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Fourier stability analysis applies most directly to linear, constant-coefficient evolution schemes on uniform infinite or periodic grids. Translation invariance makes spatial shifts diagonal in discrete Fourier modes. If a one-step scheme has $U^{n+1}={\sum }_j{A}_j{U}_{m+j}^n$, substituting $U_m^n={\hat{U}}^n(\theta )e^{im\theta }$ gives the Fourier amplification symbolThe discrete Parseval identity identifies the discrete L2 norm with the squared norm of Fourier coefficients. Uniform stability on a fixed time interval means a mesh-independent bound on $\Vert G(\theta {)}^n\Vert$ for all frequencies and $n\Delta t\le T$. In the scalar case $|G|\le 1$ yields contraction. More generally $|G|\le 1+C\Delta t$ gives the bound $e^{CT}$ and is consistent with a continuously growing well-posed equation. A fixed modulus excess independent of the step produces growth exponential in $T/\Delta t$ and fails this requirement.

For systems, eigenvalue moduli alone are insufficient. The uniform power bound for matrix Fourier symbols also controls eigenvector conditioning and Jordan growth. For example $G=\left(\begin{array}{cc}1& 1\\ 0& 1\end{array}\right)$ has only unit eigenvalues but $G^n=\left(\begin{array}{cc}1& n\\ 0& 1\end{array}\right)$, unbounded as $\Delta t\to 0$ at fixed $T$. In contrast an off-diagonal entry proportional to $\Delta t$ gives growth at most proportional to $T$, which can be legitimate. A uniformly conditioned diagonalization is a sufficient reduction to scalar modal bounds; nonnormal matrices require direct power or energy estimates. Multilevel schemes similarly require the root condition for their frequency-dependent amplification polynomial and a uniform bound on the associated companion evolution, including limiting repeated-root cases.

The simplest parabolic example is the Forward Euler method with centered spatial diffusion. For $\mu =\Delta t/h^2$,is the sharp mesh-uniform contraction range. For the theta method, $G=[1-4(1-a)\mu {\sin }^2(\theta /2)]/[1+4a\mu {\sin }^2(\theta /2)]$, giving unconditional contraction at $a\ge 1/2$. Implicit stability permits larger steps, but accuracy still constrains them, and the Crank-Nicolson method does not strongly damp high-frequency rough data.

For advection $u_t+c{u}_x=0$ with $c>0$, the upwind finite difference scheme givesThus $0\le \nu \le 1$ is its contraction range. The Lax-Friedrichs scheme has $G=\cos \theta -i\nu \sin \theta$ and is contractive exactly when $|\nu |\le 1$. These express a Courant–Friedrichs–Lewy condition: the numerical domain of dependence must encompass the physical one for convergence. That necessary condition is not sufficient by itself. Forward time with centered advection has $G=1-i\nu \sin \theta$ and $|G|>1$ at nonzero modes. At a fixed nonzero Courant number it is unstable even if $|\nu |\le 1$. Under the much stronger refinement $\Delta t=O(h^2)$, however, its powers remain bounded on fixed time intervals; the centered-advection refinement-dependent stability must not be confused with the usual hyperbolic-step instability.

Symbols also quantify dispersion and dissipation. For a mode $e^{ikx}$, the argument of $G$ gives a numerical phase speed and $|G|$ gives damping. Upwind advection has leading artificial diffusion $ch(1-\nu )/2$ under fixed-Courant refinement; excessive damping smooths genuine structure, while phase error misplaces waves. Stability controls boundedness, not either error by itself. Smooth low-frequency Taylor expansions establish consistency; high-frequency modal bounds establish stability, so analyzing only fixed physical wavenumbers can miss grid-scale instabilities.

For a well-posed linear initial-value problem, the Lax equivalence theorem makes consistency plus a uniform stability estimate equivalent to convergence in the chosen norm. Boundaries and variable coefficients need extra care: Fourier diagonalization no longer handles the full update, and an interior or frozen-coefficient symbol does not prove boundary or global stability. Boundary energy estimates, a suitable matrix analysis or a separate boundary-stability argument must supplement it. Nonlinear schemes also require controls beyond this linear symbol test. These limitations delimit what the method proves rather than reducing its usefulness: in its proper setting, it turns an arbitrarily large grid evolution into exact and interpretable modal algebra.

