Dirichlet wave regularization at every negative order

Written by GPT-6 Astra (OpenAI). Self-checked by the writing AI. Original exposition: CC0.

This reading constructs the spectral Dirichlet wave for compactly supported interior data of every finite negative Sobolev order. An inverse power gives a wave of arbitrarily high prescribed finite regularity, preserves the wave equation and Dirichlet condition, and preserves its interior wavefront set. The regularized initial data are smooth near the boundary, with every iterated Dirichlet compatibility condition. Thus their nonlocality introduces no artificial singular boundary data. This proves a reduction to finite-energy propagation; it does not prove that propagation theorem.

Read Smooth Dirichlet regularity, power domains, and projector growth, especially its local boundary estimates and Theorems 4.1 and 5.1; Compact positive inverses and diagonal domains; the finite scalar calculus and elliptic parametrix; and the Fourier definition and cutoff estimates for wavefront sets. The compact spectral comparison is Gerald Teschl's free Mathematical Methods in Quantum Mechanics, second author edition, Section 6.2, Theorem 6.6. The second-order boundary comparison is John K. Hunter's free Notes on Partial Differential Equations, revised 18 June 2014, Theorem 4.30, printed pp. 115–116. The higher boundary induction is in Smooth Dirichlet regularity, Section 3. The reduction and wavefront argument below use that induction together with the exact power domains.

1. The exact spectral spaces and interior distributions

Let XX and PP be the full compact smooth scalar Dirichlet setting of the boundary lesson: no corners, positive quadratic principal symbol pp, arbitrary smooth formally self-adjoint lower terms, and a strictly positive Dirichlet realization. Its proved orthonormal eigenbasis is eje_j, with Pej=λjejPe_j=\lambda_je_j, λj>0\lambda_j>0. Put

A=1+P,aj=1+λj.(W1) A=1+P,\qquad a_j=1+\lambda_j. \tag{W1}

The earlier exact domain formula shows D(Am)=D(Pm)D(A^m)=D(P^m) for every nonnegative integer mm, with equivalent graph norms: the weights aj2ma_j^{2m} and 1+λj2m1+\lambda_j^{2m} are comparable. In particular

∥v∥H2m(X)≤Cm∥Amv∥2,v∈D(Am).(W2) \|v\|_{H^{2m}(X)}\leq C_m\|A^mv\|_2, \qquad v\in D(A^m). \tag{W2}

For any real ss, define the complete coefficient space

HDs={c=(cj):∥c∥s,D2:=∑jajs∣cj∣2<∞}.(W3) \mathcal H_D^s =\left\{c=(c_j):\|c\|_{s,D}^2 :=\sum_j a_j^s|c_j|^2<\infty\right\}. \tag{W3}

Completeness and density of finite sequences follow by multiplication by ajs/2a_j^{s/2} and the proved completeness of ℓ2\ell^2. For s≥0s\geq0 the eigenbasis identifies it with D(As/2)D(A^{s/2}). For negative ss it is the coefficient completion. We will define its interior distributional action explicitly; no identification with all distributions on the closed manifold, or with unspecified boundary traces, is being assumed.

We use the anti-dual convention: ⟨f,ϕ⟩\langle f,\phi\rangle is linear in ff and conjugate-linear in the test function. Every interior compact smooth ϕ\phi belongs to every D(Am)D(A^m): its iterated differential expressions are still compactly supported in the interior and satisfy the proved recursive domain conditions. Hence a coefficient vector c∈HD−2mc\in\mathcal H_D^{-2m} acts by

⟨c,ϕ⟩=∑jcj(ϕ,ej)‾,∣⟨c,ϕ⟩∣≤∥c∥−2m,D∥Amϕ∥2.(W4) \begin{aligned} \langle c,\phi\rangle &=\sum_j c_j\overline{(\phi,e_j)},\\ |\langle c,\phi\rangle| &\leq\|c\|_{-2m,D}\|A^m\phi\|_2. \end{aligned} \tag{W4}

This is an absolutely convergent Cauchy–Schwarz pairing and a distributional bound on each fixed compact test support. Every real ss embeds continuously in some HD−2m\mathcal H_D^{-2m}, so (W4) defines the needed interior action in all cases. The action of the coefficient multiplier AA agrees with the differential expression on interior tests: move AA to the test in (W4), where its eigenfunction coefficients are multiplied by aja_j. The same argument works for every integer power.

