Gödel numbering for sequences
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In mathematics, a Gödel numbering for sequences provides us an effective way to represent each finite sequence of natural numbers as a single natural number. Of course, the embedding is surely possible set theoretically, but the emphasis is on the effectiveness of the functions manipulating such representations of sequences: the operations on sequences (accessing individual members, concatenation) can be "implemented" using total recursive functions, and in fact by primitive recursive functions.
It is usually used to build sequential “data types” in the realm of arithmetic-based formalizations of some fundamental notions of mathematics. It is a specific case of the more general idea of Gödel numbering.
For example, recursive function theory can be regarded as a formalization of the notion of an algorithm, and if we regard it as a programming language, we can mimic lists by encoding a sequence of natural numbers in a single natural number. To achieve this, we can use various number theoretic ideas; using the fundamental theorem of arithmetic is a straightforward way, but there are also more economic approaches, such as using the pairing function combined with the Chinese remainder theorem in a sophisticated way.
- 1 Gödel numbering
- 2 Accessing members
- 2.1 Gödel's β-function lemma
- 2.2 Proof that (coprimality) assumption for Chinese remainder theorem is met
- 2.3 The system of simultaneous congruences
- 2.4 Existence and uniqueness
- 2.5 Access of length
- 3 Notes
- 4 References
- 5 External links
Besides using Gödel numbering to encode unique sequences of symbols into unique natural numbers (i.e. place numbers into mutually exclusive or one-to-one correspondence with the sequences), we can use it to encode whole “architectures” of sophisticated “machines”. For example, we can encode Markov algorithms, or Turing machines into natural numbers and thereby prove that the expressive power of recursive function theory is no less than that of the former machine-like formalizations of algorithms.
Any such representation of sequences should contain all the information as in the original sequence—most importantly, each individual member must be retrievable. However, the length does not have to match directly; even if we want to handle sequences of different length, we can store length data as a surplus member, or as the other member of an ordered pair by using a pairing function.
We expect that there is an effective way for this information retrieval process in form of an appropriate total recursive function. We want to find a totally recursive function f with the property that for all n and for any n-length sequence of natural numbers , there exists an appropriate natural number a, called the Gödel number of the sequence, such that for all i where , .
There are effective functions which can retrieve each member of the original sequence from a Gödel number of the sequence. Moreover, we can define some of them in a constructive way, so we can go well beyond mere proofs of existence.
Gödel's β-function lemma
By an ingenious use of the Chinese remainder theorem, we can constructively define such a recursive function (using simple number-theoretical functions, all of which can be defined in a total recursive way) fulfilling the specifications given above. Gödel defined the function using the Chinese remainder theorem in his article written in 1931. This is a primitive recursive function.
Thus, for all n and for any n-length sequence of natural numbers , there exists an appropriate natural number a, called the Gödel number of the sequence such that .
Using a pairing function
Our specific solution will depend on a pairing function—there are several ways to implement the pairing function, so one method must be selected. Now, we can abstract from the details of the implementation of the pairing function. We need only to know its “interface”: let , K, and L denote the pairing function and its two projection functions, respectively, satisying specification
We shall not discuss and formalize the axiom for excluding alien objects here, as it is not required to understand the method.
Remainder for natural numbers
We shall use another auxiliary function that will compute the remainder for natural numbers. Examples:
It can be proven that this function can be implemented as a recursive function.
Using the Chinese remainder theorem
Implementation of the β function
Using the Chinese remainder theorem, we can prove that implementing as
We shall use this notation in the proof.
For proving the correctness of the above definition of the function, we shall use several lemmas. These have their own assumptions. Now we try to find out these assumptions, calibrating and tuning their strength carefully: they should not be said in an either superfluously sharp, or unsatisfactorily weak form.
Let be a sequence of natural numbers. Let m be chosen to satisfy
The first assumption is meant as
It is needed to meet an assumption of the Chinese remainder theorem (that of being pairwise coprime). In the literature, sometimes this requirement is replaced with a stronger one, e.g. constructively built with the factorial function, but the stronger premise is not required for this proof.
The second assumption does not concern the Chinese remainder theorem in any way. It will have importance in proving that the specification for is met eventually. It ensures that an solution of the simultaneous congruence system
- for each i where
A stronger assumption for m requiring automatically satisfies the second assumption (if we define the notation as above).
Proof that (coprimality) assumption for Chinese remainder theorem is met
In the section Hand-tuned assumptions, we required that
- . What we want to prove is that we can produce a sequence of pairwise coprime numbers in a way that will turn out to correspond to the Implementation of the β function.
remembering that we defined .
The proof is by contradiction; assume the negation of the original statement:
We know what “coprime” relation means (in a lucky way, its negation can be formulated in a concise form); thus, let us substitute in the appropriate way:
Using a “more” prenex normal form (but note allowing a constraint-like notation in quantifiers):
Because of a theorem on divisibility, allows us to also say
Resorting to the first hand-tuned assumption
Now we must resort to our assumption
The assumption was chosen carefully to be as weak as possible, but strong enough to enable us to use it now.
The assumed negation of the original statement contains an appropriate existential statement using indices ; this entails , thus the mentioned assumption can be applied, so holds.
Using an (object) theorem of the propositional calculus as a lemma
can be proven.
Reaching the contradiction
The negation of original statement contained
and we have just proved
should also hold. But after substituting the definition of ,
should also hold.