Assume $0<\lambda =1-\epsilon <1$, as required for this nontrivial subcritical binomial random graph. Put $\delta =\lambda -1-\log \lambda >0$. A breadth-first exploration of a binomial random graph is dominated by a Galton-Watson process whose offspring counts are independent random variables with law $\mathrm{Bin}(n,\lambda /n)$. If its total progeny $T$ is at least $j$, the first $j-1$ offspring counts sum to at least $j-1$. Their moment-generating function is bounded by that of a Poisson distribution of mean $\lambda (j-1)$. The exponential Markov inequality, optimized at $t=-\log \lambda$, yieldsTaking $j=\lceil (1+\eta )\log n/\delta \rceil$ for any fixed $\eta >0$, a union bound over all starting vertices gives $\mathbb{P}(L_1\ge j)=o(1)$.

For the matching lower bound, let $X_j$ count tree components of order $j$. The tree-component expectation in the Erdős-Rényi model is exactlyFor $j=O(\log n)$, the Stirling formula givesChoose $j=\lfloor (1-\eta )\log n/\delta \rfloor$, with $0<\eta <1$. Then $\mathbb{E}{X}_j\to \infty$. Distinct overlapping vertex sets cannot both be graph components. For disjoint sets, the joint probability differs from the product only because the $j^2$ between-set edges were counted twice as absent. ThusIt follows that $\mathrm{var}{X}_j/(\mathbb{E}{X}_j{)}^2=o(1)$. The second moment method gives $X_j>0$ with high probability. Combining both bounds, and then taking arbitrarily small fixed $\eta$, proves the sharp subcritical largest-component scaleFinally the Taylor expansion of $-\log (1-\epsilon )$ gives $\delta ={\epsilon }^2/2+{\epsilon }^3/3+\cdots$. The endpoint $\lambda =0$ has no edges and is excluded from this logarithmic asymptotic.

Write $\mu =1+\epsilon$, $p=\mu /n$, $q=1-p$, and let $T$ be the total progeny of a binomial branching process. The preceding binomial branching survival correction gives $\rho =(2+o(1))\epsilon$. For a branching process conditioned on extinction, the offspring probability generating function is $f((1-\rho )s)/(1-\rho )$, with meanfor sufficiently large $n$. Summing expected generation sizes therefore gives $\mathbb{E}[T;T<\infty ]=(1-\rho )/(1-f^{\prime }(1-\rho ))=O(1/\epsilon )$.

Put $K=\lceil {\epsilon }^{-3}\rceil$ and let $N_{\ge K}$ count vertices in graph components of order at least $K$. A breadth-first exploration of a binomial random graph is dominated by $T$. The Markov inequality applied to finite total progeny givesAlways $L_1\le K+N_{\ge K}$. Since $n{\epsilon }^4\ge n^{1/3}\to \infty$, we have $K=o(\epsilon n)$ and $n/(\epsilon K)=O(n{\epsilon }^2)=o(\epsilon n)$. Hence $\mathbb{E}{L}_1\le (2+o(1))\epsilon n$. This bound controls the expected value directly, including rare large graph components.

For the lower bound, use the breadth-first exploration of a binomial random graph with $U_t$ unseen vertices, $A_t$ active vertices and $t$ explored vertices, starting from $U_0=n$, $A_0=0$. Let $b_t=1_{\{A_{t-1}=0\}}$ indicate a new root. Conditional on the past, the newly discovered count $Z_t$ has a binomial distribution $\mathrm{Bin}(U_{t-1}-b_t,p)$. Put $D_t=Z_t-p(U_{t-1}-b_t)$. The unseen-count recursion givesHere $M_t$ is a martingale. Up to $T_0=\lceil 3\epsilon n\rceil$, martingale-difference orthogonality gives $\mathbb{E}{M}_{T_0}^2\le C\epsilon n$, since each conditional variance is at most $np<2$ and $q^{-2T_0}$ is bounded.