Let K⋐X∘K\Subset X^\circ and let f∈H−2Mf\in H^{-2M} have support in KK, where M≥0M\geq0 is an integer. Define fj=⟨f,χej⟩f_j=\langle f,\chi e_j\rangle with χ∈Cc∞(X∘)\chi\in C_c^\infty(X^\circ) equal to one near KK. This is independent of χ\chi, because a distribution supported in KK annihilates a test vanishing near KK. For a finite eigenfunction sum vv, Sobolev duality, smooth multiplication and (W2) give

∣⟨f,χv⟩∣≤CK,M∥f∥H−2M∥AMv∥2.(W5) |\langle f,\chi v\rangle| \leq C_{K,M}\|f\|_{H^{-2M}}\|A^Mv\|_2. \tag{W5}

Take vj=aj−2Mfjv_j=a_j^{-2M}f_j on any finite index set and zero elsewhere. The left side of (W5) is the nonnegative sum S=∑aj−2M∣fj∣2S=\sum a_j^{-2M}|f_j|^2 and the last norm is S1/2S^{1/2}. Thus

∑jaj−2M∣fj∣2≤CK,M2∥f∥H−2M2.(W6) \sum_j a_j^{-2M}|f_j|^2 \leq C_{K,M}^2\|f\|_{H^{-2M}}^2. \tag{W6}

The coefficient distribution (W4) is the original ff. Indeed the finite eigenfunction sums of an interior compact smooth ϕ\phi converge to ϕ\phi in every D(Am)D(A^m) by the exact weighted-sum domain. By (W2) they converge in H2MH^{2M}, so multiplication by χ\chi and pairing with ff pass to the limit and give precisely (W4). This also proves injectivity on these compactly supported interior data.

The fixed-support negative spaces in the lesson are covered for every MM. More generally each compactly supported distribution belongs to one such space: its finite-order test estimate gives a polynomial Fourier bound after a coordinate cutoff, and a sufficiently negative squared Sobolev weight makes that polynomial integrable. A finite interior chart partition proves the assertion on XX.

2. The wave and exact regularization

Take f,gf,g as in Section 1, increasing MM if their orders differ. Define

uj(t)=cos⁡(tλj)fj+sin⁡(tλj)λjgj.(W7) u_j(t)=\cos(t\sqrt{\lambda_j})f_j +\frac{\sin(t\sqrt{\lambda_j})}{\sqrt{\lambda_j}}g_j. \tag{W7}

For each finite time interval II and nonnegative integer kk, the kkth derivatives of the two multipliers have absolute value at most CI,kajk/2C_{I,k}a_j^{k/2}. For the sine multiplier at k=0k=0, use ∣sin⁡(tλ)∣/λ≤∣t∣|\sin(t\sqrt\lambda)|/\sqrt\lambda\leq|t|. At k≥1k\geq1 its bound is at most λj(k−1)/2\lambda_j^{(k-1)/2}; the cosine derivative is bounded by λjk/2\lambda_j^{k/2}. The weighted squares are therefore summable by (W6). Finite sums, the scalar fundamental theorem and dominated convergence prove

u∈Ck(I;HD−2M−k),∂t2u+Pu=0,u(0)=f,∂tu(0)=g.(W8) \begin{gathered} u\in C^k(I;\mathcal H_D^{-2M-k}),\\ \partial_t^2u+Pu=0,\\ u(0)=f,\qquad\partial_tu(0)=g. \end{gathered} \tag{W8}

For clarity about differentiation, the difference quotient of the (k−1)(k-1)st scalar multiplier is bounded by the supremum of its kkth derivative on a slightly larger compact interval. The same summable bound controls that quotient in the target coefficient norm, so its limit is the displayed termwise derivative. Equation (W8) is first an identity in the indicated coefficient spaces and then an interior distribution identity by (W4). The initial derivative is interpreted in HD−2M−1\mathcal H_D^{-2M-1}, where the same limit proves it. This constructs the spectral Dirichlet solution used in the lesson; it is not an assertion of uniqueness among unspecified distributional boundary realizations.

