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Glacial isostatic adjustment is the broader solid-Earth and sea-level response to growth and retreat of ice sheets.

A trapping region is a compact region across whose boundary the vector field points inward. It is positively invariant and confines every forward trajectory that enters it.

This is a dynamical example of an invariant; forward invariance and strict inward trapping are additional conditions.

A reproducing-kernel Hilbert space is a Hilbert space of functions in which point evaluation is continuous and satisfies $f(x)=⟨f,k(x,\cdot )⟩$.

For points $x_1,\dots ,x_n$, the kernel matrix has entries $K_{ij}=k(x_i,x_j)$ and is positive semidefinite.

A positive-definite matrix $V$ defines the inner product $x^{T}Vy$, allowing decomposition into a chosen direction and its $V$-orthogonal complement.

Velocity is the vector giving the rate of change of position with time, measured in a specified reference frame. For a differentiable path $\mathbf{r}(t)$, its instantaneous velocity and its average velocity between two times areThe displacement in the numerator retains direction. In Cartesian coordinates, each vector component is a derivative, for example $v_x=dx/dt$; its sign tells whether the corresponding coordinate is increasing or decreasing. The SI unit of velocity is $m/s$. ^[ref]

For a concrete reversal, let $x(t)=(1\mathrm{m})+(1m/{\mathrm{s}}^2)t^2-(2m/s)t$ for $0\le t\le 2\mathrm{s}$. Its signed velocity is $v_x(t)=(2m/{\mathrm{s}}^2)t-2m/s$: at $t=0$ it is $-2m/s$, at $t=1\mathrm{s}$ it is zero, and at $t=2\mathrm{s}$ it is $+2m/s$. The opposite endpoint velocities describe opposite directions, although the endpoint speeds agree. The position moves from $1\mathrm{m}$ to $0$ and back to $1\mathrm{m}$.

Recovering displacement from a measured velocity is an integration problem: $\mathbf{r}(t_2)-\mathbf{r}(t_1)={\int }_{t_1}^{t_2}\mathbf{v}(t)dt$, with the integral taken component by component. In the reversal example, ${\int }_0^{2\mathrm{s}}{v}_x(t)dt=0$: the negative and positive contributions cancel. This distinction is useful in navigation, where the final position depends on direction as well as speed.

Plane polar coordinates describe a point by its radial distance $r$ and polar angle $\theta$.

These are the planar polar coordinates; the general coordinate-system definition and transformations belong to that canonical concept.

Let $f\in F[x_1,\dots ,x_n]$ have degree at most $d_1+\cdots +d_n$, and let each $A_i\subset F$ contain $d_i+1$ distinct elements. The Alon-Tarsi coefficient formula isIt follows by applying Lagrange interpolation successively in each variable.

Hermite interpolation prescribes values and finitely many derivatives of a polynomial at distinct points.

A quadratic function of one variable has the form $a{x}^2+bx+c$ with $a\ne 0$.

For a polynomial $P={\sum }_{\mathbf{i}}{a}_{\mathbf{i}}{\mathbf{X}}^{\mathbf{i}}$, its length is the sum of the absolute values of its coefficients:

The degree of a nonzero polynomial is the largest exponent of a monomial with a nonzero coefficient. Thus $X^3-3X^2+4$ has degree three, while any nonzero constant polynomial has degree zero. The zero polynomial is treated separately in degree statements.

Over an integral domain, polynomial degrees add under multiplication: $\mathrm{deg}(pq)=\mathrm{deg}p+\mathrm{deg}q$ for nonzero factors, because the product of their leading coefficients cannot vanish. Under addition, cancellation may lower the degree: $(X^2+1)+(-X^2+X)=X+1$. This explains why degree is reliable for counting factors and bounding polynomial roots, but cannot always be inferred from the degrees of summands alone.

Polynomial division separates a polynomial into a multiple of a chosen divisor and a smaller polynomial remainder. Given $f,g\in F[X]$ over a field $F$, with $g\ne 0$, there are unique polynomials $q,r$ satisfyingHere $q$ is the polynomial quotient. The bound concerns polynomial degree, rather than the sizes of the coefficients.^[ref]

For an original example over the rational numbers, takePolynomial long division first cancels $2X^3$ by subtracting $2Xg$:Subtracting one more copy of $g$ cancels $X^2$:ThusThe final polynomial remainder has polynomial degree one, below the divisor's polynomial degree two. Multiplying out the last identity checks every coefficient, including the constant term $-2+8=6$.

