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 converges to . Yet a suitable reordering of its terms converges to , or to , or diverges to . 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.
- A rearrangement of a series is a reindexing by a bijection of ; it uses every term exactly once, just in a different order.
- If converges absolutely, every rearrangement converges to the same sum — order is irrelevant.
- If converges conditionally, the positive terms alone diverge to and the negative terms alone diverge to .
- Riemann's Rearrangement Theorem: for any conditionally convergent real series and any target , some rearrangement converges to (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 for a conditionally integrable 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 ), 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 ?
Let be a series of real (or complex) numbers. A rearrangement of this series is a series
where is a bijection. That is, we choose a new order in which to list the terms , 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 is:
- Absolutely convergent if ;
- Conditionally convergent if converges but .
Intuition
Think of as an instruction to walk along the real line: at step you move by . Absolute convergence means the total distance traveled, , 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.
The two theorems
Let be a series of real or complex numbers with , and let be any bijection. Then
converges absolutely, and
Technique: -tail estimate using absolute convergence, via the Cauchy criterion. Let and let be given.
Step 1 (tail smallness). Since , the sequence of partial sums of is Cauchy, so there exists such that
(This sum is finite because converges, so its tail past any point is a nonnegative convergent series and shrinks to .) Consequently, if denotes the -th partial sum of the original series, then
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 terms reappear). Because is a bijection, each of appears exactly once among . Let
This is a well-defined natural number since it is the maximum of a finite set of natural numbers. By construction, for every , the finite set contains as a subset (every index has , so appears among the first rearranged terms).
Step 3 (comparing partial sums of the rearrangement to ). Fix any , and let . By Step 2, , so
because the terms indexed by appear in both sums and cancel exactly (each exactly once, since is injective on ), leaving only rearranged terms whose original index exceeds . Every index appearing in this remaining sum satisfies and , a finite set of distinct indices all exceeding . Hence, by the triangle inequality and Step 1's tail estimate,
(The sum on the right is over all indices , which only enlarges a sum of nonnegative terms, so the inequality is valid.)
Step 4 (combining). For all , by (1) and (2) and the triangle inequality,
Since was arbitrary, this shows as , i.e. .
Step 5 (absolute convergence of the rearrangement). Apply Steps 1–4 verbatim to the nonnegative series in place of (a nonnegative series trivially "converges absolutely" to itself, since ). This shows , so the rearranged series converges absolutely.
∎Let be a conditionally convergent series of real numbers. Define
so that and , with . Then
Technique: proof by contradiction, splitting a series into signed parts. Suppose, for contradiction, that converges (to a finite value ). Since and both and converge (the latter by hypothesis, the former by our supposition), the series converges as well, to , 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
again by linearity of convergent series, contradicting the hypothesis that is only conditionally convergent (i.e. that ). Hence diverges; since , its partial sums are nondecreasing, so divergence forces . By an identical argument with the roles of and swapped, .
∎Let be a conditionally convergent series of real numbers, and let be any element of the extended real line . Then there exists a bijection such that
meaning: if is finite, the partial sums of the rearranged series converge to ; if (resp. ), the partial sums of the rearranged series diverge to (resp. ). Moreover, there is also a rearrangement whose partial sums neither converge nor diverge to , but oscillate boundedly or unboundedly forever.
Technique: explicit greedy construction, using the Lemma above and the fact that . First note a preliminary fact we will need: since converges, as (the terms of any convergent series tend to , since where are partial sums converging to ). Consequently and as well, since and . Let be the subsequence of strictly positive terms of , listed in their original relative order, and let be the subsequence of the absolute values of the strictly negative terms of , also listed in original relative order. (Terms equal to may be placed anywhere at the end without affecting any partial sum; discard them from this bookkeeping and reinsert them into 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 ,
and since these are subsequences of a null sequence , we also have and .
Case 1: finite. We construct the rearrangement in blocks, alternating between runs of positive terms and runs of negative terms, using the following greedy rule. Block : Since and each , there is a least integer such that
(Such an exists because the partial sums of are nondecreasing and unbounded, hence eventually exceed ; "least" makes well defined by the well-ordering principle.) Append , in order, to the rearranged sequence. Let denote the resulting partial sum, so , and — crucially — since is least, we had , so
Block : Since , there is a least integer such that
Append , in order, to the rearranged sequence. Let be the resulting partial sum, so , and by leastness of , exactly as above,
Continue inductively: having built using the next unused block of 's (least length to first exceed ) and using the next unused block of 's (least length to first go below ), the construction continues forever. This is possible at every stage because and remain true for every tail of these sequences — removing any finite number of initial terms from a series that diverges to leaves a series that still diverges to , since only finitely much has been removed from an unbounded nondecreasing sequence of partial sums. Every term and every gets used exactly once, in exactly one block, and every block is finite, so this process defines a genuine bijection 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 -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 . We must show the partial sums of the full rearranged series converge to . Consider any partial sum of the rearranged series where lies within block (a positive-block) or block (a negative-block). Within a positive block, partial sums are increasing from up to (or from 's neighborhood up to if ); within a negative block they are decreasing from down to . Hence every partial sum lies between the two most recent "turning" values, i.e.
