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  • PROFESSOR: Who can tell me what a proof is?

  • Any ideas of, what is a proof, anyway?

  • Any thoughts?

  • Yeah?

  • AUDIENCE: It's a chain of statements, each logically

  • supported by the previous ones, that

  • get you from a set of assumptions

  • to a set of conclusions.

  • PROFESSOR: Very good.

  • I like that.

  • That's very close to what we're going to do here, yeah.

  • Now, that's a special kind of proof, though.

  • That's a mathematical proof.

  • And I'm going to write a definition very

  • close to that in a few minutes.

  • But proofs exist beyond mathematics.

  • Can anybody think of a higher level

  • notion of what a proof is?

  • That's correct, what you said, but there's

  • a higher meta level notion of what a proof is beyond that.

  • It may have no logical deductions potentially.

  • It may have no assumptions.

  • Any thoughts about a proof?

  • OK, well, I think generally, a proof

  • is considered, across multiple fields,

  • as a method for ascertaining the truth.

  • And you described one method.

  • Now, by ascertaining, I mean establishing truth, verifying

  • truth.

  • And there's lots of ways to ascertain truth

  • in society, and even within science.

  • What are some examples of ways that we

  • ascertain truth in society?

  • Yeah?

  • AUDIENCE: Observations, like seeing that piece of chalk

  • will fall to the ground.

  • PROFESSOR: Observation, experiment

  • and observation-- excellent.

  • And that's the bedrock of physics.

  • I mean, who really knows if there's gravity out there?

  • Well, we observe it.

  • And so we then conclude that's the truth.

  • There's gravity, and we have laws about it.

  • That's one good way.

  • What's another way of ascertaining truth

  • across scientific disciplines, or beyond science, just

  • in society?

  • How is truth established?

  • What are the ways?

  • Yeah?

  • AUDIENCE: Well, establishing what's false,

  • you can know what things aren't true.

  • Then that helps you narrow down what is true.

  • PROFESSOR: Yes, truth-- yeah, that's great.

  • Truth is the opposite of falsehood.

  • How do we establish falsehood?

  • What are the ways in doing that?

  • How you decide something is not true in every day-- yeah?

  • AUDIENCE: Find counterexamples.

  • PROFESSOR: Find counterexamples, yeah, that's good.

  • So in fact, even a step more general, sampling.

  • Counterexamples are ways.

  • If you do something, an experiment, ten times,

  • and every time, it comes out one way, that's truth, maybe.

  • But there's fields where that becomes truth.

  • What about other ways?

  • How are we going to decide if Roger Clemens is

  • guilty of perjury for lying about steroids to Congress?

  • He did it or he didn't.

  • How are we going to decide that?

  • How is that truth going to be ascertained?

  • Yeah?

  • AUDIENCE: Would it be by examining the evidence

  • that we have?

  • PROFESSOR: Examining evidence.

  • And who makes the conclusion there?

  • AUDIENCE: Juries.

  • PROFESSOR: The jury.

  • Truth is established by juries or judges.

  • You know, Blago-- I can never pronounce

  • his name, the Illinois governor, Blagojevick-- he's guilty.

  • That's the truth of-- not of conspiracy,

  • trying to sell Obama a senate seat,

  • but of lying to the authorities about campaign financing.

  • OJ is guilty-- not of killing his wife,

  • but of breaking into an apartment to steal back

  • some of his merchandise.

  • So judges and juries make decisions on truth.

  • What are other truths-- bigger truths, even, than judges

  • and juries, in society?

  • There's one really big one that causes a lot of issues.

  • Yeah?

  • AUDIENCE: Religion.

  • PROFESSOR: What is it?

  • AUDIENCE: Religion.

  • PROFESSOR: Religion, the word of God-- broadly construed here,

  • for religion.

  • Now, that one is really hard to argue about

  • because you believe it.

  • And especially if you're not talking to God regularly

  • and somebody is, well, it's hard to argue about the truth.

  • So you rely on others to interpret it for you,

  • often-- a priest, or a minister, a rabbi.

  • And it gets complicated, because you can end up

  • with conflicting truths based on who you think you're talking to

  • or who the translator is for you.

  • Another one is the word of your boss.

  • Whatever the boss says is right.

  • Often in business, the customer is always right.