Take $h=\sqrt{\epsilon }+(n{\epsilon }^3{)}^{-1/8}$. Then $h\to 0$, $\epsilon =o(h)$ and $h^{2}n{\epsilon }^3\to \infty$. The Doob L2 maximal inequality impliesThe Taylor expansion, uniformly for $t\le T_0$, gives $F(t)=\epsilon t-t^2/(2n)+O({\epsilon }^{3}n+\epsilon )$. Thus $F(t)\ge h{\epsilon }^{2}n/3$ throughout the integer interval $[\lceil h\epsilon n\rceil ,\lfloor (2-h)\epsilon n\rfloor ]$ for large $n$. The new-root sum is nonnegative, so on the preceding event $A_t>0$ throughout this interval. No graph component finishes there: all these explored vertices belong to one graph component, of order at least $(2-2h)\epsilon n-O(1)$, with high probability. Its expected value is therefore at least $(2-o(1))\epsilon n$. Combining both inequalities provesThe barely-supercritical largest-component expectation uses both a positive exploration window and a finite-progeny bound; a bare convergence-in-probability assertion would not by itself justify this expectation.

For the binomial branching process, the offspring probability generating function is $f(s)=(1-p+ps{)}^n$. The Galton-Watson extinction fixed point gives $1-\rho =f(1-\rho )=(1-p\rho {)}^n$.

The printed finite-binomial upper bound is false without an additional asymptotic qualification. For $n=2$ and $p=(1+\epsilon )/2$, solving the fixed-point equation exactly givesFor instance $\epsilon =1/20$ gives $\rho =80/441>1/10=2\epsilon$. More generally, at every fixed $n>1$ the Taylor expansion gives $\rho =2n\epsilon /(n-1)+O_n({\epsilon }^2)$, again contradicting that upper bound for sufficiently small positive $\epsilon$.

Here is the corrected binomial branching survival correction. The Poisson branching process of mean $1+\epsilon$ has branching survival probability $r$ satisfying $-\log (1-r)=(1+\epsilon )r$. Expanding the logarithm givesThus $2\epsilon /(1+2\epsilon )\le r\le 2\epsilon$, which implies the requested lower estimate $r\ge 2\epsilon -4{\epsilon }^2$. Since $(1-p+ps{)}^n\le e^{np(s-1)}$ on $[0,1]$, iteration of the two offspring probability generating functions gives $\rho \ge r$.

For the actual binomial branching process, expansion of its exact fixed-point equation givesIf $(1+\epsilon {)}^2<n$, all coefficients are nonnegative. Keeping the first term provesIn particular, for $n\to \infty$ and $\epsilon =o(1)$ this gives $\rho =2\epsilon +O({\epsilon }^2+\epsilon /n)$. The printed bounds also hold for the binomial branching process in an explicit large-$n$ regime: $0<\epsilon \le 1/4$ and $n\epsilon \ge 2$. Indeed these conditions give $n{p}^2\le \epsilon$ and $n{p}^3\le 1/4$. In the preceding nonnegative series, evaluation at $x=2\epsilon$ givesThe series is increasing, and its value at the actual branching survival probability $\rho$ is $\epsilon$, so $\rho \le 2\epsilon$. Together with the lower bound already proved, this recovers $2\epsilon -4{\epsilon }^2\le \rho \le 2\epsilon$ in that regime. In particular it applies eventually to part (ii). The counterexample shows why a regime condition is needed for a literal finite-$n$ statement.

Take real field coordinates ${\varphi }^I$; for complex scalar fields, split them into real and imaginary parts. Assume a smooth scalar potential and positive, canonically normalized kinetic terms in a relativistic theory. At a classical vacuum, $V_I({\varphi }_0)=0$. The Taylor expansion isThus the scalar mass matrix is the Hessian matrix, and its eigenvalues give squared masses of the linearized scalar excitations.

Put $X_a(\varphi )=i{t}^a\varphi$. Infinitesimal invariance of the scalar potential gives the identity $V_I{X}_a^I=0$ at every field value. Differentiate with respect to ${\varphi }^J$ and evaluate at the classical vacuum:Every nonzero infinitesimal symmetry direction therefore lies in the kernel of the scalar mass matrix. This is the classical Goldstone theorem expressed through Goldstone directions in the scalar mass matrix.

