ArticleslgStudy

computer science

Symmetrization methods

Symmetrization methods 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 Symmetrization methods rather than just read about it. In short: In mathematics the symmetrization methods are algorithms of transforming a set A ⊂ R n {\displaystyle A\subset \mathbb {R} ^{n}} to a ball B ⊂ R n {\displaystyle B\subset \mathbb {R} ^{n}} with equal volume vol ⁡ ( B ) = vol ⁡ ( A ) {\displaystyle \operatorname {vol} (B)=\operatorname {vol} (A)} and centered at the origin. B is called the symmetrized version of A, usually denoted A ∗ {\displaystyle A^{*}} .

Symmetrization methods — main illustration
Symmetrization methods — illustration

Key takeaways

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

Reference excerpt

In mathematics the symmetrization methods are algorithms of transforming a set A ⊂ R n {\displaystyle A\subset \mathbb {R} ^{n}} to a ball B ⊂ R n {\displaystyle B\subset \mathbb {R} ^{n}} with equal volume vol ⁡ ( B ) = vol ⁡ ( A ) {\displaystyle \operatorname {vol} (B)=\operatorname {vol} (A)} and centered at the origin. B is called the symmetrized version of A, usually denoted A ∗ {\displaystyle A^{*}} . These algorithms show up in solving the classical isoperimetric inequality problem, which asks: Given all two-dimensional shapes of a given area, which of them has the minimal perimeter (for details see Isoperimetric inequality). The conjectured answer was the disk and Steiner in 1838 showed this to be true using the Steiner symmetrization method (described below). From this many other isoperimetric problems sprung and other symmetrization algorithms. For example, Rayleigh's conjecture is that the first eigenvalue of the Dirichlet problem is minimized for the ball (see Rayleigh–Faber–Krahn inequality for details). Another problem is that the Newtonian capacity of a set A is minimized by A ∗ {\displaystyle A^{*}} and this was proved by Pólya and G. Szegő (1951) using circular symmetrization (described below).

Symmetrization If Ω ⊂ R n {\displaystyle \Omega \subset \mathbb {R} ^{n}} is measurable, then it is denoted by Ω ∗ {\displaystyle \Omega ^{*}} the symmetrized version of Ω {\displaystyle \Omega } i.e. a ball Ω ∗ := B r ( 0 ) ⊂ R n {\displaystyle \Omega ^{*}:=B_{r}(0)\subset \mathbb {R} ^{n}} such that vol ⁡ ( Ω ∗ ) = vol ⁡ ( Ω ) {\displaystyle \operatorname {vol} (\Omega ^{*})=\operatorname {vol} (\Omega )} . We denote by f ∗ {\displaystyle f^{*}} the symmetric decreasing rearrangement of nonnegative measurable function f and define it as f ∗ ( x ) := ∫ 0 ∞ 1 { y : f ( y ) > t } ∗ ( x ) d t {\displaystyle f^{*}(x):=\int _{0}^{\infty }1_{\{y:f(y)>t\}^{*}}(x)\,dt} , where { y : f ( y ) > t } ∗ {\displaystyle \{y:f(y)>t\}^{*}} is the symmetrized version of preimage set { y : f ( y ) > t } {\displaystyle \{y:f(y)>t\}} . The methods described below have been proved to transform Ω {\displaystyle \Omega } to Ω ∗ {\displaystyle \Omega ^{*}} i.e. given a sequence of symmetrization transformations { T k } {\displaystyle \{T_{k}\}} there is lim k → ∞ d H a ( Ω ∗ , T k ( K ) ) = 0 {\displaystyle \lim \limits _{k\to \infty }d_{Ha}(\Omega ^{*},T_{k}(K))=0} , where d H a {\displaystyle d_{Ha}} is the Hausdorff distance (for discussion and proofs see Burchard (2009))

Steiner symmetrization

… excerpt ends here. Continue reading the full article.

Illustrations

Symmetrization methods: Circular symmetrization of set 
  
    
      
        Ω
      
    
    {\displaystyle \Omega }
Circular symmetrization of set Ω {\displaystyle \Omega }
Symmetrization methods: Polarization of set 
  
    
      
        Ω
      
    
    {\displaystyle \Omega }
Polarization of set Ω {\displaystyle \Omega }

Worked examples

Example 1 — a first encounter with Symmetrization methods

Start with the simplest possible case. Write down what Symmetrization methods 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 Symmetrization methods 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 Symmetrization methods 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 Symmetrization methods

In research
Symmetrization methods 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 Symmetrization methods 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
Symmetrization methods is common in secondary-school and first-year university syllabi. It links to neighbouring topics Geometric algorithms, Geometric inequalities, so understanding it makes those chapters shorter.
In everyday life
Look for Symmetrization methods 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.

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Symmetrization methods in 20 minutes

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

Frequently asked questions

What is Symmetrization methods in simple terms?

In mathematics the symmetrization methods are algorithms of transforming a set A ⊂ R n {\displaystyle A\subset \mathbb {R} ^{n}} to a ball B ⊂ R n {\displaystyle B\subset \mathbb {R} ^{n}} with equal volume vol ⁡ ( B ) = vol ⁡ ( A ) {\displaystyle \operatorname {vol} (B)=\operatorname {vol} (A)} an…

Why does Symmetrization methods 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 Symmetrization methods?

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 Symmetrization methods.

Tags

  • Geometric algorithms
  • Geometric inequalities

Keep exploring