For nonconserved order-parameter dynamics, the positive kinetic coefficient $\Gamma$ converts the functional derivative of the free energy into a relaxation rate through $\dot{p}=-\Gamma \delta F/\delta p$. Microscopic reversibility fixes the accompanying Gaussian white noise variance by the Model A fluctuation-dissipation relation.

Simultaneously varying a metric tensor and a scalar field by the Lie derivative along a compactly supported vector field leaves a covariant matter action invariant. Integration by parts gives the displayed Noether identity. It implies stress-energy conservation when the scalar equation holds without needing to impose the metric field equation.

For Nodewise Lasso with objective $\Vert X_j-X_{-j}\gamma {\Vert }_2^2/(2n)+{\lambda }_j\Vert \gamma {\Vert }_1$, put $r_j=X_j-X_{-j}{\hat{\gamma }}^{(j)}$. Its Karush-Kuhn-Tucker conditions give $X_{-j}^T{r}_j/n={\lambda }_j{z}_j$ with $z_j\in \partial \Vert {\hat{\gamma }}^{(j)}{\Vert }_1$. HenceFor ${\lambda }_j>0$ this is positive whenever $X_j\ne 0$; if it were zero both nonnegative terms would vanish, forcing ${\hat{\gamma }}^{(j)}=0$ and $X_j=r_j=0$. Nonzero columns are therefore an essential hypothesis for division by this quantity.

An Anosov surface homeomorphism has nonsingular invariant expanding and contracting foliations. In the closed orientable surface setting it occurs on the torus, with a hyperbolic integral linear model.

A periodic surface homeomorphism has a positive power equal to the identity. A mapping class is periodic when it has such a representative. Allowing motion of boundary circles is a different convention from requiring every isotopy to fix the boundary pointwise.

A flattened power-law Newtonian gravitational potential has equipotential spheroids $R^2+{\lambda }^2{z}^2=\text{constant}$. For ${\Phi }_0<0$ and $0<\beta <1$, its midplane circular orbit angular frequency satisfies ${\Omega }^2=-\beta {\Phi }_0{R}_0^{\beta }{R}^{-\beta -2}$.

If a monic degree-$n$ polynomial over a discretely valued field with normalized valuation has all its roots of valuation $a/n$, where $\gcd (a,n)=1$, then it is irreducible. Each irreducible factor of degree $d$ has constant term of valuation $da/n\in \mathbb{Z}$, forcing $n\mid d$. Equivalently, a single Newton polygon segment of relatively prime horizontal and vertical lengths gives irreducibility.

For either tensor helicity, neutrino free streaming produces the memory equationThe neutrino tensor free-streaming kernel encodes the angular propagation of the perturbation. Energy transferred to neutrino directional anisotropy damps the oscillation amplitude of a gravitational wave after horizon entry. This effect was calculated by Weinberg.

Projecting free-streaming neutrinos onto the tensor spherical harmonic givesHere $j_2$ is a Spherical Bessel function. The continuous value at zero follows by integrating $(1-{\mu }^2{)}^2$, whose integral is $16/15$.

For independent studies comparing treatments $A$ and $B$ to common control $C$, a consistent log odds ratio comparison uses ${\hat{\delta }}_{AB}={\hat{\delta }}_{AC}-{\hat{\delta }}_{BC}$, with variance $v_{AC}+v_{BC}$. This follows from subtracting two estimates of additive effects relative to the same reference. With overlapping evidence, subtract twice their covariance. Causal comparability across the studies is supplied by transitivity in network meta-analysis, not by the variance calculation.

For independent and identically distributed random variables with continuous distance distribution function $p_x$, the probability integral transform makes the probability content of the order-$k$ nearest ball a uniform order statistic, with the Beta distribution $\mathrm{Beta}(k,n+1-k)$.

A linear N-term approximation fixes its index set independently of the approximated function. Wavelet approximation normally orders by increasing resolution, whereas Fourier series approximation normally keeps the lowest frequencies. An arbitrary reordering can change or destroy a claimed convergence rate.

The best N-term approximation in an orthonormal basis retains $N$ coefficients of greatest absolute value. It minimizes the squared Hilbert space error over all index sets of size at most $N$. The selection makes the approximation nonlinear in the data, even though coefficient extraction is linear.

For constant phase mass densities ${\rho }_s,{\rho }_l$, a fixed solid framework has mixture density $\bar{\rho }={\rho }_s\phi +{\rho }_l(1-\phi )$. Mass conservation giveswhere $\mathbf{u}$ is Darcy flux. Equal phase densities give a divergence-free flux. Unequal densities require expansion or contraction flow during freezing or melting.

The solid fraction is the volume fraction occupied by solid in a solid–liquid mixture. The complementary liquid fraction is $1-\phi$.

A scaling function generates the approximation space $V_0$ of a multiresolution analysis by its integer translates. In an orthonormal construction those translates form an orthonormal basis, and ${\phi }_{j,k}(x)=2^{j/2}\phi (2^{j}x-k)$ generate $V_j$. Integrable orthonormal scaling functions have $|\hat{\phi }(0)|=1$, as follows from density and the MRA projection Fourier identity.

For a fixed-step multiderivative multistep method, the ordinary zero-stability root condition still controls propagation of the starting errors when all derivative evaluation maps are uniformly Lipschitz continuous on the relevant bounded region. A local defect $O(h^{p+1})$ then yields global error $O(h^p)$ over a fixed time interval, provided the starting errors are $O(h^p)$ and the implicit updates use the nearby solution branch.

For example, writing the numerical error equation as $\rho (E)e_n=h{F}_h(e_{n+s})+d_n$, with $F_h$ uniformly Lipschitz continuous, a bounded impulse response for the root condition for a multistep method givesAbsorbing the last current-step term for small $h$ and applying the discrete Gronwall inequality gives the stated order. The higher derivatives enter through $F_h$, whose bound stays uniform as $h\to 0$.

Invertibility permits reconstruction of innovations from present and past observations by a stable filter. For $Y_t-\mu ={\epsilon }_t+\theta {\epsilon }_{t-1}$, $|\theta |<1$ gives ${\epsilon }_t={\sum }_{j\ge 0}(-\theta {)}^j(Y_{t-j}-\mu )$. This is a different property from stationarity: a finite moving-average model is stationary for every finite coefficient.

For a nonconstant morphism between nonsingular curves and a local target uniformizer $t$ at the image of $P$, the index is the order of vanishing of its pullback. Changing $t$ multiplies it by a local unit in a ring and does not change that order. This is a valuation definition and remains meaningful for inseparable morphisms.

For an unbounded nondecreasing function $f:[0,\infty )\to \mathbb{R}$, its strict generalized inverse is $G(a)=\inf \{t\ge 0:f(t)>a\}$. It is nondecreasing and right-continuous in $a$. If $a_n\downarrow a$, then for any $t>G(a)$ monotonicity gives $f(t)>a$, so eventually $f(t)>a_n$ and $G(a_n)\le t$; also $G(a_n)\ge G(a)$. Local finiteness gives finite left limits. Flat parts of $f$ create jumps of $G$. For the continuous running maximum of Brownian motion, this gives the càdlàg Brownian first-passage subordinator.