The book will never die.

A lot has been written about real paper books versus ebooks. Both have their distinct advantages and disadvantages. I have to admit that I read mostly ebooks. They are cheaper and easier to get, store and carry. Mathematics ebooks often have the PDF format. So you need a reader that can handle PDFs. If you use your PC or laptop than a PDF reader is all you need. Most people know Adobe Reader but there are much better programs than Adobe around. With free readers, just like Adobe. My PDF reader of choice is Foxit Reader 5. What I particularly like about Foxit is that it is lightweight, i.e. loads and acts fast. Foxit uses tabbed reading, like internet browsers. If you were in the middle of five books, close Foxit, the program nicely remembers which books you were reading and on what page you left. Most of all, I like the feature that I can highlight what I read. It is almost as if I was reading in a paper book.

Link:
- Foxit Reader 5.

Hypercomputation

Only recently lightspeed as the ultimate limit of speed got challenged. It seems they have been challenging the Turing Machine for a while too.

If you start with studying mathematics you are only three or four centuries behind on contemporary mathematics. That's quite a lot of catching up to do. - Some fields started their development in the previous century though. Like mathematical logic, a field I have been studying this year, and have written about so now and then in this blog. Part of mathematical logic is the theory of computation which showed us what can be computed and what can't. That what can be computed is what can be computed on a Turing Machine, period. - That idea is challenged however in the theory of hypercomputation. A new field in mathematics which is trying to go beyond the limits of the Turing Machine.

A book with an overview of the theory is the following.

The mathematics of revolution

The Occupy Wall Street movement is spreading. It reminds me of Conway's Life game. It could spread enormously and still die out soon, or it could cause permanent change without real massive demonstrations. Nobody knows, nobody can predict this. Still, I think it will be very interesting to find mathematical patterns in global, Internet connected, demonstrations like this. I am sure mathematicians of government agencies are working on it.

If a government does not educate even one generation it is lost. It is in their own interest, it is in the interest of the ruling elite to give all citizens a good education. I think that rule fits all political systems. In the US however they use education to enslave people for the rest of their life to the bankers. Paying back student loans turns out to be very difficult. On top of that teachers get fired or are underpaid. - That does not seem right to me.

Primitive recursive function

Normally you calculate n factorial with Factorial[n] or short n!. Mathematica handles the details of the function for you and prints the result.

In the course M381 you have to prove that functions like factorial are a primitive recursive function. This basically means that the function can be defined only in terms of itself, add one, or set to zero. A primitive recursive definition of factorial would look as follows in Mathematica.

suc[n1_] := n1 + 1
add[n1_, 0] := n1
add[n1_, n2_] := suc[add[n1, n2 - 1]]
mul[n1_, 0] := 0
mul[n1_, n2_] := add[mul[n1, n2 - 1], n1]
fac[0] := suc[0]
fac[n_] := mul[n, fac[n - 1]]

As you can see no other Mathematica functions than "+ 1" and "= 0" are used. The functions suc, add, mul, fac are defined for the first time.

For example:
In[67]:= Factorial[6]
fac[6]

Out[67]= 720

Out[68]= 720
.

Comment on "From analog to brain computing ".

Mathematicians have a tendency to regard texts which are not written using 'protocol' as irrelevant. Long ago I wrote a note to a mathematician and his reply was that I should formulate my thoughts in 'standard mathematics'. I did my very best 'to make myself clear'. It was not enough. The thing is mathematicians lose their authority when they leave familiar territory. Well, at least I received a reply. ( Although that was all he did. And I haven't given up on the problem I was working on... )

The blog received a comment, containing what I, for the moment, call 'out-of-the-box' thinking. Non 'standard mathematics' at least. I have moved the comment to this post in an attempt to share this with as much as possible readers. I will reply. But later, I have to let it work on me first.

Regarding our active internal analog math...

