Series Solutions

Study Sheet

Series Solutions

Power series where formulas fail

The Power Series Method

Tip
Substitute, shift, match
xy−2−112246eˣ1 + xdegree 2degree 3
Partial sums of the series from (n+1)an+1=an(n+1)a_{n+1} = a_n (dashed) closing in on exe^x.

Write y=∑anxny = \sum a_nx^n, substitute into the equation, shift indices so all powers align, and set each coefficient to zero — a recurrence for the ana_n. For y′=yy' = y: (n+1)an+1=an(n+1)a_{n+1} = a_n, giving an=1n!a_n = \tfrac{1}{n!} — the series discovers exe^x on its own.

Why this is legitimate: a power series can be differentiated term by term inside its interval of convergence, so every term of the equation becomes a power series, and two power series that agree on an interval agree coefficient by coefficient (proved below). Matching the coefficient of each xnx^n therefore loses no information — the recurrence is the equation, rewritten. For y′=yy' = y the coefficient of xnx^n on the left is (n+1)an+1(n+1)a_{n+1} and on the right ana_n; with a0=1a_0 = 1 the partial sums 1+x1 + x, 1+x+x221 + x + \tfrac{x^2}{2}, 1+x+x22+x361 + x + \tfrac{x^2}{2} + \tfrac{x^3}{6} close in on exe^x.

Concept
Equations beyond elementary functions
xy−6−4−21221−1deg 6deg 12solution
The solution of y′′=xyy'' = xy, y(0)=1y(0) = 1, y′(0)=0y'(0) = 0 (solid) and two partial sums (dashed).

The Airy-type equation y′′=xyy'' = xy has no closed-form solution, but its recurrence (n+2)(n+1)an+2=an−1(n+2)(n+1)a_{n+2} = a_{n-1} generates the answer to any accuracy: with y(0)=1y(0)=1, y′(0)=0y'(0)=0 the series starts 1+x36+⋯1 + \tfrac{x^3}{6} + \cdots. Series are the solution.

Why the recurrence reaches back three places: in y′′=xyy'' = xy the second derivative lowers every power by two, while multiplying by xx raises it by one, so the coefficient of xnx^n links an+2a_{n+2} to an−1a_{n-1}. With a1=0a_1 = 0 and a2=0a_2 = 0 only the powers 0,3,6,…0, 3, 6, \ldots survive. The series converges for every xx, but each partial sum is accurate only near 00; more terms reach farther out, as the figure shows on the oscillating side x<0x < 0.

Example
Recognizing an old friend

y′=2xyy' = 2xy, y(0)=1y(0) = 1: the recurrence nan=2an−2na_n = 2a_{n-2} gives y=1+x2+x42+x66+⋯=ex2y = 1 + x^2 + \tfrac{x^4}{2} + \tfrac{x^6}{6} + \cdots = e^{x^2} — matching the separable-method answer, coefficient for coefficient.

Where the recurrence comes from: substituting gives ∑n≥1nanxn−1=∑n≥02anxn+1\sum_{n\ge1} na_nx^{n-1} = \sum_{n\ge0} 2a_nx^{n+1}. The coefficient of xn−1x^{n-1} is nanna_n on the left and 2an−22a_{n-2} on the right (for n≥2n \ge 2); for n=1n = 1 the right side has no constant term, so a1=0a_1 = 0 and every odd coefficient vanishes. From a0=1a_0 = 1: a2=a0=1a_2 = a_0 = 1, a4=2a24=12a_4 = \tfrac{2a_2}{4} = \tfrac12, a6=2a46=16a_6 = \tfrac{2a_4}{6} = \tfrac16, and in general a2k=1k!a_{2k} = \tfrac{1}{k!} — the series of eue^u with u=x2u = x^2.

Side note
Significance: when formulas run out

Most differential equations of physics — Airy (optics near caustics), Bessel (drumheads), Hermite (quantum oscillators) — have no elementary solutions. Series are not a fallback; they are how these functions are defined, tabulated, and computed inside every scientific library you have ever called.

Try it
Try it: two terms by recurrence

For y′=x+yy' = x + y, y(0)=1y(0) = 1, find a1a_1, a2a_2 and a3a_3 in y=∑anxny = \sum a_nx^n, and compare with the Taylor coefficients of the exact solution 2ex−x−12e^x - x - 1.

