Back in the 60s, Kolmogorov and Chaitin independently found a way to connect information theory with computability theory. (They built on earlier work by Solomonoff.) Makes sense: flip a fair coin an infinite number of times, and compare the results with the output of a program. If you don’t get a 50% match, that’s pretty suspicious!
Three aspects of the theory strike me particularly. First, you can define an entropy function for finite bit strings, H(x), which shares many of the formal properties of the entropy functions of physics and communication theory. For example, there is a probability distribution P such that H(x)=−log P(x)+O(1). Next, you can give a precise definition for the concept “random infinite bit string”. In fact, you can give rather different looking definitions which turn out be equivalent; the equivalence seems “deep”. Finally, we have an analog of the halting problem: loosely speaking, what is the probability that a randomly chosen Turing machine halts? The binary expansion of this probability (denoted Ω by Chaitin) is random.
I wrote up my own notes on the theory, mostly to explain it to myself, but perhaps others might enjoy them.
The first sentence of Pollard’s review sums up my feelings perfectly: “This rewarding, exasperating book…” On balance, I found it more exasperating than rewarding. But it does have its charms.
I participated in a meetup group that went through the first two parts of S&F. My fellow participants possessed considerable mathematical knowledge and sophistication, but had only slight prior acquaintance with mathematical logic and none with axiomatic set theory. (The opinions here are strictly my own, but they reflect my experience in the meetup.) If I had just skimmed the book, glancing at familiar material, I would probably have a more positive impression.
I wrote an extensive set of notes for the meetup. This post is basically the last section of those notes.
I will begin with the book’s minuses, so as to end on a positive note.
Filed under Logic, Reviews
If you’re reading this blog, you probably know Stirling’s formula:
It’s not hard to estimate n! to within a factor of √2; I wrote up a note on this and even easier derivations. It’s quite a bit harder to show that the ratio of the two sides approaches a definite limit as n→∞ and that this limit is 1. You can find a variety of proofs in a number of places, one being Ahfors’ Complex Analysis. I wrote up a note about this too, expanding on some of the details.
Incidentally, the two sides are asymptotic not just for positive integers n. Replace n! with Γ(z+1) on the left, and both n‘s with z‘s on the right. Allow z to go to infinity in the complex plane, while staying at least a fixed finite distance to the right of the imaginary axis. Then the two sides remain asymptotic. Ahfors proves this stronger result, and uses it to derive the integral form for the Γ function.
Note that if you replace the n‘s with z‘s, you have zz on the right. So you’ve got to worry about branches of the complex logarithm (since zz is defined as ez log z). The note deals with this (and other things).
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MW: I made up a little chart to help me keep all these adjoints straight:
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MW: Time to start on Enayat’s paper in earnest. First let’s review his notation. M is a model of T, a recursively axiomatizable extension of ZF. He writes for the ω of M equipped with addition and multiplication, defined in the usual way as operations on finite ordinals. So is what he calls a T-standard model of PA.
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MW: So let’s see. Last time we talked about the functor B from the category FinSet to the category BoolAlg of boolean algebras. Liberal infusions of coffee convinced you that B is covariant; I accidentally suggested it was contravariant. I think I’ve come round to your position, but I still have a couple of things I want to say on the matter. If it won’t be too confusing for our readers.
JB: Okay. If we’re planning to talk more about the variance, it’s probably good to start out by getting the reader a bit confused. I used to always be confused about it myself. Then I finally felt I had it all straightened out. Then you shocked me by arguing that it worked the opposite way. Your argument was very sneaky.
These notes on Simple Sets are a grabbag about the simple sets of recursion theory. If you don’t know what those are, you probably are not interested, but the Wikipedia article is nice and short and gives the basics.
The last result uses the “shiny black box” (see below), which seems like cheating, but isn’t!
I wrote up the notes sometime in the 1980s based on two papers, and on a lecture by Michael Stob at MIT (reporting on joint work with Maas and Shore). They discuss effectively simple sets and promptly simple sets.