ArticleslgStudy

science

Gilbert–Varshamov bound

Gilbert–Varshamov bound 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 Gilbert–Varshamov bound rather than just read about it. In short: In coding theory, the Gilbert–Varshamov bound (due to Edgar Gilbert and independently Rom Varshamov) is a bound on the size of a (not necessarily linear) code. It is occasionally known as the Gilbert–Shannon–Varshamov bound (or the GSV bound), but the name "Gilbert–Varshamov bound" is by far the most popular.

Key takeaways

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

Reference excerpt

In coding theory, the Gilbert–Varshamov bound (due to Edgar Gilbert and independently Rom Varshamov) is a bound on the size of a (not necessarily linear) code. It is occasionally known as the Gilbert–Shannon–Varshamov bound (or the GSV bound), but the name "Gilbert–Varshamov bound" is by far the most popular. Varshamov proved this bound by using the probabilistic method for linear codes. For more about that proof, see Gilbert–Varshamov bound for linear codes.

Statement of the bound Recall that a code has a minimum distance d {\displaystyle d} if any two elements in the code are at least a distance d {\displaystyle d} apart. Let

A q ( n , d ) {\displaystyle A_{q}(n,d)}

denote the maximum possible size of a q-ary code C {\displaystyle C} with length n and minimum Hamming distance d (a q-ary code is a code over the field F q {\displaystyle \mathbb {F} _{q}} of q elements). Then:

A q ( n , d ) ⩾ q n ∑ j = 0 d − 1 ( n j ) ( q − 1 ) j ≥ q n ( 1 − H q ( d / n ) ) {\displaystyle A_{q}(n,d)\geqslant {\frac {q^{n}}{\sum _{j=0}^{d-1}{\binom {n}{j}}(q-1)^{j}}}\geq q^{n(1-H_{q}(d/n))}}

where H q {\displaystyle H_{q}} is the q-ary entropy function,

H q ( x ) = x log q ⁡ ( q − 1 ) − x log q ⁡ x − ( 1 − x ) log q ⁡ ( 1 − x ) . {\displaystyle H_{q}(x)=x\log _{q}(q-1)-x\log _{q}x-(1-x)\log _{q}(1-x).}

Proof Let C {\displaystyle C} be a code of length n {\displaystyle n} and minimum Hamming distance d {\displaystyle d} having maximal size:

| C | = A q ( n , d ) . {\displaystyle |C|=A_{q}(n,d).}

Then for all x ∈ F q n {\displaystyle x\in \mathbb {F} _{q}^{n}} , there exists at least one codeword c x ∈ C {\displaystyle c_{x}\in C} such that the Hamming distance d ( x , c x ) {\displaystyle d(x,c_{x})} between x {\displaystyle x} and c x {\displaystyle c_{x}} satisfies

d ( x , c x ) ⩽ d − 1 {\displaystyle d(x,c_{x})\leqslant d-1}

since otherwise we could add x to the code whilst maintaining the code's minimum Hamming distance d {\displaystyle d} – a contradiction on the maximality of | C | {\displaystyle |C|} . Hence the whole of F q n {\displaystyle \mathbb {F} _{q}^{n}} is contained in the union of all balls of radius d − 1 {\displaystyle d-1} having their centre at some c ∈ C {\displaystyle c\in C} :

F q n = ⋃ c ∈ C B ( c , d − 1 ) . {\displaystyle \mathbb {F} _{q}^{n}=\bigcup _{c\in C}B(c,d-1).}

Now each ball has size

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Gilbert–Varshamov bound

Start with the simplest possible case. Write down what Gilbert–Varshamov bound 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 Gilbert–Varshamov bound 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 Gilbert–Varshamov bound 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 Gilbert–Varshamov bound

In research
Gilbert–Varshamov bound 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 Gilbert–Varshamov bound 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
Gilbert–Varshamov bound is common in secondary-school and first-year university syllabi. It links to neighbouring topics Coding theory, so understanding it makes those chapters shorter.
In everyday life
Look for Gilbert–Varshamov bound 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.
Ask Teacher Smith questions about this articleOpens your AI tutor with a question about “Gilbert–Varshamov bound” →

Affiliate

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

How to study Gilbert–Varshamov bound in 20 minutes

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

Frequently asked questions

What is Gilbert–Varshamov bound in simple terms?

In coding theory, the Gilbert–Varshamov bound (due to Edgar Gilbert and independently Rom Varshamov) is a bound on the size of a (not necessarily linear) code. It is occasionally known as the Gilbert–Shannon–Varshamov bound (or the GSV bound), but the name "Gilbert–Varshamov bound" is by far the mo…

Why does Gilbert–Varshamov bound 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 Gilbert–Varshamov bound?

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 Gilbert–Varshamov bound.

Tags

  • Coding theory

Keep exploring