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Positive-Sobolev CGO remainders from a shifted Fourier lattice
Statement
Assume Countable Choice. Fix , and . If has support in and norm at most , there are constants , depending only on , such that for every with and , there is for which Here fractional Sobolev norms on the ball are restriction norms from the whole-space Fourier Sobolev spaces. No boundary condition is imposed. The construction is on a larger cube, so the stated regularity holds on a neighborhood of the closed unit ball.
Statement references
Facts & Assumptions
Given: The choice assumption, exponents, support, potential and null phase in the Statement.
On a finite torus the Fourier characters form a complete orthonormal basis, with Parseval and a surjective coefficient isometry. Multiplication by a fixed unit-modulus exponential gives the shifted basis. The Fourier basis and Parseval's identity on the finite torus
Whole-space Fourier transformation is unitary on . Plancherel theorem
Countable Choice is assumed at [F1]–[F2]. The Axiom of Countable Choice ()
Proof
We give the Sobolev product bounds used below. They hold for periodic functions on a fixed three-dimensional cube, and for the product of a periodic function and a function with one fixed half-integer Fourier shift. The constants can be chosen uniformly under rotations of the cube. Split Fourier frequencies into dyadic shells and write for the corresponding blocks. A shell contains at most lattice points, so Cauchy–Schwarz gives . For and , these estimates prove . For low against high , use and square-sum . For high against low , when use , and when use the uniform bound by ; the critical case has an extra factor , absorbed by . The resulting weighted terms are bounded by or by . For comparable high input shells that produce an output shell , use , obtained from the bound on the product and the number of output frequencies. Multiplication by and summation over gives a summable geometric kernel, since and ; at this case is not being used. Cauchy–Schwarz for the two input shell sequences and the geometric kernel completes the bound.
Rotate so that , where , and choose a fixed cube containing . Put and use the shifted orthonormal basis . For , , its symbol is , with . For , this gives ; for , its real part has magnitude at least . Hence for every real and the coefficient multiplier satisfies for . The Sobolev spaces here are defined by the shifted weighted coefficient norms. Parseval proves these bounds and in distributions inside , first on finite sums and then by convergence.
A second bound is for every . Here the low-high and high-low estimates from step 1.1, with output weight , have the additional decay . For comparable high shells, the output estimate becomes , with and . The geometric kernel has finite sum, and Cauchy–Schwarz bounds the product sequence in by . This proves the claimed bound. All product calculations first hold for finite Fourier sums; the bounds give convergence in the target Sobolev space and identify the product as the distributional limit. Whenever one factor belongs to , , its Fourier coefficients are absolutely summable by weighted Cauchy–Schwarz, so it is a bounded continuous multiplier and this distributional product agrees with the ordinary product.
The periodic and shifted Sobolev norms of the compactly supported potential are bounded by . For completeness, choose a fixed smooth cutoff equal to one on and supported in . Since it multiplies without changing it, each Fourier coefficient of is the convolution of its whole-space Fourier transform with a translate of the rapidly decreasing transform of this cutoff, sampled at an integer or shifted lattice point. Weighted Cauchy–Schwarz, followed by summation over the lattice, bounds the coefficient norm by the whole-space norm: the sums and the corresponding integrals are finite for , and polynomial Sobolev weights are absorbed by increasing . The reverse local bound needed later follows in the same way by multiplying the Fourier series by a smooth cutoff supported inside and equal to one on , then estimating the resulting convolution sum in whole-space weighted . The cutoffs can be chosen radial before rotation, so all constants are independent of the phase direction.
Put and . Split the periodic potential into by retaining frequencies of size at most in . Then , whereas has bounded Sobolev norms of every order with bounds depending only on . Choose , depending only on , so that as a multiplication-composition operator has norm at most both on shifted and on shifted . On this follows from the product bound in step 1.1, with multiplier and , and the bound of step 1.2. On it follows from step 2.1 with and the same bound. Next choose large enough, depending only on , that has norm at most on both spaces, using the smooth multiplier bound from step 1.1 and the bound from step 1.2. Thus has inverse given by a convergent geometric series, of norm at most two, on both spaces.
Define in shifted . The forcing in the last position is the actual compactly supported function on , represented in the shifted basis; the multiplication operators use the periodic representation of the same function. These agree pointwise inside . Step 1.2 with and gives . Since , weighted Cauchy–Schwarz for its coefficients gives . This solution is also the unique shifted solution, by the second invertibility statement in step 3.1; using step 1.2 with gives . Finally, its equation is ; since and , the bound from gives , enlarging the threshold to keep .
Applying to the equation in step 4.1 gives in the interior of . Direct conjugation and show this is exactly . The local comparison in step 2.2 transfers the fractional bounds to restriction norms on , and restriction gives the integer bound there. Pulling back the initial rotation preserves the whole-space potential norm, the support ball, and the Euclidean PDE. Since , step 4.1 yields all displayed estimates. The construction was on a fixed larger cube, so it imposes no boundary condition on the unit ball and supplies regularity on its full neighborhood.
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Sources
- Frederic Weidling, Variational Source Conditions and Conditional Stability Estimates for Inverse Problems in PDEs (standard reference, not scraped)
- Mikko Salo, Calderon problem, lecture notes (standard reference, not scraped)