  • That's the truth, whatever the customer says.

  • With Donald Trump as your boss, you'd better agree

  • or you're fired.

  • Often in classes, the professor says it, it is true.

  • Because the authority said it.

  • That's not true here.

  • That will not hold.

  • And one of the nicest things about math that I like a lot

  • is that the youngest student can stand up

  • against the most oldest, most experienced professor,

  • and win an argument on mathematics.

  • I do get pleasure when a student comes up and proves me wrong.

  • I loved it when that student came in,

  • and she showed me what I said really

  • wasn't right when you looked at it carefully

  • or in a different light.

  • Now, sometimes if I do it on the board here and it's in class,

  • well, that's fun.

  • I feel a little embarrassed afterwards.

  • But it's a good thing about mathematics,

  • is you can have that kind of dialogue.

  • OK, another one, which is related to the word of God

  • sometimes, is inner conviction-- very popular

  • in computer science, believe it or not, with the mantra,

  • there are no bugs in my program.

  • I can't tell you how many times you hear that.

  • Closely related is, I don't see why not something is true.

  • And that's a good one, because that

  • transfers the burden of proof to anybody who disagrees with you.

  • You don't have to prove.

  • You just say, I don't see why it's not true.

  • All of a sudden, the other person who's questioning you,

  • it becomes their job to disprove you, which is not so good.

  • OK, now in mathematics, there's this higher level.

  • And someone stated it very clearly up there.

  • Let me write it up here.

  • In mathematics, we have a mathematical proof

  • is a verification of a proposition

  • by a chain of logical deductions from a set of axioms.

  • Now, that's a bit of a mouthful.

  • There's three important components here--

  • propositions, logical deductions, and axioms.

  • And we're going to spend the rest of the class

  • today talking about each of these,

  • and then give an example of a proof.

  • We'll start with propositions.

  • A proposition is a statement that is either true or false.

  • You may not know which one, but it's one or the other.

  • A simple example-- 2 plus 3 equals 5.

  • Now, that's a true proposition.

  • Here's one that's a little more interesting.

  • For all n in the set of natural numbers,

  • n squared plus n plus 41 is a prime number.

  • I know I've used some notation here.

  • This is-- the upside down A is the for all symbol.

  • How many people have not seen that symbol before?

  • A bunch of you.

  • You're going to see a bunch of symbols here first week.

  • And that means for every possible choice of n--

  • and this is in the natural numbers, which is the set 0, 1,

  • 2, 3, and so forth.

  • It's the natural numbers.

  • It's basically the integers, but not negative.

  • So we're saying for every natural number, i.e. for 0,

  • for 1, for 2, and for 3, and so forth, this expression

  • is a prime.

  • Now, a prime number is a number that

  • is not divisible by any other number besides itself and 1.

  • So 1, 3, 5, 7 are prime.

  • 9 is not because it's 3 times 3.

  • Now, this part here is called the predicate.

  • And a predicate is a proposition whose truth

  • depends on the value of a variable-- in this case, n.

  • All right, this is referred to as the universe of discourse.

  • It's the space of all the things we're talking about.

  • We're only talking about natural numbers here.

  • This is called a quantifier.

  • We'll see more quantifiers later.

  • All right, now to see if this proposition is true,

  • we need to make sure that this predicate is

  • true for every natural number n.

  • So let's see if we can check that.

  • Let's try some values.

  • So we'll try n is 1, 2, 3, and so forth.

  • And we'll compute n squared plus n plus 41.

  • And then we'll check, is it prime?

  • So for n equals 0, n squared plus n plus 41 is 41.

  • Is 41 prime?

  • Yeah, nothing divides 41 but itself and 1.

  • All right, let's try 1.

  • 1 squared plus 1 plus 41 is 43.

  • Is 43 prime?

  • Yes.

  • Let's try 2.

  • We get 4 plus 2 is 6 plus 41 is 47.

  • Is 47 prime?

  • AUDIENCE: Yes.

  • PROFESSOR: Yes.

  • Looking good.

  • 3-- I got 9, 12, 53.

  • Is 53 prime?

  • Yeah.

  • And I could keep on going here.

  • I could go down to 20.

  • I get 420-- 461.

  • In fact, that is a prime.

  • And I could just keep on going here.