The polynomial degree bound makes this decomposition useful: it replaces a potentially long polynomial with a short polynomial remainder whenever multiples of $g$ can be discarded. At any root of a polynomial of $g$, those multiples vanish under polynomial evaluation. Repeated polynomial division also drives the Euclidean algorithm for finding a greatest common divisor of polynomials.

The coefficient setting matters. Over a commutative ring, the same existence and uniqueness hold when the divisor's leading coefficient is a unit in a ring. A monic polynomial therefore works over the integers, even though they do not form a field; monic polynomial division over a ring explains why zero divisors cause no difficulty in that case.^[ref]

A nonzero divisor alone is insufficient over the integers. Dividing $X$ by $2X+1$ with an integer polynomial quotient and a constant polynomial remainder would require $1=2c$ for an integer $c$, which is impossible. Over the rational numbers the division instead givesThe obstruction is the nonunit leading coefficient $2$. This example separates existence from uniqueness: over an integral domain, the polynomial degree argument still makes any admissible pair unique, if it exists.

An irreducible polynomial is a nonconstant polynomial that cannot be written as a product of two nonconstant polynomials over its coefficient field. Over a general integral domain, neither factor may be a unit.

The $k$th elementary symmetric polynomial adds every product obtained by choosing $k$ distinct positions from $x_1,\dots ,x_n$:The conventions are $e_0=1$ and $e_k=0$ for $k>n$. The positions must be distinct, but their values may coincide. Each permutation of the variables merely rearranges the summands, so this is a symmetric polynomial.

For $x_1=1$, $x_2=2$, $x_3=3$, we obtain $e_1=1+2+3=6$, $e_2=1\cdot 2+1\cdot 3+2\cdot 3=11$, and $e_3=1\cdot 2\cdot 3=6$. Expanding the product givesIn general, ${\prod }_{i=1}^n(z-x_i)=z^n-e_1{z}^{n-1}+e_2{z}^{n-2}-\cdots +(-1{)}^n{e}_n$. Thus the coefficients of a monic polynomial collect elementary symmetric polynomials of its roots of a polynomial, with alternating signs. These are the Vieta formulas.^[ref]

The resultant turns a shared-root of a polynomial question into a calculation using only coefficients. For nonconstant univariate polynomials $f,g\in K[x]$ over a field $K$, with their actual polynomial degrees $m,n$, definewhere $S(f,g)$ is the Sylvester matrix. ThenHere $\overline{K}$ is an algebraic closure. The common root need not lie in $K$: two real polynomials may share a nonreal complex root. The subscript identifies which variable is eliminated.^[ref]

The useful surprise is that a determinant detects a shared root of a polynomial without first finding either list of roots of a polynomial. If the coefficients depend on a parameter, the resultant itself is a polynomial in that parameter. Its zeros pick out possible exceptional parameter values. Elimination theory uses this to reduce a pair of polynomial equations in two variables to a single necessary equation in one variable; eliminating a variable with a resultant gives an exact example below.

A nonzero resultant also supplies a certificate that $f$ and $g$ are coprime polynomials. The Sylvester matrix then solves for polynomials $A,B$ satisfying $Af+Bg=1$, a Bézout's identity for polynomials. Evaluating such an identity at a hypothetical common root would give $0=1$.

A multilinear polynomial has degree at most one in each variable. It has a unique expansion $f(x)={\sum }_S{a}_S{\prod }_{i\in S}{x}_i$.

A root of a polynomial $f$ is a scalar $a$ satisfying $f(a)=0$ in the chosen field or ring. For $p(X)=(X+1)(X-2{)}^2$ over the real numbers, the distinct roots of a polynomial are $-1$ and $2$. The second has multiplicity of a root two, so there are three roots when counted with multiplicity.

The domain matters. $X^2+1$ has no real polynomial root, but has the two complex number roots $i,-i$. The fundamental theorem of algebra guarantees a polynomial root in the complex numbers for every nonconstant complex polynomial, and complete factorization counts its degree of a polynomial many roots with multiplicity of a root. It does not promise that those roots are real or that they have a simple expression.

A multivariate polynomial is a finite linear combination of monomials in two or more variables.

A monic polynomial has leading coefficient one.