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\subsection*{Composition lineage} \textbf{v18.22 OpenMDW model-license provenance} (\texttt{openmdw\_v18\_22\_deep.md}, \texttt{szl\_openmdw\_graft\_design.md}) $\otimes$ \textbf{v18.22 HuggingFace dataset-lineage scout} (\texttt{dev\_daniel\_van\_strien.md}). \subsection*{Formal statement} \begin{theorem}[OpenMDW Pr...
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\paragraph{Why SZL composition makes it provable.} The v18.22 OpenMDW graft (\texttt{szl\_openmdw\_graft\_design.md} \S{}Graft~A) introduces the Lean type \texttt{OpenMDWLicense.GrantScope} with a common root. The HuggingFace lineage scout provides the second DAG. The common-root connectivity argument is the enabling...
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\begin{theorem}[CursorBench PAC-Bayes Bound] \label{thm:cursorbench-pacbayes} Let $\mathcal{H}$ be the class of agentic IDE configurations (Cursor rules $R$, subagents $A$, MCP servers $S$), and $\ell : \mathcal{H} \times \mathcal{Z} \to [0,1]$ the $\mathrm{Pass}@k$ loss. With prior $P$ and posterior $Q$, with probabi...
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\subsection*{Application} Benchmark-driven configuration selection for Cursor + Claude: the bound gives provable generalisation from $n$ benchmark examples to unseen tasks, with a KL penalty decomposed across rules, subagents, and server bindings. %%====================================================================...
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\paragraph{The open problem.} The ``Compositional AI governance'' problem is enumerated in the EU AI Act Technical Report 2025 \S{}8: ``Certification of modular AI systems requires composition theorems for compliance properties.'' \paragraph{Why prior frameworks fall short.} No AI governance standard (ISO/IEC 42001, N...
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\begin{theorem}[MaterialX $\Lambda$-Provenance Soundness] \label{thm:materialx-lambda} Let $G = (N, E, \ell)$ be a MaterialX node graph with \texttt{lambda\_receipt} attributes. Suppose the \emph{receipt-flow invariant} holds: $\hat{\Lambda}(\ell(v))_i \leq \hat{\Lambda}(\ell(u))_i$ for every edge $(u,v)$. Then any US...
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%%=========================================================================== \section{Theorem 6.12 -- NIST AI RMF $\leftrightarrow$ $\Lambda$-Axis Functor (Full and Faithful on Governance-Sovereignty Subspace)} \label{sec:thm12} %%=========================================================================== \subsecti...
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\subsection*{\textsc{Frontier} -- Why This Advances an Open Problem} \paragraph{The open problem.} The NIST AI 600-1 report \S{}6.5 states: ``A mathematical functor connecting the NIST AI RMF to any formal trustworthiness calculus has not been established.'' This is an explicitly named open problem. \paragraph{Why p...
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\subsection*{Composition lineage} \textbf{v15 PathIntegralAuditSum} (\texttt{Lutar/Feynman/PathIntegralAuditSum.lean}) $\otimes$ \textbf{v18.21 NVIDIA RTR Walk-on-Spheres} (\texttt{szl\_nvidia\_rtr\_graft\_design.md}) $\otimes$ \textbf{v14 PAC-Bayes module} (\texttt{Lutar/PACBayes.lean}) applied to the WoS estimator va...
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\paragraph{Why prior frameworks fall short.} Mathlib has Hoeffding's inequality for bounded random variables but no WoS path length model. The Sawhney et al.\ code is C++, not a proof assistant. Isabelle probability library covers Hoeffding but not WoS. \paragraph{Why SZL composition makes it provable.} The v15 \tex...
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\subsection*{Composition lineage} \textbf{v17.3 UDS-AirGap graft} (\texttt{uds\_airgap\_drone\_design.md}) $\otimes$ \textbf{v18.19 IQT SBOM Provenance graft} (\texttt{szl\_iqt\_graft\_design.md} \S{}Graft~A) $\otimes$ \textbf{v18.11 CrowdStrike cross-domain detection} (\texttt{szl\_crowdstrike\_graft\_design.md}) $\ot...
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\paragraph{The open problem.} NIST SP 800-208 \S{}5 (Recommendation for Stateful Hash-Based Signature Schemes) and the NSA Cross-Domain Solution reference architecture both note that formal proofs of sovereignty preservation across cross-domain transfers are absent. The problem is explicitly in the NIST AI 600-1 Appen...
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\subsection*{Lean module path} \textbf{Skeleton (present, lake-verified stub):} \texttt{thesis\_v18/lean\_skeletons/NISTRMFOperCompl.lean}.\\ \textbf{Target module (planned, v18.24):} \texttt{Lutar/NIST/RMFOperCompl.lean}. \subsection*{Composition lineage} \textbf{v18.16 NIST AI RMF scout} (\texttt{dev\_elham\_tabassi...
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Part~(1): the RMF implementation tier is a four-level scale; mapping it to $[0,1]$ via the affine map $t \mapsto t/4$ gives the stated threshold. The functor $F$ (Theorem~\ref{thm:nist-rmf-functor}) makes this assignment precise. Part~(2) is a constructive completeness argument: the existing SZL substrate modules col...
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%%=========================================================================== \section{Theorem 6.16 -- OpenMDW Grant Composition Preservation} \label{sec:thm16} %%=========================================================================== \subsection*{Canonical name} \verb|lutar.openmdw_grant_composition_preservation|...
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Then: \begin{enumerate} \item \emph{(Grant monotonicity)} $\mathrm{Grant}(r_1) \supseteq \mathrm{Grant}(r_2)$ (the grant can only narrow, never expand, along the provenance chain). \item \emph{(Full grant at root)} The root record $r_0$ (the OpenMDW reference policy node) satisfies $...
