Rearrangements and Riemann's Rearrangement Theorem

Can you add up the same infinite list of numbers in a different order and get a different answer? For finite sums, commutativity settles the question instantly: order never matters. For infinite series, this article shows that the honest answer is sometimes. When it fails, it fails as badly as possible. The series 1−12+13−14+⋯1 - \tfrac12 + \tfrac13 - \tfrac14 + \cdots converges to ln⁡2\ln 2. Yet a suitable reordering of its terms converges to π\pi, or to −17-17, or diverges to +∞+\infty. All this uses exactly the same multiset of numbers. This phenomenon is not a curiosity to be filed away. It is a structural fact about the difference between absolute and conditional convergence. It forces a precise understanding of what "sum of a series" even means, once the order of summation is allowed to vary. The resolution splits cleanly into two theorems that are dual to each other. One says rearrangement is harmless when the series converges absolutely. The other — due to Bernhard Riemann — says rearrangement is maximally destructive when the series converges only conditionally. The big picture is this: absolute convergence is precisely the condition under which addition of infinitely many terms behaves like addition of finitely many terms. It is commutative, associative, insensitive to grouping and reordering. Conditional convergence is a much more fragile phenomenon. It is a delicate cancellation between a divergent sum of positive terms and a divergent sum of negative terms. Reordering can tip that cancellation to any value you like. This article gives the full rigorous story. It offers a clean definition of "rearrangement," and a complete proof that absolutely convergent series are rearrangement-invariant. It also gives a complete constructive proof of Riemann's theorem. That theorem states a conditionally convergent series of real numbers can be rearranged to converge to any prescribed extended real number, or to oscillate without limit.

Key takeaways
  • A rearrangement of a series is a reindexing by a bijection of N\mathbb{N}; it uses every term exactly once, just in a different order.
  • If ∑an\sum a_n converges absolutely, every rearrangement converges to the same sum — order is irrelevant.
  • If ∑an\sum a_n converges conditionally, the positive terms alone diverge to +∞+\infty and the negative terms alone diverge to −∞-\infty.
  • Riemann's Rearrangement Theorem: for any conditionally convergent real series and any target L∈[−∞,+∞]L \in [-\infty, +\infty], some rearrangement converges to LL (or oscillates, if you instead want no limit at all).
  • The proof of Riemann's theorem is explicit and algorithmic: greedily take just enough positive terms to overshoot the target, then just enough negative terms to undershoot it, and repeat forever.
  • Key idea: absolute convergence tames infinite sums into finite-sum-like objects; conditional convergence is a controlled cancellation of two divergent tails, and control over that cancellation is exactly what reordering can hijack.

Where this lives today

The absolute-convergence side of this dichotomy is why, in Fourier analysis and probability theory, one is careful to demand absolute summability (or use more delicate summation methods like Abel or Cesàro summation) before rearranging infinite sums of Fourier coefficients or of probabilities — an unjustified reordering of a conditionally convergent sum can silently corrupt a computation. In numerical analysis, floating-point summation of long conditionally-convergent-looking sequences is order-sensitive for exactly this reason, and algorithms (e.g. Kahan summation, or sorting terms to sum small-to-large) are designed around controlling this sensitivity, even though finite floating-point sums are not literally infinite series — the intuition transfers because near-cancellation is the same underlying issue. In the study of conditionally convergent integrals (improper Riemann integrals and principal values), an entirely parallel phenomenon occurs: the value of ∫−∞∞f\int_{-\infty}^\infty f for a conditionally integrable ff can depend on the manner of taking the limits of integration, exactly mirroring order-dependence in series; the Absolute vs Conditional Convergence dichotomy for series is the discrete shadow of this continuous story. In complex analysis and the study of infinite products, related rearrangement subtleties arise when reordering factors of conditionally convergent products. In the Lévy–Steinitz theorem's higher-dimensional generalization, rearrangement phenomena connect to convex geometry (the set of attainable sums is provably an affine subspace, a genuinely geometric fact about Rk\mathbb{R}^k), with further generalizations studied in infinite-dimensional Banach space theory. Finally, in a purely pedagogical role, Riemann's theorem is a canonical example in courses following Sequences and Series and Absolute vs Conditional Convergence of how rigor — not intuition from finite arithmetic — must govern reasoning about infinite processes; it is frequently paired with the Cauchy Criterion for Series as the technical engine behind both directions of the dichotomy.

Ask the tutor: How does the Lévy–Steinitz theorem generalize Riemann's rearrangement theorem to series of vectors in Rk\mathbb{R}^k?

DefinitionRearrangement of a series

Let ∑n=1∞an\sum_{n=1}^{\infty} a_n be a series of real (or complex) numbers. A rearrangement of this series is a series

∑n=1∞aσ(n)\sum_{n=1}^{\infty} a_{\sigma(n)}

where σ:N→N\sigma : \mathbb{N} \to \mathbb{N} is a bijection. That is, we choose a new order in which to list the terms a1,a2,a3,…a_1, a_2, a_3, \ldots, using each term exactly once, and sum in that order. We say the original series and its rearrangement are the same series with a different order of summation. A series ∑an\sum a_n is:

  • Absolutely convergent if ∑∣an∣<∞\sum |a_n| < \infty;
  • Conditionally convergent if ∑an\sum a_n converges but ∑∣an∣=∞\sum |a_n| = \infty.

