Book contents
- Frontmatter
- Contents
- Preface
- Thanks
- 1 What Gödel's Theorems say
- 2 Functions and enumerations
- 3 Effective computability
- 4 Effectively axiomatized theories
- 5 Capturing numerical properties
- 6 The truths of arithmetic
- 7 Sufficiently strong arithmetics
- 8 Interlude: Taking stock
- 9 Induction
- 10 Two formalized arithmetics
- 11 What Q can prove
- 12 IΔ0, an arithmetic with induction
- 13 First-order Peano Arithmetic
- 14 Primitive recursive functions
- 15 LA can express every p.r. function
- 16 Capturing functions
- 17 Q is p.r. adequate
- 18 Interlude: A very little about Principia
- 19 The arithmetization of syntax
- 20 Arithmetization in more detail
- 21 PA is incomplete
- 22 Gödel's First Theorem
- 23 Interlude: About the First Theorem
- 24 The Diagonalization Lemma
- 25 Rosser's proof
- 26 Broadening the scope
- 27 Tarski's Theorem
- 28 Speed-up
- 29 Second-order arithmetics
- 30 Interlude: Incompleteness and Isaacson's Thesis
- 31 Gödel's Second Theorem for PA
- 32 On the ‘unprovability of consistency’
- 33 Generalizing the Second Theorem
- 34 Löb's Theorem and other matters
- 35 Deriving the derivability conditions
- 36 ‘The best and most general version’
- 37 Interlude: The Second Theorem, Hilbert, minds and machines
- 38 μ-Recursive functions
- 39 Q is recursively adequate
- 40 Undecidability and incompleteness
- 41 Turing machines
- 42 Turing machines and recursiveness
- 43 Halting and incompleteness
- 44 The Church–Turing Thesis
- 45 Proving the Thesis?
- 46 Looking back
- Further reading
- Bibliography
- Index
41 - Turing machines
- Frontmatter
- Contents
- Preface
- Thanks
- 1 What Gödel's Theorems say
- 2 Functions and enumerations
- 3 Effective computability
- 4 Effectively axiomatized theories
- 5 Capturing numerical properties
- 6 The truths of arithmetic
- 7 Sufficiently strong arithmetics
- 8 Interlude: Taking stock
- 9 Induction
- 10 Two formalized arithmetics
- 11 What Q can prove
- 12 IΔ0, an arithmetic with induction
- 13 First-order Peano Arithmetic
- 14 Primitive recursive functions
- 15 LA can express every p.r. function
- 16 Capturing functions
- 17 Q is p.r. adequate
- 18 Interlude: A very little about Principia
- 19 The arithmetization of syntax
- 20 Arithmetization in more detail
- 21 PA is incomplete
- 22 Gödel's First Theorem
- 23 Interlude: About the First Theorem
- 24 The Diagonalization Lemma
- 25 Rosser's proof
- 26 Broadening the scope
- 27 Tarski's Theorem
- 28 Speed-up
- 29 Second-order arithmetics
- 30 Interlude: Incompleteness and Isaacson's Thesis
- 31 Gödel's Second Theorem for PA
- 32 On the ‘unprovability of consistency’
- 33 Generalizing the Second Theorem
- 34 Löb's Theorem and other matters
- 35 Deriving the derivability conditions
- 36 ‘The best and most general version’
- 37 Interlude: The Second Theorem, Hilbert, minds and machines
- 38 μ-Recursive functions
- 39 Q is recursively adequate
- 40 Undecidability and incompleteness
- 41 Turing machines
- 42 Turing machines and recursiveness
- 43 Halting and incompleteness
- 44 The Church–Turing Thesis
- 45 Proving the Thesis?
- 46 Looking back
- Further reading
- Bibliography
- Index
Summary
In this chapter, we introduce Turing's classic analysis of effective computability. And then – in the next chapter – we will establish the crucial result that the Turing-computable total functions are exactly the μ-recursive functions. This result is fascinating in its own right; it is hugely important historically; and it enables us later to establish some further results about recursiveness and incompleteness in a particularly neat way. So let's dive in without more ado.
The basic conception
Think of executing an algorithmic computation ‘by hand’, using pen and paper. We follow strict rules for writing down symbols in various patterns. To keep things tidy, let's write the symbols neatly one-by-one in the squares of some suitable square-ruled paper. Eventually – assuming that we don't find ourselves carrying on generating output forever – the computation process stops and the result of the computation is left written down in some block of squares on the paper.
Now, Turing suggests, using a two-dimensional grid for writing down the computation is not of the essence. Imagine cutting up the paper into horizontal strips a square deep, and pasting these together into one long tape. We could use that as an equivalent workspace.
Using a rich repertoire of symbols is not of the essence either. Suppose some computational system uses 27 symbols. Number these off using a five-binarydigit code (so the 14th symbol, for example, gets the code ‘01110’). Then divide each of the original squares on our workspace tape into a row of five small cells.
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- Information
- An Introduction to Gödel's Theorems , pp. 310 - 320Publisher: Cambridge University PressPrint publication year: 2013