Let $H_0$ be the full stabilizer subgroup of ${\varphi }_0$. The linear map from the Lie algebra of $G$ to field space, $T\mapsto iT{\varphi }_0$, has kernel equal to the Lie algebra of $H_0$. The rank-nullity theorem givesThere are consequently at least $\dim G-\dim H_0$ massless scalar directions, namely the tangent directions to the symmetry orbit through the classical vacuum. If the intended $H$ is $H_0$, these are the $\dim G-\dim H$ symmetry-required Goldstone bosons. Exactly that many massless modes occur if the scalar mass matrix is positive definite on a complement of those tangent directions. A nonsingular positive field-space kinetic metric changes normalization, but not the number of zero masses.

Two qualifications are needed for the literal assumptions. A subgroup fixing the classical vacuum need not be the full stabilizer subgroup. For example, take $G=SO(3)$ acting on a real triplet and $V=\lambda (|\varphi {|}^2-v^2{)}^2/8$ with $\lambda ,v>0$. At ${\varphi }_0=v{e}_3$, the scalar mass matrix is $\lambda v^2\mathrm{diag}(0,0,1)$: there are two massless modes. Choosing $H=\{1\}$ satisfies the printed invariance condition but would incorrectly predict three. The full stabilizer subgroup is $SO(2)$.

Even with the full stabilizer subgroup, symmetry does not exclude an accidental massless scalar. Take $G=SO(2)$ rotating $(x,y)$, with an invariant singlet $z$, andAt $(v,0,0)$ the full continuous stabilizer is trivial, but the scalar mass matrix is $\mathrm{diag}(2\lambda v^2,0,0)$. One zero direction is the Goldstone boson; the other is an accidental massless scalar at quadratic order. The proof establishes the symmetry-required count, not unconditional equality with the total number of massless fields. The statement concerns global internal symmetry; gauging it changes the physical interpretation through the Higgs mechanism.

Put $d=\Delta x$, $k=\Delta t$ and use the diffusion Courant number $r=k/d^2$. To discuss consistency of a numerical method, refine the mesh with a fixed positive $r$. With ${\delta }^2{U}_m=U_{m-1}-2U_m+U_{m+1}$, the printed update is $U^{n+1}-U^n=\alpha {\delta }^2{U}^{n+1}$. A Taylor expansion of a smooth exact solution, about the new time level, gives the residual divided by $k$:Here the heat equation implies $u_t=u_{xx}$ and $u_{tt}=u_{xxxx}$. Since $\alpha$ depends only on $r$, the leading term can vanish for every smooth solution only if $\alpha (r)=r$. Thus the method is the Backward Euler diffusion scheme, with local truncation errorIts highest general accuracy is first order in time and second order in space, or order two in $d$ under $k=r{d}^2$. The coefficient of $d^2{u}_{xxxx}$ is $-(r/2+1/12)$, so it cannot cancel for any positive diffusion Courant number. This is a conclusion about the stencil actually printed: the new-time spatial difference fixes the sign of its temporal error. With sufficiently smooth compatible data, stability of a numerical method below turns the $O(k+d^2)$ consistency estimate into an $O(k+d^2)$ global error bound on a fixed time interval.

For fixed finite matrices, the matrix exponential and a Taylor expansion showThis agrees through degree two with $e^{h(A+B)}$, even when $A$ and $B$ do not commute. On a fixed time interval, $\Vert S(h)\Vert \le e^{h(\Vert A\Vert +\Vert B\Vert )}$ and the telescoping identityturns the $O(h^3)$ one-step defect into $O(N{h}^3)=O(h^2)$ global error for $Nh\le T$. Hence Strang splitting is second order in general; for commuting matrices it is exact.

For the spatial discretization, use $d=2/(M+1)$, $x_m=-1+md$ and the interior vector $U=(u_1,\dots ,u_M{)}^T$, with $u_0=u_{M+1}=0$. The central finite differences giveHere $\mathrm{tridiag}$ lists lower diagonal, main diagonal and upper diagonal, in that order. Thus $A^T=A$ and $B^T=-B$. Discrete summation by parts givesThe matrix exponential $e^{hA/2}$ is consequently a contraction in the Euclidean norm, while $e^{hB}$ is an orthogonal matrix for real $\alpha$. ThereforeRepeated split steps are contractive in the mesh-weighted norm $d\sum |u_m{|}^2$, uniformly in the spatial mesh and without a Courant–Friedrichs–Lewy condition. The split semidiscretization is unconditionally stable. No commutativity or shared eigenvectors are needed for this Strang splitting contraction for symmetric diffusion and skew advection. Its time-order proof is for fixed spatial matrices; as $d\to 0$, commutators can grow, so this stability result alone is not a uniform-in-mesh second-order error estimate.

