converges to x

Now our target has changed to an existential statement. How are we going to find an x that the sequence converges to?

Sometimes proving existential statements is very hard, but here it is easy, since we have a candidate for the limit staring us in the face, and better still it is the only candidate around. So let us make a very reasonable guess that the sequence is going to converge to a, and make proving that our new target.

(a_n) is a Cauchy sequence
a_{n_k}\to a
——————————————-
a_n\to a

That’s nice because we’ve got rid of that existential quantifier. But what do we do next? We must continue to expand: this time the definition of a_n\to a. Note that if you want to be able to do this, it is absolutely vital that you know your definitions. Otherwise, you obviously can’t do this expansion move. And if you can’t do that, then you can kiss goodbye to any hopes you might have had of proving this kind of result.

(a_n) is a Cauchy sequence
a_{n_k}\to a
——————————————-
\forall\epsilon>0\ \exists N\ \forall n\geq N\ |a_n-a|<\epsilon

Now we have a target that begins with a universal quantifier, so it’s time for the “let” move again.

(a_n) is a Cauchy sequence
a_{n_k}\to a
\epsilon>0
——————————————-
\exists N\ \forall n\geq N\ |a_n-a|<\epsilon

Now things become slightly harder, because this time we do not have a candidate staring us in the face for the thing we are trying to find. (The thing we are trying to find is N.) It’s not a bad idea in this situation to try to write out in vague terms what the key statements mean. One can do something like this.

Eventually all terms of (a_n) are close to each other
Eventually all terms of (a_{n_k}) are close to a
————————————————
Eventually all terms of (a_n) are close to a

The rough idea of the proof should now be clear: if all terms in the subsequence are close to a and all terms are close to each other, then eventually for each term we can say that it is close to a term in the subsequence, which is itself close to a.

Since we are going to need to take two steps from a term in (a_n), one to the subsequence and one from the subsequence to a, it seems a good idea to apply the two main hypotheses with \epsilon/2. So let’s just go ahead and do that and see what we get.

\exists N_1\ \forall p,q\geq N_1\ |a_p-a_q|<\epsilon/2
\exists N_2\ \forall k\geq N_2\ |a_{n_k}-a|<\epsilon/2
——————————————-
\exists N\ \forall n\geq N\ |a_n-a|<\epsilon

Now we are once again in a position where we have been “given” something — in this case N_1 and N_2. So let’s quietly drop the existential quantifiers and use the names N_1 and N_2. (Purists might object to using the same names for the particular choices of N_1 and N_2 that we used when merely asserting that they exist. But this is very common practice amongst mathematicians and does not lead to confusion.)

\forall p,q\geq N_1\ |a_p-a_q|<\epsilon/2
\forall k\geq N_2\ |a_{n_k}-a|<\epsilon/2
——————————————-
\exists N\ \forall n\geq N\ |a_n-a|<\epsilon

How do we propose to “force” |a_n-a| to be less than \epsilon? We are going to try to ensure, for suitable k, that |a_n-a_{n_k}|<\epsilon/2 and |a_{n_k}-a|<\epsilon/2. The first hypothesis tells us that we will be able to get the first condition if n and n_k are both at least N_1, and the third hypothesis tells us that we we will be able to get the second condition if k\geq N_2.

So our plan is going to be to choose p=n and q=n_k. For the plan to work, we shall need n\geq N_1, n_k\geq N_1, and k\geq N_2.

We are now in a position to choose N. We want our conclusion to hold when n\geq N, and the tool we use works when n\geq N_1, so it makes sense to take N=N_1. If we substitute that in, we lose the existential quantifier in the target and arrive at the following.

\forall p,q\geq N_1\ |a_p-a_q|<\epsilon/2
\forall k\geq N_2\ |a_{n_k}-a|<\epsilon/2
——————————————-
\forall n\geq N_1\ |a_n-a|<\epsilon

Now we can apply the “let” move again, to get rid of the universal quantifier in the target statement.

\forall p,q\geq N_1\ |a_p-a_q|<\epsilon/2
\forall k\geq N_2\ |a_{n_k}-a|<\epsilon/2
n\geq N_1
——————————————-
|a_n-a|<\epsilon

We know we’re going to take p=n, and that we can, since n\geq N_1, so let’s go ahead and choose that value for p in the first hypothesis. That leaves us with the following.

\forall q\geq N_1\ |a_n-a_q|<\epsilon/2
\forall k\geq N_2\ |a_{n_k}-a|<\epsilon/2
——————————————-
|a_n-a|<\epsilon

Just to make clear what I did there, it was a move called substitution. If you have a hypothesis of the form \forall u\ P(u)\implies Q(u) and a hypothesis P(x), then you can substitute in x for u and get out Q(x). (One can also call this modus ponens: I prefer to call it substitution in this case because the condition p\geq N_1 is somehow not a very serious hypothesis, but more like a “restriction” applied on p.)

Since I’ve used the hypothesis n\geq N_1 and am unlikely to need it again. I have deleted it.

