The Power Series Method
Write , substitute into the equation, shift indices so all powers align, and set each coefficient to zero — a recurrence for the . For : , giving — the series discovers 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 therefore loses no information — the recurrence is the equation, rewritten. For the coefficient of on the left is and on the right ; with the partial sums , , close in on .
The Airy-type equation has no closed-form solution, but its recurrence generates the answer to any accuracy: with , the series starts . Series are the solution.
Why the recurrence reaches back three places: in the second derivative lowers every power by two, while multiplying by raises it by one, so the coefficient of links to . With and only the powers survive. The series converges for every , but each partial sum is accurate only near ; more terms reach farther out, as the figure shows on the oscillating side .
, : the recurrence gives — matching the separable-method answer, coefficient for coefficient.
Where the recurrence comes from: substituting gives . The coefficient of is on the left and on the right (for ); for the right side has no constant term, so and every odd coefficient vanishes. From : , , , and in general — the series of with .
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.
For , , find , and in , and compare with the Taylor coefficients of the exact solution .
Show the answerHide the answer
Substitute: the coefficient of in is ; on the right, contributes and the extra contributes to the coefficient of only. So (from ), gives (from ), and gives (from ). The series begins . Check: , the same four coefficients.
Second-Order Equations at Ordinary Points
A point is ordinary for when and have convergent power series there. Then every solution is a power series : the coefficients and are free, and the recurrence fixes all the others. Taking and gives two independent solutions , , and every solution is .
Why exactly two are free: the coefficient of in is , and the other terms involve only , so each matching equation determines from earlier coefficients. Nothing ever determines or — 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 is .
Solve , , , by series.
Substitute : . Shift the first sum () so that every sum is written in : .
Step 1 — match the coefficient of : , and since , the factor cancels: .
Step 2 — seed with , . Every odd coefficient inherits ; the even ones are , , .
Step 3 — recognize the pattern : the series is .
Step 4 — check without series: , and has , so and the equation holds. The recurrence found a closed form nobody had to guess.
Find both series solutions of about .
After the same shift, the coefficient of is , so
Step 1 — even solution, , : , and then . The factor vanishes at , so every later even coefficient is as well: , a polynomial. Check: and , so .
Step 2 — odd solution, , : , , ; the factor is never for odd , so never stops.
Step 3 — the general solution is . This is Hermite's equation with ; whenever is a whole number, one of the two series terminates, giving the Hermite polynomials of the quantum oscillator.
For it is tempting to read off "the -th terms" of and write , that is — every coefficient zero, so , contradicting . The error: the first sum's -th term multiplies , the others' multiply , so those terms are not like terms. Only after shifting the first sum to do the coefficients of one power line up, giving .
For , , , find the recurrence and the coefficients .
Show the answerHide the answer
Shift the sum so all terms carry : . Since , the factor cancels and . From : , . From : , . So . (The even part is , by the same pattern as the worked example with the sign flipped.)
How Far a Series Reaches
For with polynomial coefficients, the singular points are the zeros of — complex zeros included. About an ordinary point , every series solution converges at least for , where is the distance from to the nearest zero of 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 — the series still feels it, exactly as the geometric series for stops at .
Solve , , , by series, and find where the series converges.
Substituting and shifting the sum gives, for the coefficient of : , and .
Step 1 — cancel the common factor : .
Step 2 — with all even coefficients vanish; from : , , . So .
Step 3 — confirm directly: the equation says , so and .
Step 4 — the radius: the leading coefficient vanishes at , at distance from the centre, and indeed the terms grow without bound when . The function is smooth on the whole real line, yet its series about works only for .
How far must the series solutions of converge, about and about ?
Singular points are the zeros of the leading coefficient: at .
Step 1 — no real singular points, but the complex ones still limit the disk of convergence.
Step 2 — about the distance to is (the same for ), so both series solutions converge at least for .
Step 3 — about the singular points are straight above and below, at distance : the guaranteed interval is .
Step 4 — the guarantee is a lower bound; a particular solution may converge farther (here is a solution, a polynomial, converging everywhere), but the general one cannot be promised more.
For , , (the Airy-type solution above), compute to five decimal places.
The nonzero coefficients are , , , , each from .
Step 1 — sum through at : .
Step 2 — bound the tail. From on, each coefficient is at most of the previous one, so the tail is less than .
Step 3 — so , and to five decimals.
Step 4 — the lesson: near the centre a handful of terms suffices, and the recurrence itself supplies the error bound. At the same accuracy needs far more terms, because the powers fight the factorials much longer.
Since and the coefficient are smooth for every real , one might evaluate the series at . The partial sums are , then , then gives , then gives — swinging ever wider, while . The zeros of cap the radius at . To get from a series, expand about a centre closer to , or use .
About , how large an interval of convergence is guaranteed for the series solutions of ? And about ?
Show the answerHide the answer
The leading coefficient vanishes at , the only singular points. From the distance to is , so the series about converge at least on . From the distance is : at least . 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
A power series that sums to zero on an interval has all coefficients zero (differentiate repeatedly and evaluate at the center: ).
So when substituting into an equation produces , each must individually vanish — turning the differential equation into an exact recurrence, not an approximation.
Substitute: . Shift the left index and match coefficients of : . With , induction gives : , and .
The series — the definition of — emerges with no prior knowledge of exponentials.
Going Deeper: Explanations & Worked Problems
Write and differentiate term by term: , .
Substitute into the equation; now every sum must be re-indexed so all run over the same power — the shift turns into , and multiplying by shifts the other way. Collect the coefficient of each 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: , . 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.
Solve , , , by series.
Step 1 — substitute: .
Step 2 — shift the left index by : .
Step 3 — equate the coefficient of every : .
Step 4 — seed and run: , ; then ; (all odd coefficients inherit ); ; .
Step 5 — recognize: — the series method has derived the cosine series from the oscillator equation, not assumed it.
Begin , , .
Step 1 — substitute and align powers: the left side is ; the right side .
Step 2 — match: for : , so ; for : .
Step 3 — run it: ; ; ; .
Step 4 — the solution so far: , with nonzero coefficients only at powers — 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.