Intuition

Think of ∑an\sum a_n as an instruction to walk along the real line: at step nn you move by ana_n. Absolute convergence means the total distance traveled, ∑∣an∣\sum |a_n|, is finite — you make a finite journey, and no matter what order you take the steps in, you end up at the same destination, because the steps' sizes shrink fast enough that reordering them can only permute a finite total displacement among finite partial errors that vanish in the limit. Conditional convergence is different: you take infinitely many steps forward whose total length is infinite, and infinitely many steps backward whose total length is also infinite, and these two infinite journeys are just barely choreographed to cancel down to a finite net displacement. Riemann's insight is that this choreography is not intrinsic to the numbers — it is an artifact of the original order. Since the positive steps alone can carry you arbitrarily far right, and the negative steps alone can carry you arbitrarily far back left, you can re-choreograph: walk forward using only positive steps until you pass any target you like, then walk backward using only negative steps until you undershoot it, then forward again, forever, homing in on whatever target you chose.

Figure
Two rearrangements of 1−12+13−14+⋯1-\tfrac12+\tfrac13-\tfrac14+\cdots targeting different limits
n (step) value 0 ln 2 ≈ 0.693 (original order) original order → ln 2 rearranged → target L = 2 L=2 Both series use the same terms {±1, ±1/2, ±1/3, …}; only the order of summation differs. Blue: partial sums S_N of 1 − 1/2 + 1/3 − 1/4 + ⋯ converge to ln 2. Red: a rearranged partial sum sequence, built by Riemann's algorithm, converges to 2 instead.

The two theorems

TheoremInvariance of absolutely convergent series under rearrangement

Let ∑n=1∞an\sum_{n=1}^{\infty} a_n be a series of real or complex numbers with ∑n=1∞∣an∣<∞\sum_{n=1}^{\infty} |a_n| < \infty, and let σ:N→N\sigma : \mathbb{N} \to \mathbb{N} be any bijection. Then

∑n=1∞aσ(n)\sum_{n=1}^{\infty} a_{\sigma(n)}

converges absolutely, and

∑n=1∞aσ(n)=∑n=1∞an.\sum_{n=1}^{\infty} a_{\sigma(n)} = \sum_{n=1}^{\infty} a_n.
Proof

Technique: ε\varepsilon-tail estimate using absolute convergence, via the Cauchy criterion. Let S=∑n=1∞anS = \sum_{n=1}^{\infty} a_n and let ε>0\varepsilon > 0 be given.

Step 1 (tail smallness). Since ∑∣an∣<∞\sum |a_n| < \infty, the sequence of partial sums of ∑∣an∣\sum|a_n| is Cauchy, so there exists N∈NN \in \mathbb{N} such that

∑n=N+1∞∣an∣<ε2.\sum_{n=N+1}^{\infty} |a_n| < \frac{\varepsilon}{2}.

(This sum is finite because ∑∣an∣\sum |a_n| converges, so its tail past any point is a nonnegative convergent series and shrinks to 00.) Consequently, if SN=∑n=1NanS_N = \sum_{n=1}^N a_n denotes the NN-th partial sum of the original series, then

∣S−SN∣=∣∑n=N+1∞an∣≤∑n=N+1∞∣an∣<ε2,(1)|S - S_N| = \left|\sum_{n=N+1}^\infty a_n\right| \le \sum_{n=N+1}^\infty |a_n| < \frac{\varepsilon}{2}, \tag{1}

using the triangle inequality for the (finite-tail) sum, extended to the infinite tail by taking a limit of finite partial tails, which is legitimate since the tail series converges absolutely.

Step 2 (finding where all the first NN terms reappear). Because σ\sigma is a bijection, each of 1,2,…,N1, 2, \ldots, N appears exactly once among σ(1),σ(2),…\sigma(1), \sigma(2), \ldots. Let

M=max⁡{σ−1(1),σ−1(2),…,σ−1(N)}.M = \max\{\sigma^{-1}(1), \sigma^{-1}(2), \ldots, \sigma^{-1}(N)\}.

This MM is a well-defined natural number since it is the maximum of a finite set of natural numbers. By construction, for every m≥Mm \ge M, the finite set {σ(1),…,σ(m)}\{\sigma(1), \ldots, \sigma(m)\} contains {1,2,…,N}\{1, 2, \ldots, N\} as a subset (every index k≤Nk \le N has σ−1(k)≤M≤m\sigma^{-1}(k) \le M \le m, so k=σ(σ−1(k))k = \sigma(\sigma^{-1}(k)) appears among the first mm rearranged terms).