Show the answer

Substitute: the coefficient of xnx^n in y′y' is (n+1)an+1(n+1)a_{n+1}; on the right, yy contributes ana_n and the extra xx contributes 11 to the coefficient of x1x^1 only. So a1=a0=1a_1 = a_0 = 1 (from x0x^0), 2a2=a1+1=22a_2 = a_1 + 1 = 2 gives a2=1a_2 = 1 (from x1x^1), and 3a3=a23a_3 = a_2 gives a3=13a_3 = \tfrac13 (from x2x^2). The series begins 1+x+x2+x331 + x + x^2 + \tfrac{x^3}{3}. Check: 2ex−x−1=2(1+x+x22+x36+⋯ )−x−1=1+x+x2+x33+⋯2e^x - x - 1 = 2\left(1 + x + \tfrac{x^2}{2} + \tfrac{x^3}{6} + \cdots\right) - x - 1 = 1 + x + x^2 + \tfrac{x^3}{3} + \cdots, the same four coefficients.

Second-Order Equations at Ordinary Points

Tip
Two free coefficients, two solutions

A point x0x_0 is ordinary for y′′+p(x)y′+q(x)y=0y'' + p(x)y' + q(x)y = 0 when pp and qq have convergent power series there. Then every solution is a power series ∑an(x−x0)n\sum a_n(x - x_0)^n: the coefficients a0=y(x0)a_0 = y(x_0) and a1=y′(x0)a_1 = y'(x_0) are free, and the recurrence fixes all the others. Taking (a0,a1)=(1,0)(a_0, a_1) = (1, 0) and (0,1)(0, 1) gives two independent solutions y1y_1, y2y_2, and every solution is a0y1+a1y2a_0y_1 + a_1y_2.

Why exactly two are free: the coefficient of xnx^n in y′′y'' is (n+2)(n+1)an+2(n+2)(n+1)a_{n+2}, and the other terms involve only a0,…,an+1a_0, \ldots, a_{n+1}, so each matching equation determines an+2a_{n+2} from earlier coefficients. Nothing ever determines a0a_0 or a1a_1 — the series version of the fact that a second-order initial-value problem needs two numbers. The two solutions are independent because their Wronskian at x0x_0 is y1y2′−y1′y2=1⋅1−0⋅0=1y_1y_2' - y_1'y_2 = 1\cdot1 - 0\cdot0 = 1.

Example
Worked: a recurrence that sums to a known function
xy−3−2−112−11246exact
Partial sums of degree 2,4,62, 4, 6 (dashed) against e−x2/2e^{-x^2/2}; each hugs it over a wider interval.

Solve y′′+xy′+y=0y'' + xy' + y = 0, y(0)=1y(0) = 1, y′(0)=0y'(0) = 0, by series.

Substitute y=∑anxny = \sum a_nx^n: ∑n≥2n(n−1)anxn−2+∑n≥1nanxn+∑n≥0anxn=0\sum_{n\ge2} n(n-1)a_nx^{n-2} + \sum_{n\ge1} na_nx^n + \sum_{n\ge0} a_nx^n = 0. Shift the first sum (n→n+2n \to n + 2) so that every sum is written in xnx^n: ∑n≥0(n+2)(n+1)an+2xn\sum_{n\ge0}(n+2)(n+1)a_{n+2}x^n.

Step 1 — match the coefficient of xnx^n: (n+2)(n+1)an+2+nan+an=0(n+2)(n+1)a_{n+2} + na_n + a_n = 0, and since nan+an=(n+1)anna_n + a_n = (n+1)a_n, the factor n+1n + 1 cancels: an+2=−ann+2a_{n+2} = -\dfrac{a_n}{n+2}.

Step 2 — seed with a0=1a_0 = 1, a1=0a_1 = 0. Every odd coefficient inherits a1=0a_1 = 0; the even ones are a2=−12a_2 = -\tfrac12, a4=18a_4 = \tfrac18, a6=−148a_6 = -\tfrac1{48}.

Step 3 — recognize the pattern a2k=(−1)k2kk!a_{2k} = \dfrac{(-1)^k}{2^kk!}: the series is ∑(−x2/2)kk!=e−x2/2\sum \dfrac{(-x^2/2)^k}{k!} = e^{-x^2/2}.

Step 4 — check without series: y′′+xy′+y=(y′+xy)′y'' + xy' + y = (y' + xy)', and y=e−x2/2y = e^{-x^2/2} has y′=−xyy' = -xy, so y′+xy=0y' + xy = 0 and the equation holds. The recurrence found a closed form nobody had to guess.

