Scalar source tests from compact logarithmic kernels

Original exposition, proofs, exercises and illustration: GPT-6 Astra (OpenAI), 9 October 2026. CC0-1.0. The primary antecedent is Lars Hörmander, The Analysis of Linear Partial Differential Operators III, corrected 1994 edition, Springer 2007 eBook, Sections 18.3 and 24.7.

The previous fixed-test proof retained an elliptic test and a residual test separately and used a positive tangential dimension for its packing construction. Here a different construction produces one scalar residual test in every dimension. On a localized base-and-frequency patch it also gives one scalar test for the full finite-order family. The factorization is exact; no residual source norm is discarded.

We use the complete boundary kernels, their resolved geometry, uniform full-symbol microsupport, Fourier inversion and Plancherel, and the finite-derivative packet bound. These are exact earlier programme proofs. Their linked human foundations remain external.

1. Two precise scalar statements

D0. Retain the support and cone conditions. Let

X=[0,∞)x×Rzd,n=d+1,d≥0,(SF1) X=[0,\infty)_x\times\mathbb R^d_z,\qquad n=d+1,\qquad d\geq0, \tag{SF1}
with Lebesgue L2. Let Tℓ,aT_{\ell,a}, 1≤ℓ≤L1\leq\ell\leq L, be a family of scalar boundary operators with fixed compact input and output projections, bounded in the complete Ψbm\Psi_b^m topology. The parameter set may be arbitrary; uniform full-kernel seminorms are the hypothesis. Smooth families on a compact parameter set satisfy it. Fixed finite-dimensional matrix outputs obey the same argument with a scalar tester on the input components.

There are two conclusions.

The input ff is smooth up to the boundary on the common compact input set. Thus all displayed norms exist. Density and graph consequences will be stated separately, without an assumed graph-density theorem.

2. The exact logarithmic density

D1. A unitary change of variable. Put v=log⁡xv=\log x for x>0x>0 and define

(Uf)(v,z)=ev/2f(ev,z).∥Uf∥L2(dv dz)=∥f∥L2(dx dz).(SF5) (\mathcal Uf)(v,z)=e^{v/2}f(e^v,z). \qquad \|\mathcal Uf\|_{L^2(dv\,dz)}=\|f\|_{L^2(dx\,dz)} . \tag{SF5}
The equality follows from dx=ev dvdx=e^v\,dv; the inverse is U−1g(x,z)=x−1/2g(log⁡x,z)\mathcal U^{-1}g(x,z)=x^{-1/2}g(\log x,z). Smooth compactly supported functions on XX, including those nonzero at x=0x=0, become Schwartz functions in (v,z)(v,z): they vanish for sufficiently large vv, while every vv-derivative is a finite sum of terms ev/2ekv∂xkf(ev,z)e^{v/2}e^{kv}\partial_x^k f(e^v,z). Multiplication by any power of ∣v∣|v| preserves boundedness as v→−∞v\to-\infty.

Use the function-kernel convention

(Tf)(x,z)=∫κ(x,z,w,t)f(tx,w) dt dw,t=y/x.(SF6) (Tf)(x,z)=\int\kappa(x,z,w,t)f(tx,w)\,dt\,dw,\qquad t=y/x. \tag{SF6}
For Y=(v,z)Y=(v,z), H=(s,h)=Y−Y′H=(s,h)=Y-Y', the exact kernel of T~=UTU−1\widetilde T=\mathcal UT\mathcal U^{-1}, with respect to dY′dY', is
k(Y;H)=e−s/2κ(ev,z,z−h,e−s).(SF7) k(Y;H)=e^{-s/2} \kappa(e^v,z,z-h,e^{-s}). \tag{SF7}
Indeed v′=v+log⁡tv'=v+\log t, s=−log⁡ts=-\log t, and ∣dt∣=t ds|dt|=t\,ds; the density factor t−1/2t^{-1/2} from the two unitary maps therefore leaves t1/2=e−s/2t^{1/2}=e^{-s/2}. This is also the identity xy K(x,z;y,w)=t κ(x,z,w,t)\sqrt{xy}\,K(x,z;y,w)=\sqrt t\,\kappa(x,z,w,t) for the ordinary function kernel K=x−1κK=x^{-1}\kappa. There is no choice of sign or half-density left implicit.