Step 3 (comparing partial sums of the rearrangement to SNS_N). Fix any m≥Mm \ge M, and let Tm=∑k=1maσ(k)T_m = \sum_{k=1}^m a_{\sigma(k)}. By Step 2, {1,…,N}⊆{σ(1),…,σ(m)}\{1, \ldots, N\} \subseteq \{\sigma(1), \ldots, \sigma(m)\}, so

Tm−SN=∑k=1maσ(k)−∑n=1Nan=∑j∈{σ(1),…,σ(m)}j>Naj,T_m - S_N = \sum_{k=1}^m a_{\sigma(k)} - \sum_{n=1}^N a_n = \sum_{\substack{j \in \{\sigma(1),\ldots,\sigma(m)\} \\ j > N}} a_j,

because the terms indexed by 1,…,N1, \ldots, N appear in both sums and cancel exactly (each exactly once, since σ\sigma is injective on {1,…,m}\{1,\ldots,m\}), leaving only rearranged terms whose original index exceeds NN. Every index jj appearing in this remaining sum satisfies j>Nj > N and j∈{σ(1),…,σ(m)}j \in \{\sigma(1), \ldots, \sigma(m)\}, a finite set of distinct indices all exceeding NN. Hence, by the triangle inequality and Step 1's tail estimate,

∣Tm−SN∣≤∑j>N∣aj∣<ε2.(2)|T_m - S_N| \le \sum_{\substack{j > N}} |a_j| < \frac{\varepsilon}{2}. \tag{2}

(The sum on the right is over all indices j>Nj > N, which only enlarges a sum of nonnegative terms, so the inequality is valid.)

Step 4 (combining). For all m≥Mm \ge M, by (1) and (2) and the triangle inequality,

∣Tm−S∣≤∣Tm−SN∣+∣SN−S∣<ε2+ε2=ε.|T_m - S| \le |T_m - S_N| + |S_N - S| < \frac{\varepsilon}{2} + \frac{\varepsilon}{2} = \varepsilon.

Since ε>0\varepsilon > 0 was arbitrary, this shows Tm→ST_m \to S as m→∞m \to \infty, i.e. ∑n=1∞aσ(n)=S=∑n=1∞an\sum_{n=1}^\infty a_{\sigma(n)} = S = \sum_{n=1}^\infty a_n.

Step 5 (absolute convergence of the rearrangement). Apply Steps 1–4 verbatim to the nonnegative series ∑∣an∣\sum |a_n| in place of ∑an\sum a_n (a nonnegative series trivially "converges absolutely" to itself, since ∣∣an∣∣=∣an∣||a_n|| = |a_n|). This shows ∑n=1∞∣aσ(n)∣=∑n=1∞∣an∣<∞\sum_{n=1}^\infty |a_{\sigma(n)}| = \sum_{n=1}^\infty |a_n| < \infty, so the rearranged series converges absolutely. ■\blacksquare

∎
LemmaPositive and negative parts of a conditionally convergent series

Let ∑an\sum a_n be a conditionally convergent series of real numbers. Define

pn=max⁡(an,0),qn=max⁡(−an,0),p_n = \max(a_n, 0), \qquad q_n = \max(-a_n, 0),

so that an=pn−qna_n = p_n - q_n and ∣an∣=pn+qn|a_n| = p_n + q_n, with pn,qn≥0p_n, q_n \ge 0. Then

∑n=1∞pn=+∞and∑n=1∞qn=+∞.\sum_{n=1}^\infty p_n = +\infty \qquad \text{and} \qquad \sum_{n=1}^\infty q_n = +\infty.
Proof

Technique: proof by contradiction, splitting a series into signed parts. Suppose, for contradiction, that ∑pn\sum p_n converges (to a finite value PP). Since qn=pn−anq_n = p_n - a_n and both ∑pn\sum p_n and ∑an\sum a_n converge (the latter by hypothesis, the former by our supposition), the series ∑qn=∑(pn−an)\sum q_n = \sum(p_n - a_n) converges as well, to Q:=P−∑anQ := P - \sum a_n, by linearity of convergent series (a finite sum of two convergent series converges to the sum of the limits — this is immediate from the definition of a limit of partial sums and does not use anything about rearrangement). But then

∑n=1∞∣an∣=∑n=1∞(pn+qn)=P+Q<∞,\sum_{n=1}^\infty |a_n| = \sum_{n=1}^\infty (p_n + q_n) = P + Q < \infty,

again by linearity of convergent series, contradicting the hypothesis that ∑an\sum a_n is only conditionally convergent (i.e. that ∑∣an∣=∞\sum |a_n| = \infty). Hence ∑pn\sum p_n diverges; since pn≥0p_n \ge 0, its partial sums are nondecreasing, so divergence forces ∑pn=+∞\sum p_n = +\infty. By an identical argument with the roles of pnp_n and qnq_n swapped, ∑qn=+∞\sum q_n = +\infty. ■\blacksquare

∎
TheoremRiemann's Rearrangement Theorem

Let ∑n=1∞an\sum_{n=1}^\infty a_n be a conditionally convergent series of real numbers, and let LL be any element of the extended real line [−∞,+∞][-\infty, +\infty]. Then there exists a bijection σ:N→N\sigma : \mathbb{N} \to \mathbb{N} such that

∑n=1∞aσ(n)=L,\sum_{n=1}^\infty a_{\sigma(n)} = L,

meaning: if LL is finite, the partial sums of the rearranged series converge to LL; if L=+∞L = +\infty (resp. −∞-\infty), the partial sums of the rearranged series diverge to +∞+\infty (resp. −∞-\infty). Moreover, there is also a rearrangement whose partial sums neither converge nor diverge to ±∞\pm\infty, but oscillate boundedly or unboundedly forever.

