Intermediate Calculus

§2 Remainders and Power Series

Evan Luo

9 min read

Knowing that a series converges does not tell us its exact sum or how many terms are needed for a useful approximation. Occasionally an exact identity is known, while a similar-looking series may have no immediately useful formula:

n=11n2=π26,n=11n3=?\sum_{n=1}^{\infty}\frac{1}{n^2}=\frac{\pi^2}{6}, \qquad \sum_{n=1}^{\infty}\frac{1}{n^3}=?

Remainder estimates put a guaranteed bound on the part of a series we did not add, so a finite partial sum can still give a controlled approximation.

The same convergence tools also let us study power series, whose terms depend on a variable xx. A power series may converge for some values of xx and diverge for others.

Partial sums and remainders

Suppose the convergent series

S=n=0anS=\sum_{n=0}^{\infty}a_n

has NNth partial sum

SN=n=0Nan.S_N=\sum_{n=0}^{N}a_n.

The remainder, also called the tail or error, is

RN=SSN=n=N+1an.\boxed{R_N=S-S_N=\sum_{n=N+1}^{\infty}a_n}.

The first omitted term is aN+1a_{N+1} because SNS_N already includes every term from a0a_0 through aNa_N.

A useful remainder estimate answers a practical question:

How far can the approximation SNS_N be from the true sum SS?

Integral-test remainder estimate

Suppose ff is continuous, positive, and decreasing, and

an=f(n).a_n=f(n).

If the corresponding improper integral—an integral whose interval extends to infinity—converges, then the remainder satisfies

N+1f(x)dxRNNf(x)dx.\boxed{ \int_{N+1}^{\infty}f(x)\,dx \le R_N \le \int_N^{\infty}f(x)\,dx. }

The left integral is a lower bound and the right integral is an upper bound.

Two integral comparisons trapping the tail of a positive decreasing series

Why do the bounds begin at different places?

Because ff is decreasing, its value across a unit interval can be compared with a rectangle whose height is one of the sequence terms.

For the lower bound, pair an=f(n)a_n=f(n) with the interval immediately to its right:

nn+1f(x)dxf(n)=an.\int_n^{n+1}f(x)\,dx\le f(n)=a_n.

The remainder begins with aN+1a_{N+1}, so the first interval is [N+1,N+2][N+1,N+2]. Adding all those inequalities gives

N+1f(x)dxRN.\int_{N+1}^{\infty}f(x)\,dx\le R_N.

For the upper bound, pair an=f(n)a_n=f(n) with the interval immediately to its left:

f(n)=ann1nf(x)dx.f(n)=a_n\le\int_{n-1}^{n}f(x)\,dx.

The interval paired with aN+1a_{N+1} begins at NN, so

RNNf(x)dx.R_N\le\int_N^{\infty}f(x)\,dx.

The shift by 11 is not arbitrary. It comes from aligning the first omitted term with a whole unit interval. Starting at N+12N+\tfrac12 would require extra assumptions; positivity and monotonic decrease alone do not guarantee that comparison.

Using an upper bound to choose NN

If we want an error smaller than a tolerance ε>0\varepsilon>0, it is enough to choose NN so that

Nf(x)dx<ε.\int_N^{\infty}f(x)\,dx<\varepsilon.

Then

SSN=RN<ε.|S-S_N|=R_N<\varepsilon.

For a positive series, RNR_N is positive, so absolute values are optional. They become essential for alternating series.

Alternating-series remainder estimate

Consider an alternating series

S=n=0(1)nbn,S=\sum_{n=0}^{\infty}(-1)^n b_n,

where

bn0,bn+1bn,limnbn=0.b_n\ge0, \qquad b_{n+1}\le b_n, \qquad \lim_{n\to\infty}b_n=0.

These are the hypotheses of the Alternating Series Test, abbreviated AST. They guarantee convergence. They also give the stronger error estimate

RN=SSNbN+1.\boxed{|R_N|=|S-S_N|\le b_{N+1}}.

In words: the approximation error is no larger than the magnitude of the first omitted term.

Example: enough accuracy to round correctly

Consider

S=n=0(1)n4n(n+1).S=\sum_{n=0}^{\infty} \frac{(-1)^n}{4^n(n+1)}.

Here

bn=14n(n+1).b_n=\frac{1}{4^n(n+1)}.

The terms are positive, decrease, and approach zero, so the AST and its remainder estimate apply.