More precisely and rigorously: for in the interior of block (a run of positive terms), the partial sum satisfies (increasing partial sums within an all-positive block, starting above or at 's undershoot and rising to overshoot ); by (3)-type bound applied at stage ,
Symmetrically, for in block (all-negative run), , and
In either case,
Since and as (each block uses at least one new term, and there are infinitely many blocks since force the process never to terminate), and since , , the right side of (5) tends to as , i.e. as . Given , choose so that for all appearing in blocks (possible since ); then for all past the start of block , by (5). Hence , proving .
Case 2: . Modify the construction: at stage , choose the least so that appending the next block of unused 's makes the partial sum exceed (rather than ), then append exactly one unused (rather than a block chosen to undershoot). This is always possible: the positive terms alone sum to so we can always find enough of them to clear any finite threshold , and we use only a single negative term per round so the negative contribution is summable in a controlled way — concretely, since , the single negative term used at stage contributes at most , an amount too small to prevent the partial sums from eventually exceeding every threshold. Formally, the partial sum after stage exceeds where , and since every original is used exactly once across all stages (there are infinitely many stages, one consumed per stage, and only requires that we have infinitely many available, which we do), the construction is a valid bijection and the partial sums diverge to . The case is symmetric, with the roles of and exchanged.
Oscillation. To make the rearranged series have no limit in , alternately target and (say): run the Case-1 construction toward for finitely many blocks until the partial sum is within of , then switch and run finitely many blocks of the Case-1 construction toward until the partial sum is within of , 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 of and infinitely often come within of ; hence , so has no limit in . Every original term is still used exactly once across the infinite alternation, by the same tail-never-runs-out argument as before, so is a genuine bijection.
∎Worked examples
Example 1: Rearranging the alternating harmonic series to converge to . Let , so . This is conditionally convergent: , but converges (by the alternating series test, since ). We rearrange it, by Riemann's algorithm, to converge to . Here (positive terms ) and (absolute values of negative terms ). Block 1 (positive terms until we exceed ): ? We need strictly greater than ; alone already gives partial sum , which is not strictly greater than (ties go to "not yet"), so we need . So : append . Partial sum . Block 2 (negative terms until we drop below ): . So : append . Partial sum . Block 3 (more positive terms until we exceed again): . So append just . Partial sum . Block 4 (negative terms until below again): . Append . Partial sum . The rearranged series so far reads
using the terms — note all five of the first five terms of the original series () have now appeared, just reordered, and no term has been skipped or repeated. Numerically the partial sums are
oscillating around with strictly shrinking overshoot/undershoot (since the terms used, ), exactly as guaranteed by bound (5) in the proof: the theorem promises this process, continued forever, has partial sums converging to , a different value from the original sum .
Example 2: Rearranging to diverge to . Let for , so . This converges (alternating series test, since ), but (compare to the divergent -series with ), so it is conditionally convergent, and Riemann's theorem applies. Positive terms of occur at even : , i.e. , , ; negative-term magnitudes occur at odd : , i.e. , . We build the -rearrangement: at stage , append unused 's until the running total exceeds threshold , then append exactly one unused . Stage (threshold ): , not yet ; add : . Append . Then append one negative term, . Running total: . Stage (threshold ): Continue adding unused () starting from until exceeding : since , this is guaranteed to happen after finitely many terms (concretely , giving running total , still ; add : total ; add : total ). Append . Then append one negative term, . Running total: . Notice the running total after each full stage is at least (threshold) minus (one shrinking ), and since only one is consumed per stage while an unbounded (and increasing in required length, but always finite) block of 's is consumed, every original term is eventually used: the 's get consumed one per stage over infinitely many stages (using up all of them since there are countably infinitely many stages and pairs stage with ), and the 's get consumed in growing finite blocks whose union is all of restricted to evens, again since 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 exceeds (since ), so the partial sums (restricted to ends-of-stages) diverge to ; the argument in the theorem's proof shows the full sequence of partial sums (not just end-of-stage ones) also diverges to , since within a stage the total only increases (during the -block) or decreases by a bounded, vanishing amount (the single -term). Hence this rearrangement of diverges to , even though the original series converges to a finite value.
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 , so
This series converges absolutely, since . By the first theorem above (rearrangement invariance for absolutely convergent series), every rearrangement of this series converges to the same value, . There is no bijection making , or , or : the entire mechanism of Riemann's proof — using and to freely overshoot or undershoot any target — is simply unavailable here, because for this series and 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 , because the total remaining positive mass is capped at (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 — 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
| Situation | What holds | Why |
|---|---|---|
| absolutely convergent | Every rearrangement converges to the same sum | Tail estimate: finite total variation controls all reorderings uniformly |
| conditionally convergent | Rearrangements can be made to converge to any , or oscillate | gives unlimited "overshoot/undershoot" capacity |
| divergent, not conditionally convergent in the above sense (e.g. ) | Riemann's theorem does not directly apply | The proof needs (hence ) to guarantee convergence, not just divergence to , of the reordered partial sums |
| Rearranging a finite sum | Always order-independent | Commutativity of finite addition; no limiting process involved at all |
| Complex conditionally convergent series | Real 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 | Genuinely 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
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.
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 " 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 , 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 are all real numbers, every partial sum is real, so the limit, if it exists, must be real (or 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 (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 ?
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 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 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 — for convergence, without addressing absolute convergence at all. Many series satisfying this test (like ) 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 converges at all (and separately, that 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 agrees with the identity outside some finite set (i.e. only finitely many terms are permuted among themselves), then for the partial sums of the rearranged series and of the original series differ only by how a fixed finite collection of terms was permuted internally — and finite sums are commutative — so exactly for all . Hence iff , 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.