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Optimal rate for composite double discrepancy
Open problem
Assume Countable Choice. Let be real or complex Hilbert spaces over one scalar field. Let compact linear maps and have a common singular system indexed by a finite or countable set : , , and are orthonormal bases of , , and , and , , , and with . Put . Let , , , with , where , and . The common system makes and the minimum-norm solutions at their respective stages. For , let and . Assume finite constants satisfy , , and for every ; and, for every , assume a finite constant satisfies for every , where and . Fix and . Let and be decreasing positive sequences with successive ratios in for one fixed . For noisy data with , choose the first indices , when they exist, such that for every , and for every . For fixed factors, filters, parameter sequences and radius , define as the supremum of over all and all satisfying these source, noise, nonzero-data, and stopping-index conditions. Determine the sharp asymptotic order of as whenever this admissible set is nonempty. In particular, is the exponent in the upper bound optimal for fixed , or can it be improved uniformly over this composite class?
Open problem references
Status
As of 2026-10-21, the arXiv record lists v1 only. In §4, Brandt and Horn explicitly leave open whether their a-priori convergence speed is optimal. They separately call the double-discrepancy principle's finite-qualification result suboptimal and state its rate, but do not pose the DDP exponent's sharpness as that explicit open question or give a matching lower bound in Theorem 6. This item retains the DDP sharpness question as its own formulation rather than attributing it to the authors. Under the common singular system, source conditions, finite filter qualification, and both residual rules, the local theorem supplies a conditional two-term upper bound; the source's displayed radius exponent is inconsistent with its proof. Targeted searches for the exact arXiv identifier, title, and composite double-discrepancy optimality found no later resolution as of this date. No lower bound matching the two-stage rate is asserted here.
Remarks
This formulation asks about the deterministic worst-case rate of the specified two-stage residual-selection rule; it is not a claim about optimality among all reconstruction procedures.
Depends on
Used by
Nothing in the library uses this result yet.
Dependency tree · two levels
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Sources
- Christina Brandt and Patrick Horn, Regularisation and Parameter Choice Rules for Composite Linear Inverse Problems, v1 (standard reference, not scraped)