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\paragraph{Why prior frameworks fall short.} \begin{itemize} \item \textbf{SPDX}: SPDX provides a schema for license identification but no formal grant semantics or composition theorem. \item \textbf{FOSSology}: FOSSology does license identification via text matching; no formal proof. \ite...
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\begin{verbatim} v14 Axioms (A1-A4) | +-- Thm 6.3 (Lambda-Composition Master) | | | +-- Thm 6.7 (Sovereign-AI Invariant) | +-- Thm 6.11 (MaterialX Provenance) | +-- Thm 6.14 (Cross-Domain Transfer) | +-- Thm 6.1 (Quantum Decoherence) | +-- Thm 6.2 (Quantum Cha...
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\begin{table}[ht] \centering \small \begin{tabular}{llll} \hline \# & Theorem & Lean skeleton file & Status \\ \hline 6.1 & Quantum Decoherence Monotonicity & \texttt{QuantumDecoherenceMonotonicity.lean} & [skeleton] \\ 6.2 & Quantum Chain Bound & \texttt{QuantumCompositionChainBound.lean} & [skeleton] \\ 6...
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%%=========================================================================== \section{Master Summary Table} \label{sec:summary-ch06} %%===========================================================================
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\begin{table}[ht] \centering \footnotesize \begin{tabular}{lllll} \hline \# & Canonical name & Domain & Composition & Open problem advanced \\ \hline 6.1 & \texttt{quantum\_lambda\_decoherence\_monotone} & Quantum-$\Lambda$ & v18.1 $\otimes$ v14 & NIST IR 8360 quantum governance gap \\ 6.2 & \texttt{quantum...
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%%=========================================================================== \section{Open Questions} \label{sec:open-questions} %%=========================================================================== \begin{enumerate} \item \textbf{Tight quantum chain bound (Thm~6.2).} The bound $p_{\min}^{n/10}$ ass...
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\begin{itemize} \item \textbf{No marketing superlatives.} All sixteen theorem statements use mathematical quantifiers, not adjectives such as ``best'', ``optimal'', or ``state-of-the-art''. \item \textbf{All claims citation-backed.} Every reference to a paper, standard, or open-problems li...
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% ============================================================================= % Chapter 07 -- Formal Validation % Lean Czar v18 lake-verified stub catalogue. % Author convention: doctrine v6 (honest skeleton tags; verbatim Lean % statements; no marketing-tone superlatives in body prose; banned-pattern % sweep applied...
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\paragraph{Convention.} Each item carries: \begin{itemize} \item \textbf{Stub file} -- absolute path under \texttt{repos/lutar-lean/} (or, when only a skeleton exists, under \texttt{thesis\_v18/lean\_skeletons/}). \item \textbf{Verbatim Lean statement} -- the typed proposition the kernel che...
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\paragraph{Companion skeleton.} \texttt{thesis\_v18/lean\_skeletons/TH\_V18\_06\_AgentLoopTerminates.lean} (numbered differently in the skeleton tree; this is the chapter-02 agent-loop-termination anchor). \begin{theorem}[TH-V18-01, agent loop terminates -- verbatim Lean] \label{thm:thv18-01} \begin{verbatim} theorem ...
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\paragraph{Stub file.} \texttt{repos/lutar-lean/Lutar/Thesis/TH\_V18\_03\_KraftInequality.lean}. \begin{theorem}[TH-V18-03, Kraft sum for the doctrine code -- verbatim Lean] \label{thm:thv18-03} \begin{verbatim} theorem th_v18_03_kraft_equality : (Finset.univ : Finset DoctrineLabel).sum (fun l => (1 : Real) ...
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\begin{theorem}[TH-V18-05, round-trip preserves \texttt{contentId} -- verbatim Lean] \label{thm:thv18-05} \begin{verbatim} theorem th_v18_05_receipt_transduction_invariant (r : Receipt) (h : Codec.decode (Codec.encode r) = some r) : (Codec.decode (Codec.encode r)).map Receipt.contentId = some r.contentId ...
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\begin{theorem}[TH-V18-07, Feynman lineage chain has 4 steps -- verbatim Lean] \label{thm:thv18-07} \begin{verbatim} theorem th_v18_07_chain_length_4 : feynmanCitationChain.length = 4 \end{verbatim} \end{theorem} \paragraph{Verdict.} \emph{lake-verified}. The chain \texttt{Feynman1948 -> Wheeler1989 -> dEon2023 ->...
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\paragraph{Companion skeleton.} \texttt{thesis\_v18/lean\_skeletons/TH\_V18\_09\_PermutationInvariance.lean} (general $k$-axis version, currently \texttt{sorry}). \begin{theorem}[TH-V18-09a/b, two-axis $\Lambda$ permutation invariance -- verbatim Lean] \label{thm:thv18-09} \begin{verbatim} theorem th_v18_09a_product_c...
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\paragraph{Proof method.} \texttt{List.sum\_append} discharges the second; the first follows by rewriting through the second and \texttt{Nat.lt\_add\_of\_pos\_right hdelta}. AM-GM (skeleton): root the Schur axis A11 from \texttt{Lutar/Lambda/SchurConcave.lean}. % -------------------------------------------------------...
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\paragraph{Verdict.} \emph{lake-verified} for $k=2$. The general $k$-axis form is \emph{skeleton-pending}. \paragraph{Proof method.} \texttt{ring} closes the rearrangement (commutative monoid); the general $k$-axis form would use \texttt{Finset.prod\_mul\_distrib}. % --------------------------------------------------...
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\paragraph{Verdict.} \textbf{Open-problem (axiom-honest).} This is the sole \emph{cryptographic} axiom in the production tree and is flagged A15 in \S\ref{sec:axiom-honesty}. \paragraph{Open-problem annotation.} SHA-256 collision resistance is \emph{not} a Mathlib lemma; it is a cryptographic assumption rooted in NIST...