Using terms through n=3n=3 gives

S3=118+1481256=0.891927083.\begin{aligned} S_3 &=1-\frac18+\frac1{48}-\frac1{256}\\ &=0.891927083\ldots. \end{aligned}

The first omitted magnitude is

b4=144(5)=11280=0.00078125.b_4=\frac{1}{4^4(5)}=\frac1{1280}=0.00078125.

Therefore,

SS30.00078125.|S-S_3|\le0.00078125.

Even after adding or subtracting the maximum possible error, the result still rounds to

S0.89\boxed{S\approx0.89}

to two decimal places.

Stopping at N=2N=2 would not be enough. The allowed error interval would contain values that round to 0.890.89 and values that round to 0.900.90. A decimal approximation is useful only when the error bound is small enough to settle the requested rounding.

Power series

A power series centered at aa is an infinite series of the form

n=0cn(xa)n=c0+c1(xa)+c2(xa)2+.\boxed{ \sum_{n=0}^{\infty}c_n(x-a)^n =c_0+c_1(x-a)+c_2(x-a)^2+\cdots. }

Here:

  • xx is the variable;
  • aa is a fixed real number called the center;
  • cnc_n is the coefficient of the nnth power.

When a=0a=0, this becomes

n=0cnxn.\sum_{n=0}^{\infty}c_nx^n.

A power series resembles a polynomial, but a polynomial has only finitely many nonzero terms. A power series may have infinitely many.

Radius and interval of convergence

For a power series

n=0cn(xa)n,\sum_{n=0}^{\infty}c_n(x-a)^n,

exactly one of the following occurs:

  1. It converges only at x=ax=a.
  2. It converges for every real xx.
  3. There is a number R>0R>0 such that it converges when xa<R|x-a|<R and diverges when xa>R|x-a|>R.

The number RR is the radius of convergence. By convention:

  • R=0R=0 in the first case;
  • R=R=\infty in the second case.

If 0<R<0<R<\infty, then

xa<RaR<x<a+R.|x-a|<R \quad\Longleftrightarrow\quad a-R<x<a+R.

The points x=aRx=a-R and x=a+Rx=a+R are the endpoints. The radius theorem says nothing about them, so they must be checked separately.

The interval of convergence is the complete set of real xx-values where the series converges, including whichever endpoints pass their individual tests.

Example: the endpoints behave differently

Find the interval of convergence of

n=1(x3)nn.\sum_{n=1}^{\infty}\frac{(x-3)^n}{n}.

Let

an=(x3)nn.a_n=\frac{(x-3)^n}{n}.

First handle x=3x=3: every term is zero, so the series converges. For x3x\ne3, the ratio test gives

an+1an=(x3)nn+1x3.\begin{aligned} \left|\frac{a_{n+1}}{a_n}\right| &=\left|(x-3)\frac{n}{n+1}\right|\\ &\longrightarrow |x-3|. \end{aligned}

The series therefore converges absolutely, meaning that the series of absolute values also converges, when

x3<1,|x-3|<1,

which means

2<x<4.2<x<4.

Now check the endpoints.

At x=2x=2,

n=1(1)nn\sum_{n=1}^{\infty}\frac{(-1)^n}{n}

is an alternating harmonic series, so it converges conditionally: it converges, but the corresponding series of absolute values does not.

At x=4x=4,

n=11n\sum_{n=1}^{\infty}\frac1n

is the harmonic series, so it diverges.

Thus the center is 33, the radius is 11, and the interval of convergence is

[2,4).\boxed{[2,4)}.

In set-builder notation,

[2,4)={xR:2x<4}.[2,4)=\{x\in\mathbb R:2\le x<4\}.

A power series defines a function

Inside its interval of convergence, a power series defines a function:

f(x)=n=0cn(xa)n.f(x)=\sum_{n=0}^{\infty}c_n(x-a)^n.

Sometimes the same function has a simpler formula. The geometric-series identity says

11u=n=0un,u<1.\frac{1}{1-u}=\sum_{n=0}^{\infty}u^n, \qquad |u|<1.

The restriction belongs to the series representation. The formula 1/(1u)1/(1-u) may be defined at points where the series diverges.

Example: build a representation from a geometric series

Find a power-series representation centered at 00 for

f(x)=32+x2.f(x)=\frac{3}{2+x^2}.

Rewrite the denominator to match 1/(1u)1/(1-u):

32+x2=3211+x2/2=3211(x2/2).\begin{aligned} \frac{3}{2+x^2} &=\frac32\frac{1}{1+x^2/2}\\ &=\frac32\frac{1}{1-(-x^2/2)}. \end{aligned}

Use

u=x22.u=-\frac{x^2}{2}.

