Math Labs

Worked solution: The MRDP theorem: Diophantine sets are exactly the recursively enumerable sets (1970)

Step 1 of 9: Hilbert's tenth problem: an algorithm for Diophantine equations?
In plain words

A Diophantine equation is a polynomial puzzle where only whole-number answers count, like x2+y2=z2x^2+y^2=z^2 (which has solutions — the Pythagorean triples) or, famously, xn+yn=znx^n+y^n=z^n for n≥3n \ge 3 (which Fermat's Last Theorem says has none). In 1900, David Hilbert asked, as the tenth of his 23 famous problems, for a single universal recipe that, fed any such equation, always correctly answers "yes, it has an integer solution" or "no, it doesn't".

At the time, "algorithm" was an informal notion; only in the 1930s did Alan Turing and Alonzo Church pin the concept down precisely enough for anyone to prove a definitive "no such algorithm exists" answer to a question like this one.

P(x1,…,xn)=0,P∈Z[x1,…,xn]P(x_1, \ldots, x_n) = 0, \quad P \in \mathbb{Z}[x_1, \ldots, x_n]
Detailed analysis

Hilbert's tenth problem, the tenth of the twenty-three problems in his 1900 address to the International Congress of Mathematicians, asks for a procedure with finitely many operations that decides, for an arbitrary polynomial P(x1,…,xn)∈Z[x1,…,xn]P(x_1, \ldots, x_n) \in \mathbb{Z}[x_1, \ldots, x_n], whether the equation P(x1,…,xn)=0P(x_1, \ldots, x_n) = 0 is solvable in integers. Two features make the request strong: the algorithm must be uniform — one procedure covering all degrees and all coefficient tuples — and it must terminate with a correct yes/no answer on every input, not merely succeed on a decidable subclass.

Several subclasses were already decidable. Linear equations a1x1+⋯+anxn=ba_1 x_1 + \cdots + a_n x_n = b reduce to computing gcd⁡(a1,…,an)\gcd(a_1, \ldots, a_n); one-variable equations P(x)=0P(x) = 0 reduce, after clearing denominators, to divisibility of the constant term; and quadratic equations in two variables fall under the theory of binary quadratic forms and the Pell equation, essentially settled by continued fractions. What no classical technique could touch was the general case, where a Diophantine equation can encode arbitrarily intricate arithmetic structure and there is no bound on the number of unknowns nn.

The resolution, completed by Matiyasevich in 1970, is negative, and it requires turning the informal word "procedure" into a mathematical object. The proof below follows the route surveyed in Matiyasevich's 2008 Scholarpedia article: identify Diophantine definability with recursive enumerability, then import Turing's undecidability of the halting problem.

Terms in this step
Diophantine equation
A polynomial equation P(x1,…,xn)=0P(x_1, \ldots, x_n) = 0 with integer coefficients, for which only integer (or sometimes nonnegative integer) solutions are of interest, named after the ancient mathematician Diophantus.
Algorithm (decision procedure)
A finite, mechanical, step-by-step procedure that is guaranteed to halt and give the correct yes/no answer for every possible input; made mathematically precise in the 1930s via Turing machines and equivalent formalisms.
Knowledge used in this step