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In a polynomial representation, every matrix coefficient is a polynomial in the matrix entries. The action extends to the monoid of all matrices. The scalar action splits it into homogeneous polynomial degrees; each homogeneous degree-$n$ category is the module category of the Schur algebra $S(m,n)$. Its irreducibles are the Schur modules $D_{\lambda }({\mathbb{C}}^m)$ with $\lambda ⊢n$ and at most $m$ rows.

Tensoring a rational representation of the general linear group with a determinant power shifts every highest-weight coordinate by the same integer $r$. Positive twists can clear determinant denominators; negative twists supply rational representations that do not extend to singular matrices. Twisting preserves irreducibility and dimension.

Split a rational $S{L}_m$ representation by its finite scalar center: on $W_k$, $\rho (\zeta I)={\zeta }^{k}I$ for ${\zeta }^m=1$. The displayed extension is independent of the scalar-root choice and is a group homomorphism. A matrix coefficient of $\rho {|}_{W_k}$ can be represented on $S{L}_m$ by a sum of homogeneous polynomials $P_d$ with $d\equiv k(\mathrm{mod}m)$, by averaging over the scalar center. Its extension is ${\sum }_d(\det g{)}^{(k-d)/m}{P}_d(g)$, a regular function on $G{L}_m$. Every invariant subspace remains invariant under this extension, so irreducibility is preserved in both directions.

The irreducible rational $G{L}_m$ modules are $D_{\lambda }(V)=(\det V{)}^{{\lambda }_m}\otimes D_{\lambda -{\lambda }_m(1,\dots ,1)}(V)$. The second factor is a Schur module. Clearing determinant denominators reduces completeness to the Schur algebra classification of polynomial modules. Distinct dominant integer tuples have distinct highest torus weights. Their characters are symmetric Laurent polynomials; only polynomial modules have characters defined at every singular endomorphism.

For a dominant integer tuple $\lambda$, choose $k=\max (0,-{\lambda }_m)$ and define $D_{\lambda }={\det }^{-k}\otimes D_{\lambda +k(1,\dots ,1)}$, using the polynomial Schur module on the right. The alternant character formula for the general linear group shows that a larger admissible shift yields the same irreducible representation.

A quadratic homogeneous polynomial in the fibre variables of the cotangent bundle is a first integral of the geodesic Hamiltonian exactly when its symmetric lowered coefficients form a rank-two Killing tensor. For $v=g^{-1}p$, the Poisson bracket is $\{K,H\}={\nabla }_{(a}{K}_{bc)}{v}^a{v}^b{v}^c$, so the equivalence follows by comparing cubic coefficients at every point.

An undirected graph may have repeated edges. Choosing an incident edge uniformly gives transition probability equal to the edge multiplicity divided by the vertex degree. Its stationary probability is proportional to degree and its stationary fluxes are symmetric, making it a reversible Markov chain.

When a person's latent slope has normal distribution $N({\beta }_1,{\tau }_1^2)$, its $u$th quantile is ${\beta }_1+{\tau }_1{\Phi }^{-1}(u)$. Multiply by an elapsed time to obtain the corresponding latent change quantile. This describes population variation between people; it is distinct from a confidence interval for the mean slope and from a prediction interval that includes measurement error.

For fixed $p\in (0,1)$ and $1\le q_1\le q_2$, the random-cluster measure at $q_1$ stochastically dominates that at $q_2$. In Holley's condition, Bernoulli factors cancel. Put $a=k(S)-k(S\cup T)$ and $b=k(S\cap T)-k(T)$; supermodularity of graph component count gives $b\ge a\ge 0$, and the weight ratio is $(q_2/q_1{)}^a{q}_2^{b-a}\ge 1$. The comparison also holds with the same boundary wiring in both measures.

The threshold for the origin to have an infinite percolation cluster under a consistently chosen infinite-volume random-cluster measure, conventionally the wired measure: $p_c(q)=\inf \{p:{\theta }^{\mathrm{w}}(p,q)>0\}$. The definition alone makes no assertion about percolation exactly at the threshold.

The multiplicative factor $q$ assigned to each connected component of a graph in a finite random-cluster measure. At fixed edge probability, the weight of a configuration with $k$ components includes $q^k$. For $q=1$ this reduces to independent bond percolation; increasing $q$ at fixed $p$, for $q\ge 1$, suppresses increasing events by random-cluster weight monotonicity.