Example
Worked: a series that stops

Find both series solutions of y′′−2xy′+4y=0y'' - 2xy' + 4y = 0 about x=0x = 0.

After the same shift, the coefficient of xnx^n is (n+2)(n+1)an+2−2nan+4an(n+2)(n+1)a_{n+2} - 2na_n + 4a_n, so

an+2=2(n−2)(n+2)(n+1) an.a_{n+2} = \frac{2(n-2)}{(n+2)(n+1)}\,a_n.

Step 1 — even solution, a0=1a_0 = 1, a1=0a_1 = 0: a2=2(−2)2⋅1=−2a_2 = \dfrac{2(-2)}{2\cdot1} = -2, and then a4=2⋅04⋅3a2=0a_4 = \dfrac{2\cdot0}{4\cdot3}a_2 = 0. The factor n−2n - 2 vanishes at n=2n = 2, so every later even coefficient is 00 as well: y1=1−2x2y_1 = 1 - 2x^2, a polynomial. Check: y1′′=−4y_1'' = -4 and −2x y1′=8x2-2x\,y_1' = 8x^2, so −4+8x2+4(1−2x2)=0-4 + 8x^2 + 4(1 - 2x^2) = 0.

Step 2 — odd solution, a0=0a_0 = 0, a1=1a_1 = 1: a3=2(−1)3⋅2=−13a_3 = \dfrac{2(-1)}{3\cdot2} = -\tfrac13, a5=2⋅15⋅4a3=−130a_5 = \dfrac{2\cdot1}{5\cdot4}a_3 = -\tfrac1{30}, a7=2⋅37⋅6a5=−1210a_7 = \dfrac{2\cdot3}{7\cdot6}a_5 = -\tfrac1{210}; the factor n−2n - 2 is never 00 for odd nn, so y2=x−x33−x530−x7210−⋯y_2 = x - \tfrac{x^3}{3} - \tfrac{x^5}{30} - \tfrac{x^7}{210} - \cdots never stops.

Step 3 — the general solution is a0y1+a1y2a_0y_1 + a_1y_2. This is Hermite's equation y′′−2xy′+2λy=0y'' - 2xy' + 2\lambda y = 0 with λ=2\lambda = 2; whenever λ\lambda is a whole number, one of the two series terminates, giving the Hermite polynomials of the quantum oscillator.

Side note
Where it goes wrong: matching before shifting

For y′′+xy′+y=0y'' + xy' + y = 0 it is tempting to read off "the nn-th terms" of ∑n(n−1)anxn−2+∑nanxn+∑anxn\sum n(n-1)a_nx^{n-2} + \sum na_nx^n + \sum a_nx^n and write n(n−1)an+nan+an=0n(n-1)a_n + na_n + a_n = 0, that is (n2+1)an=0(n^2 + 1)a_n = 0 — every coefficient zero, so y≡0y \equiv 0, contradicting y(0)=1y(0) = 1. The error: the first sum's nn-th term multiplies xn−2x^{n-2}, the others' multiply xnx^n, so those terms are not like terms. Only after shifting the first sum to ∑(n+2)(n+1)an+2xn\sum (n+2)(n+1)a_{n+2}x^n do the coefficients of one power line up, giving an+2=−ann+2a_{n+2} = -\tfrac{a_n}{n+2}.

Try it
Try it: four coefficients

For y′′−xy′−y=0y'' - xy' - y = 0, y(0)=1y(0) = 1, y′(0)=1y'(0) = 1, find the recurrence and the coefficients a2,a3,a4,a5a_2, a_3, a_4, a_5.

Show the answer

Shift the y′′y'' sum so all terms carry xnx^n: (n+2)(n+1)an+2−nan−an=0(n+2)(n+1)a_{n+2} - na_n - a_n = 0. Since nan+an=(n+1)anna_n + a_n = (n+1)a_n, the factor n+1n + 1 cancels and an+2=ann+2a_{n+2} = \dfrac{a_n}{n+2}. From a0=1a_0 = 1: a2=12a_2 = \tfrac12, a4=a24=18a_4 = \tfrac{a_2}{4} = \tfrac18. From a1=1a_1 = 1: a3=13a_3 = \tfrac13, a5=a35=115a_5 = \tfrac{a_3}{5} = \tfrac1{15}. So y=1+x+x22+x33+x48+x515+⋯y = 1 + x + \tfrac{x^2}{2} + \tfrac{x^3}{3} + \tfrac{x^4}{8} + \tfrac{x^5}{15} + \cdots. (The even part is ex2/2e^{x^2/2}, by the same pattern as the worked example with the sign flipped.)

