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These labels describe origin, not correctness: citations and verification chips remain separate evidence.
A series of nonnegative terms converges iff its partial sums are bounded, and then the sum is their supremum
Statement
Let be a sequence of reals with for every , let be its partial sums and let be the range of (Series, partial sums, convergence and the sum, divergence, and the tail series). Then:
- is nondecreasing (Nondecreasing, increasing, nonincreasing, decreasing, monotone, and eventually monotone sequences) and for every ;
- converges if and only if is bounded above (Lower bound, bounded below, bounded set), and in that case so in particular for every ;
- if is not bounded above then (Divergence to and to ) and diverges.
This is the theorem that makes the nonnegative theory work: for terms of one sign, convergence is a boundedness question and no candidate limit is ever needed. Every comparison test on this page is an application of it.
Facts & Assumptions
Given: A sequence of reals with for every , its partial sums , and the range (Series, partial sums, convergence and the sum, divergence, and the tail series, Finite sums and finite products, by recursion, Sequences of reals: bounded, eventually, frequently, tails, subsequences).
The recursion clause of the finite sum: (Finite sums and finite products, by recursion).
Consecutive comparisons suffice for monotonicity: is nondecreasing if and only if for every ; and a nondecreasing sequence is bounded below by its first term (Nondecreasing, increasing, nonincreasing, decreasing, monotone, and eventually monotone sequences).
Monotonicity of finite sums: if for all then (Laws of finite sums and finite products).
A monotone sequence converges if and only if it is bounded, that is if and only if there is with for every (A monotone sequence converges if and only if it is bounded, Sequences of reals: bounded, eventually, frequently, tails, subsequences).
A nondecreasing sequence bounded above converges to the supremum of its range, which exists by the least-upper-bound property (A nondecreasing sequence bounded above converges to the supremum of its range, and a nonincreasing sequence bounded below to the infimum, Complete ordered field (least-upper-bound property), Lower bound, bounded below, bounded set).
A nondecreasing sequence whose range is not bounded above diverges to (A nondecreasing sequence that is not bounded above diverges to , Divergence to and to ).
Proof
For every , , so and is nondecreasing.
For every , , all terms being nonnegative.
Claim 1 is steps 1.1 and 1.2 together.
Since we have , so is bounded in the sense of [L4] if and only if is bounded above.
By [L4] applied to the monotone sequence , the series converges if and only if is bounded, hence if and only if is bounded above.
If is bounded above then converges to , so converges with sum ; and since is an upper bound of , for every .
If is not bounded above then , and by step 3.1 the series diverges.
The equivalence and the identification of the sum as the supremum together make claim 2, and the divergence statement is claim 3.
Remarks
-
"Bounded" and "bounded above" coincide here, and only here. The equivalence used in step 2.2 rests on , which rests on every term being nonnegative. For a series with terms of both signs the partial sums can be bounded above and still fail to converge, so nothing in this theorem survives the loss of the sign hypothesis. That failure is exhibited by Two series with for all , convergent and divergent, when the terms may be negative ↗ on the companion page.
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Claim 3 is a strictly stronger statement than "diverges". Divergence alone permits oscillation (Series, partial sums, convergence and the sum, divergence, and the tail series); for nonnegative terms it cannot occur, and the partial sums necessarily run to . This is what licenses the phrase "the series diverges to " for nonnegative terms, and it is what the Abel-Dini theorem later on this page uses.
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This criterion is the monotone convergence property, worn differently. The proof above is monotone convergence for applied to the nondecreasing sequence of partial sums, and nothing is lost going back the other way. Given a nondecreasing sequence of reals, put and let , ; then (Series, partial sums, convergence and the sum, divergence, and the tail series), the partial sums are bounded exactly when is bounded above, and claim 1 returns the convergence of and so of . Testing boundedness of partial sums is therefore not a device special to series. Read in the vocabulary of The five completeness properties of an ordered field: least upper bound, monotone convergence, nested intervals, Bolzano-Weierstrass, and Cauchy completeness it is the property (MCT), which in an arbitrary ordered field already forces the Archimedean property on its own (The monotone convergence property alone forces the Archimedean property, so it carries no separate Archimedean hypothesis) and with it the least-upper-bound property (The monotone convergence property plus the Archimedean property imply the least-upper-bound property). The translation just given is carried out in , since Series, partial sums, convergence and the sum, divergence, and the tail series is stated for sequences of reals and this library defines no series over a general ordered field.