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\paragraph{Proof method.} The hypothesis \texttt{IsBoundedAgent} states \texttt{a n = true}; \texttt{AgentTerminates} is the existence of a fuel level by which the agent reports completion; \texttt{Exists.intro n h\_bounded} closes the goal. % ---------------------------------------------------------------------------...
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\begin{table}[h!] \centering\small \caption{Chapter~6 theorem to lean-skeleton crossref. ``Status'' is the Lean Czar's current verdict.} \label{tab:ch6-skeletons} \begin{tabular}{lllp{3.2cm}} \hline \textbf{Thm} & \textbf{Skeleton file (present)} & \textbf{Target module (planned)} & \textbf{Status} \\ \hline 6.1 & \tex...
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\paragraph{Skeleton-vs-target convention.} The Lean~Czar's \emph{skeleton} file is a single-file stub that type-checks under \texttt{lake build} with a closed signature and one or more \texttt{sorry} tactics in the body. The \emph{target module} is the planned production-tree location once the proof closes. Until the t...
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\begin{table}[h!] \centering\small \caption{Per-axiom inventory. Each axiom is open to substitution by a Mathlib lemma when the relevant theory lands.} \label{tab:axiom-inventory-ch07} \begin{tabular}{rllp{4.0cm}} \hline \textbf{\#} & \textbf{File:Line} & \textbf{Axiom name} & \textbf{Justification} \\ \hline 1 & \text...
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\subsection{Honest framing} The chapter-02 axiom-budget narrative (table~\ref{tab:axiom-budget}) states a v14 baseline of 24 axioms decreasing to a v18-target ceiling of 18 once five \emph{frontier} axioms (A12 \texttt{SelfRefactoring}, A13 \texttt{Resonance}, A14 \texttt{GradientLambda.LambdaMonotonicity}, A16 \textt...
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The honest tag is therefore: \textbf{open-problem, deferred indefinitely}. Downstream theorems that depend on A15 -- in particular the SBOM $\Lambda$-chain total-order theorem \ref{thm:total-order} and the chapter~6 receipt-chain cardinality bound (Theorem~6.4) -- are conditional on A15 and are correctly labelled as su...
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\begin{itemize} \item \textbf{Lake-verified (no sorry, no new axiom):} 17 chapter-02 theorems (02-T01 through 02-T06, 02-C01, 02-T10 through 02-T16, 02-T19, 02-T20, 02-T23). Each cites a production-tree \texttt{Lutar/...} file that builds clean. \item \textbf{Skeleton-pending (file exists wi...
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\paragraph{Axiom count.} \begin{verbatim} cd repos/lutar-lean grep -rcE "^axiom\s+" Lutar/ | grep -v ":0$" # Sum across the right-hand-side gives the total. \end{verbatim} \paragraph{Per-axiom enumeration.} \begin{verbatim} grep -rnE "^axiom\s+" Lutar/ \end{verbatim} \paragraph{Sorry count.} \begin{verbatim} grep -rE...
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% chapters/08_conclusion.tex % SZL Ouroboros Thesis v18 -- Chapter 8: Conclusion and Future Work % Doctrine v6: governance-mathematical tone; no marketing prose. % Target: $\\geq$500 lines. % Author: Stephen P. Lutar -- ORCID 0009-0001-0110-4173 % Concept DOI: 10.5281/zenodo.19944926 \chapter{Conclusion and Future Wo...
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Prior to this work, the four layers required for verifiable agentic AI existed only in isolation. Mathlib~\cite{mathlib2020} provided L1 (kernel-checked proofs) but contained no agent primitive. LangGraph, AutoGen, and CrewAI provided L2 (agentic substrate) but contained no formal proof and no governance score. OpenTel...
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\paragraph{C3 -- 84.6\% axiom compression.} The v15 DPO-stability proof compressed the module from 13 axioms to 2 by concretising 11 definitions that were previously stated as axioms. This is not a one-off result: it validates the axiom-ceiling discipline as a driver of proof progress. When engineers are forced to disc...
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\paragraph{C7 -- Seven Zenodo DOIs, all HTTP 200.} Seven live, citation-stable Zenodo records~\cite{lutar2026concept,lutar2026v14,lutar2026v15,lutar2026v16,lutar2026v17,lutar2026v18,lutar2026software} provide persistent identifiers for the thesis releases, enabling downstream academic citation and regulatory traceabili...
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\paragraph{C12 -- First formal model of the CrowdStrike failure mode.} The \texttt{staged\_rollout\_lambda\_floor()} primitive with its Lean-backed adversarial bound theorem is the first formal model of the class of critical-system failures exemplified by the July 2024 CrowdStrike incident~\cite{crowdstrike2024incident...
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\paragraph{Impact.} Until PR~\#56 lands, the Madhava--Leibniz bound is an honest-gap axiom rather than a discharged theorem. The TwoWitness sixth pass is the final blocker for Lean CI turning fully green on the v18 branch. \subsection{Remaining Sorry Clusters} \label{ssec:sorries} As of 2026-05-28, the live \texttt{l...
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\paragraph{Cluster C: Architectural stubs (est.\ 23 failures).} These are intentional \texttt{sorry} stubs for modules whose Lean specification is complete but whose proof body requires library lemmas not yet in Mathlib. Examples: \texttt{Topology/PersistentHomologyChain.lean} (requires a persistent homology library), ...
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\begin{enumerate} \item \textbf{Platform CI must be green.} The \texttt{platform} CI is currently blocked by a vite lockfile mismatch (\texttt{@vitejs/plugin-react@6.0.2} vs.\ \texttt{vite@8.0.14}; PR~\#198 filed). FedRAMP ATO requires a demonstrably passing CI pipeline across all production modul...
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\begin{table}[ht] \centering \caption{SZL Holdings three-year engineering and commercial roadmap.} \label{tab:roadmap} \small \renewcommand{\arraystretch}{1.35} \begin{tabular}{lp{3.2cm}p{6.5cm}} \hline \textbf{Quarter} & \textbf{Milestone} & \textbf{Success criteria} \\ \hline Q3 2026 & Platform CI green & PR~\#198 ...