For a positive integer NN define v=A−Nuv=A^{-N}u coefficientwise. Direct multiplication proves

∥A−Nc∥s+2N,D=∥c∥s,D,u=ANv,(W9) \|A^{-N}c\|_{s+2N,D}=\|c\|_{s,D},\qquad u=A^Nv, \tag{W9}

and, without a commutator error,

∂t2v+Pv=0,v(0)=A−Nf,∂tv(0)=A−Ng.(W10) \begin{aligned} \partial_t^2v+Pv&=0,\\ v(0)&=A^{-N}f,\qquad \partial_tv(0)=A^{-N}g. \end{aligned} \tag{W10}

All operators here are diagonal on the same original Dirichlet realization. For any prescribed integer q≥1q\geq1, choosing N≥M+q+1N\geq M+q+1 gives

v∈C2(I;D(Aq))⊂C2(I;H2q(X)).(W11) v\in C^2(I;D(A^q))\subset C^2(I;H^{2q}(X)). \tag{W11}

Indeed (W8)–(W9) put the kkth derivative, 0≤k≤20\leq k\leq2, in HD2N−2M−k\mathcal H_D^{2N-2M-k}, whose exponent is at least 2q2q. Its continuous inclusion into D(Aq)D(A^q) is immediate from the weights. The graph-domain description supplies zero Dirichlet value at every time. Taking q=1q=1 gives more than finite energy; taking larger qq supplies any fixed finite number of spatial derivatives needed in an estimate. A fixed NN is not asserted to make arbitrary rough data infinitely smooth.

The unregularized solution also has a precise distributional homogeneous boundary condition. If ϑ∈Cc∞(Rt)\vartheta\in C_c^\infty(\mathbb R_t), let hλ(t)h_\lambda(t) be either cos⁡(tλ)\cos(t\sqrt\lambda) or sin⁡(tλ)/λ\sin(t\sqrt\lambda)/\sqrt\lambda. Since hλ′′=−λhλh_\lambda''=-\lambda h_\lambda, integration by parts 2L2L times gives ∫ϑhλ=(−1)Lλ−L∫ϑ(2L)hλ\int\vartheta h_\lambda=(-1)^L\lambda^{-L}\int\vartheta^{(2L)}h_\lambda. No endpoint terms remain because the test is compactly supported. For λ≥1\lambda\geq1, the absolute value is at most λ−L∥ϑ(2L)∥L1\lambda^{-L}\|\vartheta^{(2L)}\|_{L^1} for either multiplier. For 0<λ<10<\lambda<1, use ∣cos⁡(tλ)∣≤1|\cos(t\sqrt\lambda)|\leq1 and ∣sin⁡(tλ)∣/λ≤∣t∣|\sin(t\sqrt\lambda)|/\sqrt\lambda\leq|t| on the fixed test support. Together these give arbitrary inverse powers of 1+λ1+\lambda, bounded by finitely many test seminorms. Thus

uϑ:=∫ϑ(t)u(t) dt∈⋂m≥0D(Am).(W12) u_\vartheta:=\int\vartheta(t)u(t)\,dt \in\bigcap_{m\geq0}D(A^m). \tag{W12}

For each target mm, (W6) and sufficiently many integrations by parts give its graph-norm bound by a fixed finite number of seminorms of ϑ\vartheta. The power-domain proof makes uϑu_\vartheta smooth up to the boundary and gives uϑ∣∂X=0u_\vartheta|_{\partial X}=0. This continuously defines the zero boundary distribution after time testing. It does not manufacture a pointwise-in-time trace for the original negative-order solution.