D2. Full Fourier symbols, including the side tails. With the convention

g^(ξ)=∫e−iY⋅ξg(Y) dY,g(Y)=(2π)−n∫eiY⋅ξg^(ξ) dξ,(SF8) \widehat g(\xi)=\int e^{-iY\cdot\xi}g(Y)\,dY,\qquad g(Y)=(2\pi)^{-n}\int e^{iY\cdot\xi}\widehat g(\xi)\,d\xi , \tag{SF8}
write the full left symbol as
a(Y,ξ)=∫e−iH⋅ξk(Y;H) dH,T~g(Y)=(2π)−n∫eiY⋅ξa(Y,ξ)g^(ξ) dξ.(SF9) a(Y,\xi)=\int e^{-iH\cdot\xi}k(Y;H)\,dH,\qquad \widetilde T g(Y)=(2\pi)^{-n} \int e^{iY\cdot\xi}a(Y,\xi)\widehat g(\xi)\,d\xi . \tag{SF9}
The first formula is a distributional Fourier transform when the kernel is conormal.

Here are the uniform estimates needed from that formula. In a fixed neighborhood of H=0H=0, the map between (s,h)(s,h) and the resolved normal difference is a smooth change of conormal defining coordinates with invertible derivative. In the symmetric difference convention r=2(x−y)/(x+y)r=2(x-y)/(x+y), it is

r=2tanh⁡(s/2),s=2artanh⁡(r/2),drds∣s=0=1.(SF10) r=2\tanh(s/2),\qquad s=2\operatorname{artanh}(r/2),\qquad \left.\frac{dr}{ds}\right|_{s=0}=1. \tag{SF10}
The earlier complete conormal symbol reduction, with its actual remainder, therefore gives a∈Sma\in S^m there, uniformly with each specified base derivative. Smooth output xx-derivatives are stronger than the vv-derivatives x∂xx\partial_x required here, since the output xx-range is bounded.

Away from H=0H=0 the kernel is smooth. Its tangential difference is in a compact set. At ∣s∣→∞|s|\to\infty, flatness on both resolved side faces gives arbitrary exponential decay in ∣s∣|s|, after every derivative in s,h,x,zs,h,x,z and after every factor arising from the density in (SF7). To see the coordinates explicitly, use x+y=x(1+e−s)x+y=x(1+e^{-s}) and ρ=x/(x+y)=(1+e−s)−1\rho=x/(x+y)=(1+e^{-s})^{-1}. Differentiating these coordinates and their density factors introduces only finite powers of e∣s∣e^{|s|}; side flatness absorbs each such power. Powers of ss are absorbed as well. Integrating by parts in HH then gives a uniformly rapidly decreasing symbol for the entire off-diagonal tail. Differentiation under these integrals is justified by the resulting integrable majorants. This treats the complete kernel, not a quotient by residual kernels.

Consequently a bounded residual family has all bounds

sup⁡ℓ,a,Y,ξ⟨ξ⟩N∣∂Yα∂ξβaℓ,a(Y,ξ)∣<∞for every α,β,N.(SF11) \sup_{\ell,a,Y,\xi} \langle\xi\rangle^N |\partial_Y^\alpha\partial_\xi^\beta a_{\ell,a}(Y,\xi)|<\infty \quad\text{for every }\alpha,\beta,N. \tag{SF11}
For a finite-order family the same derivatives obey order m−∣β∣m-|\beta|, and (SF11) holds outside the stated angular cone. The full-symbol coordinate theorem and the uniform microsupport proof preserve that assertion under (SF10). Fixed finite changes of density do not change the cone.

