\chapter{Mathematical contribution, dependencies, and limits} \section{Established foundations and the proposed synthesis} The soul theorem of Cheeger and Gromoll, Perelman's soul-conjecture theorem, O'Neill's submersion equations, and the Ambrose--Singer theorem provide the classical Riemannian background \cite{cheeger-gromoll,perelman,oneill,ambrose-singer}. Associated-bundle constructions with large normal holonomy are already part of that literature \cite{tapp}. The existence of nonnegative curvature with nontrivial normal holonomy is not claimed as a new discovery here. There is also an established quantitative study of loop length and holonomy. Sol\'orzano's holonomic spaces explicitly retain a norm on the holonomy group defined by the least length of a realizing loop, rather than recording only the abstract group \cite{solorzano}. Thus the distinction between holonomy as a group and holonomy with a length cost is not itself new. The present problem further specifies a single marked ray, scalar observations, finite-dimensional frame criteria, and a noise experiment. Regular simplices and tight frames are classical \cite{benedetto-fickus}. Finite-dimensional realization from input--output quantities has a classical systems-theoretic history \cite{HoKalman}. The explicit Gaussian simulation kernel is an application of the comparison-of-experiments framework \cite{Blackwell}. The manuscript proves its precise special case rather than attributing novelty to that framework. The candidate mathematical contribution is the conjunction of the following proved statements in one compatible observation model: an explicit fixed-soul degeneration; a global bound with the factor $\lambda(1-\lambda)$; a uniform sharp small-loop constant; an exact circle writer; an exact conversion of the maximal scalar deficit into optimal Gram and exterior-sensor resources; the resulting two-level sensitivity law; and a sharp statistical cost under a fully stated Gaussian experiment. The finite-radius comparison supplies a geometric calibration compatible with weak signals rather than an unrelated absolute error estimate. These claims of derivation and proof should not be read as a certified historical-priority statement. A targeted primary-source search was performed for this release, but it is not a comprehensive classification of all work on holonomy control, inverse connection problems, experimental design, or statistical comparison. Independent specialist review is still required to assess priority and the most appropriate publication framing. \section{Proof dependency map} The main statements have a short dependency structure despite the number of applications. The quotient metric is established independently of the observation algebra. Its connection formula then feeds the transport ODE. The two pure-gauge endpoints and the second parameter derivative give the uniform quadratic bound. Normal coordinates, a sharp alternating-area inequality, and the exact circle construction give the sharp local scalar law. No numerical fit enters that chain. The exact scalar-resource bridge uses only bounded-length compactness, stabilizer symmetry, and cap frame optimization. It does not require an explicit finite-length formula for the maximizing loop. Exterior singular values then provide deterministic inverse bounds. The Gaussian theorem uses only the interval of accessible scalar gaps and a comparison kernel; the geometric asymptotic is inserted afterward. This separation prevents a weakness in a numerical example from being mistaken for a dependency of the main theorem. \begin{longtable}{>{\raggedright\arraybackslash}p{.28\textwidth}>{\raggedright\arraybackslash}p{.31\textwidth}>{\raggedright\arraybackslash}p{.32\textwidth}} \toprule Statement&Essential inputs&What is not required\\ \midrule\endhead Fixed soul and full normal holonomy&Quotient metric; curvature span; standard submersion and holonomy results&An experimental model or scalar decoder\\ Uniform scalar asymptotic&Parameter interpolation; area bound; exact circle writer&Finite-length global optimality of that circle\\ Exact Gram/exterior bridge&Scalar extremum; compactness; stabilizer action; cap optimization&A reconstruction algorithm that discovers the optimizer without calibration\\ Noisy target recovery&Known error bounds; positive true Gram matrix&Independent entry noise or a Gaussian assumption\\ Exact adaptive risk&Two known hypotheses; reset scalar Gaussian shots; fixed sample size&Full matrix reconstruction or a second physical ray\\ Finite-radius comparison&Explicit connection metric; totally geodesic fibers; local convex neighborhoods&A universal detector-noise law\\ \bottomrule \end{longtable} \section{Precisely what is complete} All numbered statements in the manuscript are accompanied by proofs or an explicit reference to an earlier proved statement. The principal external Riemannian theorems are identified rather than silently reproved. The computational library and its executed checks are supplied in readable source form. The manuscript, implementation, example tables, theorem ledger, and machine-readable verification record form a complete release for these stated results. The evidence does not include a proof-assistant formalization, independent peer review, an optical experiment, or a benchmark of a physical computing system. The percentage $142/142=100\%$ describes the listed automated checks only. It is not a numerical probability that the mathematics is correct and not a percentage of worldwide novelty verification. \section{Boundaries that do not obstruct the proved results} The exact finite-length optimum $D_\lambda(L)$ is not expressed in an elementary closed form. The circle formula gives an explicit admissible loop and the correct sharp leading constant. The exact resource identities remain valid in terms of $D_\lambda(L)$ without solving the separate finite-length isoholonomic optimization problem. The theorems are not a classification for arbitrary souls or arbitrary normal connections. The fixed-soul family is sufficient to disprove the specified universal conditioning claim and to derive a complete local observation law. Additional curvature nondegeneracy, derivative, or control assumptions could yield different positive bounds in other families. Likewise, scalar testing does not determine every feature of an unknown ambient manifold. The statistical null and alternative are specified connections on the same marked experiment. Access to the ambient metric, external frames, multiple initial vectors, or independent curvature data would be a different experiment and might distinguish the hypotheses more efficiently. \section{The central conclusion} For this explicit Riemannian family, the operational content of hidden holonomy is not captured by the group alone. One scalar extremum links geometric displacement, matrix conditioning, and Gaussian testing risk: \[ D_\lambda(L) \quad\longrightarrow\quad \Gamma_\lambda(L)=\Omega_\lambda(L) =\frac d{d-1}(2D_\lambda(L)-D_\lambda(L)^2) \quad\longrightarrow\quad \Phi\!\left(-\frac{\sqrt nD_\lambda(L)}{2\sigma}\right). \] The arrows are exact theorems under their stated cap and noise assumptions. The sharp local coefficient in $D_\lambda(L)$ turns them into explicit length and noise laws. This is the substantive endpoint of the manuscript: qualitative geometric freedom can persist while every bounded-resource scalar observation becomes arbitrarily weak, and the weakening has a computable, optimally attainable leading scale.