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Sum of Geometric Series
Discrete Mathematics · Chapter 3: Sequences and SeriesSection 3.7 · lesson 23 of 879 min · free with a free account
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Next lesson: Practice: Arithmetic and Geometric Series →← Sum of Arithmetic SeriesNext lesson: Practice: Arithmetic and Geometric Series →
In this lesson
Adding finitely many terms - and when infinitely many still add to a finite number.
- Derive the finite geometric series formula
- Compute partial sums in closed form
- Define convergence of an infinite series
- Apply the sum-to-infinity formula, and its condition
Transcript
Everything said in the video, section by section (1,342 words). Read along, or search it.
Sequences and Series
Sum of Geometric Series
Section three point four studied geometric sequences term by term. This section adds them up. We'll derive a formula for summing finitely many terms of a geometric sequence. Then we'll find a precise condition under which summing infinitely many of them still produces a finite number.
The Opening Problem
How Long Has the Client Waited?
Section three point four looked at the exponential-backoff retry policy, with a first delay of five hundred milliseconds and a common ratio of two. It asked how long the wait is before the tenth retry alone. That question has a one-term answer. A different, equally practical question doesn't. How much total time has the client spent waiting, once all its retries are added up? That asks for a sum of terms, a partial sum of a geometric sequence. And section three point four also had a shrinking timeout budget, starting at eight thousand milliseconds, with a ratio of one half. If that pattern were extended forever, would its total be finite? Or would it also grow without bound?
Partial Sums
From Terms to Sums
For a sequence, the n-th partial sum, S sub n, is the sum of its first n terms. A series is that running total, studied as its own object. Section three point six summed arithmetic series by pairing the sequence with its own reverse. That trick won't help here. It works only because consecutive arithmetic terms differ by a fixed amount. Consecutive geometric terms differ by a fixed factor instead. So summing them calls for a different technique.
Derivation
Multiply by r, Then Subtract
Let S sub n be the sum of the first n terms. a one, plus a one r, plus a one r squared, up to a one r to the n minus one. Multiply both sides by r. That gives a one r, plus a one r squared, up to a one r to the n. Now subtract the second equation from the first. Every term from a one r up to a one r to the n minus one appears in both sums, and cancels. Only the first term of the first sum, and the last term of the second, survive. So S sub n minus r S sub n equals a one minus a one r to the n. Factor both sides: one minus r, times S sub n, equals a one times one minus r to the n.
Theorem
The Finite Geometric Series Sum
Divide by one minus r, provided r isn't one. The theorem. The sum of the first n terms of a geometric sequence is a one, times one minus r to the n, all over one minus r. If r equals one, the denominator is zero, and the formula doesn't apply. But in that case every term equals a one, so the sum of n terms is simply n times a one.
Worked Example 1
Total Wait After 5 Retries
Let's find the total wait after five retries, with first delay five hundred and ratio two. S five equals five hundred, times one minus two to the fifth, over one minus two. That's five hundred times minus thirty-one, over minus one. Fifteen thousand five hundred milliseconds. Check it by direct addition. Five hundred, one thousand, two thousand, four thousand, and eight thousand add to fifteen thousand five hundred. It matches. The closed form also changes the cost. Adding n terms one at a time takes work that grows with n. The formula needs one exponentiation and a few operations, which, with an efficient algorithm, grows only with the logarithm of n.
Definition
When Does an Infinite Sum Make Sense?
Now suppose the number of terms isn't fixed at all. The sequence keeps going forever. It's not obvious that adding infinitely many positive numbers could ever produce a finite result. For many sequences, it doesn't. So the sum of an infinite series is given a precise meaning, as a limit. An infinite series converges to a sum S, if its partial sums approach S as n grows without bound. If the partial sums don't approach one finite value, because they grow without bound or oscillate without settling, the series diverges, and no sum is assigned.
Sum to Infinity
Everything Hinges on r to the n
Start from the finite sum formula, and watch what happens as n grows. Everything in the formula is fixed except r to the n. So the behavior of the sum depends entirely on the behavior of r to the n. If the absolute value of r is less than one, r to the n shrinks toward zero, even for negative r. Substituting zero gives a one over one minus r. If the absolute value of r is greater than one, r to the n grows without bound, so the series diverges. If r equals one, the sum is n times a one, which grows without bound. And if r equals minus one, the partial sums swing between a one and zero forever. Both diverge.
Theorem
The Sum to Infinity
Putting the cases together gives a single, precise condition. An infinite geometric series converges if and only if the absolute value of r is less than one. When it converges, its sum is a one over one minus r. When the absolute value of r is one or more, the series diverges, and no finite sum exists.
Worked Example 2
Does the Budget Add Up to Something Finite?
Take the timeout budget, starting at eight thousand milliseconds with ratio one half. Suppose, hypothetically, the pattern were extended indefinitely. Check convergence first. The absolute value of r is one half, which is less than one. So the series converges. Apply the formula. Eight thousand over one minus one half is eight thousand over one half, which is sixteen thousand milliseconds. Sixteen seconds. Even though this policy never stops proposing another, smaller allotment, the total is bounded. However many terms are included, the running total never reaches sixteen seconds. It only approaches it.
Figures 1 and 2
Divergent Versus Convergent
This figure compares the two series. On the left are the running totals of the retry delays, for one through six retries. Each bar is a cumulative wait, not a single delay. They climb ever more steeply, rather than leveling off. That's the signature of a series with no sum to infinity. On the right are the running totals of the timeout budget. They flatten toward the dashed line at sixteen thousand milliseconds, without ever reaching it. That's the qualitative difference between a divergent and a convergent series.
The Engineering Distinction
Growing Delays Have No Finite Total
For the retry delays, asking for the total if the retries never stop isn't a matter of computing a bigger number. It isn't a valid question. The absolute value of r is two, which is at least one, so the series diverges. So a retry policy whose wait times grow geometrically has no finite worst-case total wait, if it's allowed to continue indefinitely. One whose wait times decay geometrically does. That's a genuine engineering distinction, and it has the same mathematical root as the condition, the absolute value of r less than one.
Comparing 3 Kinds of Series
Only One Can Be Summed to Infinity
This table places three kinds of series side by side. The arithmetic series from section three point six needs the first term, the last term or the difference, and n. Its terms never shrink, so it grows without bound. The finite geometric series needs the first term, r, and n. It's finite for any finite n. And the infinite geometric series needs only the first term and r. n plays no role, because there's no last term. It converges to a finite value only if the absolute value of r is less than one. Otherwise no sum exists at all.
Takeaways
Telescoping, and a Condition
To summarize. The finite geometric series formula comes from multiplying by r and subtracting, so the middle terms cancel. That's a different technique from the arithmetic pairing trick. An infinite geometric series converges if and only if the absolute value of r is less than one. Then its sum is a one over one minus r. And terms shrinking toward zero is what makes convergence possible, but the sum itself generally isn't zero. Here's something to think about. A classmate says, the terms shrink toward zero, so adding infinitely many of them should give zero. But the budget example gave sixteen thousand milliseconds. Where does the reasoning go wrong? Be precise about the difference between a claim about the terms, and a claim about the partial sums.
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About Sum of Geometric Series
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