This chapter and the next contain a summary of material, mainly definitions, needed for later chapters, of a kind that can be found expounded more fully and at a more relaxed pace in introductory-level logic textbooks. Section 9.1 gives an overview of the two groups of notions from logical theory that will be of most concern: notions pertaining to formulas and sentences, and notions pertaining to truth under an interpretation. The former group of notions, called syntactic, will be further studied in section 9.2, and the latter group, called semantic, in the next chapter.

In the preceding several chapters we have introduced the intuitive notion of effective computability, and studied three rigorously defined technical notions of computability: Turing computability, abacus computability, and recursive computability, noting along the way that any function that is computable in any of these technical senses is computable in the intuitive sense. We have also proved that all recursive functions are abacus computable and that all abacus-computable functions are Turing computable. In this chapter we close the circle by showing that all Turing-computable functions are recursive, so that all three notions of computability are equivalent. It immediately follows that Turing's thesis, claiming that all effectively computable functions are Turing computable, is equivalent to Church's thesis, claiming that all effectively computable functions are recursive. The equivalence of these two theses, originally advanced independently of each other, does not amount to a rigorous proof of either, but is surely important evidence in favor of both. The proof of the recursiveness of Turing-computable functions occupies section 8.1. Some consequences of the proof of equivalence of the three notions of computability are pointed out in section 8.2, the most important being the existence of a universal Turing machine, a Turing machine capable of simulating the behavior of any other Turing machine desired. The optional section 8.3 rounds out the theory of computability by collecting basic facts about recursively enumerable sets, sets of natural numbers that can be enumerated by a recursive function. […]

In the preceding chapter we introduced the classes of primitive recursive and recursive functions. In this chapter we introduce the related notions of primitive recursive and recursive sets and relations, which help provide many more examples of primitive recursive and recursive functions. The basic notions are developed in section 7.1. Section 7.2 introduces the related notion of a semirecursive set or relation. The optional section 7.3 presents examples of recursive total functions that are not primitive recursive.

Ramsey's theorem is a combinatorial result about finite sets with a proof that has interesting logical features. To prove this result about finite sets, we are first going to prove, in section 26.1, an analogous result about infinite sets, and are then going to derive, in section 26.2, the finite result from the infinite result. The derivation will be an application of the compactness theorem. Nothing in the proof of Ramsey's theorem to be presented requires familiarity with logic beyond the statement of the compactness theorem, but at the end of the chapter we indicate how Ramsey theory provides an example of a sentence undecidable in P that is more natural mathematically than any we have encountered so far.

This chapter connects our work on computability with questions of logic. Section 11.1 presupposes familiarity with the notions of logic from Chapter 9 and 10 and of Turing computability from Chapters 3–4, including the fact that the halting problem is not solvable by any Turing machine, and describes an effective procedure for producing, given any Turing machine M and input n, a set of sentences Г and a sentence D such that M given input n will eventually halt if and only if Г implies D. It follows that if there were an effective procedure for deciding when a finite set of sentences implies another sentence, then the halting problem would be solvable; whereas, by Turing's thesis, the latter problem is not solvable, since it is not solvable by a Turing machine. The upshot is, one gets an argument, based on Turing's thesis for (the Turing–Büchi proof of) Church's theorem, that the decision problem for implication is not effectively solvable. Section 11.2 presents a similar argument–the Gödel-style proof of Church's theorem–this time using not Turing machines and Turing's thesis, but primitive recursive and recursive functions and Church's thesis, as in Chapters 6–7. The constructions of the two sections, which are independent of each other, are both instructive; but an entirely different proof, not dependent on Turing's or Church's thesis, will be given in a later chapter, and in that sense the present chapter is optional. […]

Suppose that a sentence A implies a sentence C. The Craig interpolation theorem tells us that in that case there is a sentence B such that A implies B, B implies C, and B involves no nonlogical symbols but such as occur both in A and in B. This is one of the basic results of the theory of models, almost on a par with, say, the compactness theorem. The proof is presented in section 20.1. The proof for the special case where identity and function symbols are absent is an easy further application of the same lemmas that we have applied to prove the compactness theorem in Chapter 13, and could have been presented there. But the easiest proof for the general case is by reduction to this special case, using the machinery for the elimination of function symbols and identity developed in section 19.4. Sections 20.2 and 20.3, which are independent of each other, take up two significant corollaries of the interpolation theorem, Robinson's joint consistency theorem and Beth's definability theorem.