  • Go down to 39.

  • I get 1,601.

  • You can check.

  • That is a prime.

  • The first 40 values of n, the proposition is true.

  • The predicate is true.

  • It is prime.

  • Now, this is a great example because in a lot of fields--

  • physics, for example; statistics, often-- you

  • checked 40 examples.

  • That's above and beyond the call of duty.

  • It's always true.

  • So yeah, this must be true, right?

  • No, wrong.

  • Often, you'll see this in a lot of scientific fields.

  • It is not true.

  • Can anybody give me an example of n

  • for which n squared plus n plus 41 is not prime?

  • Yeah?

  • AUDIENCE: 40.

  • PROFESSOR: 40, good.

  • Let's see about 40.

  • 40 squared plus 40 plus 41 is 1,681.

  • What's that equal?

  • 41 squared.

  • So it is not prime.

  • Somebody give me an obvious example where it's not prime.

  • AUDIENCE: 41.

  • PROFESSOR: 41-- yeah, 41 squared,

  • we get everything is divided by 41.

  • But 40 is the first break-point.

  • So the first 40 examples work, and then it failed.

  • So this proposition is false, even though it

  • was looking pretty good.

  • There's a reason I'm doing this.

  • In fact, I'm going to do it some more here.

  • I'm going to beat you over the head with it.

  • Here's a famous in mathematics statement.

  • a to the fourth plus b to the fourth plus c to the fourth

  • equals d to the fourth has no positive integer solutions.

  • That is a proposition.

  • Now, this proposition was conjectured to be true by Euler

  • in 1769.

  • Euler's a big honcho in math.

  • We still talk about him a lot even though he's

  • been dead for centuries.

  • It was unsolved for over 2 centuries.

  • Mathematicians worked on it.

  • It was finally disapproved by a very clever fellow

  • named Noam Elkies 218 years later after it was conjectured.

  • He worked at that other school down the street.

  • And he came up with this.

  • a equals 95,800.

  • b equals 217,519.

  • c equals 414,560.

  • You don't have to remember these numbers.

  • We're not going to quiz you on that-- 422,481.

  • Now, he claims-- I've never personally checked it,

  • but presumably, people have-- you plug those in here,

  • and you have an equality.

  • So he says.

  • So in fact, the correct proposition

  • is there does exist a, b, c, d in the positive natural

  • numbers such that a the fourth plus b to the fourth plus

  • c to the fourth equals d to the fourth.

  • I used a new quantifier here called there exists.

  • Instead of an upside down A, it's

  • a backwards E. Don't ask me why.

  • That's what it is.

  • The plus means you can't have 0 or negative numbers.

  • So these are the positive natural numbers.

  • And here's your predicate, which of course, the truth of this

  • depends on the values of a, b, c and d.

  • It took a long time to figure out that actually, there

  • was a solution here.

  • Obviously, everything they tried until that time failed.

  • Let me give you another one.

  • 313 x cubed plus y cubed equals z cubed has no positive integer

  • solutions.

  • This turns out to be false.

  • But the shortest, smallest counter-example

  • has over 1,000 digits.

  • This one was easy.

  • It only has six digits.

  • So there's no way ever you'd use a computer

  • to exhaustively search 1,000 digit numbers here

  • to show it's false.

  • Now, of course, some of you are probably thinking, why on earth

  • would I care if 313 times x cubed plus y cubed equals

  • z cubed has a solution?

  • And that probably won't be the last time

  • that thought occurs to you during the term.

  • And why on earth would anybody ever try

  • to even find a solution to that?

  • I mean, mathematicians are sort of a rare breed.

  • Now, actually in this case, that's

  • really important in practice.

  • This equation is an example of what's

  • called an elliptic curve-- elliptic curve.

  • You study these if you're really a specialist in mathematics

  • in graduate school, or if you work

  • for certain three-letter agencies

  • because it's central to the understanding of how

  • to factor large integers.

  • That means factoring, showing that-- what was it--

  • 1,681 is 41 times 41.

  • And I said, OK, who cares about factoring?

  • Well, factoring is the way to break cryptosystems

  • like RSA, which are used for everything

  • that we do electronically today.

  • You have a Paypal account.

  • You buy something online.

  • You're using SSL.

