The solar corona is the Sun's hot, dilute outer atmosphere. Its optically thin atomic lines diagnose temperature, density and composition through collisional-radiative models and ionization balance. Its plasma extends into the solar wind; the coronal approximation describes useful low-density equilibrium limits rather than every coronal condition.

An empty sum has no terms and is defined to be zero, the identity element for addition. This keeps the rule for combining sums valid when one index set is empty. In a Galton-Watson process, an empty generation contributes an empty sum of offspring counts, so the next generation is empty too. The corresponding convention for multiplication is the empty product, which equals one.

The adjacency matrix of a directed graph whose vertices are symbols and whose directed edges are the permitted consecutive pairs. Its entries indicate permission. In comparison, the transition matrix of a Markov chain records transition probabilities.

A fixed point of the $n$th iteration of a map of a subshift of finite type is determined uniquely by its length-$n$ block with a permitted closing transition. Summing the counts of length-$n$ closed walks over their starting symbols gives the displayed trace. This counts points whose least period divides $n$. If $P_n$ counts points of least period exactly $n$, then $\mathrm{tr}(A^n)={\sum }_{d\mid n}{P}_d$, and Möbius inversion gives $P_n={\sum }_{d\mid n}{\mu }_{\mathrm{M}}(n/d)\mathrm{tr}(A^d)$. The number of distinct least-period-$n$ periodic orbits is $P_n/n$.

Set inclusion $C\subseteq D$ means that every set element of the set $C$ also belongs to the set $D$. Strict set inclusion additionally requires $C\ne D$. A maximal clique cannot grow through strict set inclusion, while a maximum clique maximizes cardinality.

In a category with finite limits and a subobject classifier, every monic endomorphism $f$ of $\Omega$ is an involution. The subobject $g:U\hookrightarrow \Omega$ classified by $f$ is subterminal, since $fg=\top {!}_U$ is monic. If $V\hookrightarrow U$ is classified by $g$, pullback uniqueness gives $f\top {!}_U=g$, hence $f^{2}g=g$. If $u$ classifies $U\hookrightarrow 1$, the pullback of $g$ along $f$ is $\top {!}_U$, so $f^2(p)=u\wedge p$. Monicity implies $u=\top$, because $u\wedge u=u\wedge \top$, proving the displayed identity.

In the covariant functor category $[\mathbb{N},\mathbf{Set}]$, the classifier at $n$ consists of thresholds $k\ge n$ and the empty threshold $\infty$. Its transition to $n+1$ sends $k$ to $\max (k,n+1)$. The displayed maps commute with transitions and are all surjective, so define an epimorphism. They identify $n$ and $n+1$, so the endomorphism is not an isomorphism.

An object $A$ in a category with a terminal object is well-pointed when every monomorphism $m:B\to A$ through which all points $1\to A$ factor is invertible. This definition concerns detection of proper subobjects by points, and does not designate a chosen basepoint. If there are no points, it asserts that every subobject is the whole object. In particular, the empty set is well-pointed.

A normal series is a chain $1=G_0\le G_1\le \cdots \le G_r=G$ whose terms are all normal subgroups of the ambient group. A subnormal series only requires each term normal in the next. Confusing these conditions would incorrectly require every term of a composition series to be normal in the full group.

Let $A^{\prime }⊴A$ and $B^{\prime }⊴B$ be subgroups of one group. Put $C=A\cap B$ and $D=(A^{\prime }\cap B)(A\cap B^{\prime })$. Then $D⊴C$ and the first isomorphism theorem identifies bothwith $C/D$. Indeed $C$ maps onto either displayed quotient group, and its kernel in either case is $D$. This gives the matching factors used in the Schreier refinement theorem.

Any two finite subnormal series have refinements with the same successive factors up to ordering and group isomorphism. For descending chains $A_i$ and $B_j$, insert $A_{i+1}(A_i\cap B_j)$ between $A_i$ and $A_{i+1}$ and insert $B_{j+1}(B_j\cap A_i)$ in the other chain. The Zassenhaus butterfly lemma identifies the factor indexed by $(i,j)$ in the first refinement with the factor indexed by $(j,i)$ in the second. If both chains are composition series, their simple factors admit no nontrivial refinement, giving the Jordan–Hölder theorem.

Under the usual filtration conditions, a càdlàg submartingale of Class D on a finite horizon has a unique decomposition into a uniformly integrable martingale and a predictable integrable nondecreasing process starting at zero. A general continuous semimartingale decomposition instead allows an arbitrary continuous finite-variation drift. A convex function of a semimartingale need not be a submartingale when that drift has unrestricted sign.

