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On a closed oriented Riemannian manifold of dimension four, the Hodge star operator preserves harmonic two-forms and splits them into orthogonal spaces ${\mathcal{H}}^{+}$ and ${\mathcal{H}}^{-}$ with eigenvalues $+1$ and $-1$. The real de Rham intersection form in dimension four equals the positive $L^2$ inner product on ${\mathcal{H}}^{+}$ and its negative on ${\mathcal{H}}^{-}$. It is nondegenerate, since $Q(h,\ast h)=\Vert h{\Vert }_2^2$. Its signature pair is $(\dim {\mathcal{H}}^{+},\dim {\mathcal{H}}^{-})$.

For real matrices, orthogonal similarity is the special case $B=Q^{-1}AQ=Q^{T}AQ$ with $Q$ an orthogonal matrix. Then a symmetric matrix remains symmetric, because $B^T=Q^T{A}^{T}Q=B$. The expression $QA{Q}^T$ describes the reverse conversion and has the same property. An orthonormal basis retains the ordinary dot product formula for its coordinate vectors.

An arbitrary change of basis need not preserve entrywise symmetry. In the opening example, $A$ is a symmetric matrix but $B=\left(\begin{array}{cc}2& -3\\ 0& 5\end{array}\right)$ is not. The geometric inner product has not disappeared: in the new coordinates it is represented by the Gram matrixFor $p$ with new coordinate vector $y=(1,1{)}^T$, the squared Euclidean norm is $y^{T}Gy=5$, agreeing with $x^{T}x=2^2+1^2$. The naive coordinate sum $y^{T}y=2$ would use the wrong inner product.

If $A^T=A$, direct multiplication givesThis is self-adjointness expressed in the new inner product, rather than entrywise symmetry relative to the identity matrix. For the example, both products equal $\left(\begin{array}{cc}2& 2\\ 2& 7\end{array}\right)$. Thus arbitrary matrix similarity preserves the linear operator, while its geometric interpretation requires transforming the Gram matrix as well. Matrix congruence supplies the corresponding rule for a bilinear form and should be distinguished from matrix similarity.

Consider ordinary least squares with an intercept, one nonconstant predictor, $n>2$ cases, $S_{xx}={\sum }_i(x_i-\bar{x}{)}^2>0$ a nonconstant response, and a positive residual sum of squares. With the usual common-variance standard error, put $s^2=\mathrm{RSS}/(n-2)$. ThenThe least-squares normal equations give zero residual sum and zero residual inner product with the centred predictor, proving the first identity and $\hat{\beta }=S_{xy}/S_{xx}$. The fitted centred sum of squares is ${\hat{\beta }}^2{S}_{xx}$. Dividing it by $s^2$ gives the one-predictor F statistic and the squared zero-slope t statistic. Dividing fitted and residual sums of squares by their total gives the last expression. If $0\le R^2<1$, the adjusted coefficient of determination is $1-(1-R^2)(n-1)/(n-2)$.

These are algebraic consistency identities for one specified fit; the mean identity needs no normal-error assumption. A normal linear model supplies the usual finite-sample t and F reference distributions. Heteroscedasticity-robust standard errors need not satisfy the displayed F=t-squared relationship to the classical sums-of-squares F statistic. Rounding can create small discrepancies, while different analysed records or a changed model can create larger ones; neither should be silently treated as the same fit.^[ref]

For a singular system of a compact operator with $A{v}_i={\sigma }_i{u}_i$, Tikhonov regularization gives $x_{\alpha }={\sum }_i{g}_{\alpha }({\sigma }_i)(y,u_i)v_i$, where $g_{\alpha }(\sigma )=\sigma /({\sigma }^2+\alpha )$ and the inner product is linear in the first argument. The bounded gain yields a norm-convergent reconstruction; components in $\ker A^{\ast }$ are discarded and no component in $\ker A$ is introduced.