  • They're all using cryptosystems, almost all of which

  • are based on number theory.

  • And in particular, they're based on factoring.

  • And if you can find good solutions to things like this,

  • or solutions to things like this, all of a sudden,

  • you can get an angle and a wedge on factoring.

  • And it's because of that that now

  • RSA uses 1,000 digit moduluses instead of hundred

  • digit moduluses like they used to use,

  • because people figured out how to factor

  • and how to break the cryptosystem.

  • If you could break those cryptosystems,

  • well, you can't rule the world, but it's close.

  • All right, so we'll talk more about this

  • the week after next when we do number theory,

  • and we work up to RSA and how that cryptosystem works,

  • and why factoring is so important.

  • So yeah, you don't have to really have

  • to worry about this.

  • But these things are important.

  • And the bigger message is that you don't just try a few cases,

  • and if it works, you think it's done.

  • That's not how the game works in mathematics.

  • You can get an idea of maybe it's

  • true, but doesn't tell you the answer.

  • All right, let me give you another one.

  • This is another very famous one that probably most of you

  • have heard of.

  • The regions in any map can be colored in four colors

  • so that adjacent regions have different colors.

  • Like a map of the United States--

  • every state gets a color.

  • If two states share a border, they

  • have different colors so you can distinguish them.

  • This is known as the four color theorem.

  • And it's very famous in the popular literature.

  • How many people have heard of this theorem before?

  • Yeah, OK.

  • So you've all heard of it.

  • It has a long history.

  • It was conjectured by somebody named Guthrie in 1853.

  • He's the first person to say this ought to be possible.

  • And there were many false proofs over the ensuing century.

  • One of the most convincing was a proof using pictures

  • by Kempe in 1879, 26 years later.

  • And this proof was believed for over a decade.

  • Mathematicians thought the proof was right

  • until another mathematician named Heawood found

  • a fatal flaw in the argument.

  • Now, this proof by Kempe consisted

  • of drawing pictures of what maps have to look like.

  • So he started by saying, a map has

  • to look like one of these types.

  • And he would draw pictures of them.

  • And then he argued that those types that he drew pictures of,

  • it worked for.

  • Proofs by picture are often very convincing and very wrong.

  • And I'm going to give you one to start lecture next time.

  • It'll be a proof by PowerPoint, which is even worse than proof

  • by picture.

  • And it is compelling.

  • And the point will to be to show you proofs by picture

  • are generally not a good thing.

  • Because your brain just locks in-- oh,

  • that's what it has to look like.

  • And you don't think about other ways that it might look like.

  • Now, the four color theorem was finally

  • proved by Appel and Haken in 1977,

  • but they had to use a computer to check thousands of cases.

  • Now, this was a little disturbing to mathematicians,

  • because how do they know the computer did the right thing?

  • Your colleague writes a proof on the board.

  • You can check it.

  • But how do you know the computer didn't mess up,

  • or not do some cases?

  • Now, everybody believes it's true now.

  • But it's unsatisfying.

  • A few years ago, a 12-page human proof was discovered,

  • but it's not been verified.

  • And people are very suspicious of it

  • because the proof of the main lemma says,

  • quote, "details of this lemma is left to the reader.

  • See figure seven."

  • That's what the main lemma of the proof is.

  • But people think that maybe there

  • were some good ideas there, but very suspicious proof.

  • All right, let's do another one, another proposition--

  • also very famous.

  • Every even integer but 2-- actually,

  • positive integer but 2-- is the sum of two primes.

  • For example, 24 is the sum of 11 and 13, which are prime.

  • Anybody know?

  • Is this true or false, this proposition?

  • Yeah?

  • AUDIENCE: I wish I knew.

  • PROFESSOR: [LAUGHS] Yeah, that's right.

  • Me too.

  • Nobody knows if this is true or false.

  • This is called Goldbach's conjecture.

  • It was conjectured by Christian Goldbach in 1742.

  • This is a really simple proposition.

  • And it's amazing it's not known.

  • In fact, I spent a couple years working on-- I thought,

  • oh, well, this has to be easy enough

  • to prove when I was younger, and didn't get very far.

  • So people still don't know if it's true.

  • And in fact, it was listed by the Globe

  • as one of the great unsolved mysteries.

