Radius of Convergence

When a calculator approximates a function by adding up a power series, the trick only works inside a certain window around the centre; step outside it and the sum turns to nonsense. Knowing exactly how wide that trustworthy window is — its radius of convergence — is what keeps every such approximation honest.

A power series \sum c_n (x-a)^n is an infinite polynomial, and an infinite polynomial is a gamble: plug in an x and the sum might settle to a number, or it might explode. You would expect the winning values of x to be a mess — a scatter of lucky points, different for every series. They never are. Every power series comes with a blast radius: a single number R \in [0, \infty] such that

No half-measures, no scattered islands of convergence out beyond the boundary. The only points the number R refuses to classify are the two boundary points x = a \pm R themselves, and each of those must be interrogated by hand. That is the entire theory of where a power series lives, compressed into one number — and this page is about how to compute that number. The workhorse tool is the ratio test.

For every power series \sum c_n (x-a)^n there is a unique R \in [0, \infty], the radius of convergence, and exactly one of three things happens:

Deriving the radius from the ratio test

The ratio test looks at the limiting ratio of consecutive terms of a series \sum u_n: if \lim |u_{n+1}/u_n| = L, the series converges absolutely when L < 1 and diverges when L > 1. Apply it to the power series with u_n = c_n (x-a)^n — treating x as a fixed but unknown number — and the radius falls straight out.

Step 1 — form the ratio of consecutive terms.

\left|\frac{u_{n+1}}{u_n}\right| = \left|\frac{c_{n+1}(x-a)^{n+1}}{c_n (x-a)^n}\right| = \left|\frac{c_{n+1}}{c_n}\right|\,|x - a|.

Step 2 — take the limit. Suppose the coefficient ratio settles to a limit, \displaystyle \lim_{n\to\infty}\left|\frac{c_{n+1}}{c_n}\right| = \ell. Since |x-a| is a constant as far as n is concerned, it pulls outside the limit:

L = \lim_{n\to\infty}\left|\frac{u_{n+1}}{u_n}\right| = \ell \,|x - a|.

Step 3 — impose the convergence condition. The ratio test demands L < 1 for convergence:

\ell\,|x - a| < 1 \quad\Longleftrightarrow\quad |x - a| < \frac{1}{\ell}.

Step 4 — read off the radius. Comparing with |x - a| < R, the radius is the reciprocal of the coefficient-ratio limit:

\boxed{\,R = \frac{1}{\ell} = \lim_{n\to\infty}\left|\frac{c_n}{c_{n+1}}\right|\,}

with the natural conventions R = \infty when \ell = 0 (the coefficients shrink so fast the series converges everywhere) and R = 0 when \ell = \infty (it converges only at the centre). Notice what happened to x in Step 3: the condition L < 1 carved the number line into an inside and an outside — which is exactly why the convergence set is always an interval and never a ragged scatter.

Three radii, three worlds

(a) \sum x^n/n! gives R = \infty. Here c_n = 1/n!, so the coefficient ratio is

\left|\frac{c_{n+1}}{c_n}\right| = \frac{n!}{(n+1)!} = \frac{1}{n+1} \;\longrightarrow\; 0 = \ell \quad\Longrightarrow\quad R = \frac{1}{0} = \infty.

The factorial in the denominator crushes the powers of x no matter how large |x| is — eventually n! outgrows |x|^n and the terms plummet. The series converges for every real x: no endpoints to check, because there is no boundary. This is the series for e^x.

(b) \sum n!\,x^n gives R = 0. Flip the factorial upstairs: now c_n = n!, so

\left|\frac{c_{n+1}}{c_n}\right| = \frac{(n+1)!}{n!} = n+1 \;\longrightarrow\; \infty = \ell \quad\Longrightarrow\quad R = \frac{1}{\infty} = 0.

However tiny you make x \neq 0, the factorial eventually overwhelms it and the terms blow up. The series converges only at the single point x = 0 — a power series that is barely a function at all. Again no endpoint check: a point has no endpoints.

(c) \sum x^n/n gives R = 1, endpoints differing. Here c_n = 1/n:

\left|\frac{c_{n+1}}{c_n}\right| = \frac{n}{n+1} \;\longrightarrow\; 1 = \ell \quad\Longrightarrow\quad R = 1.