For a strictly positive Dirichlet realization of an elliptic operator with smooth coefficients and smooth boundary, put $X_0=L^2(U)$. For each integer $k\ge 1$,These are the domains $D(A_D^{k/2})$, with norms equivalent to the indicated Sobolev space norms. The bilinear forms $((u,v){)}_{2l}=(L^{l}u,L^{l}v{)}_{L^2}$ and $((u,v){)}_{2l+1}=B[L^{l}u,L^{l}v]$ are inner products on $X_{2l}$ and $X_{2l+1}$. The higher boundary conditions are essential: for $L=-d^2/d{x}^2$ and $u=x(\pi -x)$, $u$ is smooth and zero at the boundary but $L^{2}u=0$, so $\Vert L^{2}u{\Vert }_2$ is not a norm on all of $H^4\cap H_0^1$. Repeated elliptic regularity proves $A_D:X_{k+2}\to X_k$ is an isomorphism, which gives the norm equivalence inductively from $X_0$ and $X_1=H_0^1$.

The displayed inner product on the first-order Sobolev space induces its usual Sobolev norm. A continuous reaction-diffusion weak formulation with unit diffusion and unit reaction has this exact bilinear form, so its conforming Galerkin method gives a best approximation with constant one in the first-order Sobolev norm.

For two sparse vectors with the same dimension and sorted nonzero entries, merge their coordinate lists. Equal indices contribute their product and advance both cursors. If one index is smaller, advance only that cursor: the other vector has zero at that coordinate, because all its smaller indices have already been processed and all remaining indices are larger. This proves a loop invariant consisting of the accumulated inner product over settled indices. Every iteration consumes at least one stored entry, giving time complexity $O(k_x+k_y+1)$ and constant auxiliary space for $k_x,k_y$ nonzero entries. The method avoids work proportional to the ambient dimension. Its floating-point arithmetic error remains distinct from its exact algorithm correctness.

For a positively oriented basis $\mathbf{a},\mathbf{b},\mathbf{c}$, put $\tau =\mathbf{a}\cdot (\mathbf{b}\times \mathbf{c})>0$. The center of an interior sphere at distance $r$ from each of the three tetrahedron face planes through the origin has the displayed expression. The three inward unit vectors are the normalized cross products $\mathbf{b}\times \mathbf{c}$, $\mathbf{c}\times \mathbf{a}$, $\mathbf{a}\times \mathbf{b}$. Taking inner products with these vectors solves three independent signed-distance equations. Reversing some signs instead produces centers on exterior sides. Existence of a sphere contained in the full tetrahedron also requires clearance from the fourth face.

For a state initially $z$-up and precessing about $y$, measurement along $\mathbf{n}=(0,\sin \theta ,\cos \theta )$ has the displayed probabilities. eigenvectors can be chosen as $(\cos (\theta /2),i\sin (\theta /2){)}^T$ and $(i\sin (\theta /2),\cos (\theta /2){)}^T$. Their phases must be retained when taking inner products. Full $2\pi$ rotation changes their signs but leaves isolated-state probabilities unchanged.

Prepare the $J_1=+\hslash$ spin coherent state and evolve with Hamiltonian operator $H=\omega J_3$ for time $t$. In the descending-$J_3$ basis of the spin-one angular momentum matrices, the initial vector is $(1,\sqrt{2},1{)}^{\mathsf{T}}/2$ and the evolved vector is $(e^{-i\theta },\sqrt{2},e^{i\theta }{)}^{\mathsf{T}}/2$, where $\theta =\omega t$. The $J_1$ orthonormal basis has vectors $(1,\sqrt{2},1{)}^{\mathsf{T}}/2$, $(1,0,-1{)}^{\mathsf{T}}/\sqrt{2}$ and $(1,-\sqrt{2},1{)}^{\mathsf{T}}/2$. Taking their inner products with the evolved vector gives probability amplitudes $(1+\cos \theta )/2$, $-i\sin \theta /\sqrt{2}$ and $(\cos \theta -1)/2$. Their squared moduli give the Born rule probabilities in the title. At integer half-turns $\theta =\pi k$, the outcome is deterministically $(-1{)}^k\hslash$.