Tarski's theorem tells us that the set V of (code numbers of) first-order sentences of the language in arithmetic that are true in the standard interpretation is not arithmetically definable. In section 23.1 we show that this negative result is poised, so to speak, between two positive results. One is that for each n the set Vn of sentences of the language of arithmetic of degree of complexity n that are true in the standard interpretation is arithmetically definable (in a sense of degree of complexity to be made precise). The other is that the class {V} of sets of natural numbers whose one and only member is V is arithmetically definable (in a sense of arithmetical definability for classes to be made precise). In section 23.2 we take up the question whether the class of arithmetically definable sets of numbers is an arithmetically definable class of sets. The answer is negative, according to Addison's theorem. This result is perhaps most interesting on account of its method of proof, which is a comparatively simple application of the method of forcing originally devised to prove the independence of the continuum hypothesis in set theory (as alluded to in the historical notes to Chapter 18).

The intuitive notion of an effectively computable function is the notion of a function for which there are definite, explicit rules, following which one could in principle compute its value for any given arguments. This chapter studies an extensive class of effectively computable functions, the recursively computable, or simply recursive, functions. According to Church's thesis, these are in fact all the effectively computable functions. Evidence for Church's thesis will be developed in this chapter by accumulating examples of effectively computable functions that turn out to be recursive. The subclass of primitive recursive functions is introduced in section 6.1, and the full class of recursive functions in section 6.2. The next chapter contains further examples. The discussion of recursive computability in this chapter and the next is entirely independent of the discussion of Turing and abacus computability in the preceding three chapters, but in the chapter after next the three notions of computability will be proved equivalent to each other.

In the preceding chapter we introduced the distinction between enumerable and nonenumerable sets, and gave many examples of enumerable sets. In this short chapter we give examples of nonenumerable sets. We first prove the existence of such sets, and then look a little more closely at the method, called diagonalization, used in this proof.

Modal logic extends ‘classical’ logic by adding new logical operators ▪ and ♦ for ‘necessity’ and ‘possibility’. Section 27.1 is an exposition of the rudiments of (sentential) modal logic. Section 27.2 indicates how a particular system of modal logic GL is related to the kinds of questions about provability in P we considered in Chapters 17 and 18. This connection motivates the closer examination of GL then undertaken in section 27.3.

By a model of (true) arithmetic is meant any model of the set of all sentences of the language L of arithmetic that are true in the standard interpretation N. By a nonstandard model is meant one that is not isomorphic to N. The proof of the existence of an (enumerable) nonstandard model of arithmetic is as an easy application of the compactness theorem (and the Löwenheim–Skolem theorem). Every enumerable nonstandard model is isomorphic to a nonstandard model M whose domain is the same as that of N, namely, the set of natural numbers; though of course such an M cannot assign the same denotations as N to the nonlogical symbols of L. In section 25.1 we analyze the structure of the order relation in such a nonstandard model. A consequence of this analysis is that, though the order relation cannot be the standard one, it at least can be a recursive relation. By contrast, Tennenbaum's theorem tells us that it cannot happen that the addition and multiplication relations are recursive. This theorem and related results will be taken up in section 25.2. Section 25.3 is a sort of appendix (independent of the other sections, but alluding to results from several earlier chapters) concerning nonstandard models of an expansion of arithmetic called analysis.

In the preceding chapter we introduced the notion of Turing computability. In the present short chapter we give examples of Turing-uncomputable functions: the halting function in section 4.1, and the productivity function in the optional section 4.2. If Turing's thesis is correct, these are actually examples of effectively uncomputable functions.