The bounded classical solution is the heat-kernel convolutionThe two-dimensional heat kernel has integral one. Boundedness of $g$ permits differentiation under the integral for $t>0$, proving $u_t=\Delta u$ and $|u|\le \Vert g{\Vert }_{\infty }$. Its approximate identity property gives $u(x,t)\to g(x)$, locally uniformly since $g$ is continuous. This bounded solution satisfies the required Gaussian-growth bound.

For heat-equation uniqueness under Gaussian growth, let $w$ be the difference of two solutions, so $w(x,0)=0$ and $|w|\le M_0{e}^{a|x{|}^2}$ on a finite time interval. Choose $b>a$ and a slab $0\le t\le \tau <1/(4b)$. The positive comparison solutionsatisfies $({\Phi }_b{)}_t=\Delta {\Phi }_b$. For any $\epsilon >0$, its faster spatial growth makes $|w|\le \epsilon {\Phi }_b$ on a sufficiently large lateral cylinder boundary. At the initial boundary, $w=0$. The heat equation maximum principle applied to $\pm w-\epsilon {\Phi }_b$ proves the same inequality inside. First allow the cylinder radius to increase, then let $\epsilon \downarrow 0$. Repeating these slabs proves uniqueness on every finite interval with the stated uniform growth bound. No spatial integrability of $g$ is required.

At time $T$, this is Gaussian filtering with covariance $2TI$, hence $\sigma =\sqrt{2T}$ per coordinate. With the angular-frequency Fourier transform convention $\hat{f}(\xi )=\int e^{-ix\cdot \xi }f(x)dx$, the Gaussian filtering Fourier multiplier isFor merely bounded $g$, this identity is understood through tempered distributions. The multiplier leaves the zero frequency unchanged and attenuates large frequencies exponentially: it suppresses rapid noise fluctuations but blurs image edges. In cycles-per-length frequency $k$, the multiplier is $e^{-4{\pi }^{2}T|k{|}^2}$.

For the printed Perona-Malik equation, retain the supplied conductance $c(s)=s{e}^{-s^2/(2{\lambda }^2)}$, which includes an extra factor $s$. In one dimension write $p=u_x$ and $F(p)=c(|p|)p=p|p|e^{-p^2/(2{\lambda }^2)}$. Then $u_t=F^{\prime }(u_x)u_{xx}$, withThe forward-backward threshold for gradient-weighted exponential diffusion is thereforeAt $|u_x|=0$ and $\sqrt{2}\lambda$ the coefficient vanishes, giving degenerate diffusion. Increasing $\lambda$ increases the forward-diffusion range. Small nonzero slopes smooth, while large slopes formally sharpen; a negative coefficient produces short-wave growth and ill-posedness, so this is a dynamics explanation, not a general existence theorem for arbitrary data. Replacing the printed conductance by $e^{-s^2/(2{\lambda }^2)}$ would give threshold $\lambda$, but that is a different equation.

The four-neighbour mean expansion follows by Taylor expansion: opposing first and third derivatives cancel, soIf $u(x_0)={\mathrm{mean}}_h(u)(x_0)$ for every sufficiently small $h$, division by $h^2$ and passage to the limit give $\Delta u(x_0)=0$. This is a pointwise conclusion; it does not assert harmonicity in a whole neighbourhood.

For the area median over the disk, the disk-median curvature expansion, at a point where $|\nabla u|\ne 0$, isConsequently the analogous median fixed-point condition yieldsThis is the vanishing of the level-line curvature at $x_0$: to second order the level line is straight there. It need not be a straight segment. For example $u(x,y)=y+x^3$ has zero disk median at the origin for every radius, by odd symmetry, but its zero level line is the cubic $y=-x^3$. Vanishing curvature on an entire connected regular level arc would force that arc to be straight. The factor $1/6$ is for the disk's uniform area measure; a circle-boundary median has a different scale factor, while producing the same zero-curvature equation.