  • So if you get out this Globe article here, one of the hand--

  • does everybody have this handout?

  • You don't?

  • We'll get it passed out.

  • Somebody missing that handout up over there and over here?

  • All right, if we get those passed out.

  • Now, it lists the three conjectures.

  • Do you see Goldbach's conjecture there?

  • Now, can anybody point out something

  • that's a little disturbing about what the Globe says

  • about Goldbach's conjecture?

  • AUDIENCE: 9 as a prime number.

  • PROFESSOR: Yeah, it gives the example.

  • Like, instead of 24 is 11 plus 13,

  • it says 20 is the sum of 9 and 11.

  • Now, if we're allowed to use things like 9 as primes,

  • Goldbach's conjecture's pretty easy to prove is true.

  • This won't be the last time we get examples

  • from the literature.

  • In fact, we're going to do this a lot,

  • along this theme of, you cannot believe everything you read.

  • Now, the Globe is easy pickings, but we'll

  • do some more interesting ones later.

  • Now, this article lists two other famous conjectures

  • which most people believe to be true-- the Riemann hypothesis

  • after an 1859 paper written by Bernard Riemann

  • suggested that zeros in an infinite series of numbers

  • known as a zeta function form along a straight line

  • on that complex plane.

  • The hypothesis has been proved to 1.5 billion zeros, not far

  • enough to prove it completely.

  • If they did 1.5 trillion zeros, it

  • wouldn't be far enough to prove it completely, of course.

  • And then the-- no, actually, the Riemann hypothesis,

  • a couple years ago, somebody credible

  • claimed to have proved it.

  • Proof turned out not to be right.

  • Then there's the Poincare conjecture.

  • Now, this one was finished off.

  • It was proved to be true in 2003 by a Russian named

  • Grigori Perelman.

  • The conjecture says, roughly speaking,

  • that 3D objects without holes, like no a doughnut,

  • are equivalent to the sphere.

  • They can sort of be deformed into a sphere.

  • This is known to be true in four dimensions and higher,

  • but nobody could prove it for three dimensions

  • until Perelman came along.

  • Now, there's a bit of a controversy around this guy.

  • He had an 80-page proof, but didn't have all the details.

  • So then other teams of mathematicians

  • got together and wrote 350 pages of details.

  • And then most people believe now that it's right,

  • and that his original proof might not

  • have had all the details, but he had the right structure

  • of the proof.

  • So he won prizes for this.

  • He won the highest prize in mathematics, the Fields Medal.

  • And just earlier this year, he was awarded the $1 million

  • Millennium Prize.

  • And there's about six problems or so

  • that if you solve one of them, the Clay Institute gives you

  • a million dollars.

  • And he's the first one to win the million dollars.

  • Now, the guy's a little strange.

  • He rejected the Fields Medal and refused to go to the ceremony

  • where he was being honored.

  • And he's recently rejected the Millennium prize.

  • And anyway, this area's murky, and we have an expert

  • to explain it all for us on video,

  • which I thought I'd show.

  • All right, let's do a simpler one here.

  • For all n in Z, n greater than or equal to 2

  • implies n squared is greater than or equal to 4.

  • Now, Z, we use for the integers.

  • And so that would be 0, 1, minus 1, 2, minus 2, and so forth.

  • And this symbol here is implies.

  • I In fact, one thing you can notice

  • when you read the text is we use different notation there

  • as the standard than I will use in lecture.

  • And there's lots of ways of doing it.

  • You could have a double arrow, a single arrow.

  • You could write out implies every time

  • as it's done in the text.

  • And it doesn't really matter which one

  • you want to use as long as you use one

  • of the conventions for implies.

  • And let me define what implies means.

  • An implication p implies q is said to be true if p is false

  • or q is true, either one.

  • So we can write this down in terms of a truth table

  • as follows.

  • You have the values of p and q.

  • And I'll give the value of p implies q.

  • If p is true and q is true, what about p implies q?

  • It's true, because q is true in the definition.

  • If p is true and q is false?

  • AUDIENCE: False.

  • PROFESSOR: False.

  • P is false.

  • Q is true.

  • True.

  • What about false and false?

  • It's true.

  • Even though this is false, as long as p is false,

  • p implies q is true.

  • So this is important to remember.

  • False implies anything is true, which is a little strange.