How Far a Series Reaches

Tip
Radius at least the distance to the nearest singular point

For P(x)y′′+Q(x)y′+R(x)y=0P(x)y'' + Q(x)y' + R(x)y = 0 with polynomial coefficients, the singular points are the zeros of PP — complex zeros included. About an ordinary point x0x_0, every series solution converges at least for ∣x−x0∣<ρ|x - x_0| < \rho, where ρ\rho is the distance from x0x_0 to the nearest zero of PP in the complex plane.

Why complex zeros count: a power series converges on a disk in the complex plane, and the disk cannot contain a point where the solution may blow up or branch. The real line can look perfectly clear while a singular point sits just off it at ±i\pm i — the series still feels it, exactly as the geometric series 1−x2+x4−⋯1 - x^2 + x^4 - \cdots for 11+x2\dfrac{1}{1 + x^2} stops at ∣x∣=1|x| = 1.

Example
Worked: arctan from its equation
xy−2−11−2−115715arctan x
Partial sums of degree 5,7,155, 7, 15 (dashed) follow arctan⁡x\arctan x inside ∣x∣<1|x| < 1 and break away outside, however many terms are used.

Solve (1+x2)y′′+2xy′=0(1 + x^2)y'' + 2xy' = 0, y(0)=0y(0) = 0, y′(0)=1y'(0) = 1, by series, and find where the series converges.

Substituting and shifting the y′′y'' sum gives, for the coefficient of xnx^n: (n+2)(n+1)an+2+n(n−1)an+2nan=0(n+2)(n+1)a_{n+2} + n(n-1)a_n + 2na_n = 0, and n(n−1)+2n=n(n+1)n(n-1) + 2n = n(n+1).

Step 1 — cancel the common factor n+1n + 1: an+2=−nn+2 ana_{n+2} = -\dfrac{n}{n+2}\,a_n.

Step 2 — with a0=0a_0 = 0 all even coefficients vanish; from a1=1a_1 = 1: a3=−13a_3 = -\tfrac13, a5=−35a3=15a_5 = -\tfrac35a_3 = \tfrac15, a7=−57a5=−17a_7 = -\tfrac57a_5 = -\tfrac17. So y=x−x33+x55−x77+⋯=arctan⁡xy = x - \tfrac{x^3}{3} + \tfrac{x^5}{5} - \tfrac{x^7}{7} + \cdots = \arctan x.

Step 3 — confirm directly: the equation says ((1+x2)y′)′=0\big((1 + x^2)y'\big)' = 0, so y′=11+x2y' = \dfrac{1}{1 + x^2} and y=arctan⁡xy = \arctan x.

Step 4 — the radius: the leading coefficient 1+x21 + x^2 vanishes at x=±ix = \pm i, at distance 11 from the centre, and indeed the terms x2k+12k+1\tfrac{x^{2k+1}}{2k+1} grow without bound when ∣x∣>1|x| > 1. The function arctan⁡x\arctan x is smooth on the whole real line, yet its series about 00 works only for ∣x∣≤1|x| \le 1.

Example
Worked: reading off a radius without solving

How far must the series solutions of (x2−2x+5)y′′+xy′−y=0(x^2 - 2x + 5)y'' + xy' - y = 0 converge, about x0=0x_0 = 0 and about x0=1x_0 = 1?

Singular points are the zeros of the leading coefficient: x2−2x+5=(x−1)2+4=0x^2 - 2x + 5 = (x - 1)^2 + 4 = 0 at x=1±2ix = 1 \pm 2i.

Step 1 — no real singular points, but the complex ones still limit the disk of convergence.

Step 2 — about x0=0x_0 = 0 the distance to 1+2i1 + 2i is 12+22=5≈2.24\sqrt{1^2 + 2^2} = \sqrt5 \approx 2.24 (the same for 1−2i1 - 2i), so both series solutions converge at least for ∣x∣<5|x| < \sqrt5.

Step 3 — about x0=1x_0 = 1 the singular points are straight above and below, at distance 22: the guaranteed interval is (−1,3)(-1, 3).

Step 4 — the guarantee is a lower bound; a particular solution may converge farther (here y=xy = x is a solution, a polynomial, converging everywhere), but the general one cannot be promised more.

Example
Worked: how many terms for five decimals

For y′′=xyy'' = xy, y(0)=1y(0) = 1, y′(0)=0y'(0) = 0 (the Airy-type solution above), compute y(1)y(1) to five decimal places.

