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Topic: Science > Philosophy
User: "Sir Frederick"
Date: 05 Apr 2004 06:16:37 AM
Object: On Mathematics
-In search of a formula
Math can't be pinned down to one set of rules, unusual number shows

http://www.dallasnews.com/sharedcontent/dws/news/healthscience/stories/040504dnlivmath.f6d1.html

07:28 PM CDT on Sunday, April 4, 2004
By TOM SIEGFRIED / The Dallas Morning News
Usually in life, compassion and understanding go hand in hand.
But not in mathematics. In math, the key to understanding is not compassion, it's compression.
It's the same with science. Understanding nature means describing the world in a concise way.
Scientists search for simple "laws of nature" with consequences that correspond to all the stuff
that happens in the world. The fewer the laws, the greater the degree of understanding.
Understanding means being able to explain more with less. And that's why physicists are so hot to
find the one equation that incorporates all the laws – a "theory of everything" that would fit on a
T-shirt. A century ago, mathematicians had similar dreams. The German mathematical giant David
Hilbert had proposed a quest for the math equivalent of a theory of everything – not a single law
of nature, but a set of basic propositions, or axioms, from which all mathematical truth could be
derived.
Anybody who has taken high school geometry knows the idea. You start with a few simple statements –
the shortest distance between two points is a straight line, for instance, or all right angles are
equal. Then, by applying the power of reason to such axioms, you can prove all sorts of things
about triangles and circles and angles that work without fail for surveying land or building
bridges or shooting billiard balls.
Other branches of math exploit the same strategy. A textbook full of mathematical truths can be
compressed into a few simple axioms. There was no reason, Hilbert believed, why all possible
mathematical truth could not be compressed into one set of axioms.
But during the past century, Hilbert's dream was repeatedly dashed. Today mathematicians have a
drastically different view of math's foundations. Truth, mathematicians now know, cannot be
confined in a closed mathematical cage. Math has its limits. But mathematicians are free to roam.

In a new book published online, IBM mathematician Gregory Chaitin tells the story of math's fall
from certainty. It's a personal tale of his own efforts to grasp the 20th century's greatest
mathematical insights, and how he then reformulated them. It's a story about the limits of
compression – and therefore the limits of understanding. Yet it tells a deep truth about how
understanding math really means understanding those limits – understanding what cannot be
compressed.
Dr. Chaitin's ultimate achievement resides in a single number that he calls omega. It's a number
whose precise value can never be known, yet it's a number whose value to mathematics is priceless.
And it's a number that proves that Hilbert's dream was impossible.
It wasn't the first such proof. Hilbert's dream was effectively denied as early as 1931, when the
Austrian logician Kurt Gödel deduced a fatal flaw in Hilbert's reasoning. You can't find a system
to prove all mathematical truths, Gödel discovered, because some true statements can't be proved.
For example, "this statement can't be proved" is true, but you can't prove it, because then it
would be false.
Applied to sufficiently sophisticated math, Gödel's reasoning showed that no axiom system could be
complete – it would contain true statements that were not provable within the system. So Hilbert
was out of luck.
And then, the British mathematician Alan Turing showed in 1936 that there are some problems that no
computer can solve, no matter how well you program it. Specifically, you can't prove for sure
whether a program that keeps running and running will ever eventually stop. It's another way of
destroying Hilbert's dream. If you had a complete axiom system for all math, it would be able to
tell you if that program would halt.
So there's no way to capture all mathematical truth in one system of axioms. Math cannot be caged.
It has to evolve, adding new principles and axioms if necessary, Dr. Chaitin declares in his book,
titled Meta Math! "And this means," he writes, "that the idea of absolute certainty in mathematics
becomes untenable."