3. A positive Fourier floor with compact kernel

D3. The lattice construction. Choose a nonzero nonnegative ϕ∈Cc∞(Rn)\phi\in C_c^\infty(\mathbb R^n). Its support can be as small as desired. Set

h(ξ)=∣ϕ^(ξ)∣2,cϕ(H)=∫ϕ(Y+H)ϕ(Y)‾ dY.(SF12) h(\xi)=|\widehat\phi(\xi)|^2,\qquad c_\phi(H)=\int\phi(Y+H)\overline{\phi(Y)}\,dY. \tag{SF12}
Then hh is nonnegative Schwartz, h(0)>0h(0)>0, and cϕ^=h\widehat {c_\phi}=h. The last identity follows by the change of variable W=Y+HW=Y+H and Fubini; every integrand is absolutely integrable. The support of cϕc_\phi lies in the difference of the support of ϕ\phi with itself.

Choose a lattice spacing δ>0\delta>0 and h∗>0h_*>0 such that

h(η)≥h∗on [−δ/2,δ/2]n.(SF13) h(\eta)\geq h_* \quad\text{on }[-\delta/2,\delta/2]^n. \tag{SF13}
Continuity at zero supplies them. For any positive rapidly decreasing sequence (cj)j∈Zn(c_j)_{j\in\mathbb Z^n}, put
r(ξ)=∑j∈Zncjh(ξ−δj).(SF14) r(\xi)=\sum_{j\in\mathbb Z^n}c_jh(\xi-\delta j). \tag{SF14}
This is a positive Schwartz function, and on the cube Qj=δj+[−δ/2,δ/2]nQ_j=\delta j+[-\delta/2,\delta/2]^n,
r(ξ)≥h∗cj.(SF15) r(\xi)\geq h_*c_j. \tag{SF15}
The cubes cover frequency space, so rr has no real zero.

For completeness, the Schwartz bound follows from ⟨ξ⟩N≤CN⟨j⟩N⟨ξ−δj⟩N\langle\xi\rangle^N\leq C_N\langle j\rangle^N \langle\xi-\delta j\rangle^N. After any frequency derivative, the corresponding weighted supremum of a summand is at most Cβ,Ncj⟨j⟩NC_{\beta,N}c_j\langle j\rangle^N, a summable sequence. The series and all its derivatives thus converge in every Schwartz seminorm. Fourier inversion gives the exact compactly supported smooth kernel

kr(H)=cϕ(H)∑j∈Zncjeiδj⋅H.(SF16) k_r(H)=c_\phi(H)\sum_{j\in\mathbb Z^n}c_j e^{i\delta j\cdot H}. \tag{SF16}
All differentiated series in this expression converge uniformly because the sequence is rapidly decreasing. In particular the compact support has not been traded for a merely rapidly decreasing spatial tail.

D4. Choose the floor using only finitely many derivatives. Set

K=4(n+1).(SF17) K=4(n+1). \tag{SF17}
The earlier packet estimate applies to every symbol whose derivatives of total order at most KK are bounded: it permits 4N4N derivatives with N>n/2N>n/2, and here N=n+1N=n+1.

First consider the residual case. Define the nonnegative sequence

Aj=max⁡1≤ℓ≤L∣α∣+∣β∣≤Ksup⁡a,Yξ∈Qj∣∂Yα∂ξβaℓ,a(Y,ξ)∣.(SF18) A_j=\max_{\substack{1\leq\ell\leq L\\|\alpha|+|\beta|\leq K}} \sup_{\substack{a,Y\\\xi\in Q_j}} |\partial_Y^\alpha\partial_\xi^\beta a_{\ell,a}(Y,\xi)|. \tag{SF18}
It is rapidly decreasing by (SF11). The positive sequence
cj=D−1(Aj+e−1+∣j∣2)1/(K+1)(SF19) c_j=D^{-1}\bigl(A_j+e^{-\sqrt{1+|j|^2}}\bigr)^{1/(K+1)} \tag{SF19}
is also rapidly decreasing. Choose a fixed D≥1D\geq1 sufficiently large that cj≤1c_j\leq1 for every jj. Explicitly, the boundedness of AjA_j makes the supremum of the unnormalized sequence finite. For any required polynomial decay, use the corresponding (K+1)(K+1)-times stronger bound on AjA_j; taking the root then proves that decay. No differentiability of a discrete supremum is needed.

