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Radon–Nikodym theorem

Radon–Nikodym 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 Radon–Nikodym theorem rather than just read about it. In short: In mathematics, the Radon–Nikodym theorem, named after Johann Radon and Otto M. Nikodym, is a result in measure theory that expresses the relationship between two measures defined on the same measurable space.

Key takeaways

  • Radon–Nikodym 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 Radon–Nikodym theorem to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Radon–Nikodym theorem from memory before moving on to harder problems.

Reference excerpt

In mathematics, the Radon–Nikodym theorem, named after Johann Radon and Otto M. Nikodym, is a result in measure theory that expresses the relationship between two measures defined on the same measurable space. A measure is a set function that assigns a consistent magnitude to the measurable subsets of a measurable space. Examples of a measure include area and volume, where the subsets are sets of points; or the probability of an event, which is a subset of possible outcomes within a wider probability space. One way to derive a new measure from one already given is to assign a density to each point of the space, then integrate over the measurable subset of interest. This can be expressed as

ν ( A ) = ∫ A f d μ , {\displaystyle \nu (A)=\int _{A}f\,d\mu ,}

where ν {\displaystyle \nu } is the new measure being defined for any measurable subset A {\displaystyle A} and the function f {\displaystyle f} is the density at a given point. The integral is with respect to an existing measure μ {\displaystyle \mu } , which may often be the canonical Lebesgue measure on the real line R {\displaystyle \mathbb {R} } or the n {\displaystyle n} -dimensional Euclidean space R n {\displaystyle \mathbb {R} ^{n}} (corresponding to our standard notions of length, area and volume). For example, if f {\displaystyle f} represented mass density and μ {\displaystyle \mu } was the Lebesgue measure in three-dimensional space R 3 {\displaystyle \mathbb {R} ^{3}} , then ν ( A ) {\displaystyle \nu (A)} would equal the total mass in a spatial region A {\displaystyle A} . The Radon–Nikodym theorem essentially states that, under certain conditions, any measure ν {\displaystyle \nu } can be expressed in this way with respect to another measure μ {\displaystyle \mu } on the same space. The function f {\displaystyle f} is then called the Radon–Nikodym derivative and is denoted by d ν / d μ {\displaystyle d\nu /d\mu } . An important application is in probability theory, leading to the probability density function of a random variable. The theorem is named after Johann Radon, who proved the theorem for the special case where the underlying space is R n {\displaystyle \mathbb {R} ^{n}} in 1913, and for Otto Nikodym who proved the general case in 1930. In 1936, Hans Freudenthal generalized the Radon–Nikodym theorem by proving the Freudenthal spectral theorem, a result in Riesz space theory; this contains the Radon–Nikodym theorem as a special case. A Banach space Y {\displaystyle Y} is said to have the Radon–Nikodym property if the generalization of the Radon–Nikodym theorem also holds (with the necessary adjustments made) for functions with values in Y {\displaystyle Y} . All Hilbert spaces have the Radon–Nikodym property.

Formal description

Radon–Nikodym theorem The Radon–Nikodym theorem involves a measurable space ( X , Σ ) {\displaystyle (X,\Sigma )} on which two σ-finite measures are defined, μ {\displaystyle \mu } and ν . {\displaystyle \nu .} It states that, if ν ≪ μ {\displaystyle \nu \ll \mu } (that is, if ν {\displaystyle \nu } is absolutely continuous with respect to μ {\displaystyle \mu } ), then there exists a Σ {\displaystyle \Sigma } -measurable function f : X → [ 0 , ∞ ) , {\displaystyle f:X\to [0,\infty ),} such that for any measurable set A ∈ Σ , {\displaystyle A\in \Sigma ,}

ν ( A ) = ∫ A f d μ . {\displaystyle \nu (A)=\int _{A}f\,d\mu .}

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Radon–Nikodym theorem

Start with the simplest possible case. Write down what Radon–Nikodym 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 Radon–Nikodym 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 Radon–Nikodym 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 Radon–Nikodym theorem

In research
Radon–Nikodym 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 Radon–Nikodym 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
Radon–Nikodym theorem is common in secondary-school and first-year university syllabi. It links to neighbouring topics Generalizations of the derivative, Integral representations, Theorems in measure theory, so understanding it makes those chapters shorter.
In everyday life
Look for Radon–Nikodym 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 Radon–Nikodym theorem in 20 minutes

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

Frequently asked questions

What is Radon–Nikodym theorem in simple terms?

In mathematics, the Radon–Nikodym theorem, named after Johann Radon and Otto M. Nikodym, is a result in measure theory that expresses the relationship between two measures defined on the same measurable space.

Why does Radon–Nikodym 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 Radon–Nikodym 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 Radon–Nikodym theorem.

Tags

  • Generalizations of the derivative
  • Integral representations
  • Theorems in measure theory

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