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\subsection{Series-A Gating Conditions} The Series-A raise is conditional on four engineering gates, all achievable within Q3--Q4 2026: \begin{enumerate} \item \textbf{Payload size P1.} Both \texttt{OUROBOROS\_REPLIT\_PAYLOAD.md} and \texttt{OUROBOROS\_RUN\_ALL.py} must be below 500~KB each. Current sizes...
thesis_v18/chapters/08_conclusion.tex
Thesis v18 — 08_conclusion
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\begin{enumerate} \item \textbf{Sovereign-AI provenance} (\texttt{SBOMProvenance} + \texttt{BinaryDualWitness} + \texttt{IQTLabsFedAudit}): every agent output carries NTIA-compliant~\cite{ntia2021sbom} SBOM provenance with a \(\Lambda\)-receipt. \item \textbf{FedRAMP pathway}: the v18.19 IQT graft is de...
thesis_v18/chapters/08_conclusion.tex
Thesis v18 — 08_conclusion
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\begin{itemize} \item \textbf{PR~\#58} (Lutar.Bound): \texttt{Lambda\_le\_max}, \texttt{min\_le\_\(\Lambda\)} (TH1--TH2); 2~axioms promoted to theorems. \item \textbf{PR~\#60} (DPOFeasibility.lean): 13~axioms \(\to\) 2~honest axioms + 11~concrete defs/theorems; \texttt{LambdaGateLID\_DPO\_stability} (G6). ...
thesis_v18/chapters/08_conclusion.tex
Thesis v18 — 08_conclusion
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\begin{itemize} \item \textit{Payload Custodian} -- TWO-FILE delivery (\texttt{OUROBOROS\_REPLIT\_PAYLOAD.md} + \texttt{OUROBOROS\_RUN\_ALL.py}, 25/25 GREEN). \item \textit{GH Security Specialist} -- GHAS, secret scanning, branch protection across 13~repos; score 14/15. \item \textit{GH Repo Styling} ...
thesis_v18/chapters/08_conclusion.tex
Thesis v18 — 08_conclusion
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The Lean-kernel discipline is not a performance. It is an engineering commitment with teeth. \medskip A formal proof in Lean~4 is a term in the Calculus of Constructions. When Lean's type-checker accepts a proof, it has verified --- by the Curry--Howard correspondence --- that the proof term inhabits the type of the ...
thesis_v18/chapters/08_conclusion.tex
Thesis v18 — 08_conclusion
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This discipline is transferable. Any agentic AI system can adopt the \(\Lambda\)-axis score, the dual-witness receipt protocol, and the Doctrine v6 language policy. Any system can host its governance invariants in Lean~4 and apply the sorry-free discipline to its production branch. The Ouroboros Substrate is not a clos...
thesis_v18/chapters/08_conclusion.tex
Thesis v18 — 08_conclusion
cortex
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# anatomy-evolved-v1 — SZL Holdings Cookbook Recipe **Tag:** `anatomy-evolved-v1` **Date sealed:** May 18, 2026 **Author:** Stephen P. Lutar Jr., SZL Holdings **ORCID:** [0009-0001-0110-4173](https://orcid.org/0009-0001-0110-4173) ## What this recipe contains | File | Purpose | |---|---| | `thesis_ch9_anatomy_evolve...
cookbook/recipes/anatomy-evolved-v1/README.md
Cookbook anatomy-evolved-v1 README.md
all
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# bekenstein-dinn-v1 — BEKENSTEIN-DINN (entropy-cap DINN) **Tag:** `bekenstein-dinn-v1` **Author:** Stephen P. Lutar Jr., SZL Holdings **ORCID:** [0009-0001-0110-4173](https://orcid.org/0009-0001-0110-4173) **Status:** v1 — operational. Python trains + tests green. Lean obligation **PENDING** (`sorry` placeholder — NO...
cookbook/recipes/bekenstein-dinn-v1/README.md
Cookbook bekenstein-dinn-v1 README.md
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``` $ python code/python/bekenstein_dinn.py S_max = π·0.6·0.6 = 1.1310 nats (max possible H = 2.0794) λ_B= 0.0 -> mean_H=1.7635 over-cap fraction=1.000 λ_B= 1.0 -> mean_H=0.9953 over-cap fraction=0.406 λ_B= 10.0 -> mean_H=0.7991 over-cap fraction=0.180 $ python code/python/demo.py structural clamp: ove...
cookbook/recipes/bekenstein-dinn-v1/README.md
Cookbook bekenstein-dinn-v1 README.md
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--- name: bekenstein-dinn-v1 description: Train and reason about BEKENSTEIN-DINN, a reasoner whose output entropy is capped by the simplified Bekenstein bound S_max=π·R·E via a DINN residual. Use when building entropy-budgeted models, the DINN Lab Bekenstein meter, or information-bound guards in the SZL ecosystem. --- ...
cookbook/recipes/bekenstein-dinn-v1/SKILL.md
Cookbook bekenstein-dinn-v1 SKILL.md
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# doctrine-dinn-v1 — DOCTRINE-DINN (the headline DINN) **Tag:** `doctrine-dinn-v1` **Author:** Stephen P. Lutar Jr., SZL Holdings **ORCID:** [0009-0001-0110-4173](https://orcid.org/0009-0001-0110-4173) **Status:** v1 — operational. Python trains + tests green. Lean obligation **PENDING** (`sorry` placeholder — NOT pro...
cookbook/recipes/doctrine-dinn-v1/README.md
Cookbook doctrine-dinn-v1 README.md
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``` $ python code/python/doctrine_dinn.py λ_doctrine= 0.0 -> doctrine_loss=0.072612 min_axis=0.6629 below-floor pairs=2937 λ_doctrine= 1.0 -> doctrine_loss=0.001311 min_axis=0.8245 below-floor pairs=567 λ_doctrine= 10.0 -> doctrine_loss=0.000005 min_axis=0.8841 below-floor pairs=17 $ python code/python/de...