Proof

Technique: explicit greedy construction, using the Lemma above and the fact that an→0a_n \to 0. First note a preliminary fact we will need: since ∑an\sum a_n converges, an→0a_n \to 0 as n→∞n \to \infty (the terms of any convergent series tend to 00, since an=Sn−Sn−1→S−S=0a_n = S_n - S_{n-1} \to S - S = 0 where SnS_n are partial sums converging to SS). Consequently pn→0p_n \to 0 and qn→0q_n \to 0 as well, since 0≤pn≤∣an∣0 \le p_n \le |a_n| and 0≤qn≤∣an∣0 \le q_n \le |a_n|. Let (pn)(p_n) be the subsequence of strictly positive terms of (an)(a_n), listed in their original relative order, and let (qn)(q_n) be the subsequence of the absolute values of the strictly negative terms of (an)(a_n), also listed in original relative order. (Terms equal to 00 may be placed anywhere at the end without affecting any partial sum; discard them from this bookkeeping and reinsert them into σ\sigma arbitrarily at the very end of the construction — this changes no partial sums past their insertion point, and formally does not disturb convergence, since adding zero terms to a partial sum leaves it unchanged.) By the Lemma applied to ∑an\sum a_n,

∑kpk=+∞,∑kqk=+∞,\sum_{k} p_k = +\infty, \qquad \sum_k q_k = +\infty,

and since these are subsequences of a null sequence an→0a_n \to 0, we also have pk→0p_k \to 0 and qk→0q_k \to 0.

Case 1: LL finite. We construct the rearrangement in blocks, alternating between runs of positive terms and runs of negative terms, using the following greedy rule. Block 11: Since ∑kpk=+∞\sum_k p_k = +\infty and each pk>0p_k > 0, there is a least integer m1m_1 such that

p1+p2+⋯+pm1>L.p_1 + p_2 + \cdots + p_{m_1} > L.

(Such an m1m_1 exists because the partial sums of ∑pk\sum p_k are nondecreasing and unbounded, hence eventually exceed LL; "least" makes m1m_1 well defined by the well-ordering principle.) Append p1,…,pm1p_1, \ldots, p_{m_1}, in order, to the rearranged sequence. Let R1R_1 denote the resulting partial sum, so R1>LR_1 > L, and — crucially — since m1m_1 is least, we had p1+⋯+pm1−1≤Lp_1 + \cdots + p_{m_1 - 1} \le L, so

R1=(p1+⋯+pm1−1)+pm1≤L+pm1,i.e.0<R1−L≤pm1.(3)R_1 = (p_1 + \cdots + p_{m_1-1}) + p_{m_1} \le L + p_{m_1}, \quad\text{i.e.}\quad 0 < R_1 - L \le p_{m_1}. \tag{3}

Block 22: Since ∑kqk=+∞\sum_k q_k = +\infty, there is a least integer n1n_1 such that

R1−(q1+⋯+qn1)<L.R_1 - (q_1 + \cdots + q_{n_1}) < L.

Append −q1,…,−qn1-q_1, \ldots, -q_{n_1}, in order, to the rearranged sequence. Let R2R_2 be the resulting partial sum, so R2<LR_2 < L, and by leastness of n1n_1, exactly as above,

0<L−R2≤qn1.(4)0 < L - R_2 \le q_{n_1}. \tag{4}

Continue inductively: having built R2j−1>LR_{2j-1} > L using the next unused block of pp's (least length to first exceed LL) and R2j<LR_{2j} < L using the next unused block of qq's (least length to first go below LL), the construction continues forever. This is possible at every stage because ∑pk=∞\sum p_k = \infty and ∑qk=∞\sum q_k = \infty remain true for every tail of these sequences — removing any finite number of initial terms from a series that diverges to +∞+\infty leaves a series that still diverges to +∞+\infty, since only finitely much has been removed from an unbounded nondecreasing sequence of partial sums. Every term pkp_k and every qkq_k gets used exactly once, in exactly one block, and every block is finite, so this process defines a genuine bijection σ:N→N\sigma: \mathbb{N} \to \mathbb{N} from the position in the newly built list to the original index — every original term appears exactly once in the new order. (Zero terms of the original series, set aside earlier, are appended in a final infinite "tail" arbitrarily reinserted at density zero without effect on limits — formally, one interleaves them so that the NN-th partial sum of the true full rearrangement differs from the partial sum of the nonzero-only construction by a sum of finitely many zeros; we suppress this bookkeeping detail below since it changes no value.)

Convergence to LL. We must show the partial sums of the full rearranged series converge to LL. Consider any partial sum TmT_m of the rearranged series where mm lies within block 2j−12j-1 (a positive-block) or block 2j2j (a negative-block). Within a positive block, partial sums are increasing from R2j−2R_{2j-2} up to R2j−1R_{2j-1} (or from LL's neighborhood up to R1R_1 if j=1j=1); within a negative block they are decreasing from R2j−1R_{2j-1} down to R2jR_{2j}. Hence every partial sum TmT_m lies between the two most recent "turning" values, i.e.

min⁡(R2j−2,R2j)−qnj  ≤  (actually more precisely)Tm∈[ interval bounded by consecutive Ri ].\min(R_{2j-2}, R_{2j}) - q_{n_{j}} \;\le\; \text{(actually more precisely)} \quad T_m \in [\,\text{interval bounded by consecutive } R_i\,].

