Recurrent Series

Summary: A series whose coefficients satisfy a fixed linear recurrence. Euler (§62) credits the name to De Moivre — one must “run back” to previous terms to compute a new one. Every rational function with non-vanishing constant in its denominator expands into a recurrent series, and the recurrence is read directly off the denominator. The closed-form general term, the inverse problem, and the sum are developed in Chapter 13. Chapter 16 applies the theory to partition generating functions . Chapter 17 inverts the construction to turn recurrent series into a root-finder for algebraic equations.

Sources: chapter4, chapter13, chapter16, chapter17

Last updated: 2026-05-11


Definition (§62)

A series is recurrent if there is a fixed law — independent of the position — by which each coefficient is determined from a fixed number of its predecessors. The order of the recurrence equals the degree of the denominator of the rational function that produced the series (source: chapter4, §62).

Euler attributes the name to Abraham de Moivre, “who has examined their nature very carefully”: the name comes from the need to run back to preceding terms in order to compute subsequent ones.

Canonical form (§63)

Any rational function whose denominator has a nonzero constant term can be written, after normalizing the constant to and putting the remaining terms with negative signs, as

Setting this equal to and multiplying out gives

Each coefficient is a weighted sum of preceding coefficients (with weights ) plus the corresponding numerator entry (source: chapter4, §63). Once the numerator runs out, the recurrence becomes homogeneous:

where are consecutive coefficients. The negative signs in the denominator are Euler’s convention so that the recurrence comes out with all positive coefficients (source: chapter4, §63).

Properness requirement (§63)

The law of the recurrence holds for all coefficients only if the rational function is proper — numerator degree strictly less than denominator degree. If the function is improper, the polynomial part disturbs early terms and the fixed law fails there.

Euler’s illustrating example: gives the series

The Fibonacci-like law “each coefficient is the sum of the two before” works everywhere except at the term, where the in the numerator intervenes (source: chapter4, §63). The remedy is to first split off the polynomial part using an improper-rational-function decomposition.

Examples

Fibonacci-like (§61)

— each coefficient is the sum of the two preceding ones (Lucas numbers).

Arithmetic progression (§64)

— arithmetic progression as a recurrent series with denominator , recurrence . See higher-order-arithmetic-progressions.

Higher-order progression (§65–§66)

Denominators produce progressions of second, third, … order — those with constant higher differences.

Non-constant laws (§68)

If the denominator is the power of a multinomial — — the coefficient law still involves a fixed number of predecessors, but the coefficients in the recurrence depend on the index :

where is the coefficient of (source: chapter4, §68). Euler notes this non-constant law applies only when the numerator is (or a constant); a general numerator makes the recurrence more complicated, a problem he defers to differential calculus.

The same non-constant law arises in §76 for the binomial expansion — see binomial-series.

Zero constant term (§69)

When the denominator factors as , i.e. its constant term vanishes, the series acquires negative powers of :

The coefficients are those of the corresponding recurrent series for the rational function without the factor (source: chapter4, §69). In modern language this is a Laurent expansion at the origin.

Non-uniqueness (§70)

A single rational function admits infinitely many distinct recurrent-series representations, because one can always reparametrize by substitution (see chapter-3-on-the-transformation-of-functions-by-substitution). Euler illustrates with : under and one obtains entirely different recurrent series for the same (source: chapter4, §70).

Closed-form theory (Chapter 13)

Chapter 4 gave the recurrence; Chapter 13 gives the closed-form general term and sum by combining real partial fractions with explicit per-fraction expansions:

  • The general term is obtained by partial-fractioning the rational function and summing per-piece closed forms — a polynomial-times- for each linear factor and a form for each quadratic factor.
  • The recurrence multipliers are De Moivre’s [[scale-of-the-relation|scale of the relation]] (§224), equivalent data to the denominator of the generating rational function.
  • For two-member scales, the Binet-type closed form has invariant .
  • The sum of the infinite series equals the rational function; the partial sum has its own clean closed form.

Applications in Chapter 16 — partition generating functions

Chapter 16 uses recurrent series to enumerate integer partitions. For each the rational function

is the generating function for partitions of into distinct or unrestricted parts respectively (§307, §313). The scale of the relation is the signed expansion of .

For the full partition function , generated by , the pentagonal number theorem gives an infinite but sparse scale of the relation supported on the pentagonal-number lattice , the first known recurrent series whose effective recurrence uses only predecessors.

Inverse use in Chapter 17 — roots from the scale

Chapter 17 runs the chapter-13 correspondence backwards. Given an algebraic equation , the scale is read off the coefficients; any recurrent series with that scale (the cleanest choice is the one arising from numerator ) has consecutive-term ratio converging to the largest root in absolute value — see Daniel Bernoulli’s method. The complex-pair analogue (trinomial-factor-from-recurrent-series) extracts both modulus and argument of a dominant conjugate pair from four consecutive terms. Combined with the substitution , the method finds every root of any algebraic equation.

Why recurrent series matter

  • They are the bridge between rational generating functions and linear recurrences — a modern viewpoint first systematized here.
  • They reduce the computation of every coefficient to a small fixed arithmetic rule, making it practical to generate as many terms as desired.
  • They make explicit the correspondence between the denominator of a rational function and the characteristic polynomial of the recurrence, foreshadowing the later theory of linear difference equations.