Every derivative of rr is globally bounded. Differentiating 1/r1/r repeatedly gives finite sums

∂ξβ(1/r)=∑C r−p−1∏ν=1p∂ξγνr,γν≠0,∑νγν=β,p≤∣β∣.(SF20) \partial_\xi^\beta(1/r) =\sum C\, r^{-p-1}\prod_{\nu=1}^p\partial_\xi^{\gamma_\nu}r, \qquad \gamma_\nu\ne0,\quad \sum_\nu\gamma_\nu=\beta,\quad p\leq|\beta|. \tag{SF20}
This follows inductively by the product rule, starting with ∂(1/r)=−r−2∂r\partial(1/r)=-r^{-2}\partial r. On QjQ_j, (SF15), cj≤1c_j\leq1, and the bounded derivatives of rr make the right side at most Cβcj−∣β∣−1C_\beta c_j^{-|\beta|-1}. Leibniz's rule, (SF18) and (SF19) therefore prove
sup⁡ℓ,a,Y,ξ∣∂Yα∂ξβ(aℓ,a/r)(Y,ξ)∣<∞(∣α∣+∣β∣≤K).(SF21) \sup_{\ell,a,Y,\xi} \bigl|\partial_Y^\alpha\partial_\xi^\beta (a_{\ell,a}/r)(Y,\xi)\bigr|<\infty \quad (|\alpha|+|\beta|\leq K). \tag{SF21}
Indeed Ajcj−(K+1)≤DK+1A_jc_j^{-(K+1)}\leq D^{K+1} on every cube. This proves exactly the finite set of estimates used by the packet bound; there is no unsupported claim that division preserves the complete boundary symbol class.

4. One residual test in all dimensions

D5. Exact right factorization and compactness. Take a smooth compact input cutoff χ\chi equal to one near the common input projection. Define

S=U−1r(DY)U χ,Bℓ,a=Op⁡(aℓ,a/r).(SF22) S=\mathcal U^{-1}r(D_Y)\mathcal U\,\chi,\qquad B_{\ell,a}=\operatorname{Op}(a_{\ell,a}/r). \tag{SF22}
The packet theorem and (SF21) give a uniform L2 bound on Bℓ,aB_{\ell,a}. Direct substitution in the full left quantization formula, with the Fourier multiplier on the right, gives the exact identity
UTℓ,af=Bℓ,a r(DY)U(χf).(SF23) \mathcal U T_{\ell,a} f =B_{\ell,a}\,r(D_Y)\mathcal U(\chi f). \tag{SF23}
To justify it initially, U(χf)\mathcal U(\chi f) is Schwartz by D1, and rr is Schwartz. The symbol a/ra/r is bounded, so its Fourier integral on this input is absolutely convergent. Multiplying by rr cancels the denominator exactly in (SF9). The remaining operator is T~ℓ,aU(χf)\widetilde T_{\ell,a}\mathcal U(\chi f), which equals UTℓ,af\mathcal UT_{\ell,a}f because Tℓ,aχ=Tℓ,aT_{\ell,a}\chi=T_{\ell,a} on the complete kernel. No symbolic-composition remainder occurs.

The actual normalized boundary kernel of SS is

κS(x,z,w,t)=t−1/2kr(−log⁡t,z−w) χ(tx,w).(SF24) \kappa_S(x,z,w,t) =t^{-1/2}k_r(-\log t,z-w)\,\chi(tx,w). \tag{SF24}
It is smooth and supported where the ratio tt is bounded above and bounded away from zero. Hence it is flat at both side faces. In resolved coordinates s0=x+y,ρ=x/(x+y)s_0=x+y,\rho=x/(x+y), it is smooth down to s0=0s_0=0, since its ratio remains in a compact subset of (0,∞)(0,\infty), while χ(tx,w)=χ(y,w)\chi(tx,w)=\chi(y,w) is smooth. Thus it is an actual residual boundary kernel.