I'm a civil/environmental engineer by education but I've been working off and on on a theory which takes the tact that all abstract math symbols and expressions are secondary and arise from a handful of internal analog "math" artifacts and processes. This may not be a very polite thing to say to a mathematician, but I am wondering if you have impressions along the same line?

It turns out that we all get energy to think and do math and other things from the respiration reaction (organics + oxygen -> water + carbon dioxide +energy). And basically, what that means, if you remember your biology or organic chemistry, is, body-wide, within our cells is a ~steady creative flow of about 10^20 water molecules per second -- coming from the 160 kg of O2 we each respire each year. Generally, each water molecule is sort of tetrahedral in shape with two positive and two negative vertices and so, it turns out that there are at least six ways each water molecule can orient within an enfolding field when it first comes into being at a respiration site. That also means that a chain of n-molecules can form in 6^n different ways. Thus a sequence of 12 molecules could form in 6^12, or about 2 billion different ways. A chain of eighteen molecules could associate with 6^18 or 10^14 different impressions. Now, in this analog math theory, I am assuming that repeating vibrations in the environment ought to result in formation of similar stacks and chains of structurally coded water molecules being formed. This gets us a rather crude image of the vibrations of our internal and external environment forming an internal echo or representation within this active internal analog "math", or "language".

I say it's active because the 6^n stacks of water molecules are really also structurally coded hydrogen-bonding packets and such things, when they unfurl, are connected with and influential in protein-formation and protein-folding, which is to say, memory formation and muscle movement, which is to say, in our case, ALL human expression, perhaps beginning with our nearly universal actions and impressions of counting each of our ten fingers and ten toes, and the like.

Bizarre stuff, huh? Lots of little internal Turin devices writing out structural coded signals.


I'm wondering if mathematicians are taught this type of internal analog math as the basis of the abstract math symbols and expressions, or if they are given different associations or impressions, perhaps leaving it that there is just an uncanny (and unknown) relationship between much or all of nature and math?

Also, I vaguely see the similarity between 2^n binary or boolean math and the 6^n "multiple-state structural coding" that I've made up or stumbled onto. I expect the trend continues with starting with other polyhedra which have limited orientations "within enfolding fields" -- when a containing structure is added. My general hunch is the initial condition IS actually significant for us and we can immediately get to multiple states (relevant to ~quantum mechanics/quantum gravity) by starting with tetrahedron and adding the enfolding cube container, rather than the way it's done presently of beginning with the xyz-cubic framework and adding variants.

Initial conditions do matter in mathematics, don't they?

Best regards,
Ralph Frost

@frostscientific
http://magtet.com/images/phpshow.php

Thanks you, Ralph Frost.

Who am I ?

I am the square root of -1. Who am i?

and of course from GEB:

This sentence contains ten words, eighteen syllables, and sixty-four letters.

From Mathworld - Self-Recursion

From analog to brain computing

Before digital computing took over completely, analog computing was dominant for a short while. An analog computer is based on the creation of a model which represents the problem to be solved. But mathematical models of problems can be created of ( almost ) any problem and these models can be implemented on a digital computer. A digital computer is nothing more than a convenient, fast, Turing Machine or equivalent thereof, i.e. the URM or Abacus. And from Mathematical Logic ( Goedel ) we know that these systems have its limitations. It is theoretically impossible to create a program that solves all mathematical problems. - But physicists and biologists say ( and why should we disagree? ) that we -are- computer ( brain ) controlled machines.

Is that a paradox? Humans can do more than computers, we can solve mathematical problems, in fact we -created- the concept of a 'Turing Machine'. This leads us to Roger Penrose. In The Emperor's New Mind, 1999 he claims that artificial intelligence in computers is impossible. He argued that the human brain must exploit a type of physics that he described as 'non-computable'. By this he means beyond algorithmic computing, and thus digital computing.

A picture that keeps fascinating me is that of a predator bird flying high over its prey before, at a carefully -chosen- moment, it makes the dive and following kill. And this is all done with a tiny bird brain. The best comparable thing made by humans thus far is the drone. A huge flying case loaded with bombs operated by a battery of digital computers assisted by human -computers-. Although humans have created a model of a flying bird, it is operated by a human computer on the ground.



