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Every set of at least $d+2$ points in ${\mathbb{R}}^d$ can be partitioned into two nonempty parts with intersecting convex hulls. To see this, take a nonzero affine dependence on $d+2$ of its points. Its positive and negative coefficient sums have the same magnitude $L>0$. Dividing by $L$ expresses one point as a convex combination of the positive-coefficient points and also as a convex combination of the negative-coefficient points. Distribute zero-coefficient and remaining points arbitrarily between the parts. This theorem obstructs arbitrary labels for affine linear classifiers.

The convex hull of the six Pauli eigenstates in the Bloch ball. A mixture has a Bloch vector obeying the displayed inequality. Conversely, assign weights $|s_x|,|s_y|,|s_z|$ to the corresponding signed vertices and distribute the leftover weight over any opposite pair; this realizes every vector satisfying the inequality. Single-qubit Clifford gates permute its vertices, while a T gate can take a vertex to a pure state outside it.

A useful subdivision curve interface provides parameter ranges, endpoint and limit evaluation, derivatives, subdivision into equivalent restricted pieces, a certified bounding volume, and a certified error relative to a chord. Positive subdivision masks often give a convex hull bound. Masks with negative coefficients need a separate enclosing bound; their control-point hull need not enclose the limit curve.

For an event $A$ in a product of finitely many probability spaces with its product measure, take the closed convex hull of the mismatch vectors $(1_{x_i\ne y_i}{)}_i$, $y\in A$. The distance of this hull from zero is $d_T(x,A)$. Equivalently it is the supremum, over nonnegative coordinate weights of squared sum at most one, of their minimum mismatch sum. Averaging mismatch patterns is the feature that distinguishes this quantity from ordinary Hamming distance.

For feasible independent set activation vectors $S$, the throughput region is their convex hull. Its downward closure is the same set because deleting active vertices preserves feasibility. Ideal carrier-sense multiple access can supply strict margins above every vector in its interior by adjusting attempt rates.

A triangle is the convex hull of three noncollinear points: the three vertices must not lie on one line. Its boundary consists of the three joining line segments; depending on context, "triangle" can mean this boundary or the filled region it encloses. Here a triangle's area refers to the filled region. The noncollinearity assumption excludes a collapsed shape with zero area, for which ordinary interior angles are not defined.

For example, the positions $(0,0)$, $(4,0)$ and $(0,3)$ form a right triangle with a right angle at the origin. Taking the side of length $4$ as its base gives perpendicular height $3$, so its area is $4\cdot 3/2=6$. The height is measured at a right angle to the chosen base; it is not generally the length of another side. In this example it happens to be a side because the triangle is a right triangle.

By contrast, side lengths $3,4,6$ define a valid triangle: each side is shorter than the sum of the other two, as required by the strict triangle inequality. But $3^2+4^2=25\ne 36=6^2$, so this is not a right triangle and the Pythagorean theorem cannot calculate its longest side from the other two. The law of cosines instead gives the opposite interior angle $C$ throughThis example separates the definition of a triangle from the additional assumption of a right angle.

Every triangle in the Euclidean plane has interior angles summing to $\pi$ radians, a result proved in Euclid's Elements I.32.^[ref] It lets two measured angles determine the third, and underlies the angle-angle criterion for similar triangles. The qualification "Euclidean plane" matters: the earlier spherical triangle demonstrates a different sum.