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For a bounded simply connected domain $D$ and a conformal bijection $f:\mathbb{D}\to D$, $f$ extends continuously to the closed disc if and only if $\partial D$ is a locally connected space. A Jordan boundary gives a homeomorphism of closed discs, but local connectedness alone need not give injectivity on the boundary: a slit has two boundary approaches. The same statement applies on the sphere to unbounded domains after a suitable change of coordinates. This boundary theorem is different from the Caratheodory extension theorem for measures.

For a stratified parallel shear flow, the gradient Richardson number compares the squared buoyancy frequency with squared vertical shear. The Miles–Howard theorem excludes exponentially growing inviscid normal modes when this ratio is at least $1/4$ everywhere. Where $U^{\prime }=0$, the equivalent criterion is written directly as $N^2\ge (U^{\prime }{)}^2/4$.

For $Y\sim N(X\beta ,V_{\theta })$ and a full-column-rank design matrix $X\in {\mathbb{R}}^{n\times p}$, take $A\in {\mathbb{R}}^{n\times (n-p)}$ with $A^{T}A=I$ and $A^{T}X=0$. Then $A^{T}Y\sim N(0,A^T{V}_{\theta }A)$, so restricted maximum likelihood maximizesChanging the orthonormal basis by an orthogonal matrix leaves this expression unchanged.

The order-s restricted isometry constant is the smallest nonnegative $\delta$ satisfying $(1-\delta )\Vert x{\Vert }_2^2\le \Vert Ax{\Vert }_2^2\le (1+\delta )\Vert x{\Vert }_2^2$ for every vector with at most $s$ nonzero coordinates. Equivalently it is ${\max }_{|S|\le s}\Vert A_S^{\ast }{A}_S-I{\Vert }_{2\to 2}$. The sparse-vector quantifier is essential, and the constant can equal zero.

Suppose $J$ is nonnegative and sequentially lower semicontinuous, and its sublevel sets are strongly sequentially compact. For a solvable exact equation $Au=f$, every sequence of residual-method minimizers with $\delta \to 0$ has a strongly convergent subsequence, and every limit is a J-minimizing solution. Indeed, comparison with an exact penalty minimizer bounds all reconstructions in one compact sublevel set; the residual bound gives $\Vert A{u}_{\delta }-f\Vert \le 2\delta$. Continuity of $A$ and lower semicontinuity of $J$ identify each subsequential limit as an exact minimizer. Thus the distance to a set of exact penalty minimizers tends to zero. Uniqueness of the exact minimizer upgrades this to full strong convergence.

Uniqueness cannot be omitted: for $A=0$, $f_{\delta }=f=0$, and $J(u)=\max \{|u|-1,0\}$ on $\mathbb{R}$, the sublevel sets are compact intervals but the minimizers $u_{1/k}=(-1{)}^k$ do not converge.

A roughness penalty penalizes variation of derivatives, such as $\int (m^{\prime \prime }{)}^2$. The second-derivative penalty vanishes precisely on affine functions and is represented in a chosen basis by a roughness penalty matrix.

For $\lambda \ge 0$, a full-column-rank design matrix $B$, and a positive semidefinite matrix $\Omega$, minimize $\Vert y-B\beta {\Vert }^2+\lambda {\beta }^T\Omega \beta$. Differentiation gives $(B^{T}B+\lambda \Omega )\hat{\beta }=B^{T}y$. The fitted-value matrix is $B(B^{T}B+\lambda \Omega {)}^{-1}{B}^T$, whose trace measures the effective degrees of freedom.

The Möbius line bundle over the circle iswith projection to $t$ modulo $2\pi$. It is a smooth rank-one vector bundle. A section is represented by a function $s$ satisfying $s(t+2\pi )=-s(t)$, so the intermediate value theorem forces every continuous section to vanish somewhere. Thus it has no nowhere-zero section and is not isomorphic to the trivial vector bundle of rank one.

For a degree-$N$ rational map, the angular Jacobian of a rational map has average $N$, so the Cauchy-Schwarz inequality gives $\mathcal{I}\ge N^2$. In dimensionless Skyrme model units the radial energy within the rational-map ansatz isFirst minimize $\mathcal{I}$ over admissible maps, then minimize over profiles with $f(0)=\pi$, $f(\infty )=0$. This gives a restricted variational approximation and an upper bound on the unrestricted minimum in that topological sector, not an exact multi-Skyrmion solution. Houghton, Manton and Sutcliffe developed this construction in arxiv.org/abs/hep-th/9705151.