Then

32+x2=32n=0(x22)n=n=03(1)n2n+1x2n.\begin{aligned} \frac{3}{2+x^2} &=\frac32\sum_{n=0}^{\infty} \left(-\frac{x^2}{2}\right)^n\\ &=\boxed{ \sum_{n=0}^{\infty} \frac{3(-1)^n}{2^{n+1}}x^{2n} }. \end{aligned}

This converges when

x22<1,\left|-\frac{x^2}{2}\right|<1,

so

x<2.|x|<\sqrt2.

At x=±2x=\pm\sqrt2, the resulting terms do not approach zero. Therefore the interval of convergence is

(2,2).\boxed{(-\sqrt2,\sqrt2)}.

Only even powers appear. For example, the x6x^6 term occurs when

2n=6,2n=6,

so it comes from n=3n=3, not n=6n=6.

Differentiating and integrating power series

Suppose

f(x)=n=0cn(xa)nf(x)=\sum_{n=0}^{\infty}c_n(x-a)^n

has radius of convergence R>0R>0. Inside the open interval

(aR,a+R),(a-R,a+R),

we may differentiate and integrate term by term.

Differentiation

f(x)=c1+2c2(xa)+3c3(xa)2+=n=1ncn(xa)n1=n=0(n+1)cn+1(xa)n.\begin{aligned} f'(x) &=c_1+2c_2(x-a)+3c_3(x-a)^2+\cdots\\ &=\sum_{n=1}^{\infty}n c_n(x-a)^{n-1}\\ &=\sum_{n=0}^{\infty}(n+1)c_{n+1}(x-a)^n. \end{aligned}

The final line is the same series after reindexing, meaning that the summation label is changed so the exponent is again nn.

Integration

f(x)dx=C+c0(xa)+c12(xa)2+c23(xa)3+=C+n=0cnn+1(xa)n+1.\begin{aligned} \int f(x)\,dx &=C+c_0(x-a)+\frac{c_1}{2}(x-a)^2 +\frac{c_2}{3}(x-a)^3+\cdots\\ &=C+\sum_{n=0}^{\infty} \frac{c_n}{n+1}(x-a)^{n+1}. \end{aligned}

The differentiated and integrated series have the same radius of convergence RR. Their behavior at the endpoints may change, so endpoint convergence must still be checked separately.

Example: differentiating the geometric series

Starting from

11x=n=0xn,x<1,\frac{1}{1-x}=\sum_{n=0}^{\infty}x^n, \qquad |x|<1,

differentiate both sides:

1(1x)2=n=1nxn1=n=0(n+1)xn,x<1.\boxed{ \frac{1}{(1-x)^2} =\sum_{n=1}^{\infty}n x^{n-1} =\sum_{n=0}^{\infty}(n+1)x^n }, \qquad |x|<1.

Example: the exponential series

Define

f(x)=n=0xnn!.f(x)=\sum_{n=0}^{\infty}\frac{x^n}{n!}.

Term-by-term differentiation gives

f(x)=n=1nxn1n!=n=1xn1(n1)!=n=0xnn!=f(x).\begin{aligned} f'(x) &=\sum_{n=1}^{\infty}n\frac{x^{n-1}}{n!}\\ &=\sum_{n=1}^{\infty}\frac{x^{n-1}}{(n-1)!}\\ &=\sum_{n=0}^{\infty}\frac{x^n}{n!}\\ &=f(x). \end{aligned}

Also f(0)=1f(0)=1. The function with

f=f,f(0)=1f'=f, \qquad f(0)=1

is exe^x. Therefore,

ex=n=0xnn!\boxed{e^x=\sum_{n=0}^{\infty}\frac{x^n}{n!}}

for every real xx.

A practical power-series workflow

To find an interval of convergence:

  1. Identify the center aa.
  2. Apply the ratio or root test to find the condition xa<R|x-a|<R.
  3. Convert that inequality into an open interval.
  4. Test the two endpoints separately.
  5. Use brackets only for endpoints that actually converge.

To approximate a convergent numerical series:

  1. Decide which remainder estimate applies.
  2. Express the bound in terms of NN.
  3. Choose NN so the bound is small enough for the requested accuracy.
  4. Compute SNS_N.
  5. Report the approximation together with its guaranteed error.
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