Every finite positive Borel measure on Euclidean space is inner regular by compact sets and outer regular by open sets. For an open set $U$, the compact sets $\{x:|x|\le n,\mathrm{dist}(x,U^c)\ge 1/n\}$ increase to $U$, so continuity from below of a measure gives inner approximation. The empty complement is handled by compact balls. The class of Borel sets admitting both approximations is closed under complements: interchange inner and outer approximations, then truncate the inner closed set by a large compact ball, using finiteness of the measure. For a countable union, approximate its components from outside with summable errors, and approximate finitely many components from inside after making the remaining union's measure small. Thus this class is a sigma-algebra containing the open sets. In particular, a finite measure carried by a Borel null set has compact subsets of that carrier capturing arbitrarily nearly all its mass.

A rational homogeneous equation ${\sum }_i{a}_i{x}_i=0$ has a monochromatic positive odd solution in every finite colouring of the odd integers exactly when its full coefficient sum is zero. Sufficiency uses a constant odd vector. For necessity, clear denominators and, if the total $S$ is nonzero, colour by odd residue classes modulo $2^K>|S|$. A common odd residue is invertible, so a solution would require $2^K\mid S$, impossible. This is stronger than the zero-sum-subset criterion for unrestricted partition regularity.

On a fiberwise star-shaped neighborhood, let $H_s$ scale fibers by $s$ and let $E$ be the radial vector field. For a closed differential form $\delta$ with zero pullback to the zero section, the homotopy primitive $\eta ={\int }_0^1{s}^{-1}{H}_s^{\ast }({\iota }_E\delta )ds$ satisfies $d\eta =\delta$. For a two-form, it vanishes as an ambient covector along that section, providing the fixed-submanifold condition in the relative Moser theorem.

A pseudo-prior can make model parameter vectors have equal dimensions, allowing identity-matched RJ-MCMC moves. If active and inactive coordinates share the same prior density in the two augmented targets, these factors cancel in model-switch ratios. Within-model updates must preserve the augmented target, including the inactive coordinate's pseudo-prior law.

If two closed subspaces of a Hilbert space give $H=V\oplus W$, the projection onto $V$ along $W$ fixes $V$ and vanishes on $W$. It need not be an orthogonal projection. The bounded inverse theorem applied to the addition map $(v,w)\mapsto v+w$ on the complete component spaces proves boundedness of the component maps. With both complementary subspaces nonzero, its operator norm and that of $I-Q$ equal $\sec {\theta }_{V,W^{\perp }}$, with the directed subspace angle convention. Indeed, for fixed $v\in V$, the smallest possible norm of $v+w$ over $w\in W$ is $\Vert P_{W^{\perp }}v\Vert$, which proves the formula for $\Vert Q\Vert$. Equality with $\Vert I-Q\Vert$ follows from the block representation $Q=\left(\begin{array}{cc}I& B\\ 0& 0\end{array}\right)$ on $V\oplus V^{\perp }$: both squared operator norms are $1+\Vert B{\Vert }^2$. If a summand is zero, $Q$ is zero or the identity operator, and one complementary operator norm is zero; those cases must be treated directly.

The diagonal multiplicative group of a number field is discrete in its idele group. Require local units at every finite place and an archimedean neighbourhood of one. A diagonal element $x$ meeting these restrictions has integral $x-1$. If $x\ne 1$, its nonzero integer field norm cannot have absolute value less than one, while sufficiently small archimedean differences would force exactly that.

For comoving differential number density $n(M)=dn/dM$, the abundance in an order-unity logarithmic mass bin is approximately $Mn(M)$. A characteristic mean spacing is therefore $[Mn(M){]}^{-1/3}$. A cumulative mass fraction cannot replace this number directly; cumulative halo counts require integrating $n(M)$ over mass.

If the linearly extrapolated rms amplitude scales as $\sigma (M)\propto M^{-s}$, a fixed peak-height cutoff in the Press-Schechter halo mass function has $M_{\ast }\propto D^{1/s}$, where $D$ is the linear growth factor. The differential prefactor scales as $M^{s-2}$ and the exponential argument as $M^{2s}$. The cutoff convention must be stated when fixing its absolute normalization: $\nu =1$ and ${\nu }^2/2=1$ select different masses, although their redshift scaling is the same.

A polynomial regression of degree two is linear in its unknown regression coefficients despite being curved in the predictor. Its design matrix has columns $1,x,x^2$; three distinct predictor values give full column matrix rank.