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The full collared EIT class satisfies the centered range and source interfaces
Statement
Assume the Axiom of Choice, Countable Choice and Dependent Choice. Let , , , and . Use the exact intrinsic Hilbert norm from the collared source-functional lemma, and put Let , and assume for . Set , and choose . Write for the centered mean-zero Neumann voltage sequence space, regarded as a real Hilbert space, and give the sum norm. Let , , and .
There is a globally Lipschitz, continuously Fréchet differentiable map with globally Lipschitz derivative, agreeing for with the centered physical observation . Define Then on , and its inverse are globally Lipschitz, and these facts hold on the admitted set The projected points belong to for .
On the ambient linear space define the proper convex regularizer where the indicator is zero on and elsewhere. On every admitted physical coefficient this is exactly the original quadratic Sobolev penalty. The functional is a subgradient at , and its Bregman distance on is exactly . On every fixed sublevel containing the truth, the VSC holds with and a continuous nondecreasing concave truncated logarithmic index continued constantly above a sufficiently small . Its subadditivity constant may be taken as .
Put and let . For , the projection-coupling constant may be taken as , and For the frozen method choose , and . Then the required compatibility bound holds with In particular, the structural hypotheses of the joint and frozen one-step estimates hold with , the displayed exact regularizer, for the joint method, and the displayed for the frozen method. For frozen rates additionally require , choose , and use the remaining parameter, tolerance and stopping conditions of the frozen rate theorem. This small-neighborhood hypothesis is local around the chosen initial conductivity; it restricts neither the stated Besov truth class nor its logarithmic exponent.
Statement references
Centered Neumann voltage sequences on the three-dimensional ball
H1 logarithmic stability from centered three-dimensional NtD data
Besov smoothness gives the exact collared Sobolev penalty a cutoff source bound
Joint and frozen-Newton objectives for range-invariant relaxations
The joint relaxed objective controls Bregman and range errors
Facts & Assumptions
Given: The choice assumptions and full conductivity, Sobolev, Besov, collar and local-admission data in the Statement.
The centered physical map on uniformly elliptic collared coefficients is globally Lipschitz on each fixed ellipticity class, is continuously Fréchet differentiable there, and has a uniform Lipschitz derivative. Centered Neumann voltage sequences on the three-dimensional ball
Uniform collared classes satisfy stability with modulus in their centered sequence distance. H1 logarithmic stability from centered three-dimensional NtD data
For the exact intrinsic quadratic penalty, the modulus and truth imply a VSC with coefficient and logarithmic exponent in the Statement. The proof treats the exact domain inner product. Besov smoothness gives the exact collared Sobolev penalty a cutoff source bound
Truncated logarithmic indices are concave when the truncation point is small enough, and their conjugates satisfy . Logarithmic source indices and their admissible parameter scales
All three choice assumptions are retained from [F1]–[F4]. The Axiom of Choice, The Axiom of Countable Choice (), The axiom of dependent choice: a relation in which every element is related to something admits an -indexed chain
Proof
Domains for the generic estimates. The canonical maps , , and , , are linear isometries onto and . In the generic one-step estimates, transport the regularizer and subgradient by and the frozen penalty by . The map preserves the dual pairing, so the subgradient inequality verified in step 3.2 transports to . It also preserves the Bregman distance: The penalty is a functional on under and has the required norm there. These are the domains used by the generic joint and frozen estimates.
The space is closed in the intrinsic Sobolev Hilbert space, since convergence there implies convergence and preserves vanishing on the collar. For its elements, zero extension is bounded into by [F3]. Fourier Cauchy–Schwarz gives because . Thus embeds continuously into the bounded collared coefficient space. The set is convex and closed in : convexity preserves the pointwise bounds, and uniform convergence from this embedding preserves them under a norm limit.
Choose a smooth scalar function with , equal to one on and zero outside , and set . Then on , , and globally. All its first and second derivatives are bounded. Put . Since outside and , for every . Moreover, is globally Lipschitz from into and continuously Fréchet differentiable, with derivative and globally Lipschitz derivative; its Taylor remainder is bounded by . Use the centered map [F1] with fixed strict ellipticity bounds and , and denote it by . Since , every is admissible for that map. Define explicitly The chain rule gives . The bounded and Lipschitz derivatives of and the Lipschitz derivative of the centered supplier give all the asserted global bounds for and . For , , so this formula agrees with the centered physical observation.
The identities for and the inverse follow by direct substitution. The map is globally Lipschitz with , so both and have Lipschitz constant at most in the sum norm. In particular . The restriction of a bijection to is a bijection onto ; its projected inverse point has the same coefficient and zero artificial voltage, hence remains in . The extension to all of supplies the global factorization domain required by the original generic hypotheses without changing the physical forward map on any admitted point.
The indicator of the convex set in step 1.1 is convex, and adding the quadratic functional makes proper and nonnegative. For any admitted , expansion of its square gives ; outside the set the subgradient inequality is automatic because the left value is infinite. This proves the asserted subgradient and exact Bregman formula. On a fixed sublevel , the coefficients have bounded intrinsic norm; subtracting the constant background and zero-extending gives a uniform whole-space bound by [F3]. Thus [F2] applies uniformly on that sublevel, including the truth. Applying [F3] yields the VSC source term for small data differences. Replacing the norm argument by its square changes only a fixed constant in the logarithm. Choose small enough and then enlarge to dominate the source inequality also at larger data differences; on the fixed sublevel the absolute linear pairing is uniformly bounded. The truncated logarithmic index in [F4] is then a valid concave VSC index on the entire sublevel.
Concavity and imply subadditivity: for positive , and ; summing gives . Hence . The derivative remainder of has only the second component . Integrating the Lipschitz derivative along the segment gives norm at most . Since and the first component of is , this is at most . No differentiability of the boundary of is needed, since the map was differentiated on the full ambient space.
If , then . Squaring gives a bound by . Because , concavity gives . The displayed therefore proves the full frozen compatibility inequality for every admitted range variable. Its denominator is positive since the logarithmic index is positive away from zero. The stated has the required lower bound with equality and vanishes at zero.
All projected coefficients in have , so one fixed covers their regularizer values and the truth. The preceding steps verify every structural range, domain, Lipschitz, projection, subgradient, VSC, compatibility and penalty hypothesis. With and , the frozen constants are , , and . The bound makes and . The displayed choice of is exactly the required linked-parameter bound because and . Thus the original generic estimates apply on the admitted set with their remaining stated algorithmic hypotheses. The ambient extension and indicator do not change any admitted objective value.
Depends on
- The Axiom of Choice
- The Axiom of Countable Choice ($\mathrm{AC}_\omega$)
- The axiom of dependent choice: a relation in which every element is related to something admits an $\mathbb{N}$-indexed chain
- Centered Neumann voltage sequences on the three-dimensional ball
- H1 logarithmic stability from centered three-dimensional NtD data
- Besov smoothness gives the exact collared Sobolev penalty a cutoff source bound
- Logarithmic source indices and their admissible parameter scales
- Joint and frozen-Newton objectives for range-invariant relaxations
- The joint relaxed objective controls Bregman and range errors
- A frozen Newton step yields a controlled error inequality
Used by
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Sources
- Barbara Kaltenbacher, Convergence rates under a range invariance condition with application to electrical impedance tomography (standard reference, not scraped)
- Frederic Weidling, Variational Source Conditions and Conditional Stability Estimates for Inverse Problems in PDEs (standard reference, not scraped)