The leading Stokes drift comes from evaluating the oscillatory velocity at the displaced particle position. Taylor expansion givesHere $u_x=-ak\omega e^{kz}\sin \vartheta$ and $u_z=ak\omega e^{kz}\cos \vartheta$. Inserting the initial-position displacements from the preceding solution yieldsIn particular the instantaneous difference is zero at $t=0$, as it must be. The unaveraged constant equality in the PDF is incompatible with its initial labels. Averaging over a period $\mathcal{T}=2\pi /\omega$ removes the oscillatory term:Equivalently, using mean parcel labels and the purely oscillatory displacements gives $a^{2}k\omega e^{2kz}({\sin }^2\vartheta +{\cos }^2\vartheta )$ at this order. This recovers the intended constant result. The period-mean drift is in the wave-propagation direction and decreases as $e^{2kz}$. The corresponding second-order vertical difference is $a^{2}k\omega e^{2kz}\sin (\omega t)$ for initial labels and has zero mean. The resulting horizontal displacement per cycle is $u_s\mathcal{T}$; closed first-order circles do not imply zero second-order transport.

Insert an exact smooth solution into the linear multistep method and define its unscaled local truncation error byIts Taylor expansion has coefficientsThe method has order at least $p$ exactly when $c_0=\cdots =c_p=0$, since then ${\mathcal{R}}_h[y]=O(h^{p+1})$ for every sufficiently smooth $y$. Necessity can be checked by inserting polynomials of successive degrees. This also corresponds to the usual truncation error ${\mathcal{R}}_h/h=O(h^p)$.

On the other hand, expansion of the characteristic polynomials of a linear multistep method givesThus the exponential-symbol order criterion for a multistep method isIf “order $p$” is meant to be the exact rather than guaranteed order, one additionally requires $c_{p+1}\ne 0$. The first two vanishing conditions are the usual consistency of a numerical method relations $\rho (1)=0$, ${\rho }^{\prime }(1)=\sigma (1)$.

To prove (a) implies (c), shrink to a contractible coordinate neighborhood. The real Poincaré lemma gives a real one-form $\eta$ with $\omega =d\eta$. Write $\eta ={\eta }^{1,0}+{\eta }^{0,1}$. Because $\omega$ has type $(1,1)$, $\bar{\partial }{\eta }^{0,1}=0$ and $\partial {\eta }^{1,0}=0$. The Dolbeault-Poincaré lemma supplies a smooth function $\psi$ with ${\eta }^{0,1}=\bar{\partial }\psi$. Reality of $\eta$ gives ${\eta }^{1,0}=\partial \overline{\psi }$. ThusTaking the real function $f=2\mathrm{Im}\psi$ gives the local real potential for a closed (1,1)-form. Conversely, $d(i\partial \bar{\partial }f)=0$, by ${\partial }^2={\bar{\partial }}^2=0$ and anticommutation. Hence (a) and (c) are equivalent, completing all three conditions.

For the unheaded radial continuation, take the real potential $f$ as in (c). Rotation invariance makes $f$ constant on every circle of radius $r>0$, sois well defined and smooth by composition. This avoids treating a smooth function as if it had a convergent Taylor series. At nonzero $z$, put $t=\log |z{|}^2$. The identities ${\partial }_{z}t=1/z$ and ${\partial }_{\bar{z}}t=1/\bar{z}$ giveLet $q(z)=f_{z\bar{z}}(z)$, which is smooth on the whole plane. ThenAt the origin, rotation invariance gives the finite Taylor expansion $f(z)=f(0)+b|z{|}^2+O(|z{|}^4)$, with $b=q(0)$. Alternatively continuity of $q$ directly givesThe metric is positive away from the origin exactly when $u^{\prime \prime }(t)>0$ for all finite $t$, and it is positive at the origin exactly when this limit is positive. Smoothness at the origin is already supplied by the original smooth potential. Consequently the positivity criterion for a radial Kähler potential isClosedness is automatic from the potential, and positivity completes the Kähler condition. No completeness of this metric is asserted. The rotation-invariant Kähler potential on the complex plane is understood as real; if a complex radial potential is initially allowed with real $\omega$, its smooth radial imaginary part is harmonic and hence constant, so that constant can be removed.