More precisely and rigorously: for mm in the interior of block 2j−12j-1 (a run of positive terms), the partial sum TmT_m satisfies R2j−2<Tm≤R2j−1R_{2j-2} < T_m \le R_{2j-1} (increasing partial sums within an all-positive block, starting above or at LL's undershoot R2j−2<LR_{2j-2} < L and rising to overshoot R2j−1>LR_{2j-1} > L); by (3)-type bound applied at stage jj,

0≤Tm−L≤R2j−1−L≤pmj(the last new term added in that block).0 \le T_m - L \le R_{2j-1} - L \le p_{m_j} \quad (\text{the last new term added in that block}).

Symmetrically, for mm in block 2j2j (all-negative run), R2j≤Tm<R2j−1R_{2j} \le T_m < R_{2j-1}, and

0≤L−Tm≤L−R2j≤qnj.0 \le L - T_m \le L - R_{2j} \le q_{n_j}.

In either case,

∣Tm−L∣≤max⁡(pmj,qnj).(5)|T_m - L| \le \max(p_{m_j}, q_{n_j}). \tag{5}

Since mj→∞m_j \to \infty and nj→∞n_j \to \infty as j→∞j \to \infty (each block uses at least one new term, and there are infinitely many blocks since ∑pk,∑qk=∞\sum p_k, \sum q_k = \infty force the process never to terminate), and since pk→0p_k \to 0, qk→0q_k \to 0, the right side of (5) tends to 00 as j→∞j \to \infty, i.e. as m→∞m \to \infty. Given ε>0\varepsilon > 0, choose JJ so that pk,qk<εp_k, q_k < \varepsilon for all kk appearing in blocks ≥2J\ge 2J (possible since pk,qk→0p_k, q_k \to 0); then for all mm past the start of block 2J2J, ∣Tm−L∣<ε|T_m - L| < \varepsilon by (5). Hence Tm→LT_m \to L, proving ∑aσ(n)=L\sum a_{\sigma(n)} = L.

Case 2: L=+∞L = +\infty. Modify the construction: at stage jj, choose the least mjm_j so that appending the next block of unused pkp_k's makes the partial sum exceed jj (rather than LL), then append exactly one unused qkq_k (rather than a block chosen to undershoot). This is always possible: the positive terms alone sum to +∞+\infty so we can always find enough of them to clear any finite threshold jj, and we use only a single negative term per round so the negative contribution is summable in a controlled way — concretely, since qk→0q_k \to 0, the single negative term used at stage jj contributes at most qk→0q_k \to 0, an amount too small to prevent the partial sums from eventually exceeding every threshold. Formally, the partial sum after stage jj exceeds j−qkjj - q_{k_j} where qkj→0q_{k_j} \to 0, and since every original qkq_k is used exactly once across all stages (there are infinitely many stages, one qkq_k consumed per stage, and ∑qk=∞\sum q_k = \infty only requires that we have infinitely many qkq_k available, which we do), the construction is a valid bijection and the partial sums diverge to +∞+\infty. The case L=−∞L = -\infty is symmetric, with the roles of pkp_k and qkq_k exchanged.

Oscillation. To make the rearranged series have no limit in [−∞,∞][-\infty,\infty], alternately target L=0L = 0 and L=1L = 1 (say): run the Case-1 construction toward L=0L=0 for finitely many blocks until the partial sum is within 13\tfrac13 of 00, then switch and run finitely many blocks of the Case-1 construction toward L=1L=1 until the partial sum is within 13\tfrac13 of 11, then switch back, forever. At each switch the argument of Case 1 (specifically bound (5), applied locally) guarantees the target is approached before switching again, so the partial sums infinitely often come within 16\tfrac16 of 00 and infinitely often come within 16\tfrac16 of 11; hence lim inf⁡Tm≤16<56≤lim sup⁡Tm\liminf T_m \le \tfrac16 < \tfrac56 \le \limsup T_m, so (Tm)(T_m) has no limit in [−∞,∞][-\infty,\infty]. Every original term is still used exactly once across the infinite alternation, by the same tail-never-runs-out argument as before, so σ\sigma is a genuine bijection. ■\blacksquare

