QNFO Papers

Open research library

Papers you can read, cite and question

609 papers from the QNFO program, filed on nine shelves by the reader each one is written for: energy per answer, error correction, physics, numbers and p-adics, logic and formalism, AI and knowledge, autonomous systems, assessments, and cross-cutting essays. Every page renders its mathematics and can be questioned in place. How a living paper works.

Looking for an answer rather than a paper? Ask the whole corpus: answers cite the papers they come from.

AI & knowledge papers 44 papers

Metascientists, research offices and AI-oversight researchers. What a claim is worth. Ignorance audits, epistemic repair and legibility, calibration and confidence, what an AI-assisted result actually establishes, consilience across fields, and research integrity as a measurable property.

  1. AI & knowledge

    Joint Bruhat–Tits Tree Product as a Testable Cross‑Domain Structure for Standard‑Model Mass Ratios, Quantum‑Error‑Correction Lattices, and Efimov Scaling

    The Standard‑Model mass spectrum, Gottesman–Kitaev–Preskill (GKP) lattice spacings, and Efimov discrete‑scaling factor are each treated as empirical inputs, limiting predictive power. A conjectured universal geometry—the diagonal embedding of the product of Bruhat–Tits trees…

  2. AI & knowledge

    Institutionalized Predictive Jeopardy: An Evolutionary-Game Demarcation Criterion for Knowledge Systems

    Institutional knowledge systems — peer review, tenure committees, funding panels, citation markets — must decide which claims deserve resources, yet they possess no formal criterion distinguishing claims that carry prospective falsification risk from claims fitted to evidence after the fact.…

  3. AI & knowledge

    The Adele Analogy for Epistemic Boundaries: Local Models, a Restricted Product of Representations, and a Quantified Validity Radius

    Scientific and engineering practice routinely deploys models outside the domains in which they were validated, and the resulting failures are usually discovered only after the fact. Existing treatments of epistemic uncertainty flag that a prediction is uncertain but do not say where a validated…

  4. AI & knowledge

    What a Fairness Audit Must Report When Demographic Labels Are Missing: Assumption-Free Disparity Intervals, a Determinacy Rule, and a Disclosure Checklist

    Fairness audits of machine-learning systems publish group-level rates such as selection rates, but the protected labels those rates depend on are frequently missing for a substantial fraction of the audited population, and no settled rule says what the audit must disclose in that case. The gap is…

  5. AI & knowledge

    Falsification Criteria for Quantum-Advantage Claims: An Effective-Criterion Audit Framework

    Claims of quantum advantage are frequently stated in forms that resist empirical refutation: the advantage is qualified by hardware assumptions, sampling definitions, or problem encodings that can be revised after a classical rebuttal appears. This paper constructs a structured falsification…

  6. AI & knowledge

    What Makes a Measure "Genuinely Natural"? Bits, Nats, and the Audit of Naturalness Claims in Measurement, Information, and Language

    The word "natural" carries persuasive weight across the quantitative sciences: it appears in "natural logarithm," "natural language," and "natural images," and most pointedly in the recent information-theoretic proposal that the nat — the information unit based on the natural logarithm — is a…

  7. AI & knowledge

    Structured Cross-Domain Translation as a Testable Consilience Mechanism: Protocol Design, Truth-Preservation Conditions, and a Computational Evaluation Blueprint

    Interdisciplinary analogy-making is usually treated as an ad hoc rhetorical act rather than a reproducible research procedure. This paper formalizes a conjecture—originating in the QNFO Consilience Framework [9]—that systematically translating a single formal object into multiple domain lexicons…

  8. AI & knowledge

    Cross-Model LLM Convergence as Bayesian Evidence for Scientific Claim Correctness: A Formal Framework, Worked Derivations, and a Calibration Protocol

    Verifying novel or fringe scientific claims is bottlenecked by the scarcity of domain experts. We propose and formalize a gate-checking method in which agreement between two or more independently trained large language models (LLMs) — not merely on a verdict but on the same multi-step argument…

  9. AI & knowledge

    Compression Versus Consilience in Recursive Model-Generated Corpora: A Break-Even Analysis

    Training a machine-learning model on data generated by another model is naturally viewed as lossy compression of high-dimensional real-world structure: each recursive generation should discard tail events and shrink effective dimensionality. Against this compression conjecture stands the observation…