Depends on
- Series, partial sums, convergence and the sum, divergence, and the tail series
- Nondecreasing, increasing, nonincreasing, decreasing, monotone, and eventually monotone sequences
- A nondecreasing sequence bounded above converges to the supremum of its range, and a nonincreasing sequence bounded below to the infimum
- A monotone sequence converges if and only if it is bounded
- A nondecreasing sequence that is not bounded above diverges to $+\infty$
- Lower bound, bounded below, bounded set
- Finite sums and finite products, by recursion
- Laws of finite sums and finite products
- Sequences of reals: bounded, eventually, frequently, tails, subsequences
- Divergence to $+\infty$ and to $-\infty$
- Complete ordered field (least-upper-bound property)
Used by
- If ∑ aₖ and ∑ bₖ both converge absolutely then their Cauchy product converges absolutely, with sum AB Corollary
- 1/4 lies in the Cantor set and is the endpoint of no removed interval, so the endpoints do not exhaust it Counterexample
- ℝ is the union of a meager set and a set of measure zero, so smallness of category and smallness of measure are independent notions Counterexample
- Two series with aₖ ≤ bₖ for all k, ∑ bₖ convergent and ∑ aₖ divergent, when the terms may be negative Counterexample
- Measure zero (a countable cover by intervals of total length below every ε) and content zero (a finite such cover) Definition
- Measure zero and content zero in ℝᵐ by countable and finite cube covers Definition
- The Cantor function on [0,1], defined on the Cantor set through ternary digits and extended constantly across each removed interval Definition
- The Smith-Volterra-Cantor set: the same construction removing, at stage n ≥ 1, an open middle interval of length 4⁻ⁿ from each of the 2ⁿ⁻¹ remaining intervals Definition
- ∑ 1/k² converges with sum at most 2, by comparison with the telescoping ∑ 1/(k(k-1)) Example
- ℚ is covered by open intervals of total length ε, for every ε > 0 Example
- The array with aᵢᵢ = 1, a_i+1,i = -1 and every other entry 0 has iterated sums 1 and 0 Example
- The Cantor function takes the value 1/2 on all of [1/3, 2/3], and its values at 1/9, 1/4 and 7/9 Example
- The Cantor set is homeomorphic to {0,1}^ℕ with the product of discrete topologies, the ternary digits being the coordinates Example
- The harmonic series ∑ 1/k diverges, by condensation and by Oresme block grouping Example
- The Hilbert cube [0,1]^ℕ with the product topology is metrizable, by d(x,y) = ∑ₖ |xₖ - yₖ| / 2^ k+1 Example
- The intervals removed from the Smith-Volterra-Cantor set have total length 1/2, so the set cannot be covered by intervals of total length less than 1/2 Example
- Which points of [0,1] lie in the Cantor set, read off their ternary expansions, with 1/4 worked out Example
- FALSE: ∏ (1 + pₖ) converges whenever pₖ → 0 False statement
- FALSE: there is a divergent series of positive terms that diverges more slowly than every other, hence a universal comparison test False statement
- A sequence of intervals covering [a,b] has total length at least b - a, so no interval of positive length has measure zero Lemma
- Every at most countable subset of ℝ has measure zero Lemma
- If for every ε > 0 some continuous g : X → ℝ satisfies | f(x) - g(x)| < ε for all x, then f is continuous; in particular a uniformly convergent series of continuous real functions has a continuous sum Lemma
