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Many-one reduction

Many-one reduction is a 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 Many-one reduction rather than just read about it. In short: In computability theory and computational complexity theory, a many-one reduction (also called mapping reduction) is a reduction that converts instances of one decision problem (whether an instance is in L 1 {\displaystyle L_{1}} ) to another decision problem (whether an instance is in L 2 {\displaystyle L_{2}} ) using a computable function. The reduced instance is in the language L 2 {\displaystyle L_{2}} if and on…

Key takeaways

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

Reference excerpt

In computability theory and computational complexity theory, a many-one reduction (also called mapping reduction) is a reduction that converts instances of one decision problem (whether an instance is in L 1 {\displaystyle L_{1}} ) to another decision problem (whether an instance is in L 2 {\displaystyle L_{2}} ) using a computable function. The reduced instance is in the language L 2 {\displaystyle L_{2}} if and only if the initial instance is in its language L 1 {\displaystyle L_{1}} . Thus if we can decide whether L 2 {\displaystyle L_{2}} instances are in the language L 2 {\displaystyle L_{2}} , we can decide whether L 1 {\displaystyle L_{1}} instances are in the language L 1 {\displaystyle L_{1}} by applying the reduction and solving for L 2 {\displaystyle L_{2}} . Thus, reductions can be used to measure the relative computational difficulty of two problems. It is said that L 1 {\displaystyle L_{1}} reduces to L 2 {\displaystyle L_{2}} if, in layman's terms L 2 {\displaystyle L_{2}} is at least as hard to solve as L 1 {\displaystyle L_{1}} . This means that any algorithm that solves L 2 {\displaystyle L_{2}} can also be used as part of a (otherwise relatively simple) program that solves L 1 {\displaystyle L_{1}} . Many-one reductions are a special case and stronger form of Turing reductions. With many-one reductions, the oracle (that is, our solution for L 2 {\displaystyle L_{2}} ) can be invoked only once at the end, and the answer cannot be modified. This means that if we want to show that problem L 1 {\displaystyle L_{1}} can be reduced to problem L 2 {\displaystyle L_{2}} , we can use our solution for L 2 {\displaystyle L_{2}} only once in our solution for L 1 {\displaystyle L_{1}} , unlike in Turing reductions, where we can use our solution for L 2 {\displaystyle L_{2}} as many times as needed in order to solve the membership problem for the given instance of L 1 {\displaystyle L_{1}} . Many-one reductions were first used by Emil Post in a paper published in 1944. Later Norman Shapiro used the same concept in 1956 under the name strong reducibility.

Definitions

Formal languages Suppose A {\displaystyle A} and B {\displaystyle B} are formal languages over the alphabets Σ {\displaystyle \Sigma } and Γ {\displaystyle \Gamma } , respectively. A many-one reduction from A {\displaystyle A} to B {\displaystyle B} is a total computable function f : Σ ∗ → Γ ∗ {\displaystyle f:\Sigma ^{*}\rightarrow \Gamma ^{*}} that has the property that each word w {\displaystyle w} is in A {\displaystyle A} if and only if f ( w ) {\displaystyle f(w)} is in B {\displaystyle B} . If such a function f {\displaystyle f} exists, one says that A {\displaystyle A} is many-one reducible or m-reducible to B {\displaystyle B} and writes

A ≤ m B . {\displaystyle A\leq _{\mathrm {m} }B.}

Subsets of natural numbers Given two sets A , B ⊆ N {\displaystyle A,B\subseteq \mathbb {N} } one says A {\displaystyle A} is many-one reducible to B {\displaystyle B} and writes

A ≤ m B {\displaystyle A\leq _{\mathrm {m} }B}

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Many-one reduction

Start with the simplest possible case. Write down what Many-one reduction claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In 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 Many-one reduction 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 Many-one reduction 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 Many-one reduction

In research
Many-one reduction appears in 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 Many-one reduction 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
Many-one reduction is common in secondary-school and first-year university syllabi. It links to neighbouring topics Reduction (complexity), so understanding it makes those chapters shorter.
In everyday life
Look for Many-one reduction 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 Many-one reduction in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Many-one reduction 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 Many-one reduction out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Many-one reduction in simple terms?

In computability theory and computational complexity theory, a many-one reduction (also called mapping reduction) is a reduction that converts instances of one decision problem (whether an instance is in L 1 {\displaystyle L_{1}} ) to another decision problem (whether an instance is in L 2 {\displa…

Why does Many-one reduction matter?

Because it connects several 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 Many-one reduction?

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 Many-one reduction.

Tags

  • Reduction (complexity)

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