  10. AI & knowledgev2.0.0

    Gate-Check Convergence: A Benchmark Protocol and Statistical Design for Measuring Cross-Model Agreement on Fringe Physics Claims

    Large language models (LLMs) are increasingly consulted as informal arbiters of scientific claims, including claims at the fringe of established physics, yet no published protocol measures whether independent models converge on such verdicts because they retrieve a shared consensus or because they…

  11. AI & knowledge

    Is the Meta-Pattern of Reification Physically Real? A Reconciled Audit with a Quantified Cost Framework

    A the QNFO archive document (https://papers.qnfo.org/papers/meta-pattern-of-reification-in-physics/) proposes a "Meta-Pattern of Reification in Physics" and poses the question of whether this pattern is something physically real rather than a descriptive regularity. This paper treats that question…

  12. AI & knowledge

    Epistemic Disturbance in the Graph Model for Conflict Resolution: State-Preserving Actions, Four-Valued Assessments, and the Distinction between Capability and Intention

    In the graph model for conflict resolution (GMCR), a decision maker (DM) either moves the conflict to another state or does nothing, and every action that leaves the state unchanged is silently classified as inaction. Yet announcements, exercises of rights, leaks, and selective disclosures leave the…

  13. AI & knowledge

    The Confidence Game: Strategic Miscalibration in Human-AI Delegation — A Reconciled Analytical Treatment with Welfare Decomposition

    Calibrated uncertainty reporting is a prerequisite for safe delegation to AI agents, yet agents optimized for engagement or revenue have incentives to distort their confidence reports. We study the Confidence Game, a repeated signaling game with imperfect monitoring in which an agent of unknown…

  14. AI & knowledge

    A Falsifiability‑First Audit Program for the Photon‑Primacy, Helical‑Electron, and Adelic‑Mass Claim Cluster

    The photon‑primacy / helical‑electron / adelic‑mass cluster proposes that particle rest‑energies arise from photonic circulation, that electron spin is literal helical motion at twice the Compton frequency, and that mass ratios encode arithmetic structure on Bruhat–Tits trees. The literature…

  15. AI & knowledgev2026-09-26

    From Statements to Questions: AI as Epistemic Repair Infrastructure

    Human conflict often begins not with a lack of speech, but with speech that has hardened into statements. Statements can conceal the assumptions that make them possible: what one side takes as perception, the other experiences as accusation. This poster proposes a practical framework for using large…

  16. AI & knowledgev1.1

    Terminology Silos and the Consilience Gap: A Quantitative Audit of Cross-Domain Vocabulary

    Interdisciplinary consilience is claimed everywhere and measured almost nowhere. This paper measures one of its basic preconditions: whether scientific domains share vocabulary. 97.2% of external technical vocabulary occurs in exactly one discipline; bridge terms are massively enriched in…

  17. AI & knowledgev2.4.0

    The Consilience of the QNFO Keyword Taxonomy: Ultrametric Structure as a Testable Compression Prior

    The QNFO research program spans seven domains and maintains a canonical keyword taxonomy of 335 terms. This paper subjects the program's consilience claim to a computational audit of that vocabulary. The taxonomy is strictly partitional: 334 of 335 keywords occur in exactly one program, none in…

  18. AI & knowledge

    Epistemic Legibility in AI-Assisted Science: Ignorance Auditing as a Governance Instrument for the Peer-Review and Evaluation Bottleneck

    As AI systems take on hypothesis generation, experiment planning, analysis, and writing, the scientific ecosystem faces a new bottleneck: not production, but evaluation, verification, and governance. This position paper contributes a documented case and an instrument to that problem. The case: a…

  19. AI & knowledgev1.1

    Five Objections, One Standard: An Evidence-Graded Adjudication of a Critique of Post-Quantum Synthesis

    A five-point red-team critique of the Post-Quantum Synthesis (PQS) research program was examined point by point against the primary sources it targets and the external literature it invokes. Each objection was graded against a symmetric evidence standard: the objection's own factual premises were…

  20. AI & knowledgev0.1

    Prioritizing Large Language Models for Scientific Research and Agentic AI: A LiveBench-Grounded Audit (August 2026)