When spatial and spin factors separate, a spin orbital combines a spatial orbital ${\varphi }_a$ with a normalized spin state ${\chi }_{\sigma }$. For an electron, choose spin one-half along an axis with $\sigma =\uparrow ,\downarrow$. The two spin orbitals $u_{a\uparrow }$ and $u_{a\downarrow }$ are orthogonal even though their spatial orbital is identical, since their inner product contains $⟨{\chi }_{\uparrow }|{\chi }_{\downarrow }⟩=0$. When spatial and spin variables do not separate, the complete one-particle state is instead a multicomponent wavefunction $u(\mathbf{r},s)$; exclusion still applies to that complete quantum state.

A semisimple Lie algebra over a field of characteristic zero is split if it has a Cartan subalgebra whose adjoint action is simultaneously diagonalizable over that field. Its root-space decomposition then needs no extension of scalars. The sl2R Lie algebra is split, with the real diagonal Cartan subalgebra. The real special unitary Lie algebra $\mathfrak{su}(2)$ is not: its adjoint operators are skew-adjoint for the positive definite inner product obtained by negating its Killing form. Thus a split adjoint operator would have to be zero.

On the C-star algebra of convergent complex sequences, a functional in the displayed coordinate representation is a state on a C-star algebra exactly when all its weights are nonnegative and sum to one. Coordinate projections test positivity of $w_j$ at finite indices. Positive sequences with the first $N$ terms zero and the rest one test $w_{\infty }$ after passage to the limit. The known dual isometry makes the norm the sum of the absolute weights, proving necessity and sufficiency.

If only finitely many weights are positive, the GNS construction identifies the quotient by $\{\alpha :F({\alpha }^{\ast }\alpha )=0\}$ with the values at precisely those supporting indices. Its inner product is the weighted coordinate inner product. Passing to the standard Hilbert norm gives diagonal evaluation operators and cyclic vector whose entries are the square roots of the weights. Arbitrary finite coordinate values and the limiting value can be assigned independently by a convergent sequence, which proves cyclicity. For weights $1/2$ at infinity and $1/4$ at each of the first two indices, the space is ${\mathbb{C}}^3$ and the cyclic vector is $(1/\sqrt{2},1/2,1/2)$.

The sudden approximation treats a rapid, finite change of a Hamiltonian operator as leaving the quantum state approximately unchanged during the switch. The energy measurement can nevertheless change immediately: the same quantum state has different probability amplitudes in the new eigenbasis. Compute their inner products with the new energy eigenstates, then apply the Born rule. The two-level sudden quench below makes this distinction quantitative without assuming the change is small.

An ideal finite step has exact quantum state continuity at a finite Hamiltonian step; a finite-duration implementation has a small evolution error under the bounded-model conditions below. An impulsive quantum kick is different: its Hamiltonian operator grows as its duration shrinks, retaining a finite integrated action and a finite change of quantum state. A sudden approximation therefore concerns short evolution during switching, not conservation of energy during externally driven change. The subsequent unitary time evolution can be substantial.^[ref]

Let $S$ be a real symmetric positive definite matrix, $C>0$ and $q\ne 0$. The Cauchy-Schwarz inequality in the $S$-weighted inner product gives $q^{T}x=(S^{-1}q{)}^{T}Sx\le \sqrt{q^T{S}^{-1}q}\sqrt{x^{T}Sx}$. Equality is attained by a positive multiple of $S^{-1}q$. Thus the displayed maximum holds. For a translated ellipsoid, add $q^{T}a$ for its centre $a$. This computes a coordinate extremum without constructing a rotation matrix.

A real matrix is symmetric when $A^T=A$. It represents a self-adjoint operator in the standard Euclidean inner product.