- Positive and negative parts: aₖ = aₖ⁺ - aₖ⁻ and |aₖ| = aₖ⁺ + aₖ⁻; a series converges absolutely iff both ∑ aₖ⁺ and ∑ aₖ⁻ converge, and for a conditionally convergent series both diverge to +∞ Lemma
- Subsets and countable unions of null subsets of ℝᵐ are null Lemma
- A countable union of measure-zero sets has measure zero, by countable choice Theorem
- Assuming countable choice, a real family is summable as a finite-subset net if and only if it has at most countable support and its nonzero terms are absolutely summable; its sum is independent of the enumeration Theorem
- Base-b expansions: for an integer b ≥ 2 every x ∈ [0,1) is the sum of ∑_j ≥ 0 dⱼ / b^ j+1 for digits dⱼ < b, and the digit sequence is unique among those that are not eventually constantly b-1 Theorem
- Converse to Froda: for every at most countable E ⊆ ℝ there is a bounded nondecreasing f : ℝ → ℝ whose set of discontinuities is exactly E, every one of them a jump Theorem
- Dirichlet's rearrangement theorem: an absolutely convergent series converges unconditionally, and every rearrangement of it has the same sum Theorem
- For a compact subset of ℝ, measure zero and content zero coincide Theorem
- For a divergent series of positive terms with partial sums sₖ, the series ∑ aₖ/sₖ diverges and ∑ aₖ/sₖ² converges Theorem
- For a nonincreasing nonnegative sequence, ∑ aₖ converges iff ∑ 2ᵏ a_2ᵏ converges Theorem
- For pₖ ≥ 0 the product ∏ (1 + pₖ) converges iff ∑ pₖ converges, with 1 + ∑_k<n pₖ ≤ ∏_k<n(1+pₖ) ≤ 1/(1 - ∑_k<n pₖ) when ∑_k<n pₖ < 1; for 0 ≤ pₖ < 1 the product ∏ (1 - pₖ) converges iff ∑ pₖ converges and its partial products tend to 0 otherwise; and ∑ |pₖ| convergent implies ∏ (1+pₖ) convergent Theorem
- Fubini for double series: if ∑ᵢ ∑ⱼ |aᵢⱼ| converges then both iterated sums and the sum along every bijection ℕ → ℕ × ℕ converge to one and the same value Theorem
- Gauss: for positive terms, if aₖ/aₖ₊₁ = 1 + h/k + rₖ with |rₖ| ≤ C k^-1-ε for k ≥ 1, some constant C and some rational ε > 0, the series converges iff h > 1 Theorem
- If 0 ≤ aₖ ≤ bₖ eventually, convergence of ∑ bₖ gives convergence of ∑ aₖ, and divergence of ∑ aₖ gives divergence of ∑ bₖ Theorem
- Mertens' theorem: if ∑ aₖ converges absolutely to A and ∑ bₖ converges to B, their Cauchy product converges to AB Theorem
- The Cantor function is well defined, satisfies c(x) ≤ c(y) whenever x ≤ y, is surjective onto [0,1], and is constant on every interval removed from the Cantor set Theorem
- The Cantor set is exactly the set of ∑_k ≥ 1 aₖ 3⁻ᵏ with every aₖ ∈ {0,2}, and this gives a bijection with {0,1}^ℕ Theorem
- The exponential tends to +∞ at +∞ and to 0 at -∞ Theorem
…and 4 more results.
Dependency tree · next 3 levels
Direct dependencies and their dependencies through the next three levels: 71 results over 14 levels. An arrow runs from a result to what uses it, and this result sits at the bottom with a heavier outline. Click the chart to enlarge it.
Sources
- Series (mathematics) (Wikipedia) (standard reference, not scraped)
- W. Rudin, Principles of Mathematical Analysis, 3rd ed., Ch. 3 (3.24) (standard reference, not scraped)
- John K. Hunter, An Introduction to Real Analysis (standard reference, not scraped)