  • There's a famous expression.

  • If pigs could fly, I would be king.

  • Is that true?

  • Sort of.

  • In fact, this statement, pigs fly

  • implies I'm king-- that's true, because pigs don't fly.

  • Doesn't matter whether or not I'm king, which I'm not.

  • Since pigs don't fly, even though that's false,

  • the implication is true.

  • Now, some of you have worked on these things before.

  • It's second nature.

  • If you haven't, you want to start

  • getting familiar with that.

  • Let's do another example.

  • What about this proposition?

  • For all integers, n in Z, n greater than or equal to 2--

  • this is if and only if-- n squared greater than

  • or equal to 4.

  • Is that true?

  • Is n only bigger than 2 if and only

  • if n squared is bigger than 4?

  • It's false.

  • What's an example of n for which that's false?

  • Negative, all right?

  • So it's false.

  • n equals negative 3, all right?

  • Negative 3 squared is bigger than or equal to 4,

  • but negative 3 is not bigger than or equal to 2.

  • And in fact this if and only if means you

  • have to have an implication both ways.

  • So you have to check both ways for it.

  • So let's do the truth table-- extend this truth table out

  • here to do the truth table for p if and only if q.

  • So here are p and q.

  • Is q implies p true for this row?

  • Does true imply true?

  • Yeah.

  • False implies true?

  • That's true.

  • True does not apply false.

  • That's false.

  • And false implies false.

  • And so now, we can see where p is if and only if q.

  • If they're both true, then it's true here.

  • What about here?

  • Is p true if and only if q is true in this case?

  • No, because p implies q is false, but q implies p is true.

  • So it's false.

  • False here.

  • I made a mistake there, right?

  • That was true-- oops.

  • And true if and only if true, OK.

  • They're both true, so we're OK.

  • So p if and only if q is true when they're both true

  • or both false.

  • And that's it.

  • If they're different, then it's not true.

  • The key here is to always check both ways.

  • So if you're asked to prove an if and only if,

  • you have to prove that way, and that way.

  • We've just done about 15 propositions.

  • Is every sentence a proposition?

  • Yes?

  • No?

  • AUDIENCE: No.

  • PROFESSOR: No.

  • What's an example of something that's no a proposition?

  • AUDIENCE: This statement is false.

  • PROFESSOR: A what?

  • AUDIENCE: This statement is false.

  • PROFESSOR: This statement is false.

  • That's true.

  • Well, it's true it's not a proposition.

  • Because if it were true, it wouldn't be false.

  • And if was false, then it'd be true

  • and you'd have a contradiction.

  • So it's neither true nor false.

  • What's a more simple example of something

  • that's not a proposition?

  • AUDIENCE: This is a tissue.

  • Isn't that a [INAUDIBLE]?

  • PROFESSOR: Ooh.

  • Boy, I would have said that's true in some world.

  • Because yeah, that's a tissue.

  • So it's a true statement.

  • AUDIENCE: Hello.

  • PROFESSOR: Hello.

  • That's good.

  • That's neither true or false, yeah.

  • A question.

  • Who are you-- neither true nor false.

  • So not everything is a proposition.

  • But in this course, pretty much everything

  • we deal with will be a proposition.

  • All right, so that's it for propositions.

  • Any questions on propositions?

  • Next, we're going to talk about axioms.

  • Now, the good news is that axioms are the same thing,

  • really, as propositions.

  • The only difference is that axioms are propositions

  • that we just assume are true.

  • An axiom is a proposition that is assumed to be true.

  • There's no proof that an axiom is true.

  • You just assume it because you think it's reasonable.

  • In fact, the word "axiom" comes from Greek.

  • It doesn't mean to be true.

  • It means to think worthy-- something

  • you think is worthy enough to be assumed to be true.

  • Now, a lot of times, you'll hear people say-- sometimes, we'll

  • even say it to you-- don't make assumptions

  • when you're doing math.

  • No, that's not true.

  • You have to make assumptions when you do math.

  • Otherwise, you can't do anything because you

  • have to start with some axioms.

  • The key in math is to identify what your assumptions are

  • so people can see them.

  • And the idea is that when you do a proof,

  • anybody who agrees with your assumptions or your axioms

  • can follow your proof.

  • And they have to agree with your conclusion.

