Algorithm
Named by 7 essays across 4 fields — each of them below, with the objects they name alongside it.
A price for every person and task
The cheapest assignment can be found without comparing it to any other. Attach a number to each person and each task so that no pair's two numbers exceed its cost, and if the numbers add to an assignment's total, that assignment is cheapest — proved, by an argument that never mentions the alternatives.
A method that is allowed to miss
Bhāskara's cyclic method solves x² − Dy² = 1 by aiming at the wrong target. It keeps a pair a, b with a² − Db² = k for some small k, combines it with a helper chosen so that k can be divided out, and repeats until k is 1. For D = 61 it reaches the ten-digit fundamental solution in 13 steps, where walking the convergents of √61 takes 22 — and for every D up to 100 it is faster.
Matching as they arrive
Applicants arrive one at a time, and each must be given a post or turned away on the spot. Any sensible rule matches at least half as many as the best assignment chosen with hindsight, and an adversary arranging the arrivals can hold every fixed rule to exactly half. Shuffle the posts once, at random, and give each arrival its best-ranked free post: the guarantee rises to 1 − 1/e, about 63%, and no rule of any kind can do better.
Prices the bidders raise
The cheapest assignment is certified by a price on every task, and those prices can be found without anyone in charge. Let each unassigned person bid for the task that suits them best at current prices, raise its price by a little more than it is worth to them over the next best, and wait. The bidding ends, and when the increment is small enough the prices it ends at are a proof of optimality.
The order decides the colours
The simplest way to colour a graph is to take the vertices one at a time and give each the first colour its neighbours are not already using. It never needs more than one colour beyond the largest degree — and on a graph that needs only two colours it can be made to use as many as there are vertices on a side, depending on nothing but the order it is handed.
A cube root that looks like chance
The continued fraction of √61 repeats after eleven terms, and every square root's must. The cube root of 2 obeys no such law. Computed exactly, by a method of Lagrange's that never leaves the whole numbers, its terms run 1, 3, 1, 5, 1, 1, 4 … and throw up a 534 at the thirty-fifth place and a 7,451 at the 571st — and in every statistic anyone has measured, they look like the terms of a number picked at random.
Four lists find a collision sooner
Two lists of random 24-bit strings need about four thousand entries each before some string appears in both — the birthday bound. Ask instead for one string from each of four lists whose exclusive-or is zero, and lists of a few hundred suffice, because merging the lists in pairs manufactures the near-misses a direct search would have to find by luck. David Wagner's algorithm turns the square root into a cube root, and more lists into smaller roots.
Named alongside it
The objects these essays reach for when they reach for this one.
AssignmentCertificateComplementary slacknessContinued fractionsDualityExpectationGreedy algorithmLinear programmingMatchingRandomnessAlgebraic numberBinary