Now we have to decide how to choose q and how to choose k. Recall that we needed k\geq N_2 and n_k\geq N_1. In a human proof one just writes, “Let k be such that k\geq N_2 and n_k\geq N_1.” It’s a bit trickier for a computer to find it obvious that such a k exists, but again that doesn’t matter to us here. I’ll use r to denote the k I’m choosing, and write down the conditions I’ve made sure r satisfies.

\forall q\geq N_1\ |a_n-a_q|<\epsilon/2
\forall k\geq N_2\ |a_{n_k}-a|<\epsilon/2
n_r\geq N_1
r\geq N_2
——————————————-
|a_n-a|<\epsilon

Now we can substitute n_r into the first hypothesis.

|a_n-a_{n_r}|<\epsilon/2
\forall k\geq N_2\ |a_{n_k}-a|<\epsilon/2
r\geq N_2
——————————————-
|a_n-a|<\epsilon

We can also substitute r into the second hypothesis.

|a_n-a_{n_r}|<\epsilon/2
|a_{n_r}-a|<\epsilon/2
——————————————-
|a_n-a|<\epsilon

And now we are done by the triangle inequality.

What were the moves we used?

Now that we have gone through a proof, let me list the main proof-generating moves we used.

The “let” move

If you are trying to prove a statement of the form “For every x such that P(x) holds, Q(x) also holds,” then write, “Let x be such that P(x) holds,” (or words to that effect) and adjust your target to proving that Q(x) holds.

The “naming” move

If you are told that something exists, then give it a name. For example, if you are given the hypothesis (a_{n_k}) is convergent, then you are told that a limit exists. So give it a name such as a and change the hypothesis to a_{n_k}\to a.

Expansion

If you are trying to prove something and you can’t find a high-level argument (by which I mean one that uses results from the course that are relevant to the statement you are trying to prove), and if what you are trying to prove involves concepts such as convergence or continuity that can be written out in low-level language (often, but not always, involving quantifiers), then rephrase what you are trying to prove in this lower-level way. That is, expand out the definition.

Substitution into a hypothesis

If you are given a hypothesis of the form \forall u\ P(u), then given any object x of the same type as u, you are free to substitute it in for u and obtain the hypothesis P(x).

For example, in the proof above, we had the hypothesis “(a_n) is Cauchy”. In expanded form, this reads

\forall \eta>0\ \exists N\ \forall p,q\geq N\ |a_p-a_q|<\eta

We decided to substitute in \epsilon/2, which is of the same type of thing as \eta (both are positive real numbers), and yielded for us the statement

\exists N\ \forall p,q\geq N\ |a_p-a_q|<\epsilon/2

(We then applied the “naming” move to get rid of the \exists N.)

Modus ponens

Often a hypothesis takes a slightly more general form, where conditions are assumed. That is, it takes the form

\forall u\ P(u)\implies Q(u)

or still more generally

\forall x\ P_1(u)\wedge\dots\wedge P_k(u)\implies Q(u)

There the symbol \wedge means “and”, so this is saying that whenever you can find a x that satisfies the conditions P_1(x),\dots,P_k(x), then you can give yourself the hypothesis Q(x).

Substitution into a target

Suppose that you are trying to prove a statement of the form \exists u\ P(u), and suppose you have identified an object x of the same type as u that you believe is going to do the job. Then you can change your target statement from \exists u\ P(u) to P(x). (In words, instead of trying to show that there exists something that satisfies P, you are going to try to show that x satisfies P.)

We did this when we moved from trying to prove that (a_n) converges to something to trying to prove that it converges to a.


This is not a complete set of useful moves. However, it is a start, and I hope it will help to back up my assertion that a large fraction of the proof steps that I take when writing out proofs in lectures are fairly automatic, and steps that you too will find straightforward if you put in the practice. I’ll try to discuss more moves in future posts.

About these ads

14 Responses to “How to work out proofs in Analysis I”

  1. Joel Says:

    An FAQ in most of my modules in Nottingham is “Why do we have to memorize so many proofs?”
    A typical request that I receive is that I should select a small subset of the proofs and declare those as the ones that might turn up in the exam, because otherwise there are too many to memorize. (I am, however, only willing to declare a very small number of proofs to be non-examinable.)
    I have made my own efforts to counter this based on the idea that the important thing is understanding the material and developing general fluency in at least many of the “routine” portions of “doing proofs”. However a significant number of students still appear to abandon understanding in favour of memorization. In the anonymous feedback, some students have explicitly told me that the abstract material and reasoning/doing proofs is too big a jump from A level to cope with, and that is why they have resorted to memorization.
    I shall continue to refer my students to this blog, in the hope that it will help!
    Joel

  2. Timothy Gowers’s blog | Explaining mathematics Says:

    […] See http://gowers.wordpress.com/2014/02/03/how-to-work-out-proofs-in-analysis-i/ for some discussion of proofs. I like his immediate illustrative example of how understanding aids memory, which I quote here: […]

  3. Joel Says:

    “Let’s take as an example the proof that if a Cauchy sequence has a convergent subsequence then the sequence itself is Cauchy.”