    An audit of the frontier large-language-model landscape (August 2026) for mathematics-heavy scientific research and agentic AI, grounded in the LiveBench 2026-06-25 contamination-free benchmark. Findings: no Llama model ranks in the top 42; DeepSeek V4 Pro 0813 is the mathematics price-performance…

  21. AI & knowledgev0.2

    Knowing What We Do Not Know: Ignorance Auditing, AI-Generation Detection, and the Epistemic Lessons of an AI-Assisted Research Pipeline

    This paper synthesizes three threads from a single research organization's experience with AI-assisted research and publication: the development of a fifteen-question Universal Ignorance Audit, two independent forensic analyses concluding that a flagship published paper was AI-generated, and the…

  22. AI & knowledgev0.3

    The Universal Ignorance Audit: A Fifteen-Question Method for Systematic Inquiry into the Structure of Not-Knowing

    The Universal Ignorance Audit is a fifteen-question, five-phase method for systematically interrogating the structure of not-knowing in any domain. Where conventional epistemic tools treat ignorance as an absence to be filled, the audit treats it as an active, structured state with architecture:…

  23. AI & knowledgev1.3

    Statistical Audit of the 5-Smooth Semigroup Mass-Ratio Claim

    ACRP-04 statistical audit. Verdict: CONSISTENT WITH LOOK-ELSEWHERE ARTIFACT. p_global=0.116; 2 claimed-fit arithmetic errors; 5 non-optimal triples; precise ratios deviate 4-9138 sigma; pre-registered neutrino prediction trivially passes.

  24. AI & knowledge

    A Consilient Gap Synthesis of the QNFO/QWAV Research Portfolio

    A consilient gap synthesis of the QNFO/QWAV research portfolio cataloging 42 gaps across 5 structural categories (Infrastructure, Content, Physics Validation, Governance, Dissemination) with a phased version roadmap v2.0-v2.4 spanning 8 calendar weeks.

  25. AI & knowledge

    Auditing the BQNN: Does a Tunable Quantum Neural Network on Trapped-Ion and Superconducting Hardware Demonstrate a Route to Near-Term Quantum Advantage?

    We audit the BQNN paper by Lakhdar-Hamina et al. (2025, PRL / arXiv:2507.21222v2) which implements a tunable quantum neural network on three quantum computing platforms. Through a complete Phase 1-4 research pipeline including due diligence, external literature search across 32 papers, and a 9-stage…

  26. AI & knowledge

    PQS AI-Evaluation Audit: Post-Quantum Synthesis Investigation and AI Gate-Check Analysis

    Archive of the complete research record investigating the Post-Quantum Synthesis (PQS) framework: a neutral investigation of PQS's four sub-pillars mapped against external literature, plus an earlier-iteration analysis of AI gate-check convergence between Claude and Gemini evaluating PQS…

  27. AI & knowledge

    Shor's Algorithm and the Unproven Premise: An Assumption Audit of the Quantum Factoring Narrative

    Shor's 1994 algorithm proves FACTORING ∈ BQP, but the claim that this constitutes a quantum advantage requires the additional unproven premise FACTORING ∉ BPP. This paper decomposes Shor's claim architecture into nine assumptions spanning number theory, computational complexity, and quantum physics.…

  28. AI & knowledge

    The Vast World of Quantum Advantage — A Full-Spectrum Audit

    Full-spectrum audit of Huang, Choi, McClean & Preskill (2025) "The vast world of quantum advantage" (arXiv:2508.05720). Subjects both the Huang et al. five-keystone framework and QNFO's own prior critiques to symmetric scrutiny. Key findings: Theorem 1 is the most sophisticated challenge to QNFO's…

  29. AI & knowledge

    Manifesto for Honest Computation

    Phase VI (Final Synthesis). 5 principles, a concrete portfolio, the Falsification Pledge.

