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Locally decodable code

Locally decodable code 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 Locally decodable code rather than just read about it. In short: A locally decodable code (LDC) is an error-correcting code that allows a single bit of the original message to be decoded with high probability by only examining (or querying) a small number of bits of a possibly corrupted codeword. This property could be useful, say, in a context where information is being transmitted over a noisy channel, and only a small subset of the data is required at a particular time and the…

Key takeaways

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

Reference excerpt

A locally decodable code (LDC) is an error-correcting code that allows a single bit of the original message to be decoded with high probability by only examining (or querying) a small number of bits of a possibly corrupted codeword. This property could be useful, say, in a context where information is being transmitted over a noisy channel, and only a small subset of the data is required at a particular time and there is no need to decode the entire message at once. Locally decodable codes are not a subset of locally testable codes, though there is some overlap between the two. Codewords are generated from the original message using an algorithm that introduces a certain amount of redundancy into the codeword; thus, the codeword is always longer than the original message. This redundancy is distributed across the codeword and allows the original message to be recovered with good probability even in the presence of errors. The more redundant the codeword, the more resilient it is against errors, and the fewer queries required to recover a bit of the original message.

Overview More formally, a ( q , δ , ϵ ) {\displaystyle (q,\delta ,\epsilon )} -locally decodable code encodes an n {\displaystyle n} -bit message x {\displaystyle x} to an N {\displaystyle N} -bit codeword C ( x ) {\displaystyle C(x)} such that any bit x i {\displaystyle x_{i}} of the message can be recovered with probability 1 − ϵ {\displaystyle 1-\epsilon } by using a randomized decoding algorithm that queries only q {\displaystyle q} bits of the codeword C ( x ) {\displaystyle C(x)} , even if up to δ N {\displaystyle \delta N} locations of the codeword have been corrupted. Furthermore, a perfectly smooth local decoder is a decoder such that, in addition to always generating the correct output given access to an uncorrupted codeword, for every j ∈ [ q ] {\displaystyle j\in [q]} and i ∈ [ n ] {\displaystyle i\in [n]} the j t h {\displaystyle j^{th}} query to recover the i t h {\displaystyle i^{th}} bit is uniform over [ N ] {\displaystyle [N]} . (The notation [ y ] {\displaystyle [y]} denotes the set { 1 , … , y } {\displaystyle \{1,\ldots ,y\}} ). Informally, this means that the set of queries required to decode any given bit are uniformly distributed over the codeword. Local list decoders are another interesting subset of local decoders. List decoding is useful when a codeword is corrupted in more than δ / 2 {\displaystyle \delta /2} places, where δ {\displaystyle \delta } is the minimum Hamming distance between two codewords. In this case, it is no longer possible to identify exactly which original message has been encoded, since there could be multiple codewords within δ {\displaystyle \delta } distance of the corrupted codeword. However, given a radius ϵ {\displaystyle \epsilon } , it is possible to identify the set of messages that encode to codewords that are within ϵ {\displaystyle \epsilon } of the corrupted codeword. An upper bound on the size of the set of messages can be determined by δ {\displaystyle \delta } and ϵ {\displaystyle \epsilon } . Locally decodable codes can also be concatenated, where a message is encoded first using one scheme, and the resulting codeword is encoded again using a different scheme. (Note that, in this context, concatenation is the term used by scholars to refer to what is usually called composition). This might be useful if, for example, the first code has some desirable properties with respect to rate, but it has some undesirable property, such as producing a codeword over a non-binary alphabet. The second code can then transform the result of the first encoding over a non-binary alphabet to a binary alphabet. The final encoding is still locally decodable, and requires additional steps to decode both layers of encoding.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Locally decodable code

Start with the simplest possible case. Write down what Locally decodable code 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 Locally decodable code 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 Locally decodable code 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 Locally decodable code

In research
Locally decodable code 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 Locally decodable code 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
Locally decodable code is common in secondary-school and first-year university syllabi. It links to neighbouring topics Error detection and correction, so understanding it makes those chapters shorter.
In everyday life
Look for Locally decodable code 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 Locally decodable code in 20 minutes

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

Frequently asked questions

What is Locally decodable code in simple terms?

A locally decodable code (LDC) is an error-correcting code that allows a single bit of the original message to be decoded with high probability by only examining (or querying) a small number of bits of a possibly corrupted codeword. This property could be useful, say, in a context where information…

Why does Locally decodable code 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 Locally decodable code?

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 Locally decodable code.

Tags

  • Error detection and correction

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