  • Now, they might disagree with your axioms,

  • in which case, they're not going to buy your proof.

  • Now, there are lots of axioms used in math.

  • For example, if a equals b and b equals c, then a equals c.

  • There is no proof of that.

  • But it seems pretty good.

  • And so we just throw it in the bucket of axioms and use it.

  • Now, axioms can be contradictory in different contexts.

  • Here's a good example.

  • In Euclidean geometry, there's a central axiom that

  • says given a line L and a point p not on L,

  • there is exactly one line through p parallel

  • to L. You all saw this in geometry in middle school,

  • right?

  • You've got a point in a line.

  • There's exactly another line through the point

  • that's parallel to the line.

  • Now, there's also a field called spherical geometry.

  • And there, you have an axiom that contradicts this.

  • It says, given a line L and a point p not on L,

  • there is no line through p parallel to L on the sphere.

  • There's a field called hyperbolic geometry.

  • And there, there's an axiom that says,

  • given a line L and a point p not on L,

  • there are infinitely many lines through p parallel to L.

  • So how can this be?

  • Does that mean one of these fields is totally bogus,

  • or two of them are?

  • Because they've got contradictory axes.

  • That's OK.

  • Just whatever field you're in, state you're axioms.

  • And they do make sense in their various fields.

  • This is planar geometry.

  • This is on the sphere.

  • And this is on hyperbolic geometry.

  • They make sense in those contexts.

  • So you can have more or less whatever axioms you want.

  • There are sort of two guiding principles to axioms.

  • Axioms should be-- it's called consistent-- and complete.

  • Now, a set of axioms is consistent

  • if no proposition can be proved to be both true and false.

  • And you can see why that's important.

  • If you spend three weeks proving something's true,

  • and the next day, somebody proves it's also false,

  • I mean, the whole thing was pointless.

  • So it only makes sense if your axioms, as a group,

  • are consistent.

  • A set of axioms is said to be complete

  • if it can be used to prove every proposition is

  • either true or false.

  • Now, this is desirable because it means-- well,

  • you can solve every problem.

  • Everything is-- you can prove it's true,

  • or you can prove it's false.

  • You can get to the end.

  • Now, you'd think it shouldn't be too

  • hard to get a set of axioms that satisfies these two

  • basic properties.

  • You're allowed to choose whatever you want, really.

  • Just, you don't want to be creating contradictions.

  • And you want a set that's powerful enough

  • that allows you to prove everything is true or false,

  • one of the two.

  • Turned out not to be so easy to do this.

  • And in fact, many logicians spent their careers--

  • famous logicians-- trying to find

  • a set of axioms, just one set, that

  • was consistent and complete.

  • In fact, Russell and Whitehead are probably

  • the two most famous.

  • They spent their entire careers doing this,

  • and they never got there.

  • Then one day, this guy named Kurt Godel showed up.

  • And in the 1930s, he proved it's not possible

  • that there exists any set of axioms that are

  • both consistent and complete.

  • Now, this discovery devastated the field.

  • It was a huge discovery.

  • Imagine poor Russell and Whitehead.

  • They spent their entire careers going after this holy grail.

  • Then Kurt shows up and said, hey, guys.

  • There's no grail.

  • It doesn't exist.

  • And that's a little depressing-- pretty bad day

  • when that happened.

  • Now, it's an amazing result, because it

  • says if you want consistency-- and that's a must--

  • there will be true facts that you will never

  • be able to prove.

  • We're not going to prove that here.

  • It's proved in a logic course.

  • For example, maybe Goldbach's conjecture is true

  • and it is impossible to prove.

  • Now, we're going to try not to assign any

  • of those problems for homework.

  • And in fact, they do exist.

  • It's complicated.

  • You can state a problem that you can't prove is true or false.

  • And you may be thinking that from time to time.

  • Hey, it's one of those.

  • Remember when your parents told you if you work hard enough,

  • you can do anything?

  • They were wrong.

  • All right, that's enough for now.

  • And we'll do more of this next time.

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Lec 1|MIT 6.042J コンピュータサイエンスのための数学, 2010年秋学期 (Lec 1 | MIT 6.042J Mathematics for Computer Science, Fall 2010)

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    Justin に公開 2021 年 01 月 14 日
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