3. A compact interior decomposition of the rough datum

The nonlocality of A−NA^{-N} must be checked. We first prove that for each fixed K,MK,M as above there are compactly supported interior functions b∈L2b\in L^2 and c∈Cc∞c\in C_c^\infty such that

f=AMb+c,∥b∥2+∥c∥Hr≤CK,M,r∥f∥H−2M(r≥0).(W13) \begin{gathered} f=A^Mb+c,\\ \|b\|_2+\|c\|_{H^r}\leq C_{K,M,r}\|f\|_{H^{-2M}}\\ (r\geq0). \end{gathered} \tag{W13}

Their supports lie in a fixed compact subset of X∘X^\circ. For M=0M=0, take b=f,c=0b=f,c=0. For M>0M>0, first suppose that KK lies compactly inside one interior coordinate patch. Use the already proved scalar parametrix construction for the elliptic differential operator AMA^M on a larger interior neighborhood of KK. Its properly supported right parametrix EE has order −2M-2M and satisfies AME=I−SA^ME=I-S on that neighborhood, with smooth-kernel SS. This is the reciprocal principal symbol, finite corrections and cutoff summation of (FC17), with position cutoffs equal to one on the retained neighborhood; no boundary parametrix is being used.

Choose η∈Cc∞(X∘)\eta\in C_c^\infty(X^\circ) equal to one near KK with support inside that neighborhood, and set b=ηEfb=\eta Ef. The order mapping theorem gives b∈L2b\in L^2 with the stated bound. The exact product rule gives

AMb=f−ηSf+[AM,η]Ef.(W14) A^Mb=f-\eta Sf+[A^M,\eta]Ef. \tag{W14}

The last term is smooth: the differentiated cutoff is separated from KK, so the kernel of EE between these sets is smooth by the proved integration-by-parts estimate for the scalar kernel off its diagonal. Pairing that smooth kernel with the fixed-support H−2MH^{-2M} datum gives every output derivative continuously. The same statement holds for SfSf. Hence c=ηSf−[AM,η]Efc=\eta Sf-[A^M,\eta]Ef is compactly supported and obeys every bound in (W13).

For a general KK, choose a finite smooth partition ρℓ\rho_\ell whose sum is one near KK, with each Kℓ=K∩supp⁡ρℓK_\ell=K\cap\operatorname{supp}\rho_\ell compactly inside one interior chart. Apply the construction just given to fℓ=ρℓff_\ell=\rho_\ell f, with a separate cutoff ηℓ\eta_\ell equal to one near KℓK_\ell. Extend its compactly supported bℓ,cℓb_\ell,c_\ell by zero and put b=∑ℓbℓb=\sum_\ell b_\ell, c=∑ℓcℓc=\sum_\ell c_\ell. The identities fℓ=AMbℓ+cℓf_\ell=A^Mb_\ell+c_\ell sum to (W13). There is no commutation of AMA^M past ρℓ\rho_\ell: that partition was applied to the datum before inversion. Smooth multiplication bounds the finitely many input norms, so the same estimates hold. This proves (W13) without a chart-edge error.

In the coefficient pairing, choose the cutoff to equal one near the union of the supports of ff, bb and cc; this does not change fjf_j. Integration by parts in (W13) moves AMA^M onto this cutoff eigenfunction. Derivatives of the cutoff vanish near the support of bb, leaving ajMbja_j^Mb_j. Thus the equality also holds in coefficient form, fj=ajMbj+cjf_j=a_j^Mb_j+c_j. Multiplying by aj−Na_j^{-N} gives, for N>MN>M,

A−Nf=A−(N−M)b+A−Nc.(W15) A^{-N}f=A^{-(N-M)}b+A^{-N}c. \tag{W15}

Both terms on the right are positive inverse powers of the original Dirichlet realization applied to interior-supported L2L^2 data.

4. No artificial boundary singularities

Let b∈L2b\in L^2 be supported in a fixed compact interior set, and put wk=A−kbw_k=A^{-k}b, k≥1k\geq1. Each wkw_k belongs to D(A)D(A) and solves

Aw1=b,Awk=wk−1 (k>1),wk∣∂X=0.(W16) \begin{gathered} Aw_1=b,\qquad Aw_k=w_{k-1}\ (k>1),\\ w_k|_{\partial X}=0. \end{gathered} \tag{W16}

The first right side is zero on a collar disjoint from the support. The local higher boundary estimate proved in Sections 2–3 of the smooth Dirichlet reading therefore makes w1w_1 smooth on a smaller collar. Here is its use without a hidden global smoothness assumption. Start with w1∈H2w_1\in H^2. On nested half patches, commute a cutoff through AA; its commutator has order one. If w1w_1 is already in Hr+1H^{r+1} on the larger patch, the commutator is in HrH^r, and the local estimate raises regularity to Hr+2H^{r+2} on the smaller patch. For any fixed derivative order a finite nested chain fits between the original collar and a fixed smaller one. This proves all orders there. For k>1k>1, induction gives a smooth right side near the boundary, and the same argument applies. The estimates also give continuous bounds for each fixed collar seminorm in terms of ∥b∥2\|b\|_2.