For a submartingale with ${\sup }_n\mathbb{E}|X_n|=C<\infty$, its positive part is a submartingale by the conditional Jensen inequality. Thus the displayed conditional expectations increase in $p$. Their limits are finite almost surely and have expectations at most $C$, by the monotone convergence theorem. Conditional monotone convergence and the tower property of conditional expectation give $\mathbb{E}[M_{n+1}\mid {\mathcal{F}}_n]=M_n$. Moreover $M_n\ge X_n^{+}$. Consequently $Y_n=M_n-X_n$ is a nonnegative supermartingale, ${\sup }_n\mathbb{E}{Y}_n\le 2C$, and $X=M-Y$. The resulting martingale need not have uniform integrability.

For a sublimating surface with exponentially absorbed volumetric heating, use a frame moving into the solid at speed $V$. Its steady heat equation is $k{T}^{\prime \prime }+\rho c_{p}V{T}^{\prime }+q_0{e}^{-\lambda z}=0$. The surface Stefan condition is $k{T}^{\prime }(0)=\rho LV$. Integrating over the half-space gives the displayed energy-limited speed. The surface gradient is positive, but the far field is colder, so the temperature has a subsurface maximum where melting can begin.

For a locally linear ice temperature with positive gradient $G$ into the solid, a corrugated sublimation front receives a perturbation in heat flux proportional to its horizontal wavenumber $\alpha$. The Gibbs-Thomson effect suppresses short waves, giving the displayed quasi-static growth rate. It requires $V/(\kappa \alpha )\ll 1$ and $|\sigma |/(\kappa {\alpha }^2)\ll 1$, as well as a perturbation depth short enough for the linear background approximation. Unstable modes have $0<\alpha <\sqrt{G/\Gamma }$.

For a subset $W$ of the vertex set of a hypergraph $H$, the induced subhypergraph retains exactly the edges wholly contained in $W$. This is the restriction used by a hereditary hypergraph property; it differs from intersecting every edge with $W$, which can change uniformity.

For locally integrable real $u$ with nonnegative distributional derivative $\Delta u$, its ball means increase with radius. To see this, mollify: for a smooth subharmonic function the derivative of its spherical mean is the integral of $\Delta u$ over the ball divided by the sphere area. The ball means inherit monotonicity; local $L^1$ convergence passes this to $u$. Their decreasing-radius limit exists, may be minus infinity at exceptional points, and equals $u$ almost everywhere by the Lebesgue differentiation theorem. It is upper semicontinuous as an infimum of continuous ball means and satisfies the mean-value inequality. Arbitrary changes of a representative on a null set can destroy its pointwise maximum principle.

A locally integrable real function is superharmonic in the distributional sense if its Laplacian is nonpositive on every nonnegative test function. Equivalently its negative is a subharmonic function. The canonical lower semicontinuous representative satisfies the reverse ball mean inequality. A function both subharmonic and superharmonic has zero distributional Laplacian and a smooth harmonic function representative by the Weyl lemma.

For a countable family of subharmonic functions, a locally integrable pointwise supremum is subharmonic in the distributional derivative sense. Finite maxima preserve subharmonicity: approximate the maximum by the smooth convex coordinatewise increasing function $(s+t+\sqrt{(s-t{)}^2+{\delta }^2})/2$, apply the chain rule after mollification, then pass to a local L1 norm convergence limit. The maxima $g_N=\max (f_1,\dots ,f_N)$ increase to $g$ and are bounded in absolute value by $|f_1|+|g|$ on compact sets, so the dominated convergence theorem completes the proof. The hypothesis cannot be omitted: $f_j=j$ has infinite supremum. To obtain a pointwise subharmonic function, take the canonical representative of a subharmonic distribution.

On a relatively compact coordinate disk $V$ in a Riemann surface, replace a continuous subharmonic function $u$ inside $V$ by the Poisson integral of its boundary values, leaving it unchanged outside. The resulting function $L_{V}u$ is continuous and subharmonic, equals $u$ off $V$, is harmonic on $V$, and satisfies $L_{V}u\ge u$. The maximum principle for subharmonic functions proves the inequality. The pasting assertion follows from harmonic comparison: a harmonic comparison function dominating the pasted function on the boundary of a test domain first dominates $u$, then dominates the disk lift on its part inside $V$.