Turing Machines and algorithm

Effective computability: Turing machines

What is an ‘algorithm’?

‘Devise a procedure by which it can be decided, by the finite number of operations, whether a given multivariate polynomial consists of integral roots’.

Example: x2 + y2 + 1 consists of no real integral roots, while xy + x - y -1 has infinitely many (example: x = 1, y arbitrary).

Hilbert’s formulation entails the supposition that such a decision procedure exists, waiting to be discovered. For polynomials in the single variable, P(x) = a0 + a1 x + a2 x2 + ... + an xn, such a decision procedure was known, based on the formulas which probably bound to the absolute value of any root x0, example:|x0| ≤ 1 + max  |ai/an |, where max runs over the indices i = 0 to n-1. Any such bound B outcomes a trivial decision process by trying all the integers of absolute value < B.

This appears that mathematicians of the year 1900 could not envision the possibility that no such decision procedure might exists. Not till the theory of computability was founded in 30s by Alonzo Church, Alan Turing and others, it became apparent that Hilbert’s 10-th problem must be formulated as a question: ‘Does there exist a procedure according to which it can be found out by a finite number of operations ...?’ In the year 1970 it was no longer a surprise when Y. Matijasevich verified the Theorem:

Hilbert’s 10-th problem is undecidable, that is, there exists no algorithm to resolve it.

For this to be a theorem, we require to define thoroughly the concept of algorithm or efficient procedure.

Turing’s definition of efficient procedure obeys from an analysis of how a human (!) computer proceeds if executing an algorithm.  Alan M. Turing: On computable numbers, with application to the Entscheidungs problem.

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Computing is usually completed by writing some symbols on paper. We might suppose this paper is classified into squares such as a child’s arithmetic book. In elementary arithmetic, the two-dimensional character of paper is at times used. However such utilization is always avoidable and it will be agreed that the two-dimensional character of paper is no necessary of computation. Suppose that the computation is taken out on one-dimensional paper, that is, on a tape divided to squares. Also assume that the number of symbols that might be printed is finite. When we were to permit infinity of symbols, then there would be symbols varying to a randomly small extent. The consequence of this restriction on the number of symbols is not much serious. This is always probable to employ sequences of symbols in place of single symbols. The difference from our view point among the single and compound symbols is that the compound symbols, when they are too lengthy, can’t be observed at a glance. We can’t tell at a glance whether 9999999999999999 and 999999999999999 are similar.

The behavior of computer at any moment is found out by the symbols that is observing and his ‘state of mind’ at the moment. We might assume that there is a bound B to the number of symbols or squares that the computer can view at one moment. When he wishes to view more, he should use successive observations. We will as well assume that the number of states of mind which require be taken into account is finite.

Let us envisage the operations executed by the computer to be split up to ‘simple operations’ that are so elementary which is not easy to imagine them further classified. Each such operation comprises of some change of the physical system comprising of the computer and his tape. We recognize the state of system if we know the series of symbols on the tape, which of such are observed by the computer and the state of mind of computer. We might assume that in a simple operation, not more than one symbol is modified.

Besides such modifications of symbols, the simple operations should contain changes of distributions of observed squares. It is reasonable to assume that they can merely be squares whose distance from the closest of immediately previously observed squares doesn’t surpass a certain fixed amount. Let us state that each of new observed squares is in L squares of an instantly previously observed square.

The simple operations should thus comprise:

(i) Modification of symbol on one of the observed squares.

(ii) Modifications of one of squares observed to the other square in L squares of one of formerly observed squares.

The most common single operation should therefore be taken to be one of the given:

(i) The possible modification (a) of symbol altogether with a possible change of state of mind.

(ii) The possible modification (b) of observed squares, altogether with a possible modification of state of mind.

We might now build a machine to do work of this computer.

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