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Computability

1936 CE20th-century Britain and United States (Turing and Church)

If a procedure is exact, will it eventually solve every question?

Where two intuitions collide

Defining computation precisely made it possible to prove that some problems cannot be decided by any general program.

This voyage is an editorial path for understanding, not a claim of direct historical influence or sole invention.

Understand it in one breath

"Which functions can any algorithm compute?" In 1936 Turing idealized paper-and-pencil calculation and proved a limit on the decision problem. In modern halting-problem language, no general algorithm decides whether every arbitrary program halts. Calculating machines already existed; the paper clarified an abstract model of universal computation.

At a glance

Problem

Decidable?

Note

Primality testing

Sieve of Eratosthenes

Sorting and searching

Algorithms differ only in efficiency

Polynomial with integer solutions (Hilbert’s Tenth Problem)

Hilbert’s Tenth Problem — Matiyasevich, 1970

Halting problem

Turing, 1936 — diagonal argument

Do two programs compute the same function?

Rice’s theorem (every nontrivial semantic property)

Word problem (group theory)

Novikov 1955

Undecidable problems are not exceptions but the overwhelming majority. Decidable problems are rare gems.

Concept

The mathematical study of what fixed procedures can compute. In 1936 Church and Turing clarified its power and limits with different formal models.

Key formula

f computable    M (Turing machine):M(x)=f(x)f \text{ computable} \iff \exists\, M \text{ (Turing machine)}: M(x) = f(x)

Ports in time

This concept was not invented in one instant

Follow the scenes to see problems, notation, standards of proof, and applications changing across different times and places.

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Hilbert — the Entscheidungsproblem

Is there a mechanical procedure that can decide whether every mathematical statement is true or false? It was one of Hilbert’s last great questions.

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Church and Turing — independently, no

In the same period, Alonzo Church through lambda calculus and Alan Turing through his machine model independently showed that no such universal decision algorithm exists.

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Turing defines the Turing machine

Turing introduced an abstract machine that captured what it means for a process to be computable — a theoretical starting point for computer science.

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P versus NP — a new open problem

Work by Stephen Cook and Richard Karp crystallized the question of whether problems whose solutions can be checked efficiently can also be solved efficiently. It became a million-dollar Millennium Prize Problem.

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Modern applications

The limits of compiler analysis, automated theorem proving, theoretical limits of AI, and the expressive power of programming languages.

Beyond MathVoyage

Curated sources and problems. Bring one discovery back from OEIS, Project Euler, MathOverflow, or arXiv.

No concept belongs to one person

Follow people who played different roles

These are not inventor credits. They are different ports: opening a problem, sharpening a language, or carrying it into another world.

Number lenses

A concept looks different when its world of numbers changes

These numbers are editorial lenses for the voyage, not required prerequisites.

Concept genealogy

What supports it, and what does it open?

Concepts arriving from before

Current port

Computability

Only direct editorial links are shown; this is not a complete learning order or historical influence line.