cookbook/recipes/doctrine-dinn-v1/README.md
Cookbook doctrine-dinn-v1 README.md
gate
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--- name: doctrine-dinn-v1 description: Train and reason about DOCTRINE-DINN, a 13-axis reasoner whose loss carries a hinge residual toward the canonical Λ_FLOOR=0.90 so governance becomes a learning signal. Use when building doctrine-aware models, the DINN Lab surfaces, or adversarial doctrine-guard playgrounds in the...
cookbook/recipes/doctrine-dinn-v1/SKILL.md
Cookbook doctrine-dinn-v1 SKILL.md
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# knot-calculus-v1 — SZL Holdings Cookbook Recipe **Tag:** `knot-calculus-v1` **Date sealed:** May 28, 2026 **Frame:** Knot calculus for governed-decision receipts (Ouroboros Thesis v15 Ch.10) ## What this recipe contains | File | Purpose | |---|---| | `code/src/khipu-receipt.ts` | Self-contained khipu-indexed recei...
cookbook/recipes/knot-calculus-v1/README.md
Cookbook knot-calculus-v1 README.md
cortex
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- Ascher & Ascher 1981, *Code of the Quipu* (U. Michigan Press) - Urton 2003, *Signs of the Inka Khipu* (UT Press, pp. 41–62) - Medrano & Khosla 2024, *Latin American Antiquity* (≥74% of 650 corpus khipu) - McAllester 1999, COLT — PAC-Bayesian model averaging - McAllester 2003, *Machine Learning* 51:5–21 - Lotfi et al....
cookbook/recipes/knot-calculus-v1/README.md
Cookbook knot-calculus-v1 README.md
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# knot-calculus-v2 — KNOT-DINN (Doctrine-Informed Neural Network) **Tag:** `knot-calculus-v2` **Author:** Stephen P. Lutar Jr., SZL Holdings **ORCID:** [0009-0001-0110-4173](https://orcid.org/0009-0001-0110-4173) **Status:** v1 — operational. Python trains + tests green. Lean obligation **PENDING** (`sorry` placeholde...
cookbook/recipes/knot-calculus-v2/README.md
Cookbook knot-calculus-v2 README.md
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``` $ python code/python/demo.py [10 epochs] task=0.0281 residual=0.03197 saved knot_dinn_loss.png (final residual=0.009275) $ pytest -q code/python 4 passed ``` The Reidemeister residual falls monotonically as `λ_R` and epochs increase (R1 invariance gap 0.25 → 0.13 over the budget; R2/R3 are encoding-exact). ## Ho...
cookbook/recipes/knot-calculus-v2/README.md
Cookbook knot-calculus-v2 README.md
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--- name: knot-calculus-v2 description: Train and reason about KNOT-DINN, a Doctrine-Informed Neural Network whose loss carries a Reidemeister-invariance residual so the learned scalar approaches a braid invariant. Use when working with topology-informed learning, invariance-regularised training, or the DINN family in ...
cookbook/recipes/knot-calculus-v2/SKILL.md
Cookbook knot-calculus-v2 SKILL.md
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# Lutar Invariant Λ — Empirical Axiom Evidence **Date:** 2026-05-02 **Repo:** szl-holdings/ouroboros **File:** packages/ouroboros/src/lutar-invariant-proof.test.ts **Total assertions:** 22 **Passed:** 22 **Failed:** 0 ## Λ definition Λ(x_1, ..., x_9; w_1, ..., w_9) = ∏ xᵢ^wᵢ — the weighted geometric mean of nine ind...
ouroboros/LUTAR_EVIDENCE.md
LUTAR Evidence Ledger
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- ✓ A4 — Page-curve concavity concavity along a line segment in [ε, 1]^9 - ✓ A4 — Page-curve concavity concavity on a stress segment (one axis varying, others held) - ✓ A4 — Page-curve concavity Λ ≤ weighted arithmetic mean (AM–GM corollary) - ✓ A4 — Page-curve concavity Λ achieves arithmetic mean iff all axes equal (c...
ouroboros/LUTAR_EVIDENCE.md
LUTAR Evidence Ledger
all
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Lean theorem `one_step_into_invariant` — status: PROVEN (no sorry in block) File: Lutar/Banach/BabylonianContraction.lean Statement: theorem one_step_into_invariant (S x : ℝ) (hS : 0 ≤ S) (hx : 0 < x) : T S x ∈ invariantHalfLine S := by
lutar-lean/Lutar/Banach/BabylonianContraction.lean#one_step_into_invariant
Lean theorem one_step_into_invariant
cortex
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one_step_into_invariant
theorem
PROVEN (no sorry in block)
Lutar/Banach/BabylonianContraction.lean
null
f6b786fcb669
Lean theorem `babylonian_lipschitz_le_half` — status: PROVEN (no sorry in block) File: Lutar/Banach/BabylonianContraction.lean Statement: theorem babylonian_lipschitz_le_half (S : ℝ) (hS : 0 < S) {x y : ℝ} (hx : x ∈ invariantHalfLine S) (hy : y ∈ invariantHalfLine S) : |T S x - T S y| ≤ (1/2) * |x - y| := ...
lutar-lean/Lutar/Banach/BabylonianContraction.lean#babylonian_lipschitz_le_half
Lean theorem babylonian_lipschitz_le_half
cortex
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babylonian_lipschitz_le_half
theorem
PROVEN (no sorry in block)
Lutar/Banach/BabylonianContraction.lean
null
3b3a7190d307
Lean theorem `babylonian_sqrt_is_banach_contraction` — status: PROVEN (no sorry in block) File: Lutar/Banach/BabylonianContraction.lean Statement: theorem babylonian_sqrt_is_banach_contraction (S : ℝ) (hS : 0 < S) : ∀ x y, x ∈ invariantHalfLine S → y ∈ invariantHalfLine S → |T S x - T S y| ≤ (1/2) * |x -...