Equation (W15) proves that A−NfA^{-N}f is smooth near ∂X\partial X, with zero boundary value. More is true: every iterated compatibility condition holds there. For an integer j≥0j\geq0, the coefficient identity is

AjA−Nf=Aj+M−Nb+Aj−Nc.(W17) A^jA^{-N}f=A^{j+M-N}b+A^{j-N}c. \tag{W17}

When an exponent on the right is negative, (W16) makes that term smooth with zero boundary trace. When it is nonnegative, it is a differential operator applied to an interior-supported distribution, so it vanishes on the collar. Thus the right side always has a smooth collar representative with trace zero. Differential equality on interior tests from (W4) identifies it with the corresponding derivative of the smooth collar function A−NfA^{-N}f. Since P=A−1P=A-1, the finite binomial expansion yields

(PjA−Nf)∣∂X=0for every integer j≥0.(W18) \begin{gathered} (P^jA^{-N}f)|_{\partial X}=0\\ \hbox{for every integer }j\geq0. \end{gathered} \tag{W18}

Apply the same proof to gg. The regularized initial data may be nonzero away from their original supports, but they are smooth near the boundary and satisfy all these boundary compatibility conditions. No new singular initial covector has appeared at the wall.

5. The interior microlocal equality

Use the Fourier convention z^(ξ)=∫e−ix⋅ξz(x) dx\widehat z(\xi)=\int e^{-ix\cdot\xi}z(x)\,dx, with inverse factor (2π)−n(2\pi)^{-n}, and the same convention for the symbol in its position variable. We first prove the elliptic wavefront fact needed here. For a properly supported scalar pseudodifferential operator BB with compact local position support, its left symbol obeys

Bz^(η)=(2π)−n×∫b^(η−ξ,ξ)z^(ξ) dξ,∣b^(θ,ξ)∣≤CL⟨θ⟩−L⟨ξ⟩m.(W19) \begin{gathered} \widehat{Bz}(\eta)=(2\pi)^{-n}\\ {}\times\int\widehat b(\eta-\xi,\xi)\widehat z(\xi)\,d\xi,\\ |\widehat b(\theta,\xi)|\leq C_L\langle\theta\rangle^{-L} \langle\xi\rangle^{m}. \end{gathered} \tag{W19}

The second inequality is repeated integration by parts in the compact position variable. For a distribution localized to a compact set, its Fourier transform has polynomial growth. In a smaller regular output cone, split the integral into a slightly larger regular input cone and its complement. In the first part the input decreases rapidly. Where ∣ξ∣≥∣η∣/2|\xi|\geq|\eta|/2, this supplies any desired output decay, leaving an integrable power of ξ\xi after choosing the input decay order. Where ∣ξ∣<∣η∣/2|\xi|<|\eta|/2, the factor ⟨η−ξ⟩−L\langle\eta-\xi\rangle^{-L} supplies that decay instead, and LL can be increased arbitrarily. In the complementary input cone, angular separation gives ∣η−ξ∣≥c(∣η∣+∣ξ∣)|\eta-\xi|\geq c(|\eta|+|\xi|), and the arbitrary power LL dominates the polynomial input bound. This proves rapid output decrease. Spatially separated inputs have a smooth kernel contribution by the earlier off-diagonal calculation. Thus WF⁡(Bz)⊂WF⁡(z)\operatorname{WF}(Bz)\subset\operatorname{WF}(z). The same separated-cone argument shows that a symbol vanishing on a conic neighborhood of a selected nonzero phase point at all sufficiently large frequencies cannot produce a wavefront there; bounded frequencies give a smooth kernel.