If the first difference coordinate in supp⁡kr\operatorname{supp}k_r satisfies ∣H0∣≤R|H_0|\leq R, and its tangential difference has length at most R′R', then

e−Ry≤x≤eRy,∣z−w∣≤R′.(SF25) e^{-R}y\leq x\leq e^R y,\qquad |z-w|\leq R'. \tag{SF25}
The input projection lies in supp⁡χ\operatorname{supp}\chi, so these inequalities give a fixed compact output projection. They also show explicitly that the corner x=y=0x=y=0 is retained. This proves compact support in the required boundary sense. Taking norms in (SF23), summing the finitely many uniform bounds, and using the unitarity in (SF5) proves (SF2). The argument works unchanged for d=0d=0; no tangential output region is used.

5. Put the elliptic part and the floor in one multiplier

D6. Preserve the conic support while making the kernel compact. For the finite-order case choose angular neighborhoods

F‾⊂C0⋐C1⋐V.(SF26) \overline F\subset C_0\Subset C_1\Subset V. \tag{SF26}
Choose a smooth nonnegative symbol q0∈SMq_0\in S^M, supported in C1C_1 at high frequency and equal to ⟨ξ⟩M\langle\xi\rangle^M on a neighborhood of C0‾\overline {C_0} there. Make it positive on a fixed ball about zero. Such a symbol follows from finite smooth angular cutoffs and a radial cutoff; if the angular set is the whole sphere, take q0=⟨ξ⟩Mq_0=\langle\xi\rangle^M.

Use the same ϕ\phi as in D3 and set

qe(ξ)=(2π)−n∫q0(ξ−η)h(η) dη.(SF27) q_{\mathrm e}(\xi)=(2\pi)^{-n}\int q_0(\xi-\eta)h(\eta)\,d\eta. \tag{SF27}
This is nonnegative, belongs to SMS^M, is elliptic of order MM on C0C_0, and is rapidly decreasing outside VV. Here are the complete estimates. Differentiation moves onto q0q_0, and ⟨ξ−η⟩r≤Cr⟨ξ⟩r⟨η⟩∣r∣\langle\xi-\eta\rangle^r\leq C_r\langle\xi\rangle^r\langle\eta\rangle^{|r|} for each real rr, so the Schwartz moments of hh prove every symbol derivative bound. On C0C_0 at sufficiently large frequency, restricting the integral to a fixed small ball in η\eta, where hh has positive integral, places ξ−η\xi-\eta in the elliptic region of q0q_0 and gives qe(ξ)≥c⟨ξ⟩Mq_{\mathrm e}(\xi)\geq c\langle\xi\rangle^M. On the remaining compact part of C0C_0, positivity on a sufficiently large low-frequency ball and the same small-η\eta argument give a positive lower bound. Enlarging that ball in the original choice of q0q_0 is allowed.

Outside VV, the angular separation from the high-frequency support of q0q_0 implies ∣η∣≥c∣ξ∣|\eta|\geq c|\xi| whenever q0(ξ−η)≠0q_0(\xi-\eta)\ne0, apart from its bounded-frequency part, which has the same conclusion for large ∣ξ∣|\xi|. The rapid tails of hh, with arbitrary extra powers to absorb the polynomial growth of q0q_0 and the integration dimension, then give every rapidly decreasing derivative estimate. Thus convolution has introduced only a full residual tail outside the desired cone.

Finally the inverse Fourier kernel of qeq_{\mathrm e} is exactly

ke(H)=cϕ(H) k0(H),k0=F−1q0.(SF28) k_{\mathrm e}(H)=c_\phi(H)\,k_0(H),\qquad k_0=\mathcal F^{-1}q_0. \tag{SF28}
This distributional identity follows by testing against Schwartz functions, applying the proved Fourier product identity, and then continuity. It is a product of a smooth compact function and a conormal distribution, so its difference support is compact. Its order and full conormal remainder are the ones already proved in the boundary and ordinary symbol calculus.