However, in the negation of the original statement p is existentially quantified and restricted to primes . This establishes the contradiction we wanted to reach.
End of reductio ad absurdum
By reaching contradiction with its negation, we have just proven the original statement:
The system of simultaneous congruences
We build a system of simultaneous congruences
We can write it in a more concise way:
Many statements will be said below, all beginning with "". To achieve a more ergonomic treatment, from now on all statements should be read as being in the scope of an quantification. Thus, begins here.
Let us chose a solution for the system of simultaneous congruences. At least one solution must exist, because are pairwise comprime as proven in the previous sections, so we can refer to the solution ensured by the Chinese remainder theorem. Thus, from now on we can regard as satisfying
which means (by definition of modular arithmetic) that
Resorting to the second hand-tuned assumption
Recall the second assumption, “”, and remember that we are now in the scope of an implicit quantification for i, so we don't repeat its quantification for each statement.
The second assumption implies that
Our original goal was to prove that the definition
is good for achieving what we declared in the specification of : we want to hold.
(The large scope of i ends here.)
Existence and uniqueness
We have just proven the correctness of the definition of : its specification requiring
is met. Although proving this was most important for establishing an encoding scheme for sequences, we have to fill in some gaps yet. These are related notions similar to existence and uniqueness (although on uniqueness, “at most one” should be meant here, and the conjunction of both is delayed as a final result).
Uniqueness of encoding, achieved by minimalization
Our ultimate question is: what number should stand for the encoding of sequence ? The specification declares only an existential quantification, not yet a functional connection. We want a constructive and algorithmic connection: a (total) recursive function that performs the encoding.
Totality, because minimalization is restricted to special functions
This gap can be filled in in a straightforward way: we shall use minimalization, and the totality of the resulting function is ensured by everything we have proven till now (i.e. the correctness of the definition of by meeting its specification). In fact, the specification
plays a role here of a more general notion (“special function”). The importance of this notion is that it enables us to split off the (sub)class of (total) recursive functions from the (super)class of partial recursive functions. In brief, the specification says that a function f  satisfying the specification
is a special function; that is, for each fixed combination of all-but-last arguments, the function f has root in its last argument:
The Gödel numbering function g can be chosen to be total recursive
Thus, let us choose the minimal possible number that fits well in the specification of the function:
It can be proven (using the notions of the previous section ) that g is (total) recursive.
Access of length
If we use the above scheme for encoding sequences only in contexts where the length of the sequences is fixed, then no problem arises. In other words, we can use them in an analogous way as arrays are used in programming.
But sometimes we need dynamically stretching sequences, or we need to deal with sequences whose length cannot be typed in a static way. In other words, we may encode sequences in an analogous way to lists in programming.
To illustrate both cases: if we form the Gödel numbering of a Turing machine, then the each row in the matrix of the “program” can be represented with tuples, sequences of fixed length (thus, without storing the length), because the number of the columns is fixed. But if we want to reason about configuration-like things (of Turing-machines), and specifically if we want to encode the significant part of the tape of a running Turing machine, then we have to represent sequences together with their length. We can mimic dynamically stretching sequences by representing sequence concatenation (or at least, augmenting a sequence with one more element) with a totally recursive function.
Length can be stored simply as a surplus member:
The corresponding modification of the proof is straightforward, by adding a surplus
to the system of simultaneous congruences (provided that the surplus member index is chosen to be 0). Also, the assumptions have to be modified accordingly.
- Monk 1976: 56–58
- Csirmaz 1994: 99–100 (see online)
- Monk 1976: 72–74
- Monk 1976: 52–55
- Csirmaz 1994: 100 (see online)
- Smullyan 2003: 56 (= Chpt IV, § 5, note 1)
- Monk 1976: 58 (= Thm 3.46)
- Hughes 1989 (see online)
- Burris 1998: Supplementary Text, Arithmetic I, Lemma 4
- see also related notions, e.g. “equals for equals” (referential transparency), and another related notion Leibniz's law / identity of indiscernibles
- either proof theoretic (algebraic steps); or semantic (truth table, method of analytic tableaux, Venn diagram, Veitch diagram / Karnaugh map)
- Monk 1976: 45 (= Def 3.1.)
- E.g. defined by
- Monk 1976: 53 (= Def 3.20, Lem 3.21)
- Csirmaz 1994: 101 (=Thm 10.7, Conseq 10.8), see online
- Burris, Stanley N. (1998). "Supplementary Text, Arithmetic I". Logic for Mathematics and Computer Science. Prentice Hall. ISBN 0-13-285974-2.
- Csirmaz, László; Hajnal, András (1994). "Rekurzív függvények". Matematikai logika (postsript + gzip) (in Hungarian). Budapest: Eötvös Loránd University. Each chapter is downloadable verbatim on author's page.
- Hughes, John (1989). "Why Functional Programming Matters". Computer Journal. 32 (2): 98–107. doi:10.1093/comjnl/32.2.98. Archived from the original on December 8, 2006.
- Monk, J. Donald (1976). Mathematical Logic. Graduate Texts in Mathematics. New York • Heidelberg • Berlin: Springer-Verlag.
- Smullyan, Raymond Merrill (1992). Gödel's Incompleteness Theorems. Oxford University Press. ISBN 0-19-504672-2.
- Smullyan, Raymond Merrill (2003). Gödel nemteljességi tételei (in Hungarian). Budapest: Typotex. ISBN 963-9326-99-2. Translation of Smullyan 1992.