As a teenager, Dr. Chaitin was fascinated by such proofs but didn't really think they told the
whole story. He embarked on his own quest to understand math's incompleteness more completely. And
in so doing he reinvented some old ideas, and came up with a few new ones of his own, based on the
notion of randomness.
While a high school sophomore, Dr. Chaitin conceived of a new (he thought) way to understand what
it means to be random. Something is random if it can't be compressed, if there is no simpler
explanation than the thing itself, he realized.
As it turns out, a similar idea had been expressed centuries earlier by the German
philosopher-mathematician Gottfried Wilhelm von Leibniz. Leibniz believed that natural phenomena
were not random, but rather reflected the perfection of the mind of God. A perfect description of
reality should be much more compressed than the phenomena themselves. Conciseness was next to
godliness.
Though unaware of Leibniz's views on compression, Dr. Chaitin knew all about another Leibniz
invention – the binary number system, in which all numbers could be expressed with 0s and 1s. It's
the way that computers measure information today. A 0 or 1 is a bit, and chunks of bits make a
byte.
Building on his high-school insights, Dr. Chaitin realized that quantifying randomness meant
quantifying information. The more random something is, the more 0s and 1s you need to describe it.
You can translate any number into 0s and 1s. But you can also program a computer to write it out
for you. Here's the key idea: If the shortest computer program that can produce the number is as
long as the number, then that number is random. If the computer program is shorter than the number,
you've compressed it. So you understand something about the number, and therefore it isn't random.
Similarly, axioms are like a short computer program that gives more output than you put in. In
fact, you could imagine translating a whole system of axioms into a program that spits out all the
theorems, the consequences of the axioms. That's basically what Hilbert wanted to do. But it can't
be done. Some things, as Turing showed, can't be computed.

Turing's proof called into question some basic ideas about numbers. The counting numbers (or
integers) are simple enough – 0, 1, 2, etc. But what about the numbers in between? There are
fractions, for example, like one-half. But there are also numbers between the fractions, numbers
that mathematicians refer to as "real." In reality, though, those real numbers seem rather
imaginary.
The key idea underlying real numbers is that between any two there is always another one, and then
another, ad infinitum. Reality as described by real numbers is therefore continuous – no gaps, no
jumps. But some scientists doubt that real numbers have anything to do with natural reality.
Perhaps reality is not smooth and continuous, but digital, like the 0s and 1s used by computers.
"There are some intriguing hints," writes Dr. Chaitin, "that this particular universe may in fact
be a discrete digital universe, not a continuous analog universe."
One of those hints, he says, is how hard it is to get a grip on a real number. If you put all real
numbers between 0 and 1 in a hat, and plucked one out, the odds are certain that it will be random
– a number that can't be compressed. And so it can't be computed.
True, some real numbers are computable, but they are infinitely less common, and therefore the odds
are zero that you would ever pluck one from a hat by chance. Instead you'll get one that no
computer program, no axiom system, could generate.
And you can't even describe it, or give it a name. The set of all names that an axiom system can
generate is smaller than the number of uncomputable numbers. There are infinitely more real numbers
than there are names.
But there is one example of a real number that can be named – Dr. Chaitin's omega. Omega proves
incompleteness again, even more deeply than before. It's a specific number that is truly random.
It's a number that cannot be generated by a program smaller than itself. It is, in other words, a
mathematical truth that cannot be deduced from an axiom system, and therefore no axiom system can
be complete.