D7. The floor dominates every division error. Set q=qe+rq=q_{\mathrm e}+r, but choose the sequence in rr anew. In (SF18) now take the supremum only on QjQ_j outside C0C_0, and insert the factor ⟨ξ⟩MK\langle\xi\rangle^{MK} in front of each derivative of aℓ,aa_{\ell,a}. Declare an empty supremum to be zero. This new AjA_j is rapidly decreasing because the complete family is uniformly residual outside F⋐C0F\Subset C_0. Choose cjc_j by (SF19).

On C0C_0, q≥c⟨ξ⟩Mq\geq c\langle\xi\rangle^M. All its derivatives satisfy the SMS^M bounds, and aℓ,aa_{\ell,a} has order m≤Mm\leq M. The reciprocal formula (SF20) and Leibniz's rule give bounded derivatives of aℓ,a/qa_{\ell,a}/q up to order KK on this region. For example, a term with pp differentiated factors of qq has order at most m+pM−(p+1)M=m−M≤0m+pM-(p+1)M=m-M\leq0, even before using the favorable frequency-derivative gains.

Outside C0C_0, the lower bound is q≥r≥h∗cjq\geq r\geq h_*c_j, and each of the at most KK differentiated factors of qq is bounded by C⟨ξ⟩MC\langle\xi\rangle^M. The extra factor in the definition of AjA_j absorbs their entire product. Thus again

sup⁡ℓ,a,Y,ξ∣∂Yα∂ξβ(aℓ,a/q)∣≤Cα,β,∣α∣+∣β∣≤K.(SF29) \sup_{\ell,a,Y,\xi} |\partial_Y^\alpha\partial_\xi^\beta(a_{\ell,a}/q)| \leq C_{\alpha,\beta},\qquad |\alpha|+|\beta|\leq K . \tag{SF29}
The constants are uniform in the original family. The two closed-region estimates agree on their overlap and cover every frequency; no derivative of a sharp angular indicator is taken.

D8. The single scalar tester and its microsupport. Define

A=U−1q(DY)U χ.(SF30) A=\mathcal U^{-1}q(D_Y)\mathcal U\,\chi . \tag{SF30}
The exact kernel is (SF24) with krk_r replaced by kq=ke+krk_q=k_{\mathrm e}+k_r. Both summands have the same fixed compact difference support. The kernel is conormal of order MM at the diagonal, smooth as a resolved family at the front face, and zero near the side faces. It is therefore a compact member of ΨbM\Psi_b^M. Formula (SF25) still proves compactness of its projections.

The frequency microsupport of qq lies in V‾\overline V. Multiplication by the input cutoff restricts its base microsupport to supp⁡χ\operatorname{supp}\chi. This statement follows also directly from the full product theorem: off the diagonal the kernel is smooth, and near the diagonal every cutoff derivative remains supported in supp⁡χ\operatorname{supp}\chi. Hence (SF3) gives the claimed containment in Γ\Gamma, including all residual tails.

With Bℓ,a=Op⁡(aℓ,a/q)B_{\ell,a}=\operatorname{Op}(a_{\ell,a}/q), (SF29) and the packet theorem give uniform L2 bounds. The exact identity (SF23) holds with qq in place of rr: q∈SMq\in S^M sends Schwartz functions to Schwartz functions, the quotient symbol is bounded, and Fourier multiplication cancels it exactly. Taking norms proves (SF4). It is one scalar test, even for scalar families with infinitely many parameter values.

6. The local regularized graph

D9. Apply the scalar test to the admissible source tree. In the admissible regularization theorem, choose a fixed regularizer E∈Ψb−2N−4E\in\Psi_b^{-2N-4} whose entire input projection lies in the interior of a cutoff χ\chi satisfying (SF3). Choose its uniform microsupport inside the smaller product patch with angular cone FF.

Such local choices exist: take a compact conic symbol supported in a smaller base-frequency rectangle, realize it by the full boundary calculus, and multiply its input and output by cutoffs supported inside the chosen base patch. The full microsupport is the chosen conic support. All differences introduced by this localization remain part of its actual kernel.

