A Poisson germ-grain model assigns a measurable region to each point of a Poisson point process and takes the union of those regions. A location remains uncovered exactly when no Poisson point has a region containing it, so its coverage probability is determined by the intensity of the corresponding set of germs and marks.

Place equal masses at points of a homogeneous Poisson point process of intensity $\rho$ on the line, and truncate their signed inverse-power forces symmetrically at radius $R$. For force $m\mathrm{sign}(x)/|x{|}^p$, with $\alpha =1/p\in (0,2)$, the characteristic exponent tends to $-2\rho {\int }_0^{\infty }(1-\cos (mt/x^p))dx$. The cosine integral for a symmetric stable exponent evaluates it as displayed. Thus the weak limit is a symmetric stable distribution. Symmetric truncation is important when the far-field force series is not absolutely summable.

For a measurable map $f$ and a Poisson random measure of intensity $\nu$, image counts in disjoint sets equal original counts in their disjoint preimages. They are therefore independent Poisson variables with the pushforward intensity. The result is a Poisson random measure even if images collide; diffuse pushforward intensity gives a simple point process.

For a Poisson point process of intensity measure $\mu$, its $k$th Poisson factorial moment measure is ${\alpha }^{(k)}={\mu }^{\otimes k}$. Writing its counting measure as $N={\sum }_i{\delta }_{Z_i}$, the identity means that for nonnegative measurable function $g$,The indices select distinct point occurrences. Their locations need not be different when $\mu$ has an atom of a measure. For a simple point process, the locations are different as well.^[ref]

For example, if all intensity is concentrated at one point $a$, with $\mu (\{a\})=\lambda$, then $N(\{a\})$ has Poisson distribution. There are $N(\{a\})(N(\{a\})-1)$ ordered pairs of distinct occurrences there, with expected value ${\lambda }^2$, even though both locations equal $a$. Counting only pairs of different locations would give zero and fail the identity.

For $k=2$, separating equal-index terms from distinct-index terms gives the second-moment calculation in Campbell's theorem. Dividing the distinct-pair sum by two instead counts unordered pairs, as in the intersection point process of a Poisson line process.

Identify an unoriented line not through the origin by $L(p,\theta )=\{z:z\cdot (\cos \theta ,\sin \theta )=p\}$, with $p>0$. A Poisson point process on this parameter space is a random collection of lines. The measure $cdpd\theta$ is invariant under rotations and translations; signed coordinates $t\in \mathbb{R}$, $0\le \theta <\pi$ give the same measure $cdtd\theta$. The number of lines meeting a disk of radius $r$ is Poisson with mean $2\pi cr$.

For the Poisson equation $\Delta u={\sum }_{n\ge 1}{b}_n\sin (n\theta )$ on the unit disk with zero Dirichlet boundary condition, separation of variables in polar coordinates gives $r^2{R}_n^{\prime \prime }+r{R}_n^{\prime }-n^2{R}_n=r^2$. For $n\ne 2$, boundedness at $r=0$ and $R_n(1)=0$ select $R_n=(r^n-r^2)/(n^2-4)$. The resonant mode is $R_2=r^2\log r/4$. For discontinuous angular data, the Poisson equation is interpreted in its weak formulation; its Dirichlet energy gives uniqueness. Orthogonality of the angular Fourier modes gives $\int ufdA=-{\sum }_n\pi b_n^2/[4(n+2{)}^2]$, with the resonant case obtained directly or by the limit $n\to 2$.

The full conditional distributions are $\lambda \mid m,x\sim \mathrm{Gamma}(\alpha +S_m,\beta +m)$ and $\varphi \mid m,x\sim \mathrm{Gamma}(\gamma +S_N-S_m,\delta +N-m)$, in shape-rate notation. Conditional on the two rates, $m$ has weights $w_j=\exp [j(\varphi -\lambda )+S_j\log (\lambda /\varphi )]$. A Gibbs sampler cycles through these three draws. Each update preserves the joint posterior distribution; subtracting the largest log weight before exponentiation stabilizes the categorical draw. Averages of $1_{\{m=N\}}$ estimate the posterior probability of no observed change.

Integrating the two rates out of the Poisson count change-point model with gamma priors gives these weights up to a common factor, by the defining Gamma function integral. Normalizing across the finitely many possible indices gives the exact marginal posterior distribution of $m$, providing a check on Markov chain Monte Carlo estimates. One can also draw $m$ from these weights and then draw both rates from their conditional Gamma distributions, producing independent exact joint posterior samples.

Start with $Y_0\sim \mathrm{Poisson}(\theta )$ and conditionally let $Y_i\sim \mathrm{Poisson}(\theta Y_{i-1})$. The mean generation size is ${\theta }^{i+1}$. The log-likelihood is $S_n\log \theta -\theta T_n$ plus a parameter-free term, where $S_n={\sum }_{i=0}^n{Y}_i$ and $T_n=1+{\sum }_{i=0}^{n-1}{Y}_i$. Expected negative curvature gives the displayed Fisher information, bounded as the horizon grows. Extinction makes the observations eventually all zero, so one longer observed family does not supply indefinitely increasing information.

// Target: convergence-of-random-variables.bigb

Let $h$ be central and a non-zero-divisor in an associative algebra, with commutative quotient modulo $h$. Dividing commutators by $h$ and reducing modulo $h$ is independent of the lifts, since changing a lift by $hc$ changes the quotient by a commutator, zero modulo $h$. Antisymmetry, the Leibniz rule and the Jacobi identity descend from the corresponding commutator identities. For the order filtration of a Weyl algebra, the convention is $\{{\xi }_i,x_j\}={\delta }_{ij}$, with the opposite sign for $\{x_i,{\xi }_j\}$.