Dr. Chaitin's omega is equal to the odds that a computer program will eventually halt. Remember, as
Turing proved, you can never know for sure whether a program will stop running. But you can figure
the odds, simply by testing all possible computer programs.
You can imagine how it might be done. Start by writing down all the possible computer programs as
sequences of 0s and 1s. Put them in a hat. Then pick a program at random and run it to see if it
halts. If it does, determine the probability of picking that program by chance. (That's easy – it's
the same as the chance of getting that string of 0s and 1s by flipping a coin, heads giving 1 and
tails giving 0.) If you add up the probabilities for all the programs that halt, you get omega.
But that would take forever. To find an approximate value of omega, though, you can test the
programs in order of size, starting with the smallest. You can get the first few digits of omega in
this way. If you keep going, you can get closer and closer to its actual value, but you can't get
it exactly because it has an infinite number of digits.
And here's the real kicker. Because you've already used the smallest programs to find some digits
of omega, you can't find a program smaller than omega to determine more digits. No system of axioms
smaller than omega can produce omega. The individual digits, the 0s and 1s of omega, are
mathematical facts, yet they are unconnected to anything else in the structure of mathematics. The
digits of omega are true for no reason simpler than themselves.
From here, Dr. Chaitin's story gets complicated. He can show how the randomness of omega can be
related to equations containing only integers, further questioning the meaningfulness of all those
other uncomputable non-integer real numbers.
But omega is truly meaningful. It contains information about the chances that a computer program
will halt. It tells you that the probability of halting is truly random, proving yet again – but in
a new way – that the halting problem is unsolvable. Omega is therefore a meaningful, identifiable
real number that is nevertheless random and incalculable.
"So the world of mathematical truth has infinite complexity," writes Dr. Chaitin, even though any
given system of axioms is necessarily limited, and incomplete.
And the moral, he says, is that no single system of axioms will suffice for understanding (or
compressing) mathematics.
"We've got to keep adding new axioms, new rules of inference, or some other kind of new
mathematical information to the foundations of our theory," he asserts. Progress requires finding
out new things "that cannot be deduced from what we already know."
So mathematicians need intuition. And mathematics must embody creative thought.
"The essence of math resides in its creativity," writes Dr. Chaitin, "in imagining new concepts, in
changing viewpoints, not in mindlessly and mechanically grinding away deducing all the possible
consequences of a fixed set of rules and ideas."
So the deepest lesson of understanding via compression may be that some things cannot be
compressed. And the randomness that results, it seems, enables the existence of creativity in the
universe.
E-mail

1686
Gottfried Wilhelm
von Leibniz,
inventor of the binary (0 and 1) system of numbers, observes that simple laws can describe
regularities underlying the complexity of the world, but random information requires a lengthier
description.
.

User: "Immortalist"

Title: Re: On Mathematics 05 Apr 2004 10:41:49 AM
"Sir Frederick" <mmcneill@fuzzysys.com> wrote in message
news:40714015.4CCFFA83@fuzzysys.com...


-In search of a formula
Math can't be pinned down to one set of rules, unusual number shows

http://www.dallasnews.com/sharedcontent/dws/news/healthscience/stories/0405

04dnlivmath.f6d1.html


07:28 PM CDT on Sunday, April 4, 2004

By TOM SIEGFRIED / The Dallas Morning News

Usually in life, compassion and understanding go hand in hand.

But not in mathematics. In math, the key to understanding is not

compassion, it's compression.


It's the same with science. Understanding nature means describing the

world in a concise way.

Scientists search for simple "laws of nature" with consequences that

correspond to all the stuff

that happens in the world. The fewer the laws, the greater the degree of

understanding.

Understanding means being able to explain more with less. And that's why

physicists are so hot to

find the one equation that incorporates all the laws - a "theory of

everything" that would fit on a

T-shirt. A century ago, mathematicians had similar dreams. The German

mathematical giant David

Hilbert had proposed a quest for the math equivalent of a theory of

everything - not a single law

of nature, but a set of basic propositions, or axioms, from which all

mathematical truth could be

derived.

Anybody who has taken high school geometry knows the idea. You start with

a few simple statements -

the shortest distance between two points is a straight line, for instance,

or all right angles are

equal. Then, by applying the power of reason to such axioms, you can prove

all sorts of things

about triangles and circles and angles that work without fail for

surveying land or building

bridges or shooting billiard balls.

Other branches of math exploit the same strategy. A textbook full of

mathematical truths can be

compressed into a few simple axioms. There was no reason, Hilbert

believed, why all possible

mathematical truth could not be compressed into one set of axioms.

But during the past century, Hilbert's dream was repeatedly dashed. Today

mathematicians have a

drastically different view of math's foundations. Truth, mathematicians

now know, cannot be

confined in a closed mathematical cage. Math has its limits. But

mathematicians are free to roam.


.

In a new book published online, IBM mathematician Gregory Chaitin tells

the story of math's fall

from certainty. It's a personal tale of his own efforts to grasp the 20th

century's greatest

mathematical insights, and how he then reformulated them. It's a story

about the limits of

compression - and therefore the limits of understanding. Yet it tells a

deep truth about how

understanding math really means understanding those limits - understanding

what cannot be

compressed.

