Interpolation
Named by 9 essays across 4 fields — each of them below, with the objects they name alongside it.
A polynomial through the gaps
Write the message as the coefficients of a polynomial and send its values instead. Any k of them determine the polynomial, so it does not matter which ones are lost — and it does not matter how many, as long as k survive.
The points that ruin the fit
A polynomial through eleven points of a gentle curve should be a good approximation to it, and adding more points should make it better. On evenly spaced points it makes it worse, without limit, and the reason is not the polynomial but where the points were put.
Averaging down the triangle
Change one word in the rule that builds Pascal's triangle — take a share of each entry above instead of adding them — and the triangle stops counting and starts averaging. The same rule then draws smooth curves from polygons and approximates every continuous function by polynomials, at a rate that no amount of smoothness can improve.
The error that keeps coming back to its worst
Judge a polynomial by its largest error on an interval and there is exactly one best one of each degree. It is recognised without comparing it to anything else — its error rises to the same largest size, alternately above and below, one more time than there are coefficients.
The best nodes have no formula
Interpolating through n points magnifies any error in the data by at most the Lebesgue constant of the points. Chebyshev's points keep it near (2/π)·log n; stretching them to the ends of the interval brings it within two hundredths of the best possible; and the best possible points, characterised in 1978 by having every bump of the error curve the same height, have never been given a formula.
Only one curve through the factorials bends the right way
Infinitely many smooth curves pass through 1, 1, 2, 6, 24, 120, and some of them even obey the factorial's own rule, f(x + 1) = (x + 1)·f(x), at every x. Ask that the logarithm of the curve bend upwards everywhere and exactly one survives — Euler's integral. A wiggle of any size breaks the condition somewhere, the smaller the wiggle the further out, and the proof that nothing else survives is a squeeze that computes √π along the way.
A rotation chosen at random
Turn a solid body to an orientation chosen at random and it has usually been turned a long way: on average 126.5 degrees, and by less than ten degrees only three times in ten thousand. Unit quaternions make the right meaning of 'at random' a picture, and two recipes that look fair fail it in opposite directions.
A wave known only at its ticks
Read a sine wave nine cycles a second at ten instants a second and the readings describe a wave of one cycle a second instead. Read a wave with nothing faster than 3.7 cycles a second at more than 7.4 instants a second and the readings determine it exactly. Both facts are the same fold of the frequency axis, and it is why wagon wheels turn backwards on film.
Where to take the samples
Every numerical integral is a weighted sum of samples of the curve. Spacing the samples evenly gives errors that shrink like a power of their number; choosing where they go, as Gauss did in 1814, makes six samples exact for every polynomial up to degree eleven and turns the power into a geometric rate. The surprise is that the humble trapezoid rule, evenly spaced and exact only for straight lines, does the same thing on any smooth curve that goes once round a circle — and that a single corner defeats every one of them.
Named alongside it
The objects these essays reach for when they reach for this one.
ApproximationPolynomialAliasingAnalytic functionChebyshev polynomialError analysisFourier seriesPolynomial approximationUniform convergenceBinomial coefficientBinomial distributionBound