∎

Worked examples

Example 1: Rearranging the alternating harmonic series to converge to 11. Let an=(−1)n+1na_n = \frac{(-1)^{n+1}}{n}, so ∑an=1−12+13−14+⋯=ln⁡2≈0.6931\sum a_n = 1 - \tfrac12 + \tfrac13 - \tfrac14 + \cdots = \ln 2 \approx 0.6931. This is conditionally convergent: ∑∣an∣=∑1n=∞\sum |a_n| = \sum \tfrac1n = \infty, but ∑an\sum a_n converges (by the alternating series test, since 1n↓0\tfrac1n \downarrow 0). We rearrange it, by Riemann's algorithm, to converge to L=1L = 1. Here pk=12k−1p_k = \frac{1}{2k-1} (positive terms 1,13,15,…1, \tfrac13, \tfrac15,\ldots) and qk=12kq_k = \frac{1}{2k} (absolute values of negative terms 12,14,16,…\tfrac12, \tfrac14, \tfrac16,\ldots). Block 1 (positive terms until we exceed 11): 1=1.0000>L=11 = 1.0000 > L=1? We need strictly greater than LL; p1=1p_1 = 1 alone already gives partial sum 11, which is not strictly greater than L=1L = 1 (ties go to "not yet"), so we need p1+p2=1+13=43≈1.333>1p_1 + p_2 = 1 + \tfrac13 = \tfrac43 \approx 1.333 > 1. So m1=2m_1 = 2: append 1,131, \tfrac13. Partial sum R1=43R_1 = \tfrac43. Block 2 (negative terms until we drop below 11): R1−q1=43−12=56≈0.833<1R_1 - q_1 = \tfrac43 - \tfrac12 = \tfrac56 \approx 0.833 < 1. So n1=1n_1 = 1: append −12-\tfrac12. Partial sum R2=56R_2 = \tfrac56. Block 3 (more positive terms until we exceed 11 again): R2+p3=56+15=2530+630=3130≈1.0333>1R_2 + p_3 = \tfrac56 + \tfrac15 = \tfrac{25}{30}+\tfrac{6}{30} = \tfrac{31}{30}\approx 1.0333 > 1. So append just p3=15p_3 = \tfrac15. Partial sum R3=3130R_3 = \tfrac{31}{30}. Block 4 (negative terms until below 11 again): R3−q2=3130−14=6260−1560=4760≈0.7833<1R_3 - q_2 = \tfrac{31}{30} - \tfrac14 = \tfrac{62}{60}-\tfrac{15}{60}=\tfrac{47}{60}\approx 0.7833 < 1. Append −14-\tfrac14. Partial sum R4=4760R_4 = \tfrac{47}{60}. The rearranged series so far reads

1+13−12+15−14+⋯ ,1 + \tfrac13 - \tfrac12 + \tfrac15 - \tfrac14 + \cdots,

using the terms 1,13,12,15,141, \tfrac13, \tfrac12, \tfrac15, \tfrac14 — note all five of the first five terms of the original series (1,−12,13,−14,151, -\tfrac12, \tfrac13, -\tfrac14, \tfrac15) have now appeared, just reordered, and no term has been skipped or repeated. Numerically the partial sums are

1.0000, 1.3333, 0.8333, 1.0333, 0.7833,…1.0000,\ 1.3333,\ 0.8333,\ 1.0333,\ 0.7833, \ldots

oscillating around L=1L=1 with strictly shrinking overshoot/undershoot (since the terms used, pmj,qnj→0p_{m_j}, q_{n_j} \to 0), exactly as guaranteed by bound (5) in the proof: the theorem promises this process, continued forever, has partial sums converging to 11, a different value from the original sum ln⁡2≈0.6931\ln 2 \approx 0.6931.

Example 2: Rearranging ∑(−1)nn\sum \frac{(-1)^n}{\sqrt n} to diverge to +∞+\infty. Let bn=(−1)nnb_n = \frac{(-1)^n}{\sqrt n} for n≥1n \ge 1, so ∑bn=−1+12−13+14−⋯\sum b_n = -1 + \tfrac{1}{\sqrt2} - \tfrac{1}{\sqrt3} + \tfrac{1}{\sqrt4} - \cdots. This converges (alternating series test, since 1n↓0\tfrac{1}{\sqrt n}\downarrow 0), but ∑∣bn∣=∑1n=∞\sum |b_n| = \sum \tfrac{1}{\sqrt n} = \infty (compare to the divergent pp-series with p=12≤1p = \tfrac12 \le 1), so it is conditionally convergent, and Riemann's theorem applies. Positive terms of bnb_n occur at even nn: pk=12kp_k = \frac{1}{\sqrt{2k}}, i.e. p1=12≈0.7071p_1 = \tfrac{1}{\sqrt2}\approx0.7071, p2=12=0.5p_2 = \tfrac{1}{2}=0.5, p3=16≈0.4082,…p_3=\tfrac{1}{\sqrt6}\approx0.4082,\ldots; negative-term magnitudes occur at odd nn: qk=12k−1q_k = \frac{1}{\sqrt{2k-1}}, i.e. q1=1q_1 = 1, q2=13≈0.5774,…q_2 = \tfrac{1}{\sqrt3}\approx0.5774,\ldots. We build the +∞+\infty-rearrangement: at stage jj, append unused pkp_k's until the running total exceeds threshold jj, then append exactly one unused qkq_k. Stage 11 (threshold 11): p1=0.7071p_1 = 0.7071, not yet >1>1; add p2p_2: 0.7071+0.5=1.2071>10.7071+0.5=1.2071>1. Append p1,p2p_1,p_2. Then append one negative term, −q1=−1-q_1=-1. Running total: 1.2071−1=0.20711.2071 - 1 = 0.2071. Stage 22 (threshold 22): Continue adding unused pkp_k (k=3,4,5,…k=3,4,5,\ldots) starting from 0.20710.2071 until exceeding 22: since ∑pk=∞\sum p_k = \infty, this is guaranteed to happen after finitely many terms (concretely p3+p4+p5+p6≈0.4082+0.3536+0.3162+0.2887=1.3667p_3+p_4+p_5+p_6 \approx 0.4082+0.3536+0.3162+0.2887=1.3667, giving running total 0.2071+1.3667=1.57380.2071+1.3667 = 1.5738, still <2<2; add p7=1/14≈0.2673p_7 = 1/\sqrt{14}\approx0.2673: total 1.84111.8411; add p8=1/4=0.25p_8=1/4=0.25: total 2.0911>22.0911>2). Append p3,…,p8p_3,\ldots,p_8. Then append one negative term, −q2≈−0.5774-q_2 \approx -0.5774. Running total: 2.0911−0.5774=1.51372.0911-0.5774=1.5137. Notice the running total after each full stage is at least (threshold) minus (one shrinking qkq_k), and since only one qkq_k is consumed per stage while an unbounded (and increasing in required length, but always finite) block of pkp_k's is consumed, every original term is eventually used: the qkq_k's get consumed one per stage over infinitely many stages (using up all of them since there are countably infinitely many stages and σ\sigma pairs stage jj with qjq_j), and the pkp_k's get consumed in growing finite blocks whose union is all of N\mathbb{N} restricted to evens, again since ∑pk=∞\sum p_k = \infty guarantees each new threshold is eventually clearably reached using only unused terms (there are always infinitely many left, since only finitely many have been used after finitely many stages). By construction the running total after stage jj exceeds j−qj→jj - q_j \to j (since qj→0q_j \to 0), so the partial sums (restricted to ends-of-stages) diverge to +∞+\infty; the argument in the theorem's proof shows the full sequence of partial sums (not just end-of-stage ones) also diverges to +∞+\infty, since within a stage the total only increases (during the pp-block) or decreases by a bounded, vanishing amount (the single qq-term). Hence this rearrangement of ∑(−1)nn\sum \frac{(-1)^n}{\sqrt n} diverges to +∞+\infty, even though the original series converges to a finite value.