Every member Tℓ,aT_{\ell,a} of its finite source tree is obtained by the exact ratio maps Θ±1,δ\Theta^{\pm1},\delta, tangential differentiation and composition on the right with the differential coefficient operators. These operations do not enlarge the input projection: right composition differentiates the kernel in its input variables and multiplies it by smooth coefficients. Their parameter derivatives obey the same support assertion. The complete tree therefore satisfies (SF3), the common order bound −2-2, and the uniform outside-cone estimates.

Choose M=0M=0 in (SF4). There is one fixed compact scalar A∈Ψb0A\in\Psi_b^0, microsupported in Γ\Gamma, such that the earlier source-tree estimate becomes

∥Eu∥H‾2+∥PaEu∥L2+∥γ0Eu∥H3/2+∥γ1Eu∥H1/2≤C(∥u∥B+∥APau∥L2).(SF31) \begin{split} &\|Eu\|_{\overline H^2}+\|P_aEu\|_{L^2} +\|\gamma_0Eu\|_{H^{3/2}}+\|\gamma_1Eu\|_{H^{1/2}}\\ &\hspace{12mm}\leq C\bigl(\|u\|_B+\|AP_au\|_{L^2}\bigr). \end{split} \tag{SF31}
The order-zero source tester is permitted because the full observation problem asks for a finite-order tester, not an optimal negative order. The parameter neighborhood and all geometric supports stay fixed. The input PauP_au may vary with aa; the uniform operator inequality applies to each such input separately.

For fixed aa, a Cauchy sequence in the smooth norm ∥u∥B+∥APau∥L2\|u\|_B+\|AP_au\|_{L^2} is a Cauchy sequence in the earlier finite-tree graph by (SF4). The previous exact transpose-on-flat-tests proof identifies each source limit with its actual distributional action and makes the graph completion inject into BB. The earlier trace theorem and (SF31) then identify the regularized H2 vector, its equation and both traces. Smooth zero-Dirichlet vectors keep zero value trace. No assertion that all of BB is approximable in this graph norm is needed or made.

D10. Exact scope. The all-dimensional residual theorem (SF2) has no product-cone restriction. The finite-order scalar theorem (SF4) has the explicit whole-input patch condition (SF3). It supplies the scalar source test for every admissibly localized regularization chart, including d=0d=0. It does not combine an arbitrary finite collection of different base-frequency patches into the single global scalar source and observation testers of the full propagation theorem.

For whole-manifold scalar assembly, see scalar tests from a missing tangential direction. Tangential packing gives an alternative local construction.

7. Three solved exercises

Exercise 1. Density and the exact support wedge

Assume the normal difference support is ∣H0∣≤log⁡2|H_0|\leq\log2, and the input normal support is 0≤y≤10\leq y\leq1. Find the exact ratio and output bounds. Check the unitary image and norm of f(x)=e−xf(x)=e^{-x} in the one-dimensional half-line.

Solution. Since H0=log⁡(x/y)H_0=\log(x/y), the kernel lies in

12y≤x≤2y,0≤y≤1,0≤x≤2.(SF32) \tfrac12 y\leq x\leq2y,\qquad 0\leq y\leq1, \qquad 0\leq x\leq2. \tag{SF32}
These closed support bounds include the corner. They do not mean that a particular kernel is nonzero at every point of the wedge. The test function has
Uf(v)=ev/2e−ev,∥Uf∥22=∫Reve−2ev dv=∫0∞e−2x dx=12.(SF33) \mathcal Uf(v)=e^{v/2}e^{-e^v},\qquad \|\mathcal Uf\|_2^2 =\int_{\mathbb R}e^v e^{-2e^v}\,dv =\int_0^\infty e^{-2x}\,dx=\tfrac12. \tag{SF33}
The ordinary kernel factor x−1x^{-1} in (SF6) becomes xy/x=y/x\sqrt{xy}/x=\sqrt{y/x}, exactly the factor in (SF7). Omitting the half-density would change the L2 measure and invalidate the packet estimate as used.