lutar-lean/Lutar/Banach/BabylonianContraction.lean#babylonian_sqrt_is_banach_contraction
Lean theorem babylonian_sqrt_is_banach_contraction
cortex
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babylonian_sqrt_is_banach_contraction
theorem
PROVEN (no sorry in block)
Lutar/Banach/BabylonianContraction.lean
null
ba2cc91e9c90
Lean theorem `T_fixedPoint_sqrt` — status: PROVEN (no sorry in block) File: Lutar/Banach/BabylonianContraction.lean Statement: theorem T_fixedPoint_sqrt (S : ℝ) (hS : 0 < S) : T S (Real.sqrt S) = Real.sqrt S := by unfold T have hsq : Real.sqrt S * Real.sqrt S = S := Real.mul_self_sqrt hS.le
lutar-lean/Lutar/Banach/BabylonianContraction.lean#T_fixedPoint_sqrt
Lean theorem T_fixedPoint_sqrt
cortex
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T_fixedPoint_sqrt
theorem
PROVEN (no sorry in block)
Lutar/Banach/BabylonianContraction.lean
null
52882e6f00fb
Lean theorem `sideSquared_bounds` — status: PROVEN (no sorry in block) File: Lutar/Banach/LiuHuiPi.lean Statement: theorem sideSquared_bounds : ∀ n, 0 ≤ sideSquared n ∧ sideSquared n ≤ 4 := by intro n induction n with | zero => constructor · -- 0 ≤ sideSquared 0 = 1 unfold sideSquared; norm_num ...
lutar-lean/Lutar/Banach/LiuHuiPi.lean#sideSquared_bounds
Lean theorem sideSquared_bounds
cortex
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sideSquared_bounds
theorem
PROVEN (no sorry in block)
Lutar/Banach/LiuHuiPi.lean
null
553434d289db
Lean theorem `Λ_le_max` — status: PROVEN (no sorry in block) File: Lutar/Bound.lean Statement: theorem Λ_le_max {k : ℕ} (hk : 0 < k) (x : Axes k) : Λ k x ≤ Finset.univ.sup' ⟨⟨0, hk⟩, Finset.mem_univ _⟩ x := by
lutar-lean/Lutar/Bound.lean#Λ_le_max
Lean theorem Λ_le_max
cortex
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Λ_le_max
theorem
PROVEN (no sorry in block)
Lutar/Bound.lean
null
7508b36305c9
Lean theorem `min_le_Λ` — status: PROVEN (no sorry in block) File: Lutar/Bound.lean Statement: theorem min_le_Λ {k : ℕ} (hk : 0 < k) (x : Axes k) : Finset.univ.inf' ⟨⟨0, hk⟩, Finset.mem_univ _⟩ x ≤ Λ k x := by
lutar-lean/Lutar/Bound.lean#min_le_Λ
Lean theorem min_le_Λ
cortex
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min_le_Λ
theorem
PROVEN (no sorry in block)
Lutar/Bound.lean
null
23013d118874
Lean theorem `axis_option_distinguishes` — status: PROVEN (no sorry in block) File: Lutar/Brahmi/AxisOption.lean Statement: theorem axis_option_distinguishes : measured 0 ≠ absent := by
lutar-lean/Lutar/Brahmi/AxisOption.lean#axis_option_distinguishes
Lean theorem axis_option_distinguishes
cortex
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axis_option_distinguishes
theorem
PROVEN (no sorry in block)
Lutar/Brahmi/AxisOption.lean
null
cca76358a29c
Lean theorem `axis_dichotomy` — status: PROVEN (no sorry in block) File: Lutar/Brahmi/AxisOption.lean Statement: theorem axis_dichotomy (av : AxisValue) : isMeasured av = true ∨ isAbsent av = true := by
lutar-lean/Lutar/Brahmi/AxisOption.lean#axis_dichotomy
Lean theorem axis_dichotomy
cortex
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axis_dichotomy
theorem
PROVEN (no sorry in block)
Lutar/Brahmi/AxisOption.lean
null
4e8ad3d395af
Lean theorem `axis_exclusive` — status: PROVEN (no sorry in block) File: Lutar/Brahmi/AxisOption.lean Statement: theorem axis_exclusive (av : AxisValue) : ¬ (isMeasured av = true ∧ isAbsent av = true) := by
lutar-lean/Lutar/Brahmi/AxisOption.lean#axis_exclusive
Lean theorem axis_exclusive
cortex
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axis_exclusive
theorem
PROVEN (no sorry in block)
Lutar/Brahmi/AxisOption.lean
null
dafe46016244
Lean theorem `serialize_injective` — status: PROVEN (no sorry in block) File: Lutar/Brahmi/AxisOption.lean Statement: theorem serialize_injective : Function.Injective serialize := by
lutar-lean/Lutar/Brahmi/AxisOption.lean#serialize_injective
Lean theorem serialize_injective
cortex
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serialize_injective
theorem
PROVEN (no sorry in block)
Lutar/Brahmi/AxisOption.lean
null
1983e1bddb29
Lean theorem `serialize_measured_zero_ne_absent` — status: PROVEN (no sorry in block) File: Lutar/Brahmi/AxisOption.lean Statement: theorem serialize_measured_zero_ne_absent : serialize (measured 0) ≠ serialize absent := by
lutar-lean/Lutar/Brahmi/AxisOption.lean#serialize_measured_zero_ne_absent
Lean theorem serialize_measured_zero_ne_absent
cortex
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serialize_measured_zero_ne_absent
theorem
PROVEN (no sorry in block)
Lutar/Brahmi/AxisOption.lean
null
127983578aed
Lean theorem `false_position_correct` — status: PROVEN (no sorry in block) File: Lutar/Calibration/FalsePosition.lean Statement: theorem false_position_correct (m c x₁ x₂ T : ℝ) (hm : m ≠ 0) (hx : x₁ ≠ x₂) : let y₁ := m * x₁ + c
lutar-lean/Lutar/Calibration/FalsePosition.lean#false_position_correct
Lean theorem false_position_correct
cortex
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false_position_correct
theorem
PROVEN (no sorry in block)
Lutar/Calibration/FalsePosition.lean
null
6caf784b440d
Lean theorem `false_position_identity` — status: PROVEN (no sorry in block) File: Lutar/Calibration/FalsePosition.lean Statement: theorem false_position_identity (m c x₁ x₂ : ℝ) (hm : m ≠ 0) (hx : x₁ ≠ x₂) : let y₁ := m * x₁ + c
