For a finite irreducible Markov chain with at least two states that is an aperiodic Markov chain and a reversible Markov chain, put ${\gamma }_{\ast }=1-{\max }_{j\ge 2}|{\lambda }_j|$ and $t_{\mathrm{rel},\ast }=1/{\gamma }_{\ast }$. This is the reciprocal of the absolute L2 spectral gap of a reversible Markov chain. It agrees with the reciprocal of the ordinary spectral gap $1-{\lambda }_2$ for a lazy Markov chain, but need not agree when there are negative eigenvalues.

Dualize the relative tautological line bundle to obtain the positive relative hyperplane line bundle. It restricts to $\mathcal{O}(1)$ on each projective fibre. This sign depends on the convention that projectivization parametrizes lines; fixing the convention avoids confusing it with the tautological line itself.

For multiplicative resource-price dynamics with positive capacities, nonempty routes and strictly positive initial prices, full row rank of the link-route incidence matrix makesstrictly concave. There is a unique optimizing price vector, possibly on the boundary, and the relative-entropy Lyapunov function for resource prices proves convergence to it. Row-rank deficiency still gives unique optimal route prices and rates, but resource prices may depend on the initial state. Full column rank alone and unrestricted zero initial prices do not yield the same uniqueness theorem.

For a compact H-hull inside the disc of radius $r$ centred at a real point, its mapping-out function of a compact H-hull displaces every point of its domain by at most $3r$. After scaling and translation, the real boundary bounds for a unit-disc H-hull put the corresponding inverse boundary interval inside $[-2,2]$. Boundary cluster points of the inverse over this interval lie in the unit disc. The maximum modulus principle applied to $w-g_K^{-1}(w)$ gives the bound without assuming local connectedness of the hull. The nearly closed semicircular slit makes the constant three sharp.

Cancel the common polynomial factors of $p$ and $q$ before computing the degree of a rational map of the Riemann sphere. Removable common zeros do not contribute sheets. The reduced maximum polynomial degree is the number of inverse images of a generic target value, counted with positive holomorphic local degrees.

For finite irreducible Markov chains that are aperiodic Markov chains and reversible Markov chains, the ratio definition of cutoff and $T_n=t_{\mathrm{mix}}^{(n)}(1/4)\to \infty$ imply the Peres product condition, with ${\gamma }_n=1-{\lambda }_{2,n}$. If ${\gamma }_n{T}_n\le B$ on a subsequence, then ${\gamma }_{\ast ,n}\le {\gamma }_n$ and the eigenvalue lower bound for total variation mixing giveFor sufficiently small fixed $\epsilon$, this contradicts the limit one forced by cutoff for Markov chains. The same argument proves the stronger conclusion ${\gamma }_{\ast ,n}{T}_n\to \infty$.

The boundary partition has singleton blocks, so no different boundary vertices are identified. Open component counting is the ordinary counting in the finite graph, including isolated vertices. This is the least wired random-cluster boundary condition.

All boundary vertices are identified into one vertex for component counting. This is the most wired random-cluster boundary condition on a fixed boundary, and maximizes increasing-event probabilities when $q\ge 1$ by boundary monotonicity of the random-cluster measure.

Here $\xi ⪯\zeta$ means each block of $\xi$ lies in a block of $\zeta$, and the measure order is stochastic domination of probability measures. The random-cluster single-edge conditional probability is increasing in both exterior open edges and wiring for $q\ge 1$. Couple two heat-bath Markov chains by identical update edges and uniform random variables, starting from ordered states. Order persists, and convergence of the finite chains to their stationary laws proves the displayed inequality. At $q=1$, the law does not depend on the boundary partition.

For $-5{\Omega }^2<N_r^2<3{\Omega }^2$ and a continuum of vertical wavenumbers, the growing branch of the radially stratified magnetorotational dispersion relation is maximized at $k^2{v}_A^2={\Omega }^2-(N_r^2+{\Omega }^2{)}^2/(16{\Omega }^2)$, with ${\sigma }_{\max }=(3{\Omega }^2-N_r^2)/(4\Omega )$. For $N_r^2\le -5{\Omega }^2$ the optimum moves to the $k\to 0$ boundary and the limiting rate is $\sqrt{-N_r^2-{\Omega }^2}$. For $N_r^2\ge 3{\Omega }^2$ there is no exponential instability. Boundaries that discretize the allowed wavenumbers can alter the actual maximum.