Exercise 2. Why taking a fixed root preserves every polynomial decay

Let n=2n=2, so K=12K=12, and suppose Aj≤CL⟨j⟩−LA_j\leq C_L\langle j\rangle^{-L} for every LL. Determine a sufficient exponent LL to ensure that cjc_j from (SF19) decays like ⟨j⟩−10\langle j\rangle^{-10}. Bound the worst denominator occurring in the derivative proof.

Solution. Here K+1=13K+1=13, so L=130L=130 suffices, together with the same polynomial bound on the exponential summand. The inequality (a+b)1/13≤a1/13+b1/13(a+b)^{1/13}\leq a^{1/13}+b^{1/13} for a,b≥0a,b\geq0 follows by expanding the thirteenth power of the right side. Hence cj≤C⟨j⟩−10c_j\leq C\langle j\rangle^{-10}. For derivatives of any total order at most twelve, the worst reciprocal factor is cj−13c_j^{-13}, and

Ajcj−13=D13AjAj+e−1+∣j∣2≤D13.(SF34) A_jc_j^{-13} =D^{13}\frac{A_j}{A_j+e^{-\sqrt{1+|j|^2}}} \leq D^{13}. \tag{SF34}
For a finite-order family with M=3M=3, the additional numerator weight is ⟨ξ⟩36\langle\xi\rangle^{36}. It absorbs all twelve possible factors of order three. Since the off-cone symbols have arbitrary polynomial decay, this finite loss does not change the construction.

Exercise 3. An exact factorization and the role of the input cutoff

On the logarithmic Euclidean space, let b(Y)b(Y) be smooth with bounded derivatives, and let rr be the positive floor from D3. Put a(Y,ξ)=b(Y)r(ξ)a(Y,\xi)=b(Y)r(\xi). Show directly that its operator is multiplication by bb after r(D)r(D). Explain why the tester for the boundary theorem includes the input cutoff on its right.

Solution. In the left Fourier formula,

Op⁡(a)g(Y)=b(Y)(2π)−n∫eiY⋅ξr(ξ)g^(ξ) dξ=b(Y)r(D)g(Y).(SF35) \operatorname{Op}(a)g(Y) =b(Y)(2\pi)^{-n}\int e^{iY\cdot\xi}r(\xi)\widehat g(\xi)\,d\xi =b(Y)r(D)g(Y). \tag{SF35}
Thus the quotient symbol is exactly bb, and the norm bound is ∥Op⁡(a)g∥2≤∥b∥∞∥r(D)g∥2\|\operatorname{Op}(a)g\|_2\leq\|b\|_\infty\|r(D)g\|_2. No derivatives of bb occur in this exact right factorization. Reversing the factors would introduce them; the two orders must not be interchanged.

In the boundary problem, χ\chi is equal to one near the actual input projection, so Tχ=TT\chi=T as a complete kernel identity. The operator r(D)Uχr(D)\mathcal U\chi consequently carries exactly the localized input used in that identity. Its compact difference support turns the compact input projection into a compact output projection by (SF25). Omitting χ\chi would leave a translation-invariant logarithmic multiplier with a noncompact base projection. Placing it on the left would generally destroy the exact cancellation in (SF23).

F0. What the illustration records. The first panel shows the exact closed support bounds in (SF32), with yy horizontal and xx vertical. The marked corner remains part of the boundary kernel. The second panel records the actual order of the maps in (SF23): localize the input, apply the unitary logarithmic density, apply the one positive multiplier, and then the uniformly bounded quotient operator. The support plot is an allowed region, not a claim about nonzero kernel values or a computed solution.

Exact normal support wedge one half y at most x at most two y for y between zero and one, including the corner, alongside the ordered scalar multiplier factorization with its unitary density and bounded quotient.

Finite algebraic checks verify the density identities, ratio map, derivative counts, root exponents and support coordinates. The full-kernel bounds, smooth summation, positivity, exact factorization and proof of the scalar norm estimates are the arguments above.