If tis maths which falls, then, tis the fall of the 20th century
ignoramouses since their fall merely "goes back" to Kant and others who have
the proper view. Therefore tis no fall back at all but a refutation of
dickheads and science.

Dr. Chaitin's ultimate achievement resides in a single number that he

calls omega. It's a number

whose precise value can never be known, yet it's a number whose value to

mathematics is priceless.

And it's a number that proves that Hilbert's dream was impossible.

It wasn't the first such proof. Hilbert's dream was effectively denied as

early as 1931, when the

Austrian logician Kurt Gödel deduced a fatal flaw in Hilbert's reasoning.

You can't find a system

to prove all mathematical truths, Gödel discovered, because some true

statements can't be proved.

For example, "this statement can't be proved" is true, but you can't prove

it, because then it

would be false.

Applied to sufficiently sophisticated math, Gödel's reasoning showed that

no axiom system could be

complete - it would contain true statements that were not provable within

the system. So Hilbert

was out of luck.

And then, the British mathematician Alan Turing showed in 1936 that there

are some problems that no

computer can solve, no matter how well you program it. Specifically, you

can't prove for sure

whether a program that keeps running and running will ever eventually

stop. It's another way of

destroying Hilbert's dream. If you had a complete axiom system for all

math, it would be able to

tell you if that program would halt.

So there's no way to capture all mathematical truth in one system of

axioms. Math cannot be caged.

It has to evolve, adding new principles and axioms if necessary, Dr.

Chaitin declares in his book,

titled Meta Math! "And this means," he writes, "that the idea of absolute

certainty in mathematics

becomes untenable."

.

As a teenager, Dr. Chaitin was fascinated by such proofs but didn't really

think they told the

whole story. He embarked on his own quest to understand math's

incompleteness more completely. And

in so doing he reinvented some old ideas, and came up with a few new ones

of his own, based on the

notion of randomness.

While a high school sophomore, Dr. Chaitin conceived of a new (he thought)

way to understand what

it means to be random. Something is random if it can't be compressed, if

there is no simpler

explanation than the thing itself, he realized.

As it turns out, a similar idea had been expressed centuries earlier by

the German

philosopher-mathematician Gottfried Wilhelm von Leibniz. Leibniz believed

that natural phenomena

were not random, but rather reflected the perfection of the mind of God. A

perfect description of

reality should be much more compressed than the phenomena themselves.

Conciseness was next to

godliness.

Though unaware of Leibniz's views on compression, Dr. Chaitin knew all

about another Leibniz

invention - the binary number system, in which all numbers could be

expressed with 0s and 1s. It's

the way that computers measure information today. A 0 or 1 is a bit, and

chunks of bits make a

byte.

Building on his high-school insights, Dr. Chaitin realized that

quantifying randomness meant

quantifying information. The more random something is, the more 0s and 1s

you need to describe it.


You can translate any number into 0s and 1s. But you can also program a

computer to write it out

for you. Here's the key idea: If the shortest computer program that can

produce the number is as

long as the number, then that number is random. If the computer program is

shorter than the number,

you've compressed it. So you understand something about the number, and

therefore it isn't random.


Similarly, axioms are like a short computer program that gives more output

than you put in. In

fact, you could imagine translating a whole system of axioms into a

program that spits out all the

theorems, the consequences of the axioms. That's basically what Hilbert

wanted to do. But it can't

be done. Some things, as Turing showed, can't be computed.

.

Turing's proof called into question some basic ideas about numbers. The

counting numbers (or

integers) are simple enough - 0, 1, 2, etc. But what about the numbers in

between? There are

fractions, for example, like one-half. But there are also numbers between

the fractions, numbers

that mathematicians refer to as "real." In reality, though, those real

numbers seem rather

imaginary.

The key idea underlying real numbers is that between any two there is

always another one, and then

another, ad infinitum. Reality as described by real numbers is therefore

continuous - no gaps, no

jumps. But some scientists doubt that real numbers have anything to do

with natural reality.