For unit mass and $\hslash =1$, this prepoint kernel tends to the identity and generates the Time-dependent Schrödinger equation. The square-root branch follows the damped Fresnel integral. Its normalized moments are $1$, $0$, and $i\Delta t$ at orders zero, one and two; these fix both the normalization and the kinetic sign.

For a scaling refinement equation $\varphi ={\sum }_n{a}_n\varphi (2\cdot -n)$, set $m(t)=\frac{1}{2}{\sum }_n{a}_n{e}^{-int}$. The quadrature mirror filter identity makes the two rows $(m(t),m(t+\pi ))$ and $(q(t),q(t+\pi ))$ a unitary matrix, where $q(t)=-e^{-it}\overline{m(t+\pi )}$. The complementary coefficients $b_n=(-1{)}^n\overline{a_{1-n}}$ yield $\psi ={\sum }_n{b}_n\varphi (2\cdot -n)$. In a multiresolution analysis, coefficient-space completeness shows its translates form an orthonormal basis of $V_1\ominus V_0$, hence its dilations and translates form an orthonormal wavelet basis of the whole space.

In an abelian category, suppose a commutative square $gf=kh$ is a pullback in a category and $g$ is an epimorphism. Then $(f,h):A\to B\oplus C$ is the categorical kernel of the epimorphism $[g,-k]$. Since an epimorphism is the cokernel of its kernel, any compatible pair $u:B\to X$, $v:C\to X$ induces a unique map $D\to X$ by factoring $[u,-v]$. Hence the square is also a pushout in a category.

For independent multivariate normal observations with unknown mean and nonsingular covariance, profiling the mean at its sample value gives negative log-likelihood proportional to $-\log \det \Omega +\mathrm{tr}(S\Omega )$ over $\Omega \succ 0$. The sample covariance matrix uses divisor $n$. Its minimizer exists exactly when $S\succ 0$, and is then $S^{-1}$.

In a Gaussian graphical model, regressing component $k$ on the others gives the displayed coefficients, residual variance $1/{\Omega }_{kk}$ and intercept ${\mu }_k-{\mu }_{-k}^{\mathsf{T}}{\theta }_{-k,k}$. Opposite directions have identical zero patterns and signs because $\Omega$ is symmetric with positive diagonal, but generally unequal coefficient magnitudes.

A planar Brownian motion starting at $1$ exits the disk of radius $r>1$ before leaving a wedge of opening $\alpha \in (0,2\pi ]$, centered on the positive axis, with probability $(4/\pi )\arctan (r^{-\pi /\alpha })$. The power-map reduction for Brownian exit from a wedge, the reflection identity for Brownian exit from a half-disc and the Möbius calculation of circular Brownian exit give the formula. Its large-radius decay exponent is $\pi /\alpha$.

A symmetric operator $L$ on a real Hilbert space is strictly positive definite when $⟨Lv,v⟩>0$ for every nonzero $v$ in its operator domain. Strict positivity proves uniqueness of a solution of $Lu=f$, but in infinite dimension it need not prove existence for every $f$. A uniformly positive definite symmetric operator additionally has a positive lower bound independent of $v$. Symmetry must be stated separately when positivity is defined only by a real quadratic expression: adding a skew-symmetric matrix changes the operator without changing that expression.

For a bounded Hermitian operator $X$, its positive part of a Hermitian operator isIt is a positive operator whose support is the positive spectral subspace. In a finite-dimensional spectral decomposition, $X_{+}={\sum }_i\max ({\lambda }_i,0)P_i$; the integral definition remains valid without an eigenbasis. Together with the negative part of a Hermitian operator, it obeys $X=X_{+}-X_{-}$, $|X|=X_{+}+X_{-}$ and $X_{+}{X}_{-}=0$.

For a bounded Hermitian operator $X$, its negative part of a Hermitian operator isIt is a positive operator, despite the word negative: its eigenvalues in a finite-dimensional diagonalization are the magnitudes of the negative eigenvalues of $X$. For such a diagonalization, $X_{-}={\sum }_i\max (-{\lambda }_i,0)P_i$. The spectral-integral formula also covers a continuous spectrum without eigenvectors. Its support is orthogonal to the support of the positive part of a Hermitian operator, and $X=X_{+}-X_{-}$.

For a compact oriented submanifold without boundary in an oriented manifold, the normal Thom class gives a compactly supported cohomology class dual to its pushed-forward fundamental class. It is independent of the tubular neighborhood and its ordinary-cohomology image vanishes on the complement of the submanifold. A noncompact submanifold closed only as a subset generally has its dual in ordinary cohomology, using locally finite homology instead.