Analog computers were special purpose computers, designed to solve one specific problem. A predator bird will never be able to learn new behavior, it cannot be trained to live with chickens. Not immediately anyaway, if ´evolution´ made the bird.

Let me summarize before this turns into a rant.
- There are other models of computing than the Turing machine, i.e. analog computing, brain computing.
- Digital computing is superior over analog computing, brain computing is superior over digital computing.
- Analog and digital computing are human creations we fully understand.
- We don't understand brain computing (yet?).
- Mathematical logic and computability theory study algorithmic ( digital ) computing.

Goedels theorems are somewhat like Russell's paradox in set theory. Goedel's incompleteness theorems are statements about logic and number theory deduced in and with the rules of logic.

Heatwave : day off study.

Took a day off study today. Have been putting a lot of time in studying lately. Felt like work instead of fun. We have a mini-heatwave in The Netherlands. For the 1st of October it was the hottest day ever ( since recorded weather anyway ). I don't like summers, especially when they turn up in my favorite season autumn. I mean, I think everybody has been off-schedule today. - Tomorrow, I take a day off as well: I really missed working with Mathematica. I got really interested in the foundations of computer science lately. Will read about formal languages, grammars and parsers tomorrow. And of course will have a look at the Mathematica built Lisp interpreter. - I am working on a program myself, SceneGraphica, I need to spend time on that as well. I think I will start all over. Nothing will be lost though. I wouldn't have had the ideas I have now without the effort put in the early versions.

The Limits of Mathematics ( or: a Lisp interpreter in Mathematica )

( ... ) mathematics because it is an extremely difficult road to traverse. The terrain is extremely demanding. The amount of work and concentration required to build the foundation necessary to continue extending the framework is immense. ( ... ) - David Andrews

Mathematics, as if you have never seen a skyscraper and are traversing the streets of Manhattan. With that mindset, you can only think that people -walk- to the 60th floor... Anyway, feeling overwhelmed by the sheer size and complexity of maths is not going to help. Only people willing to teach, without ulterior selfish motives, can help. One can write a book about mathematics to impress peers, as a way to meet publication quotas or to -teach-. Like the book The Limits of Mathematics does for example. It is a clear taste of the best mathematics has to offer, an invitation to go on to the next level.

The table of contents says it all:
- Randomness in arithmetic and the decline and fall of reductionism in pure mathematics
- Elegant LISP programs
- An invitation to algorithmic information theory
- The limits of mathematics
- Appendix. LISP interpreter in Mathematica

The appendix contains the source code of a Lisp interpreter coded in Mathematica. I love that. But the book starts with a clear description of the massive changes taking place in ( the thinking about ) mathematics during the first half of the twentieth century, from Hilbert to Turing.

Goedel, Escher, Bach - Lecture 6

In the first six minutes or so Curry gives a fairly good summary of Goedel's Theorem. Unfortunately this is the summary of the previous lecture which was not recorded. It seems nothing is free, not even free video lectures because it turns out the best ( not implying the rest is good ) is missing.

After rushing through formal stuff he wastes five minutes about a three-layer stupid joke about a book he had not read.

I quick-scanned through the rest of the video. Not worth watching, really. Too bad. I looked forward to this.

The take home message of the course. All provable things are true but not necessarily al true things are provable.
Justin Curry

Now that I am mostly through all M381 stuff I am glad it included mathematical logic. I would -not- have done it as a stand-alone course. Logic is hard in the beginning, like most new subjects. It needs time to work on you. I will get back to this in the next M381 post.

Previous posts on the series:
- Lecture 1
- Lecture 2
- Lecture 3
- Lecture 4
- Lecture 5

About M381 (1)

Regular readers of this blog know that I have a sort-of rage-button like the Hulk: it is called MathCad. Thank God, I have the anti-dote almost always open and ready: Mathematica. I am not going to repeat why MathCad is a danger to your mental health, but I have to press the MathCad button at least once.