CounterexampleDropping "conditionally convergent" breaks Riemann's theorem

Riemann's theorem requires the series to be conditionally convergent — equivalently, convergent but not absolutely convergent. If we drop this and instead apply the conclusion of Riemann's theorem to an absolutely convergent series, it is false. Take an=(−1)n+12na_n = \dfrac{(-1)^{n+1}}{2^n}, so

∑n=1∞an=12−14+18−⋯=1/21+1/2=13.\sum_{n=1}^\infty a_n = \frac12 - \frac14 + \frac18 - \cdots = \frac{1/2}{1+1/2} = \frac13.

This series converges absolutely, since ∑∣an∣=∑2−n=1<∞\sum |a_n| = \sum 2^{-n} = 1 < \infty. By the first theorem above (rearrangement invariance for absolutely convergent series), every rearrangement of this series converges to the same value, 13\tfrac13. There is no bijection σ\sigma making ∑aσ(n)=5\sum a_{\sigma(n)} = 5, or π\pi, or +∞+\infty: the entire mechanism of Riemann's proof — using ∑pk=∞\sum p_k = \infty and ∑qk=∞\sum q_k = \infty to freely overshoot or undershoot any target — is simply unavailable here, because for this series ∑pk=∑k2−(2k−1)=23<∞\sum p_k = \sum_{k} 2^{-(2k-1)} = \tfrac23 < \infty and ∑qk=∑k2−2k=13<∞\sum q_k = \sum_k 2^{-2k} = \tfrac13 < \infty are both finite. The greedy construction cannot even get started: past a certain point, no finite block of remaining positive terms can push the partial sum above an arbitrary target like 55, because the total remaining positive mass is capped at 23\tfrac23 (a specific finite number), no matter how the block is chosen. This shows precisely which hypothesis is doing the work: it is not "convergence" alone that permits Riemann's conclusion, but the specific extra feature of conditional convergence — namely that ∑pk=∑qk=∞\sum p_k = \sum q_k = \infty — that supplies the unlimited overshoot/undershoot capacity the proof exploits. Absolute convergence removes exactly this capacity, and correspondingly removes the conclusion.

Scope, edge cases & common traps

SituationWhat holdsWhy
∑an\sum a_n absolutely convergentEvery rearrangement converges to the same sumTail estimate: finite total variation controls all reorderings uniformly
∑an\sum a_n conditionally convergentRearrangements can be made to converge to any L∈[−∞,∞]L \in [-\infty,\infty], or oscillate∑pk=∑qk=∞\sum p_k = \sum q_k = \infty gives unlimited "overshoot/undershoot" capacity
∑an\sum a_n divergent, not conditionally convergent in the above sense (e.g. an↛0a_n \not\to 0)Riemann's theorem does not directly applyThe proof needs an→0a_n \to 0 (hence pk,qk→0p_k, q_k \to 0) to guarantee convergence, not just divergence to ±∞\pm\infty, of the reordered partial sums
Rearranging a finite sumAlways order-independentCommutativity of finite addition; no limiting process involved at all
Complex conditionally convergent seriesReal and imaginary parts can each independently be Riemann-rearranged; a fully general complex analogue (Lévy–Steinitz theorem) shows the set of achievable sums is an affine subspace of C≅R2\mathbb{C}\cong\mathbb{R}^2Genuinely different phenomenon from the 1-D case; not covered by the 1-D proof above

The mathematician behind it

Origins · 1 minGeorg Friedrich Bernhard Riemann and how this was discovered
GF
Georg Friedrich Bernhard Riemann
1826–1866 · 19th-century Göttingen mathematics

Riemann worked at the University of Göttingen under the influence of Gauss and Dirichlet, and in a short life produced foundational results reshaping analysis, geometry, and number theory: the Riemann integral, Riemann surfaces, Riemannian geometry (later the mathematical backbone of general relativity), and the Riemann Hypothesis on the zeta function. The rearrangement theorem discussed here appears in his 1854 Habilitationsschrift on trigonometric series, in the course of his broader investigation into exactly how delicately convergence properties of series depend on subtle analytic structure rather than crude bounds.