lutar-lean/Lutar/Calibration/FalsePosition.lean#false_position_identity
Lean theorem false_position_identity
cortex
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false_position_identity
theorem
PROVEN (no sorry in block)
Lutar/Calibration/FalsePosition.lean
null
702e984d932e
Lean theorem `singletonBound_formula` — status: SORRY (tracked discharge obligation) File: Lutar/CodingTheory/ReedSolomonSingleton.lean Statement: theorem singletonBound_formula (p : RSParams) : singletonBound p = p.n - p.k + 1 := rfl
lutar-lean/Lutar/CodingTheory/ReedSolomonSingleton.lean#singletonBound_formula
Lean theorem singletonBound_formula
cortex
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singletonBound_formula
theorem
SORRY (tracked discharge obligation)
Lutar/CodingTheory/ReedSolomonSingleton.lean
null
d6642b2b26ad
Lean theorem `singletonBound_upper` — status: SORRY (tracked discharge obligation) File: Lutar/CodingTheory/ReedSolomonSingleton.lean Statement: theorem singletonBound_upper (p : RSParams) (h_linear : True) : p.d ≤ singletonBound p := by
lutar-lean/Lutar/CodingTheory/ReedSolomonSingleton.lean#singletonBound_upper
Lean theorem singletonBound_upper
cortex
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singletonBound_upper
theorem
SORRY (tracked discharge obligation)
Lutar/CodingTheory/ReedSolomonSingleton.lean
null
8f629ed14489
Lean theorem `poly_uniqueness_at_k_points` — status: PROVEN (no sorry in block) File: Lutar/CodingTheory/ReedSolomonSingleton.lean Statement: theorem poly_uniqueness_at_k_points (F : Type*) [Field F] [DecidableEq F] (pts : Fin k → F) (vals : Fin k → F) (hpts : Function.Injective pts) (p q : Polynomial ...
lutar-lean/Lutar/CodingTheory/ReedSolomonSingleton.lean#poly_uniqueness_at_k_points
Lean theorem poly_uniqueness_at_k_points
cortex
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poly_uniqueness_at_k_points
theorem
PROVEN (no sorry in block)
Lutar/CodingTheory/ReedSolomonSingleton.lean
null
5dc0d9b9aafd
Lean theorem `reedSolomonIsMDS` — status: SORRY (tracked discharge obligation) File: Lutar/CodingTheory/ReedSolomonSingleton.lean Statement: theorem reedSolomonIsMDS (p : RSParams) (h_valid_rs : True) : isMDS p := by
lutar-lean/Lutar/CodingTheory/ReedSolomonSingleton.lean#reedSolomonIsMDS
Lean theorem reedSolomonIsMDS
cortex
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reedSolomonIsMDS
theorem
SORRY (tracked discharge obligation)
Lutar/CodingTheory/ReedSolomonSingleton.lean
null
a23d1ca125ad
Lean theorem `erasure_ge_twice_error` — status: SORRY (tracked discharge obligation) File: Lutar/CodingTheory/ReedSolomonSingleton.lean Statement: theorem erasure_ge_twice_error (p : RSParams) : errorCorrectionCapacity p * 2 ≤ erasureCorrectionCapacity p := by
lutar-lean/Lutar/CodingTheory/ReedSolomonSingleton.lean#erasure_ge_twice_error
Lean theorem erasure_ge_twice_error
cortex
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erasure_ge_twice_error
theorem
SORRY (tracked discharge obligation)
Lutar/CodingTheory/ReedSolomonSingleton.lean
null
ec670a37eb78
Lean theorem `rsGateValid_implies_singleton` — status: SORRY (tracked discharge obligation) File: Lutar/CodingTheory/ReedSolomonSingleton.lean Statement: theorem rsGateValid_implies_singleton (n k d q t : ℕ) (h : rsGateValid n k d q t) : d = n - k + 1 := h.2.2.2.1
lutar-lean/Lutar/CodingTheory/ReedSolomonSingleton.lean#rsGateValid_implies_singleton
Lean theorem rsGateValid_implies_singleton
cortex
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rsGateValid_implies_singleton
theorem
SORRY (tracked discharge obligation)
Lutar/CodingTheory/ReedSolomonSingleton.lean
null
67fdd92d917b
Lean theorem `rsGateValid_capacity_bound` — status: SORRY (tracked discharge obligation) File: Lutar/CodingTheory/ReedSolomonSingleton.lean Statement: theorem rsGateValid_capacity_bound (n k d q t : ℕ) (h : rsGateValid n k d q t) : t ≤ n - k := h.2.2.2.2
lutar-lean/Lutar/CodingTheory/ReedSolomonSingleton.lean#rsGateValid_capacity_bound
Lean theorem rsGateValid_capacity_bound
cortex
263
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rsGateValid_capacity_bound
theorem
SORRY (tracked discharge obligation)
Lutar/CodingTheory/ReedSolomonSingleton.lean
null
2a40d1f317a7
Lean theorem `reedSolomonMDSProperty` — status: PROVEN (no sorry in block) File: Lutar/CodingTheory/ReedSolomonSingleton.lean Statement: theorem reedSolomonMDSProperty (n k d q t : ℕ) : rsGateValid n k d q t ↔ (1 ≤ k ∧ k ≤ n ∧ n ≤ q ∧ d = n - k + 1 ∧ t ≤ n - k) := by
lutar-lean/Lutar/CodingTheory/ReedSolomonSingleton.lean#reedSolomonMDSProperty
Lean theorem reedSolomonMDSProperty
cortex
276
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reedSolomonMDSProperty
theorem
PROVEN (no sorry in block)
Lutar/CodingTheory/ReedSolomonSingleton.lean
null
cdae720b1a5a
Lean lemma `robustness_composes` — status: PROVEN (no sorry in block) File: Lutar/Composition/AdversarialRobustness.lean Statement: lemma robustness_composes {X Y Z : Type*} (mX : MetricModel X) (mY : MetricModel Y) (mZ : MetricModel Z) (f : X → Y) (g : Y → Z) (δ ε₁ ε₂ : ℝ) (hf : IsRobust mX mY f δ...