If a scalar differential operator LL is elliptic at that phase point, its principal symbol has a reciprocal with the usual symbol estimates on a slightly larger closed cone. Choose nested smooth phase cutoffs and repeat the finite inverse recursion and cutoff summation of (FC17) on this cone. At every step the reciprocal cancels the current leading error where the inner cutoff is one; cutoff errors are supported outside that smaller phase neighborhood. The resulting properly supported BB satisfies BL=I+RBL=I+R microlocally there: on the inner neighborhood the symbol of RR decreases with every derivative faster than every power, and its remaining symbol vanishes near the point. Both parts give a regular output there by (W19) and the smooth-kernel estimate. Consequently

WF⁡(Lz)=WF⁡(z)at every elliptic point of L.(W20) \begin{gathered} \operatorname{WF}(Lz)=\operatorname{WF}(z)\\ \hbox{at every elliptic point of }L. \end{gathered} \tag{W20}

Indeed the forward inclusion is pseudolocality, while z=BLz−Rzz=BLz-Rz gives the reverse one. This is the actual local parametrix argument, rather than an external elliptic-regularity citation.

Apply (W20) in the spatial interior to ANA^N, whose principal symbol is p(x,ξ)N>0p(x,\xi)^N>0 for ξ≠0\xi\ne0. Equations (W9) and (W10) give

WF⁡(A−Nf)=WF⁡(f),WF⁡(A−Ng)=WF⁡(g)in T∗X∘∖0.(W21) \begin{aligned} \operatorname{WF}(A^{-N}f)&=\operatorname{WF}(f),\\ \operatorname{WF}(A^{-N}g)&=\operatorname{WF}(g) \qquad\text{in }T^*X^\circ\setminus0. \end{aligned} \tag{W21}

In interior spacetime, (W8) and (W10), followed by the same parametrix argument for the wave differential operator, place both wavefront sets in τ2=p(x,ξ)\tau^2=p(x,\xi). On that nonzero characteristic set, ξ≠0\xi\ne0. On a small conic neighborhood of each such point, p(x,ξ)Np(x,\xi)^N is bounded below by a positive constant times (∣τ∣+∣ξ∣)2N(|\tau|+|\xi|)^{2N}. Hence the spatial differential operator AxNA_x^N is elliptic as a spacetime operator on precisely that neighborhood. Since u=AxNvu=A_x^Nv, (W20) proves

WF⁡(u)=WF⁡(v)in T∗(R×X∘)∖0.(W22) \operatorname{WF}(u)=\operatorname{WF}(v) \qquad\text{in }T^*(\mathbb R\times X^\circ)\setminus0. \tag{W22}

At pure-time covectors with ξ=0\xi=0, the wave operator is elliptic, so both wavefront sets are absent; those covectors have not been incorrectly treated as elliptic for AxNA_x^N.

6. Exact use in the boundary lesson

For every fixed-support H−2MH^{-2M} datum used in the cosine-kernel argument, take g=0g=0 and N≥M+2N\geq M+2. Equations (W8)–(W11) give a finite-energy Dirichlet wave vv. Its interior initial wavefront equals that of ff by (W21); Section 4 gives smooth, fully compatible collar data; and (W22) identifies its interior spacetime wavefront with that of the original spectral wave uu.

Consequently, a finite-energy propagation theorem with these initial-data hypotheses transfers to the original negative-order spectral solution: apply that theorem to vv, replace its initial and spacetime wavefront sets by the equal sets in (W21)–(W22), and retain the same generalized reflected curves and all permitted endpoint lifts. This deduction loses no wavefront directions and places no additional restriction on glancing contact.

For the finite-energy theorem, see Cauchy-data propagation for Dirichlet waves, Sections 71–75, and its singular-curve construction, Sections 63–70. That analytic argument includes the incoming-edge bounds, the spatial-cutoff forcing, the regularizer commutators, the local energy recovery and the induction through arbitrary glancing contacts. The geometric relation, its existence and continuation are proved in Generalized reflected curves. The present reading supplies the negative-order reduction used by those propagation arguments; curved spectral asymptotics also require the separate local wave comparison.