So it converges on (-1, 1) and diverges outside [-1, 1] — and now, for the first time, there is a genuine boundary to interrogate. At x = 1 the series is \sum 1/n, the harmonic series — diverges. At x = -1 it is \sum (-1)^n/n, the alternating harmonic series — converges. The interval of convergence is therefore [-1, 1): same radius, different fates at the two ends.

The full ritual, start to finish

Exam questions rarely centre a series at 0, and they always want the endpoints. Here is the complete procedure on a typical specimen:

\sum_{n=1}^{\infty} \frac{(x-3)^n}{n \cdot 2^n}.

Step 1 — ratio test for the radius. With u_n = \dfrac{(x-3)^n}{n\,2^n},

\left|\frac{u_{n+1}}{u_n}\right| = \frac{|x-3|^{n+1}}{(n+1)\,2^{n+1}} \cdot \frac{n\,2^n}{|x-3|^n} = \frac{n}{n+1}\cdot\frac{|x-3|}{2} \;\longrightarrow\; \frac{|x-3|}{2}.

Convergence requires \dfrac{|x-3|}{2} < 1, i.e. |x - 3| < 2. So R = 2, the centre is a = 3, and the interior of convergence is the interval from 3 - 2 = 1 to 3 + 2 = 5. The candidates still on trial: the two endpoints x = 1 and x = 5.

Step 2 — test the right endpoint x = 5. Substitute it in — the powers collapse into pure numbers:

\sum_{n=1}^{\infty} \frac{(5-3)^n}{n\,2^n} = \sum_{n=1}^{\infty} \frac{2^n}{n\,2^n} = \sum_{n=1}^{\infty} \frac{1}{n}.

The harmonic series — diverges. x = 5 is out.

Step 3 — test the left endpoint x = 1.

\sum_{n=1}^{\infty} \frac{(1-3)^n}{n\,2^n} = \sum_{n=1}^{\infty} \frac{(-2)^n}{n\,2^n} = \sum_{n=1}^{\infty} \frac{(-1)^n}{n}.

The alternating harmonic series — converges (by the alternating series test: terms decreasing to zero). x = 1 is in.

Verdict. Radius R = 2, interval of convergence

\boxed{\,[1, 5)\,}

— closed at the left, open at the right. Notice that the two endpoint series were ordinary numerical series, and each needed its own classical test. That is the part everyone skips, and the part every examiner checks.

Two mistakes account for most lost marks on this topic:

The trichotomy is not just bookkeeping — the three cases produce genuinely different kinds of mathematical object:

Take the geometric series \dfrac{1}{1-x} = \sum x^n, with R = 1. Fair enough: the function itself blows up at x = 1, so of course the series must stop there. The radius is the distance from the centre to the nearest disaster. Sensible.

Now try \dfrac{1}{1+x^2} = \sum (-1)^n x^{2n}. Same radius, R = 1 — but this function is perfectly smooth, bounded, and infinitely differentiable on the entire real line. There is no disaster anywhere in sight. Why on earth does its series give up at |x| = 1?

Because the disaster is hiding off the page. Allow x to be a complex number and 1 + x^2 = 0 at x = \pm i — two poles sitting one unit above and below the real axis, invisible to real eyes but exactly distance 1 from the centre 0. The deep theorem of complex analysis: the radius of convergence equals the distance from the centre to the nearest singularity in the complex plane. In \mathbb{C} the convergence set is a genuine disc — the word "radius" is literal, not a metaphor. Our real interval (a-R,\, a+R) is just the slice of that disc lying along the real axis. And the theorem even makes predictions: recentre the same function at a = 3 and the nearest pole \pm i is at distance \sqrt{3^2 + 1^2} = \sqrt{10}, so that Taylor series has R = \sqrt{10} — no ratio test required.

See the interval shrink and grow

Consider the family \sum n^{p}\, x^n, with a slider for the exponent p. The coefficient ratio |c_n/c_{n+1}| = (n/(n+1))^{p} \to 1 for every p, so the radius is always R = 1: the curve below (a partial sum, the first 18 terms) settles calmly inside (-1, 1) and blows up outside it no matter where you put the slider.

What p does change is the endpoint story — the one thing the radius cannot see. At p = -2 the coefficients are 1/n^2 and both endpoints converge (interval [-1,1]); at p = -1 you get our [-1, 1); at p = 0 the geometric series keeps neither endpoint; and for p > 0 the terms don't even tend to zero at x = \pm 1, so divergence there is instant. Watch how much more violently the partial sum rears up near x = \pm 1 as you push p upward: same radius, ever-worse behaviour on the boundary.

See it explained