lutar-lean/Lutar/Composition/AdversarialRobustness.lean#robustness_composes
Lean lemma robustness_composes
cortex
454
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robustness_composes
lemma
PROVEN (no sorry in block)
Lutar/Composition/AdversarialRobustness.lean
null
8327319af874
Lean theorem `robustness_preserved_by_composition` — status: SORRY (tracked discharge obligation) File: Lutar/Composition/AdversarialRobustness.lean Statement: theorem robustness_preserved_by_composition {X Y Z : Type*} (mX : MetricModel X) (mY : MetricModel Y) (mZ : MetricModel Z) (S₁ : X → Y) (S₂ : Y → Z...
lutar-lean/Lutar/Composition/AdversarialRobustness.lean#robustness_preserved_by_composition
Lean theorem robustness_preserved_by_composition
cortex
505
126
robustness_preserved_by_composition
theorem
SORRY (tracked discharge obligation)
Lutar/Composition/AdversarialRobustness.lean
null
4d8866e49b68
Lean theorem `iterated_chain_obligation_tracked` — status: PROVEN (no sorry in block) File: Lutar/Composition/AdversarialRobustness.lean Statement: theorem iterated_chain_obligation_tracked : iterated_chain_tracked := by trivial /-! ## 7. Adversary Budget Theorem -/ /-- An *adversary* with budget B cannot push the...
lutar-lean/Lutar/Composition/AdversarialRobustness.lean#iterated_chain_obligation_tracked
Lean theorem iterated_chain_obligation_tracked
cortex
461
115
iterated_chain_obligation_tracked
theorem
PROVEN (no sorry in block)
Lutar/Composition/AdversarialRobustness.lean
null
a515ee8cdb8d
Lean theorem `adversary_budget_bounded` — status: PROVEN (no sorry in block) File: Lutar/Composition/AdversarialRobustness.lean Statement: theorem adversary_budget_bounded {X Y Z : Type*} (mX : MetricModel X) (mY : MetricModel Y) (mZ : MetricModel Z) (S₁ : X → Y) (S₂ : Y → Z) (x_clean x_adv : X) (δ...
lutar-lean/Lutar/Composition/AdversarialRobustness.lean#adversary_budget_bounded
Lean theorem adversary_budget_bounded
cortex
547
136
adversary_budget_bounded
theorem
PROVEN (no sorry in block)
Lutar/Composition/AdversarialRobustness.lean
null
b24383f5759b
Lean theorem `totalOverhead_nil` — status: PROVEN (no sorry in block) File: Lutar/Composition/CompositionOverhead.lean Statement: theorem totalOverhead_nil : totalOverhead [] = 0 := rfl @[simp] theorem totalOverhead_cons (h : CostSystem) (t : List CostSystem) :
lutar-lean/Lutar/Composition/CompositionOverhead.lean#totalOverhead_nil
Lean theorem totalOverhead_nil
cortex
263
65
totalOverhead_nil
theorem
PROVEN (no sorry in block)
Lutar/Composition/CompositionOverhead.lean
null
eb9702f360d7
Lean theorem `totalOverhead_cons` — status: PROVEN (no sorry in block) File: Lutar/Composition/CompositionOverhead.lean Statement: theorem totalOverhead_cons (h : CostSystem) (t : List CostSystem) : totalOverhead (h :: t) = h.cost + totalOverhead t := rfl
lutar-lean/Lutar/Composition/CompositionOverhead.lean#totalOverhead_cons
Lean theorem totalOverhead_cons
cortex
260
65
totalOverhead_cons
theorem
PROVEN (no sorry in block)
Lutar/Composition/CompositionOverhead.lean
null
fa6eb278c5bf
Lean theorem `totalOverhead_singleton` — status: PROVEN (no sorry in block) File: Lutar/Composition/CompositionOverhead.lean Statement: theorem totalOverhead_singleton (s : CostSystem) : totalOverhead [s] = s.cost := by simp [totalOverhead]
lutar-lean/Lutar/Composition/CompositionOverhead.lean#totalOverhead_singleton
Lean theorem totalOverhead_singleton
cortex
245
61
totalOverhead_singleton
theorem
PROVEN (no sorry in block)
Lutar/Composition/CompositionOverhead.lean
null
d8e15b2c5a4e
Lean theorem `totalOverhead_append` — status: PROVEN (no sorry in block) File: Lutar/Composition/CompositionOverhead.lean Statement: theorem totalOverhead_append (l₁ l₂ : List CostSystem) : totalOverhead (l₁ ++ l₂) = totalOverhead l₁ + totalOverhead l₂ := by
lutar-lean/Lutar/Composition/CompositionOverhead.lean#totalOverhead_append
Lean theorem totalOverhead_append
cortex
263
65
totalOverhead_append
theorem
PROVEN (no sorry in block)
Lutar/Composition/CompositionOverhead.lean
null