Put $Z=\lfloor N^{2/5}\rfloor$ and $S={\sum }_{N<n\le N+M}{n}^{-it}$. For any positive integer shift $h\le Z^2$, translating the interval changes its sum by at most $2h$. Averaging the shifts $h=xy$ gives the bilinear shift averaging for a logarithmic phase identitySince $xy/n\le N^{-1/5}$, the alternating Taylor expansion of the logarithm has remainder at most $(xy/n{)}^{r+1}/(r+1)$. ThusFor $r=\lfloor 5.01\log t/\log N\rfloor$, we have $r+1>5.01\log t/\log N$, hence the error is at most $t^{-1/500}$. The exponential function on an imaginary argument changes by at most the change in that argument. ThereforeUse $Z^2\asymp N^{4/5}$ and $N<n\le N+M\le 2N$. Taking absolute values provesThe boundary error comes from integer shifts, so this argument also covers intervals shorter than a shift. Here $x,y$ range over positive integers; no zero term is needed.

For a smooth exact solution of the advection equation, $u(x,t)=g(x+t)$, since the transport velocity in the convention $u_t=u_x$ is minus one. Put $d=\Delta x$, $k=\mu d$ and move the scheme's right side to the left. Substitution gives the exact-solution residualIts constant, linear and quadratic Taylor expansion terms cancel. The cubic term isThe un-substituted leading term is $2k(u_t-u_x)$, so divide by $2k$ to use a normalized local truncation error. For a fixed positive Courant ratio,Thus the generic method is second order, provided stability and a compatible second-order starter are supplied.

There are two special ratios rather than an unnoticed higher generic order. At $\mu =1/2$, the scheme is $u_m^{n+1}=u_{m+1}^{n-1}$; both sides lie on the same exact characteristic, and the residual vanishes identically. At $\mu =1$ the previous-level term cancels the unshifted current term for exact data, again producing zero residual on every exact characteristic solution. The first special case is stable, while the second is not stable for arbitrary two-level perturbations, as part (b) shows. Exact propagation of specially initialized data is not a substitute for stability.

A Taylor expansion of the tangential no-slip boundary condition gives $u_{2x}(0)=-\sin \xi {\partial }_y{u}_{1x}(0)$. Since $f^{\prime \prime }(0)=-s$,For matrix-relative Brinkman velocity, the mean second-order tangential flow isThe mean tangential traction has no first-order geometric remainder: at the surface ${\partial }_y{\sigma }_{xy,1}=s(s+1)\sin \xi$ and ${\sigma }_{xx,1}=s(s+1)\cos \xi$, so the mean displaced-boundary and tilted-normal corrections cancel. Thus the force-free condition gives ${\overline{u}}_{2x}^{\prime }(0)=0$, hence $C=0$. In the $A=0$ limit boundedness likewise excludes mean shear. The swimming speed of a Brinkman sheet is thereforeIt is larger than the simple-fluid speed by $\sqrt{1+(\alpha /k{)}^2}$ for fixed waveform and frequency. The matrix offers a reaction structure for the transverse stroke and more strongly confines the induced motion; it acts as a footing against which the wave pushes. This is a prescribed-stroke comparison, not a guarantee at fixed motor power. The small-amplitude expansion is at fixed $A$; a large-$A$ use also needs $ϵs\ll 1$ to control variation across the displaced boundary.

Introduce a parameter $t$ to keep track of total degree. The power series for the matrix exponential givesSet $S=X+Y$ and $C=\frac{1}{2}[X,Y]$, where the commutator is $[X,Y]=XY-YX$. Expanding a second matrix exponential givesSincethe two expressions agree through total degree two. More explicitly, applying the local matrix logarithm to the first expansion gives $\log (e^{tX}{e}^{tY})=t(X+Y)+\frac{1}{2}{t}^2[X,Y]+O(t^3)$. This proves the displayed order of the Baker--Campbell--Hausdorff formula. The Lie algebra is closed under the commutator, so its displayed exponent lies in the same Lie algebra. The expansion is a formal power series identity, or a convergent identity sufficiently near the identity matrix; this argument does not assert unrestricted global convergence.