The nonzero coefficients are a3=16a_3 = \tfrac16, a6=1180a_6 = \tfrac1{180}, a9=112960a_9 = \tfrac{1}{12960}, a12=11710720a_{12} = \tfrac{1}{1710720}, each from an+3=an(n+3)(n+2)a_{n+3} = \dfrac{a_n}{(n+3)(n+2)}.

Step 1 — sum through x9x^9 at x=1x = 1: 1+16+1180+112960=1519312960≈1.17229941 + \tfrac16 + \tfrac1{180} + \tfrac1{12960} = \tfrac{15193}{12960} \approx 1.1722994.

Step 2 — bound the tail. From a12a_{12} on, each coefficient is at most 115⋅14<1200\tfrac{1}{15\cdot14} < \tfrac1{200} of the previous one, so the tail is less than a12(1+1200+12002+⋯ )<2a12≈1.2×10−6a_{12}\left(1 + \tfrac1{200} + \tfrac1{200^2} + \cdots\right) < 2a_{12} \approx 1.2\times10^{-6}.

Step 3 — so 1.1722994<y(1)<1.17230061.1722994 < y(1) < 1.1723006, and y(1)=1.17230y(1) = 1.17230 to five decimals.

Step 4 — the lesson: near the centre a handful of terms suffices, and the recurrence itself supplies the error bound. At x=−6x = -6 the same accuracy needs far more terms, because the powers 6n6^n fight the factorials much longer.

Side note
Where it goes wrong: trusting a smooth real graph

Since arctan⁡x\arctan x and the coefficient 1+x21 + x^2 are smooth for every real xx, one might evaluate the series x−x33+x55−⋯x - \tfrac{x^3}{3} + \tfrac{x^5}{5} - \cdots at x=2x = 2. The partial sums are 22, then 2−83≈−0.672 - \tfrac83 \approx -0.67, then +325+\tfrac{32}{5} gives 5.735.73, then −1287-\tfrac{128}{7} gives −12.55-12.55 — swinging ever wider, while arctan⁡2≈1.107\arctan 2 \approx 1.107. The zeros ±i\pm i of 1+x21 + x^2 cap the radius at 11. To get arctan⁡2\arctan 2 from a series, expand about a centre closer to 22, or use arctan⁡2=π2−arctan⁡12\arctan 2 = \tfrac\pi2 - \arctan\tfrac12.

Try it
Try it: a guaranteed radius

About x0=4x_0 = 4, how large an interval of convergence is guaranteed for the series solutions of (x2+9)y′′+xy′+y=0(x^2 + 9)y'' + xy' + y = 0? And about x0=0x_0 = 0?

Show the answer

The leading coefficient x2+9x^2 + 9 vanishes at x=±3ix = \pm 3i, the only singular points. From x0=4x_0 = 4 the distance to 3i3i is 42+32=5\sqrt{4^2 + 3^2} = 5, so the series about 44 converge at least on (−1,9)(-1, 9). From x0=0x_0 = 0 the distance is 33: at least (−3,3)(-3, 3). Moving the centre along the real axis away from the singular points enlarges the guaranteed interval — the reason one re-centres a series to reach farther.

Proofs & Why It Matters

Tip
Proof: coefficient matching is valid

A power series that sums to zero on an interval has all coefficients zero (differentiate repeatedly and evaluate at the center: an=f(n)(0)n!=0a_n = \tfrac{f^{(n)}(0)}{n!} = 0).

So when substituting y=∑anxny = \sum a_nx^n into an equation produces ∑cnxn=0\sum c_nx^n = 0, each cnc_n must individually vanish — turning the differential equation into an exact recurrence, not an approximation. ■\blacksquare

Tip
Proof: y′ = y forces aₙ = 1/n!

Substitute: ∑n≥1nanxn−1=∑n≥0anxn\sum_{n\ge1} na_nx^{n-1} = \sum_{n\ge0} a_nx^n. Shift the left index and match coefficients of xnx^n: (n+1)an+1=an(n+1)a_{n+1} = a_n. With a0=y(0)=1a_0 = y(0) = 1, induction gives an=1n!a_n = \tfrac{1}{n!}: a1=1a_1 = 1, and an+1=ann+1=1(n+1)!a_{n+1} = \tfrac{a_n}{n+1} = \tfrac{1}{(n+1)!}.