Let $A$ and $M$ be real symmetric positive-definite matrices. The principal square root of a positive semidefinite matrix construction gives an invertible matrix for each. SetThen $Ax=b$ is equivalent to $By=c$. This is a matrix congruence, and $B$ is a symmetric positive-definite matrix: $B^T=B$, and for every nonzero vector $v$,since $S^{-1}v\ne 0$. This short proof establishes both requirements for applying the conjugate gradient method to the transformed linear system.

The left transformed matrix has the same eigenvalues becauseIts correct geometry uses the weighted inner product $⟨u,v{⟩}_M=u^{T}Mv$: $⟨u,M^{-1}Av{⟩}_M=u^{T}Av=⟨M^{-1}Au,v{⟩}_M$. Thus it is symmetric in this inner product, even when it is not a symmetric matrix in ordinary coordinates. The spectral condition number governing the transformed symmetric problem is ${\kappa }_2(B)$, not generally ${\kappa }_2(M^{-1}A)$.

The Preconditioned conjugate gradient method realizes this transformation using auxiliary solves $M{z}_k=r_k$, without constructing $S$ or its matrix inverse. With fixed $M$, initialize $r_0=b-A{x}_0$ and $p_0=z_0$; while $r_k\ne 0$, usethen solve $M{z}_{k+1}=r_{k+1}$ and setStop at a zero linear-system residual before forming another ratio. Positive definiteness makes the denominators positive before termination.^[ref]

An invertible matrix alone is insufficient: with $A=I$ and $M=\mathrm{diag}(-1,1)$, the left transformed matrix has eigenvalues $-1,1$, and $M$ has no real symmetric positive-definite matrix square root. Even a valid symmetric positive-definite matrix can worsen conditioning if its scaling is unsuitable, as the next worked example shows.

Symmetrize the $p$ upper and $q$ lower indices separately, and remove every upper-lower trace. The resulting representation has highest weight $p{\omega }_1+q{\omega }_2$. Its dimension isThe subtraction is valid because contraction is onto: in the polynomial realization its adjoint, for the monomial-factorial inner product, is multiplication by the nonzero polynomial ${\sum }_i{x}_i{y}_i$, an injective map. The resulting kernel contains the highest-weight constituent and has precisely its Weyl dimension formula dimension, hence is irreducible. This highest-weight constituent is not always the largest-dimensional constituent of the full mixed tensor.

Let $s=r(1-r)$ and $p=r(1-r^2)$. Under reflection $r\mapsto 1-r$, $s$ is symmetric and $p=(3/2)s+a$, where $a=r(1-r)(r-1/2)$ is antisymmetric. Their cross terms vanish in both the $L^2$ inner product and the Dirichlet energy form: each integrand is odd about the midpoint. Their separate Rayleigh quotients are $R[s]=10$ and $R[a]=42$. Thus every quotient on their two-dimensional span is a positive weighted average of ten and forty-two, so the minimum remains ten. Adding a direction with the wrong symmetry need not improve the ground-state estimate.

The symmetric quartic $s^2=r^2(1-r{)}^2$ does add a useful direction. On the span of $s,s^2$, the generalized eigenvalue problem has stiffness matrix $K=\left(\begin{array}{cc}1/3& 1/15\\ 1/15& 2/105\end{array}\right)$ and mass matrix $M=\left(\begin{array}{cc}1/30& 1/140\\ 1/140& 1/630\end{array}\right)$. Its least eigenvalue is $56-4\sqrt{133}\simeq 9.86974962$, close to the exact Dirichlet ground value ${\pi }^2$. This is an explicit useful enlargement of a polynomial Rayleigh-Ritz trial space for a one-dimensional box.

For a family $\mathcal{F}$ of real-valued functions on a finite set and normalized inner product $⟨\cdot ,\cdot ⟩$, the test-function seminorm isIt measures the largest correlation of $g$ with an allowed test. It is a seminorm, and becomes a norm when the tests separate points.