In almost all mathematics courses you can do at the Open University there is software involved. They either deliver a standard package, or ship custom software especially developed for the course ( i.e. MT365 ). The house-package of the Mathematics Department of the Open University is MathCad, version 2001. I have argued that MathCad alone is a reason -not- to choose for the Open University. What a disgrace...

( Calming down. )

They do however recognize that software, computers, tools are relevant in mathematics. Especially in Number Theory computers are used in active research. Another area where they use software in active research is: mathematical logic. Stronger: research in Number Theory is impossible without computers.

These facts are not even mentioned in M381. There are many open source tools available for Number Theory, even more for Mathematical Logic. Not a word about it in M381. One, if not -the- reason is the fact that course development in the Open University is done in a project organization. A project is created with the objective to create course X which will then be used for the next 10 or so years. It is exactly the opposite of what one would expect of a university education. It is not reasonable to expect the Open University to be at the forefront of mathematical research. Simply because other universities in the UK have that role. But it is reasonable to expect more than a static expose of 19th century Gauss number theory and early 20th century logic from Church, Turing and Goedel. In fact, the field is presented as abstract and of theoretical importance only. But Number Theory and Mathematical Logic are extremely relevant and applicable in many industries! But I did not learn that from the course and that is sad.

It took me a lot of work but I found some relevant learning tools in the fields of number theory and mathematical logic. More about those later in this blog.

(*) - I may have misunderstood the concept of 'University' in the UK. I think many universities in the UK are what we call in the Netherlands 'schools'. They deliver professionals with a degree in all fields through excellent education but they don't do research and so on. They don't add to the body of knowledge. They process and transfer knowledge. That description fits the Open University as well. - A marketing issue is that students like to have a 'university' education. And marketing people love empty heads boxes, they have a fancy word for it too: the 'packaging'. Does that make sense?

Goedel, Escher, Bach - Lecture 5

A few months ago I started to watch the MIT video lecture series on Goedel, Escher, Bach. Due to time constraints I wasn't able to complete watching the entire series. Today I continued with watching lecture 5. I have learned quite a lot on the subject through M381 and I am about to really 'get it' as far as the Goedel Incompleteness Theorems are concerned. My first reading of GEB took months and now parts of the book begin to look simple. If you don't know what I mean browse through a mathematics book you thought was hard, a few years ago. It often seems if there is 'nothing in the book'. The odd thing with Goedel ( and with all mathematics, I suppose ) is that in your mind you think you can explain it to a laymen in one or two sentences. ( It is -that- simple, I am afraid. ) The power of mathematics is that it can capture an entire knowledge tree in a single word. That word remains meaningless without understanding of all the words in the knowledge tree.

A bit about lecture 5.

Dress shows arrogance

I wonder if Justin Curry would go to a job interview in that Club Med outfit. Students are paying customers ( and a pool of cheap labor for lucrative research deals the university makes ) deserving respect from teaching staff.

Formal number theory ( as in M381 )

Justin talks about Typographic Number Theory, ( formal number theory in M381 ). For example $$\forall x ( \neg x = \mathbf{0} ( \exists y x = y') )$$ can be interpreted as

"Every x that is not equal to 0 is the successor of some y."

Leibniz was the first to propose a formal language for number theory. He asked whether it was true that an algorithm could decide if a statement in number theory was true. - Although in M381 this question is answered negatively that does not mean computers can not play a role in proving mathematical propositions. There is an abundance of ( open source ) software for proving theorems.

( Not in video: ) Isabelle a formal proof theory assistant has been used in testing an operating system kernel written in C and assembler. It not only verified that the spec was implemented correctly but it also discovered hundreds (...) of programming and design (...) errors which were not found by traditional testing methods.

Previous posts on the series:
- Lecture 1
- Lecture 2
- Lecture 3
- Lecture 4