The series ∑xnn!\sum\tfrac{x^n}{n!} — the definition of exe^x — emerges with no prior knowledge of exponentials. ■\blacksquare

Going Deeper: Explanations & Worked Problems

Concept
The recurrence method, slowly

Write y=∑n≥0anxny = \sum_{n\ge0} a_nx^n and differentiate term by term: y′=∑n≥1nanxn−1y' = \sum_{n\ge1} na_nx^{n-1}, y′′=∑n≥2n(n−1)anxn−2y'' = \sum_{n\ge2} n(n-1)a_nx^{n-2}.

Substitute into the equation; now every sum must be re-indexed so all run over the same power xnx^n — the shift m=n−2m = n - 2 turns ∑n(n−1)anxn−2\sum n(n-1)a_nx^{n-2} into ∑(m+2)(m+1)am+2xm\sum (m+2)(m+1)a_{m+2}x^m, and multiplying by xx shifts the other way. Collect the coefficient of each xnx^n and set it to zero (legal because a power series vanishing identically has all coefficients zero — the proof slide): out drops a recurrence expressing high coefficients in terms of low ones. Initial conditions seed it: a0=y(0)a_0 = y(0), a1=y′(0)a_1 = y'(0). Then compute coefficients one at a time, as many as accuracy demands. The equation is never "solved" in closed form — and never needs to be.

Example
Worked: deriving a recurrence with the index shift shown

Solve y′′=−yy'' = -y, y(0)=1y(0) = 1, y′(0)=0y'(0) = 0, by series.

Step 1 — substitute: ∑n≥2n(n−1)anxn−2=−∑n≥0anxn\sum_{n\ge2} n(n-1)a_nx^{n-2} = -\sum_{n\ge0} a_nx^n.

Step 2 — shift the left index by 22: ∑n≥0(n+2)(n+1)an+2xn=−∑n≥0anxn\sum_{n\ge0} (n+2)(n+1)a_{n+2}x^{n} = -\sum_{n\ge0} a_nx^n.

Step 3 — equate the coefficient of every xnx^n: (n+2)(n+1)an+2=−an(n+2)(n+1)a_{n+2} = -a_n.

Step 4 — seed and run: a0=1a_0 = 1, a1=0a_1 = 0; then a2=−12⋅1=−12a_2 = \tfrac{-1}{2\cdot1} = -\tfrac12; a3=0a_3 = 0 (all odd coefficients inherit a1=0a_1 = 0); a4=−a24⋅3=124a_4 = \tfrac{-a_2}{4\cdot3} = \tfrac{1}{24}; a6=−a46⋅5=−1720a_6 = \tfrac{-a_4}{6\cdot5} = -\tfrac{1}{720}.

Step 5 — recognize: 1−x22!+x44!−x66!+⋯=cos⁡x1 - \tfrac{x^2}{2!} + \tfrac{x^4}{4!} - \tfrac{x^6}{6!} + \cdots = \cos x — the series method has derived the cosine series from the oscillator equation, not assumed it.

Example
Worked: the Airy-type start, where no closed form exists

Begin y′′=xyy'' = xy, y(0)=1y(0) = 1, y′(0)=0y'(0) = 0.

Step 1 — substitute and align powers: the left side is ∑n≥0(n+2)(n+1)an+2xn\sum_{n\ge0}(n+2)(n+1)a_{n+2}x^n; the right side xy=∑n≥1an−1xnxy = \sum_{n\ge1} a_{n-1}x^{n}.

Step 2 — match: for n=0n = 0: 2a2=02a_2 = 0, so a2=0a_2 = 0; for n≥1n \ge 1: (n+2)(n+1)an+2=an−1(n+2)(n+1)a_{n+2} = a_{n-1}.

Step 3 — run it: a3=a03⋅2=16a_3 = \tfrac{a_0}{3\cdot2} = \tfrac16; a4=a14⋅3=0a_4 = \tfrac{a_1}{4\cdot3} = 0; a5=a25⋅4=0a_5 = \tfrac{a_2}{5\cdot4} = 0; a6=a36⋅5=1180a_6 = \tfrac{a_3}{6\cdot5} = \tfrac{1}{180}.

Step 4 — the solution so far: y=1+x36+x6180+⋯y = 1 + \tfrac{x^3}{6} + \tfrac{x^6}{180} + \cdots, with nonzero coefficients only at powers 0,3,6,9,…0, 3, 6, 9, \ldots — a three-step lattice the recurrence forces. No elementary function has this series; the series itself is the honest, computable answer, good to any accuracy on any bounded interval.