Local minimum
Named by 4 essays across 2 fields — each of them below, with the objects they name alongside it.
Every site in the middle of its own cell
Move each point to the centre of mass of its own Voronoi cell, then redraw the diagram, then do it again. The rule is two lines long, it never mentions hexagons, and what it settles into is a honeycomb.
A line under every point
The chord above the curve is one definition of convexity. There is a second — a line under the curve at every point, staying under everywhere — and it is the one that turns a statement about a derivative at a point into a statement about the whole function.
Where the guarantee stops
Convexity converts every downhill method into a correct one, and its absence removes the guarantee entirely rather than degrading it. What is left is a collection of partial answers, and knowing which of them apply to a given problem is most of what non-convex optimisation is.
Three sides and four are proved
Among all shapes of a given area, the disc has the smallest lowest eigenvalue. Among triangles it is the equilateral one, among quadrilaterals the square — both proved by sliding chords to an axis. For five sides the regular pentagon wins every computation, every nudge raises its value by the square of the nudge, and there is still no proof.
Named alongside it
The objects these essays reach for when they reach for this one.
ConvexityGradientOptimisationCentroidComplexityCounterexampleDerivativeEigenvalueFixed pointHexagonal packingInequalityIsoperimetric inequality