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Percus–Yevick approximation

Percus–Yevick approximation 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 Percus–Yevick approximation rather than just read about it. In short: In statistical mechanics the Percus–Yevick approximation is a closure relation to solve the Ornstein–Zernike equation. It is also referred to as the Percus–Yevick equation.

Percus–Yevick approximation — main illustration
Percus–Yevick approximation — illustration

Key takeaways

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

Reference excerpt

In statistical mechanics the Percus–Yevick approximation is a closure relation to solve the Ornstein–Zernike equation. It is also referred to as the Percus–Yevick equation. It is commonly used in fluid theory to obtain e.g. expressions for the radial distribution function. The approximation is named after Jerome K. Percus and George J. Yevick.

Derivation The direct correlation function represents the direct correlation between two particles in a system containing N − 2 other particles. It can be represented by

c ( r ) = g t o t a l ( r ) − g i n d i r e c t ( r ) {\displaystyle c(r)=g_{\rm {total}}(r)-g_{\rm {indirect}}(r)\,}

where g t o t a l ( r ) {\displaystyle g_{\rm {total}}(r)} is the radial distribution function, i.e. g ( r ) = exp ⁡ [ − β w ( r ) ] {\displaystyle g(r)=\exp[-\beta w(r)]} (with w(r) the potential of mean force) and g i n d i r e c t ( r ) {\displaystyle g_{\rm {indirect}}(r)} is the radial distribution function without the direct interaction between pairs u ( r ) {\displaystyle u(r)} included; i.e. we write g i n d i r e c t ( r ) = exp ⁡ [ − β ( w ( r ) − u ( r ) ) ] {\displaystyle g_{\rm {indirect}}(r)=\exp[-\beta (w(r)-u(r))]} . Thus we approximate c(r) by

c ( r ) = e − β w ( r ) − e − β [ w ( r ) − u ( r ) ] . {\displaystyle c(r)=e^{-\beta w(r)}-e^{-\beta [w(r)-u(r)]}.\,}

If we introduce the function y ( r ) = e β u ( r ) g ( r ) {\displaystyle y(r)=e^{\beta u(r)}g(r)} into the approximation for c(r) one obtains

c ( r ) = g ( r ) − y ( r ) = e − β u y ( r ) − y ( r ) = f ( r ) y ( r ) . {\displaystyle c(r)=g(r)-y(r)=e^{-\beta u}y(r)-y(r)=f(r)y(r).\,}

This is the essence of the Percus–Yevick approximation for if we substitute this result in the Ornstein–Zernike equation, one obtains the Percus–Yevick equation:

y ( r 12 ) = 1 + ρ ∫ f ( r 13 ) y ( r 13 ) h ( r 23 ) d r 3 . {\displaystyle y(r_{12})=1+\rho \int f(r_{13})y(r_{13})h(r_{23})d\mathbf {r_{3}} .\,}

The approximation was defined by Percus and Yevick in 1958.

Hard spheres

For hard spheres, the potential u(r) is either zero or infinite, and therefore the Boltzmann factor e − u / k B T {\displaystyle {\text{e}}^{-u/k_{\text{B}}T}} is either one or zero, regardless of temperature T. Therefore structure of a hard-spheres fluid is temperature independent. This leaves just two parameters: the hard-core radius R (which can be eliminated by rescaling distances or wavenumbers), and the packing fraction η (which has a maximum value of 0.64 for random close packing). Under these conditions, the Percus–Yevick equation has an analytical solution, obtained by Wertheim in 1963.

Solution as C code The static structure factor of the hard-spheres fluid in Percus–Yevick approximation can be computed using the following C function:

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Percus–Yevick approximation

Start with the simplest possible case. Write down what Percus–Yevick approximation 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 Percus–Yevick approximation 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 Percus–Yevick approximation 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 Percus–Yevick approximation

In research
Percus–Yevick approximation 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 Percus–Yevick approximation 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
Percus–Yevick approximation is common in secondary-school and first-year university syllabi. It links to neighbouring topics Statistical mechanics, so understanding it makes those chapters shorter.
In everyday life
Look for Percus–Yevick approximation 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 Percus–Yevick approximation in 20 minutes

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

Frequently asked questions

What is Percus–Yevick approximation in simple terms?

In statistical mechanics the Percus–Yevick approximation is a closure relation to solve the Ornstein–Zernike equation. It is also referred to as the Percus–Yevick equation.

Why does Percus–Yevick approximation 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 Percus–Yevick approximation?

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 Percus–Yevick approximation.

Tags

  • Statistical mechanics

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