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Simple set

Simple set is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Simple set rather than just read about it. In short: In computability theory, a subset of the natural numbers is called simple if it is computably enumerable (c.e.) and co-infinite (i.e. its complement is infinite), but every infinite subset of its complement is not c.e.. Simple sets are examples of c.e. sets that are not computable.

Key takeaways

  • Simple set belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Simple set to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Simple set from memory before moving on to harder problems.

Reference excerpt

In computability theory, a subset of the natural numbers is called simple if it is computably enumerable (c.e.) and co-infinite (i.e. its complement is infinite), but every infinite subset of its complement is not c.e.. Simple sets are examples of c.e. sets that are not computable.

Relation to Post's problem Simple sets were devised by Emil Leon Post in the search for a non-Turing-complete c.e. set. Whether such sets exist is known as Post's problem. Post had to prove two things in order to obtain his result: that the simple set A is not computable, and that the K, the halting problem, does not Turing-reduce to A. He succeeded in the first part (which is obvious by definition), but for the other part, he managed only to prove nonexistence of a many-one reduction. Post's idea was validated by Friedberg and Muchnik in the 1950s using a novel technique called the priority method. They give a construction for a set that is simple (and thus non-computable), but fails to compute the halting problem.

Formal definitions and some properties In what follows, W e {\displaystyle W_{e}} denotes a standard uniformly c.e. listing of all the c.e. sets.

A set I ⊆ N {\displaystyle I\subseteq \mathbb {N} } is called immune if I {\displaystyle I} is infinite, but for every index e {\displaystyle e} , we have W e infinite ⟹ W e ⊈ I {\displaystyle W_{e}{\text{ infinite}}\implies W_{e}\not \subseteq I} . Or equivalently: there is no infinite subset of I {\displaystyle I} that is c.e.. A set S ⊆ N {\displaystyle S\subseteq \mathbb {N} } is called simple if it is c.e. and its complement is immune. A set I ⊆ N {\displaystyle I\subseteq \mathbb {N} } is called effectively immune if I {\displaystyle I} is infinite, but there exists a recursive function f {\displaystyle f} such that for every index e {\displaystyle e} , we have that W e ⊆ I ⟹ # ( W e ) < f ( e ) {\displaystyle W_{e}\subseteq I\implies \#(W_{e})<f(e)} . A set S ⊆ N {\displaystyle S\subseteq \mathbb {N} } is called effectively simple if it is c.e. and its complement is effectively immune. Every effectively simple set is simple and Turing-complete. A set I ⊆ N {\displaystyle I\subseteq \mathbb {N} } is called hyperimmune if I {\displaystyle I} is infinite, but p I {\displaystyle p_{I}} is not computably dominated, where p I {\displaystyle p_{I}} is the list of members of I {\displaystyle I} in order. A set S ⊆ N {\displaystyle S\subseteq \mathbb {N} } is called hypersimple if it is simple and its complement is hyperimmune.

Notes

References Soare, Robert I. (1987). Recursively enumerable sets and degrees. A study of computable functions and computably generated sets. Perspectives in Mathematical Logic. Berlin: Springer-Verlag. ISBN 3-540-15299-7. Zbl 0667.03030. Odifreddi, Piergiorgio (1988). Classical recursion theory. The theory of functions and sets of natural numbers. Studies in Logic and the Foundations of Mathematics. Vol. 125. Amsterdam: North Holland. ISBN 0-444-87295-7. Zbl 0661.03029. Nies, André (2009). Computability and randomness. Oxford Logic Guides. Vol. 51. Oxford: Oxford University Press. ISBN 978-0-19-923076-1. Zbl 1169.03034.

Worked examples

Example 1 — a first encounter with Simple set

Start with the simplest possible case. Write down what Simple set claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Simple set before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Simple set ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Simple set

In research
Simple set appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Simple set in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Simple set is common in secondary-school and first-year university syllabi. It links to neighbouring topics Computability theory, so understanding it makes those chapters shorter.
In everyday life
Look for Simple set outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Simple set in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Simple set means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Simple set out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Simple set in simple terms?

In computability theory, a subset of the natural numbers is called simple if it is computably enumerable (c.e.) and co-infinite (i.e. its complement is infinite), but every infinite subset of its complement is not c.e.. Simple sets are examples of c.e. sets that are not computable.

Why does Simple set matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Simple set?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Simple set.

Tags

  • Computability theory

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