The optical transfer function is the Fourier transform of the normalized intensity point spread function for incoherent imaging with translation invariance, using spatial frequency in cycles per unit length. It has $H(0)=1$. For an ideal circular pupil it is the normalized pupil autocorrelation, with cutoff $2\mathrm{NA}/{\lambda }_0$ in object coordinates: no overlap remains when two pupil copies are shifted apart by more than one pupil diameter.^[ref]

Defocus is the mismatch between the receiving plane and the intended optical focus. Changing the plane changes the point spread function even when the optical lens is otherwise ideal.

The Airy disk is the central bright region, up to the first dark ring, in the scalar diffraction pattern of a uniformly illuminated, unobscured circular aperture. The whole pattern includes the weaker surrounding rings; its radius is distinct from its full width at half maximum.

For a circular optical pupil of diameter $D$ under normal, uniform monochromatic plane wave illumination, Fraunhofer diffraction givesHere $I_0$ is the on-axis light intensity, $\theta$ is the angle from the optical axis, $\lambda$ is the wavelength in the propagation medium, and $J_1$ is the order-one Bessel function of the first kind. The paraxial approximation replaces $\sin \theta$ by $\theta$, measured in radians. The first positive zero $j_{1,1}=3.831705970\dots$ givesThis is the angular radius of the Airy disk; the angular diameter is twice as large. The Airy disk derivation explains the origin of the Bessel function of the first kind and of the numerical coefficient.^[ref]

The image and both radial curves show the same calculated light intensity, divided by its peak. The image's logarithmic scale makes the weak rings visible; its colour is a display choice. The linear curve shows how small the ring peaks are compared with the centre. A dark ring marks a zero of wave amplitude, produced by cancellation across the optical pupil; it is not the edge of all transmitted light. The first Airy disk contains about $83.78\%$ of the total radiant flux, as calculated in Airy disk normalization and encircled energy.

For an original design example, take an ideal optical lens in air with focal length $f=100\mathrm{mm}$, circular optical pupil diameter $D=5.00\mathrm{mm}$ and wavelength $\lambda =550\mathrm{nm}$. In the focal plane, the radial coordinate $r\simeq f\theta$ givesThe first-zero diameter is $26.8327\mu \mathrm{m}$. Solving $P(u_{1/2})=1/2$ gives $u_{1/2}=1.616339948\dots$, so the diameter measured by full width at half maximum is onlyThus a quoted “spot diameter” is incomplete without its definition. Doubling $D$ halves both widths at fixed wavelength and focal length; increasing magnification alone changes the image scale without improving object-space discrimination.

The Airy disk supplies a calculable reference for a point spread function, allowing diffraction to be distinguished from defocus and optical aberrations. Its beauty is that one circular boundary determines an entire sequence of bright and dark rings through a Fourier transform. The ideal formula assumes an unobscured pupil, uniform illumination, ideal optical focus, a single wavelength, and a scalar description with small output angles. A blocked centre, nonuniform pupil transmission or a significant pupil wave phase error changes the response. High numerical aperture may require polarization of an electromagnetic wave and a vector field description. The circular-aperture diffraction laboratory experiment tests the far-field pattern directly; the Rayleigh criterion uses its first zero to define a two-source convention.

In coherent imaging, complex wave amplitudes add with their relative wave phases preserved. The measured light intensity includes wave interference between the contributions.

In incoherent imaging, contributions from distinct object points add as light intensities because their mutual spatial optical coherence is negligible. A single convolution additionally requires translation invariance of the point spread function.

An optical point source has spatial extent negligible relative to the imaging scale being tested. The Dirac delta function is its idealization; a finite bead or unresolved star only approximates it.

Point spread function normalization specifies how the response is scaled. Unit-integral scaling separates image shape from total radiant flux; unit-peak scaling compares shapes but does not make their total radiant fluxes equal.

An incompressible point source of volume flux $Q$ at height $a$ above an impermeable plane has velocity potential $\varphi =-Q(1/r_{+}+1/r_{-})/(4\pi )$, with an equal image source below the plane. On the wall, $u_s=Qs/[2\pi (s^2+a^2{)}^{3/2}]$. The Bernoulli equation gives $p-p_{\infty }=-\rho Q^2{s}^2/[8{\pi }^2(s^2+a^2{)}^3]$. Integrating the pressure deficit over the plane gives the displayed attraction force relative to ambient pressure. If source strength instead denotes the coefficient $Q/(4\pi )$ of radial inverse-square velocity, the force is $\pi \rho m^2/a^2$.

A point injection of volume at rate $Q$ produces the displayed radial potential flow in three dimensions. Its velocity potential is $-Q/(4\pi r)$, and every enclosing sphere has outward volume flux $Q$. The divergence vanishes away from the source and is $Q$ times the three-dimensional Dirac delta distribution at it. The field is also a Stokes flow with constant pressure away from its singularity.

A source dipole is the limit of an equal source and sink brought together with their source-strength times separation vector fixed at $\mathbf{M}$. Differentiating the three-dimensional point source field gives $\mathbf{u}=-(\mathbf{M}\cdot \nabla )[\mathbf{r}/(4\pi r^3)]$. It has velocity potential $-\mathbf{M}\cdot \mathbf{r}/(4\pi r^3)$, zero total volume flux, and $r^{-3}$ far-field decay. Unlike a stresslet, it is an irrotational potential singularity rather than a force-dipole flow.