History
- 1837 — Dirichlet studies convergence of Fourier series and related series manipulations, laying groundwork for careful convergence analysis.
- 1854 — Riemann's habilitation thesis on the representability of functions by trigonometric series includes the rearrangement result as a striking illustration of the fragility of conditional convergence.
- 1867 — Riemann's habilitation thesis is published posthumously (Riemann died in 1866), bringing the rearrangement theorem to wider attention.
- 1883 — Ulisse Dini and later authors give alternative expositions and sharpenings, cementing the theorem's place in rigorous real analysis curricula.
- 1913 — Paul Lévy and Ernst Steinitz generalize the phenomenon to series in Rk\mathbb{R}^k and Banach spaces, identifying the set of achievable rearranged sums as an affine subspace (the Lévy–Steinitz theorem).
Why doesn't the finite-sum intuition "order doesn't matter" carry over to infinite series?

Finite sums are built from finitely many applications of the commutative, associative binary operation of addition, so any reordering is just a finite sequence of transpositions, each provably order-preserving on the total. An infinite series, by contrast, is not literally "a sum" — it is the limit of a sequence of partial sums, an entirely different kind of object built from a limiting process. Reordering the terms changes which sequence of partial sums you are taking the limit of, and limits are not generally invariant under changing the sequence that produces them unless extra structure (like absolute convergence, which controls tails uniformly) is present. Riemann's theorem shows just how much the limit can change when that extra structure is absent.

Does Riemann's theorem mean conditionally convergent series don't really have a well-defined sum?

In a precise sense, yes: the phrase "the sum of ∑an\sum a_n" is only unambiguous once you fix an order of summation, and for a conditionally convergent series, different orders genuinely produce different (or divergent) results. The standard convention is to always sum in the given natural order n=1,2,3,…n=1,2,3,\ldots, which is what "the value of the series" conventionally means. This convention is consistent and useful, but Riemann's theorem is a reminder that it is a convention, not a reflection of some order-independent Platonic total, the way a finite sum or an absolutely convergent sum is.

Can you rearrange a conditionally convergent series to make its partial sums converge to a complex number, if the series is real?

No — if ana_n are all real numbers, every partial sum ∑k=1maσ(k)\sum_{k=1}^m a_{\sigma(k)} is real, so the limit, if it exists, must be real (or ±∞\pm\infty in the extended sense). Riemann's theorem is stated for real conditionally convergent series and real (or extended-real) targets precisely for this reason. For genuinely complex series, the analogous and more intricate Lévy–Steinitz theorem describes the set of achievable sums, which turns out to be an affine subspace of C≅R2\mathbb{C} \cong \mathbb{R}^2 (a point, a line, or the whole plane), not an arbitrary set.

Is the greedy algorithm in the proof the only way to build a rearrangement hitting a target LL?

No; it is simply the cleanest constructive method and the one that makes the proof fully explicit and rigorous. Many other orderings also achieve the same target — for instance, one could overshoot by more than the minimal amount at each stage, using longer positive blocks, as long as the "overshoot/undershoot amount" still shrinks to 00 across infinitely many stages. The greedy, minimal-length version is preferred pedagogically because it gives the tightest and most transparent error bound, equation (5) in the proof, from which convergence to LL follows immediately.

How does this relate to the alternating series test?

The alternating series test (Absolute vs Conditional Convergence toolkit) gives a sufficient condition — terms alternating in sign with monotonically decreasing magnitude tending to 00 — for convergence, without addressing absolute convergence at all. Many series satisfying this test (like ∑(−1)n+1/n\sum (-1)^{n+1}/n) are exactly the conditionally convergent series to which Riemann's theorem applies. The two results are complementary: the alternating series test is typically how you first establish that a series like ∑(−1)n+1/n\sum(-1)^{n+1}/n converges at all (and separately, that ∑1/n\sum 1/n diverges, giving conditional convergence), and Riemann's theorem then tells you how radically that convergence depends on term order.

If I only rearrange finitely many terms of a series (leave all but finitely many terms in their original positions), can the sum change?

No. If σ\sigma agrees with the identity outside some finite set {1,…,N}\{1, \ldots, N\} (i.e. only finitely many terms are permuted among themselves), then for m≥Nm \ge N the partial sums TmT_m of the rearranged series and SmS_m of the original series differ only by how a fixed finite collection of terms was permuted internally — and finite sums are commutative — so Tm=SmT_m = S_m exactly for all m≥Nm \ge N. Hence Tm→ST_m \to S iff Sm→SS_m \to S, with the same limit. This is consistent with, and a special case reachable from, both theorems above: Riemann's construction genuinely requires permuting infinitely many terms (infinitely many blocks) to change the sum; no finite rearrangement can ever do it.

Before this