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Large set (combinatorics)

Large set (combinatorics) 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 Large set (combinatorics) rather than just read about it. In short: In combinatorial mathematics, a large set of positive integers S = { s 0 , s 1 , s 2 , s 3 , … } {\displaystyle S=\{s_{0},s_{1},s_{2},s_{3},\dots \}} is one such that the infinite sum of the reciprocals 1 s 0 + 1 s 1 + 1 s 2 + 1 s 3 + ⋯ {\displaystyle {\frac {1}{s_{0}}}+{\frac {1}{s_{1}}}+{\frac {1}{s_{2}}}+{\frac {1}{s_{3}}}+\cdots } diverges. A small set is any subset of the positive integers that is not large; th…

Key takeaways

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

Reference excerpt

In combinatorial mathematics, a large set of positive integers

S = { s 0 , s 1 , s 2 , s 3 , … } {\displaystyle S=\{s_{0},s_{1},s_{2},s_{3},\dots \}}

is one such that the infinite sum of the reciprocals

1 s 0 + 1 s 1 + 1 s 2 + 1 s 3 + ⋯ {\displaystyle {\frac {1}{s_{0}}}+{\frac {1}{s_{1}}}+{\frac {1}{s_{2}}}+{\frac {1}{s_{3}}}+\cdots }

diverges. A small set is any subset of the positive integers that is not large; that is, one whose sum of reciprocals converges. Large sets appear in the Müntz–Szász theorem and in the Erdős conjecture on arithmetic progressions.

Examples Every finite subset of the positive integers is small. The set { 1 , 2 , 3 , 4 , 5 , … } {\displaystyle \{1,2,3,4,5,\dots \}} of all positive integers is a large set; this statement is equivalent to the divergence of the harmonic series. More generally, any arithmetic progression (i.e., a set of all integers of the form an + b with a ≥ 1, b ≥ 1 and n = 0, 1, 2, 3, ...) is a large set. The set of square numbers is small (see Basel problem § The Riemann zeta function). So is the set of cube numbers, the set of 4th powers, and so on. More generally, the set of positive integer values of any polynomial of degree 2 or larger forms a small set. The set {1, 2, 4, 8, ...} of powers of 2 is a small set, and so is any geometric progression (i.e., a set of numbers of the form of the form abn with a ≥ 1, b ≥ 2 and n = 0, 1, 2, 3, ...). The set of prime numbers is large. The set of twin primes is small (see Brun's constant). The set of prime powers which are not prime (i.e., all numbers of the form pn with n ≥ 2 and p prime) is small although the primes are large. This property is frequently used in analytic number theory. More generally, the set of perfect powers is small; even the set of powerful numbers is small. The set of numbers whose expansions in a given base exclude a given digit is small. For example, the set { 1 , 2 , … , 5 , 6 , 8 , 9 , … , 15 , 16 , 18 , 19 , … , 65 , 66 , 68 , 69 , 80 , 81 , … } {\displaystyle \{1,2,\dots ,5,6,8,9,\dots ,15,16,18,19,\dots ,65,66,68,69,80,81,\dots \}} of integers whose decimal expansion does not include the digit 7 is small. Such series are called Kempner series. Any set whose upper asymptotic density is nonzero, is large. The set of all primes in an arithmetic progression an + b, where a and b are coprime is large (see Dirichlet's theorem on arithmetic progressions).

Properties Every subset of a small set is small. The union of finitely many small sets is small, because the sum of two convergent series is a convergent series. (Hence, the small sets form an ideal on the set of positive integers.) The complement of every small set is large. The Müntz–Szász theorem states that a set S = { s 1 , s 2 , s 3 , … } {\displaystyle S=\{s_{1},s_{2},s_{3},\dots \}} is large if and only if the set of polynomials spanned by { 1 , x s 1 , x s 2 , x s 3 , … } {\displaystyle \{1,x^{s_{1}},x^{s_{2}},x^{s_{3}},\dots \}} is dense in the uniform norm topology of continuous functions on a closed interval in the positive real numbers. This is a generalization of the Stone–Weierstrass theorem.

Open problems involving large sets Paul Erdős conjectured that all large sets contain arbitrarily long arithmetic progressions. He offered a prize of $3000 for a proof, more than for any of his other conjectures, and joked that this prize offer violated the minimum wage law. The question is still open. It is not known how to identify whether a given set is large or small in general. As a result, there are many sets which are not known to be either large or small.

See also List of sums of reciprocals

Notes

References Wadhwa, A. D. (1975). "An interesting subseries of the harmonic series". American Mathematical Monthly. 82 (9): 931–933. JSTOR 2318503.

Worked examples

Example 1 — a first encounter with Large set (combinatorics)

Start with the simplest possible case. Write down what Large set (combinatorics) 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 Large set (combinatorics) 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 Large set (combinatorics) 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 Large set (combinatorics)

In research
Large set (combinatorics) 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 Large set (combinatorics) 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
Large set (combinatorics) is common in secondary-school and first-year university syllabi. It links to neighbouring topics Combinatorics, Integer sequences, Series (mathematics), so understanding it makes those chapters shorter.
In everyday life
Look for Large set (combinatorics) 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 Large set (combinatorics) in 20 minutes

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

Frequently asked questions

What is Large set (combinatorics) in simple terms?

In combinatorial mathematics, a large set of positive integers S = { s 0 , s 1 , s 2 , s 3 , … } {\displaystyle S=\{s_{0},s_{1},s_{2},s_{3},\dots \}} is one such that the infinite sum of the reciprocals 1 s 0 + 1 s 1 + 1 s 2 + 1 s 3 + ⋯ {\displaystyle {\frac {1}{s_{0}}}+{\frac {1}{s_{1}}}+{\frac {1…

Why does Large set (combinatorics) 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 Large set (combinatorics)?

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 Large set (combinatorics).

Tags

  • Combinatorics
  • Integer sequences
  • Series (mathematics)

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