Perhaps reality is not smooth and continuous, but digital, like the 0s and

1s used by computers.


"There are some intriguing hints," writes Dr. Chaitin, "that this

particular universe may in fact

be a discrete digital universe, not a continuous analog universe."

One of those hints, he says, is how hard it is to get a grip on a real

number. If you put all real

numbers between 0 and 1 in a hat, and plucked one out, the odds are

certain that it will be random

- a number that can't be compressed. And so it can't be computed.

True, some real numbers are computable, but they are infinitely less

common, and therefore the odds

are zero that you would ever pluck one from a hat by chance. Instead

you'll get one that no

computer program, no axiom system, could generate.

And you can't even describe it, or give it a name. The set of all names

that an axiom system can

generate is smaller than the number of uncomputable numbers. There are

infinitely more real numbers

than there are names.

But there is one example of a real number that can be named - Dr.

Chaitin's omega. Omega proves

incompleteness again, even more deeply than before. It's a specific number

that is truly random.

It's a number that cannot be generated by a program smaller than itself.

It is, in other words, a

mathematical truth that cannot be deduced from an axiom system, and

therefore no axiom system can

be complete.

.

Dr. Chaitin's omega is equal to the odds that a computer program will

eventually halt. Remember, as

Turing proved, you can never know for sure whether a program will stop

running. But you can figure

the odds, simply by testing all possible computer programs.

You can imagine how it might be done. Start by writing down all the

possible computer programs as

sequences of 0s and 1s. Put them in a hat. Then pick a program at random

and run it to see if it

halts. If it does, determine the probability of picking that program by

chance. (That's easy - it's

the same as the chance of getting that string of 0s and 1s by flipping a

coin, heads giving 1 and

tails giving 0.) If you add up the probabilities for all the programs that

halt, you get omega.


But that would take forever. To find an approximate value of omega,

though, you can test the

programs in order of size, starting with the smallest. You can get the

first few digits of omega in

this way. If you keep going, you can get closer and closer to its actual

value, but you can't get

it exactly because it has an infinite number of digits.

And here's the real kicker. Because you've already used the smallest

programs to find some digits

of omega, you can't find a program smaller than omega to determine more

digits. No system of axioms

smaller than omega can produce omega. The individual digits, the 0s and 1s

of omega, are

mathematical facts, yet they are unconnected to anything else in the

structure of mathematics. The

digits of omega are true for no reason simpler than themselves.

From here, Dr. Chaitin's story gets complicated. He can show how the

randomness of omega can be

related to equations containing only integers, further questioning the

meaningfulness of all those

other uncomputable non-integer real numbers.

But omega is truly meaningful. It contains information about the chances

that a computer program

will halt. It tells you that the probability of halting is truly random,

proving yet again - but in

a new way - that the halting problem is unsolvable. Omega is therefore a

meaningful, identifiable

real number that is nevertheless random and incalculable.

"So the world of mathematical truth has infinite complexity," writes Dr.

Chaitin, even though any

given system of axioms is necessarily limited, and incomplete.

And the moral, he says, is that no single system of axioms will suffice

for understanding (or

compressing) mathematics.

"We've got to keep adding new axioms, new rules of inference, or some

other kind of new

mathematical information to the foundations of our theory," he asserts.

Progress requires finding

out new things "that cannot be deduced from what we already know."

So mathematicians need intuition. And mathematics must embody creative

thought.


"The essence of math resides in its creativity," writes Dr. Chaitin, "in

imagining new concepts, in

changing viewpoints, not in mindlessly and mechanically grinding away

deducing all the possible

consequences of a fixed set of rules and ideas."

So the deepest lesson of understanding via compression may be that some

things cannot be

compressed. And the randomness that results, it seems, enables the

existence of creativity in the

universe.

E-mail



1686


Gottfried Wilhelm

von Leibniz,

inventor of the binary (0 and 1) system of numbers, observes that simple

laws can describe

regularities underlying the complexity of the world, but random

information requires a lengthier

description.

.


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