For a random walk with independent and identically distributed random variables as increments and finite moment-generating function at $\theta$, put $\kappa (\theta )=\log \mathbb{E}{e}^{\theta X_1}$. Then $e^{\theta S_n-n\kappa (\theta )}$ is a martingale by conditioning on the next independent increment. In particular, if $r>0$ and $\mathbb{E}{r}^{X_1}=1$, then $r^{S_n}$ is a martingale. Stopping at a finite interval exit can make this process bounded, allowing the dominated convergence theorem to justify passage from bounded stopping times to the exit time.

For a centered real Gaussian random variable $\varphi$, its characteristic function gives $\mathbb{E}{e}^{i\varphi }=\exp [-\mathrm{Var}(\varphi )/2]$. Applied to a random phase screen, this controls the coherent and diffuse wave fields.

A random slope multiplies a predictor by a group-specific latent coefficient. With $b_j\sim N(0,{\tau }^2)$, a contribution $b_j{t}_i$ induces covariance ${\tau }^2{t}_i{t}_k$ for two observations in group $j$. A random slope does not necessarily include a random intercept.

Random effects are crossed when an observation can belong to levels of two grouping factors without one grouping factor being nested within the other. Independent location intercepts and incubator slopes, for example, contribute separate terms to the observation covariance matrix.

Time is divided into slots, and a slot succeeds exactly when one station transmits. With backlog $N$ and independent attempt probability $p$, the success probability is $Np(1-p{)}^{N-1}$. Fluid approximation of slotted ALOHA replaces the large-system binomial probabilities by Poisson probabilities.

A thin radiative envelope with constant enclosed mass, luminosity and mean molecular weight, ideal gas pressure and opacity $\kappa ={\kappa }_0{\rho }^n{T}^{-s}$ has $a=n+1$, $b=n+s+4$, and $C=16\pi a_{\mathrm{rad}}cGM/[3{\kappa }_0(\mu m_u/k_B{)}^{n}L]$. Combining radiative diffusion in a star with hydrostatic equilibrium gives ${\nabla }_{\mathrm{rad}}=P^a/(C{T}^b)$, so $P^a-P_0^a=(aC/b)(T^b-T_0^b)$ for nonzero exponents. Zero exponents give logarithmic limits. The model must be stopped or modified if the Schwarzschild criterion predicts convection.

A constant radiative-diffusion coefficient and constant gravity give $T^4=T_0^4+4AP/g$. Thus ${\nabla }_{\mathrm{rad}}=AP/(g{T}^4)<1/4$ for $T_0>0$. A diatomic ideal gas has adiabatic temperature gradient $2/7$, so this idealized profile never becomes convective. A physical radiative-convective boundary requires additional opacity, flux, or thermodynamic variation.

Assume a thin disk has height-independent opacity ${\kappa }_{\mathrm{op}}$ and radiation-to-gas pressure ratio $\beta$, with vertical gravity $-{\Omega }_z^{2}z$. Hydrostatic equilibrium and radiative diffusion implyBalancing its derivative against viscous heating $\rho \nu q^2{\Omega }^2$ fixes the dynamic viscosityIt is independent of height under these assumptions. For a spherically symmetric potential, ${\Omega }_z=\Omega$. Integrating $\rho \nu$ through the full surface-to-surface thickness $2H$ gives $\bar{\nu }\Sigma =2H\rho \nu$, which determines the thickness from the radial accretion rate solution.

The zero-kick circular-parent threshold is $\beta =1/2$: below it grains are initially bound, at it their conservative release orbit is parabolic, and above it they are initially unbound. Poynting–Robertson drag can modify a marginal orbit, so the threshold is a statement about the instantaneous release orbit, not an exact capture criterion with dissipation included.

For spanning slab normals, apply the maximum of finitely many Rademacher linear forms bound to $u_i=(V{\Lambda }^{1/2}{)}^T{a}_i$, whose squared norms are $a_i^{T}X{a}_i\le 1$. Some sign vector has scaling denominator squared at most $2\log (2m)$. Rademacher rounding for a semidefinite relaxation then produces a feasible vector of squared norm at least the displayed fraction of the SDP optimum. This is an existence guarantee from the probabilistic method.

For independent Rademacher random variables and $\Vert u_i{\Vert }_2\le 1$, this bound holds for $\alpha >0$. The moment-generating function satisfies ${\prod }_j\cosh (t{u}_{ij})\le e^{t^2/2}$, with strict inequality for a nonzero vector and $t>0$. Applying the exponential Markov bound to both tails and then the union bound proves a strict failure bound; a zero vector has failure probability zero. At $\alpha =\sqrt{2\log (2m)}$, the success probability is strictly positive, ensuring a sign vector with all linear forms below that threshold.