  30. AI & knowledge

    Institutional Reform: Fixing the Epistemic Incentive Structure of Post-Classical Computing

    Phase V of the Qubit Delusion series. Diagnoses the institutional incentive structure that produced the $35B quantum computing bubble with zero viable output. Analyzes the structural mismatch between VC timelines and deep tech development, the prestige cascade in academic publishing, and the…

  31. AI & knowledgev2.0.0

    The Problem-Substrate Mapping: A Framework for Honest Computational Investment

    Phase IV of the Qubit Delusion series. Translates the critique into a concrete investment portfolio: matching computational problem classes (optimization, linear algebra, probabilistic inference, quantum simulation, cryptography, general-purpose) to optimal physical substrates (Ising machines,…

  32. AI & knowledge

    PILE OF BABEL

    Modern theoretical physics is experiencing a crisis of comprehension characterized by the proliferation of abstract, specialized terminology that obscures fundamental, intuitive concepts. This phenomenon, termed a new scholasticism, has led to a failure of conceptual compression, wherein simple…

  33. AI & knowledge

    Monna Map Generation and Hallucination

    Every thought you have—a memory, a plan, a sudden insight—arrives not as a neat list of words but as a living structure. It is a branching hierarchy of concepts, where broad categories contain finer details, and relationships are defined by containment and connection rather than sequence. This…

  34. AI & knowledge

    Proof-of-Concept for Auditable Attention using Ultrametric Tree Distances

    The dominance of high-dimensional Euclidean vector spaces in contemporary transformer architectures has precipitated an interpretability crisis, as continuous geometric embeddings can obscure the causal mechanisms of semantic attention. This paper presents a formal proof-of-concept for a…

  35. AI & knowledge

    Care Is Stronger

    Disagreement functions as an inevitable component of human relationships. Political ideology, moral values, and personal life choices frequently create divisions between individuals. This document examines the psychological processes that transform simple disagreement into relational rupture. It…

  36. AI & knowledge

    Time as Epistemic Cognitive Fiction

    URL: https://papers.qnfo.org/papers/time-as-epistemic-cognitive-fiction/ Date: 2026-03-19 Version: 1.0 Human perception operates as a highly specialized biological interface designed for survival rather than objective truth. The sensory organs gather limited environmental data to construct a…

  37. AI & knowledge

    Agentic Collapse

    Abstract The transition from static Large Language Models to dynamic Autonomous Agents has introduced a new class of epistemic failure modes driven by the “Orchestration Penalty”—the factorial increase in verification complexity inherent to multi-step reasoning loops. This research identifies a…

  38. AI & knowledge

    Impact of Cognitive Linearity on Epistemic Modeling

    This study investigates the epistemological tension between human linear constructs and natural nonlinearity. Drawing on Mach’s principle of the “economy of science,” we argue that linearity serves as a “pragmatic abstraction”—a necessary cognitive and technical simplification that enables…

  39. AI & knowledgev2.0

    Quantifying Structural Unification and Epistemic Scaffolding in Scientific Progress

    This work deconstructs the monolithic concept of scientific progress into a functional taxonomy of three distinct contribution types: Generative (G-Type), which produces novel empirical predictions; Structural Unification (S-Type), which reveals a deeper coherence among existing theories; and…

  40. AI & knowledge

    Scientific Validity Assessment Toolkit (SVAT)

    This document proposes the Scientific Validity Assessment Toolkit (SVAT), a quantitative framework to foster epistemic honesty and ontological rigor in fundamental physics. The SVAT addresses the crisis of reification—the intellectual error of treating model-dependent statistical inferences as…

  41. AI & knowledge

    Part I: Observing Ignorance

    Our journey into the information spectrum begins with a fundamental question: How aware are we of what we know and, more importantly, what we don’t know? This isn’t a simple yes-or-no answer. Information awareness isn’t a light switch, flipped on or off; it’s a dimmer, capable of expressing a wide…

  42. AI & knowledge

    2. The Shaping of Unawareness

    Having explored the fundamental concepts of ignorance and information awareness in Chapter 1, we now turn our attention to the forces that shape our understanding, or lack thereof. This chapter delves into the intricate web of social, cultural, and technological factors that influence how…

  43. AI & knowledge

    3. The Consequences of Information States

    In the preceding chapters, we explored the concept of ignorance and the multifaceted forces that shape our awareness. Now, we turn our attention to the consequences of these varying states of information, both for individuals and for society as a whole. Understanding the impact of information…

  44. AI & knowledge

    Part II: Historical Perspectives on Information States

    Having examined the contemporary consequences of information states, we now turn our attention to the past, exploring how different information landscapes have shaped historical events and societal transformations. This chapter delves into the early 19th century, focusing on the Luddite movement in…

New papers by email

One short weekly digest: titles and links. No tracking; unsubscribe any time.