    I think the last occurrence of “Cauchy” should say “convergent”?

    Indeed it should. Corrected now — thanks.

    • Patrick Stevens Says:

      Well, “Cauchy” and “convergent” are the same in a complete metric space, and happily we are in a complete metric space. (But it’s probably clearer to use “convergent”, yes.)

  4. tomcircle Says:

    Reblogged this on Math Online Tom Circle.

  5. Charlie Says:

    This is not easy in any sense of the word.

    • Greg Says:

      I sort of agree with you. But there is a sense in which this is easy – namely, it’s easy because it doesn’t require mathematical creativity. These arguments can be found by understanding the terms within the statements and “easy” proof-creation techniques, without having to resort to introducing genuinely new objects or subgoals into the arguments.

    • gowers Says:

      Greg has put it very well. The point I am making is that this kind of reasoning is “easy” in the technical sense that there is a well-defined procedure that one can learn in order to carry it out. However, learning that procedure takes some work, and if you don’t do that work then finding the proofs won’t be easy in the normal sense of the word.

  6. Mario Says:

    I think the procedural approach is great. It will sure help memorization. However, wouldn’t it be nice if you could package the moves as chunks of algorithm themselves such that they are less vague. So a method of memorization of a proof will be something like: let x=, formulate the problem, expand hypothesis, etc. I am sure many proofs will follow the same trend and then more memory is conserved.

  7. chibbsa Says:

    Sir Timothy may I ask you a really weird question. When you are thinking through the ways memorization can be done right, is there any sense, ever, in which you have perceived a fundamental connection.

    I mean between the kinds of methods that do it right for memorization, and maths itself. Not memorization.

    Do you think a hard science theory is possible for the nature of science. A proof?

    Only if you have time.

    • gowers Says:

      Briefly my answer is yes, in the following sense. Although the formal notion of proof has nothing to do with memory, there is much more to mathematics than just the formal notion of proof. What is it that distinguishes between interesting mathematical definitions/conjectures/statements and uninterestingly arbitrary ones? What makes us call some proofs explanatory and others merely certificates of truth? The answers to these questions are, in my view, closely bound up with how we memorize proofs.

      But how we memorize proofs is itself closely bound up with how we discover proofs. As I am trying to convey in the post, we train ourselves to do certain steps almost automatically, and once we have done that we no longer have to memorize those steps — we just remember that the obvious thing works and then do the obvious thing.

      Finally, I believe that a hard science of how we discover proofs is possible, at least for a wide range of proofs. For example, in my work with Mohan Ganesalingam, I have found that there is a very strong correlation between the technical difficulties that arise when we try to think how a computer could discover such-and-such a proof, and the difficulties that we see undergraduates encountering when we supervise them. So we have become sensitive to a very fine gradation of difficulty, which seems to be an objective one and amenable to rigorous study.

  8. chibbsa Says:

    Thanks for your reply! Yes, I have a connection with memorization and the interest in learning/understanding outcomes. I was totally uneducated and after an access course ended up at Kings College Strand mature student. And I become fascinated with ways to structure memorizing and ways to test it. They thought I wouldn’t survive the first 3 months. I graduated 3 years later the best First of the year and 8 of the 11 possible prizes, including best 3rd year project most mathematical. And all the others. Got national prizes, free IEEE membership, entered for an international prize I didn’t short list form.

    That way way punching over my weight. Then when my daughter was born she had some learning difficulties. They marked her IQ 70 at one point. But by the time she was 9 she made it pretty clear that if life was going to one long coming last and being invisible, then she basically didn’t want it. So I quite work, and coached her, throwing some incantations and running. Two years later she banned me from her memorization files. Passed 10 GCSE’s and is currently on Math AS Level of all things.

    All true. Al Hibbs KCL 94-97 mech eng

    p.s. kind of the reason I wanted to bragg all that, is because that memorization tutorial and the generally positive, or at least if they’re doing it anyway, let’s make work better. I was really moved actually. I’ve never seen a math person or science person not totally pejorative about techniques. I’ve tried to raise the matter so often, that it’s not rote when methodical. But people throw out counter intuitive Popperian ways learning must be.

  9. chibbsa Says:

    Prof Gowers, thanks for answering. Are you saying proofs are often the same as original discovery. Or final presentation or does that not matter?

    IMHO the idea about pairing Proof and Discovery is a great idea on its own. Pairing same is the way memorization should be structured too.

    Prof Gowers, would it be ok for me to email you privately the one time? Reason being I have sort of tracked you down hoping to talk about a proof. I’m too embarrassed to talk about it public?

  10. mozibur ullah Says:

    One point that I think that might be usefully also pointed out here is why would we want to prove a statement such as:

    ‘every Cauchy sequence with a convergent subsequence converges’.

    And this I think is part of a general one in mathematics where a ‘smaller’ subproblem determines the larger one. It also helps educate one into looking for similar kinds of thinking. One might think of this as learning a kind of aesthetics in mathematics.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s


Follow

Get every new post delivered to your Inbox.

Join 1,555 other followers

%d bloggers like this: