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Lusin's theorem

Lusin's theorem is a mathematics 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 Lusin's theorem rather than just read about it. In short: In the mathematical field of mathematical analysis, Lusin's theorem (or Luzin's theorem, named for Nikolai Luzin) or Lusin's criterion states that an almost-everywhere finite function is measurable if and only if it is a continuous function on nearly all its domain. In the informal formulation of J.

Key takeaways

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

Reference excerpt

In the mathematical field of mathematical analysis, Lusin's theorem (or Luzin's theorem, named for Nikolai Luzin) or Lusin's criterion states that an almost-everywhere finite function is measurable if and only if it is a continuous function on nearly all its domain. In the informal formulation of J. E. Littlewood, "every measurable function is nearly continuous".

Classical statement For an interval [a, b], let

f : [ a , b ] → C {\displaystyle f:[a,b]\rightarrow \mathbb {C} }

be a measurable function. Then, for every ε > 0, there exists a compact E ⊆ [a, b] such that f restricted to E is continuous and

μ ( E ) > b − a − ε . {\displaystyle \mu (E)>b-a-\varepsilon .}

Note that E inherits the subspace topology from [a, b]; continuity of f restricted to E is defined using this topology. Also for any function f, defined on the interval [a, b] and almost-everywhere finite, if for any ε > 0 there is a function ϕ, continuous on [a, b], such that the measure of the set

{ x ∈ [ a , b ] : f ( x ) ≠ ϕ ( x ) } {\displaystyle \{x\in [a,b]:f(x)\neq \phi (x)\}}

is less than ε, then f is measurable.

General form Let ( X , Σ , μ ) {\displaystyle (X,\Sigma ,\mu )} be a Radon measure space and Y be a second-countable topological space equipped with a Borel algebra, and let f : X → Y {\displaystyle f:X\rightarrow Y} be a measurable function. Given ε > 0 {\displaystyle \varepsilon >0} , for every A ∈ Σ {\displaystyle A\in \Sigma } of finite measure there is a closed set E {\displaystyle E} with μ ( A ∖ E ) < ε {\displaystyle \mu (A\setminus E)<\varepsilon } such that f {\displaystyle f} restricted to E {\displaystyle E} is continuous. (If A {\displaystyle A} is locally compact and Y = R d {\displaystyle Y=\mathbb {R} ^{d}} , we can choose E {\displaystyle E} to be compact and even find a continuous function f ε : X → R d {\displaystyle f_{\varepsilon }:X\rightarrow \mathbb {R} ^{d}} with compact support that coincides with f {\displaystyle f} on E {\displaystyle E} and such that

sup x ∈ X | f ε ( x ) | ≤ sup x ∈ X | f ( x ) | {\displaystyle \ \sup _{x\in X}|f_{\varepsilon }(x)|\leq \sup _{x\in X}|f(x)|} .) Informally, measurable functions into spaces with countable base can be approximated by continuous functions on arbitrarily large portion of their domain.

On the proof The proof of Lusin's theorem can be found in many classical books. Intuitively, one expects it as a consequence of Egorov's theorem and density of smooth functions. Egorov's theorem states that pointwise convergence is nearly uniform, and uniform convergence preserves continuity.

Example The strength of Lusin's theorem might not be readily apparent, as can be demonstrated by example. Consider Dirichlet function, that is the indicator function 1 Q : [ 0 , 1 ] → { 0 , 1 } {\displaystyle 1_{\mathbb {Q} }:[0,1]\to \{0,1\}} on the unit interval [ 0 , 1 ] {\displaystyle [0,1]} taking the value of one on the rationals, and zero, otherwise. Clearly the measure of this function should be zero, but how can one find regions that are continuous, given that the rationals are dense in the reals? The requirements for Lusin's theorem can be satisfied with the following construction of a set E . {\displaystyle E.}

Let { x n ; n = 1 , 2 , … } {\displaystyle \{x_{n};n=1,2,\dots \}} be any enumeration of Q {\displaystyle \mathbb {Q} } . Set

G n = ( x n − ε / 2 n , x n + ε / 2 n ) {\displaystyle G_{n}=(x_{n}-\varepsilon /2^{n},x_{n}+\varepsilon /2^{n})}

and

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Lusin's theorem

Start with the simplest possible case. Write down what Lusin's theorem claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, 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 Lusin's theorem 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 Lusin's theorem 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 Lusin's theorem

In research
Lusin's theorem appears in mathematics 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 Lusin's theorem 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
Lusin's theorem is common in secondary-school and first-year university syllabi. It links to neighbouring topics Theorems in measure theory, Theorems in real analysis, so understanding it makes those chapters shorter.
In everyday life
Look for Lusin's theorem 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 Lusin's theorem in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Lusin's theorem 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 Lusin's theorem out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Lusin's theorem in simple terms?

In the mathematical field of mathematical analysis, Lusin's theorem (or Luzin's theorem, named for Nikolai Luzin) or Lusin's criterion states that an almost-everywhere finite function is measurable if and only if it is a continuous function on nearly all its domain. In the informal formulation of J.

Why does Lusin's theorem matter?

Because it connects several mathematics 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 Lusin's theorem?

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 Lusin's theorem.

Tags

  • Theorems in measure theory
  • Theorems in real analysis

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