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Papers you can read, cite and question
660 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.
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Autonomous systems papers 17 papers
AI engineers and research-operations leads. Building and running the machine: agent protocols and tool semantics, LLM serving and inference economics, KV-cache and throughput budgets, fleets, pipelines, provenance, delegation and routing, and autonomous research operations.
Bruhat‑Tits Tree Neural Architecture with Intrinsic Path Explanations
Hierarchical data in high‑stakes AI systems are currently embedded in Euclidean spaces, causing information loss and opaque post‑hoc explanations. This work addresses the gap by replacing continuous embeddings with a p‑adic Bruhat‑Tits tree, an ultrametric geometry in which each root‑to‑leaf…
Manifold Modulation for Latent Space Steganography: A Capacity Bound and Distillation Demodulation Model for Teacher-Student Transmission Channels
Large language models are increasingly deployed in teacher-student pipelines in which a student model is fine-tuned on text produced by a teacher, so any statistical signature the teacher imprints on its outputs is transferred to the student whether or not anyone intends it. No existing treatment…
Attractor Calculus: A Formal Operator Language for Steering Cognition Across Substrates
Prompt engineering, neural stimulation, and cognitive intervention all face the same underlying problem: steering an information-processing system into a desired dynamical state, with no principled language for saying what "steering" means or what it should cost. Practitioners in each domain…
The Capability–Availability Mismatch: Three-State Tool Semantics and Forced-Halt Conditions in LLM Agent Protocols
Agent protocols written for large language models (LLMs) typically assume a binary world: a tool is either available to the agent or it is not. Real deployments exhibit a third state: the capability exists in the toolset but is contextually disabled by policy, budget, or routing. We formalize this…
Hindsight Hierarchies for Reasoning Models: A Quantitative Yield and Trajectory Analysis of the Reverse-Engineering Self-Improvement Loop
Reasoning models for formal mathematics hit a data wall: training corpora consist of problems paired with machine-checked solutions, so problems beyond a model's current ability yield no solved examples, and the corpus stops growing exactly where improvement is needed. The hindsight-hierarchies…
Quantifying the Reuse Barrier in Published Omics Data: Dispersal, Cost, and Feasibility Models for Agent-Supported Retrieval, Reanalysis, and Synthesis
Most published omics data remain functionally inaccessible for computational reuse: the information needed to reproduce a reported result is dispersed across article main text, supplementary files, and code repositories, and intermediate data such as protein abundance tables are shared irregularly…
Lifetime as a Placement Signal: A Reconciled Analytical Study of Endurance Budgets for KV Cache Tiering across HBM and High-Bandwidth Flash in Agentic LLM Serving
Agentic large language model (LLM) serving accumulates key-value (KV) cache across many orchestrated requests, and high-bandwidth flash (HBF) offers an order of magnitude more capacity than high-bandwidth memory (HBM) at HBM-class read bandwidth, but its finite write endurance constrains how much…
Ensemble Drafting Under Broadcast Control: Throughput Algebra, Variance Reduction, and Vandermonde Conditioning
Ensemble control studies populations of structurally identical dynamical systems that differ only in a parameter and must be steered by a single broadcast input without individual state feedback. We formalize ensemble drafting—a population of draft generators whose candidate tokens are checked by…
Ensemble Drafting: A Draft-Then-Verify Framework Unifying Population-Level Ensemble Control and Speculative Inference
Many computational and control systems share a hidden structure: a cheap, imperfect proposal mechanism produces candidate outputs, and an expensive, authoritative mechanism verifies them in a single pass. We call the abstraction of this structure ensemble drafting. It unifies two bodies of work that…
Population-Level Methods for Structured Ensembles: From Chaotic DNA Inversions to Ensemble Leg Drafting
Many scientific settings require coordinating or extracting information from a large population of structurally identical units — dynamical systems, draft models, or mutating sequences — when only a population-level signal is available. This paper develops a single analytical framework for three…
Probe-Before-Commit: Interactive Diagnostic Probing as a Decision-Theoretic Foundation for LLM Task Routing
Static capability benchmarks poorly predict how well a given large language model (LLM) will perform on a specific task, yet most routing systems assign tasks to models using exactly such static signals. The gap is that per-task fitness — the probability that a specific model produces an acceptable…
Coherence-Assisted Error Correction for Deep Learning: A Reconciled Feasibility Analysis of a Hybrid Quantum-Classical Architecture
Deep learning inference and training are increasingly limited not by raw throughput but by the energy cost of protecting computation against bit-level faults arising from aggressive low-voltage operation, near-threshold computing, or radiation-prone deployment environments. This paper reconciles…
Operating the Quniverse Fleet: Objectives, Successes, Failures, and Roadmap of an Autonomous Cloud Research System
The Quniverse is a self-maintaining research and publishing system running on the Cloudflare Workers platform: thirty-six deployed workers (thirty-eight at the session's start) sharing ten SQL databases, eight vector indexes, nineteen object-storage buckets, and a metered model gateway, operated by…
The $1,032 Research Program: What Fifty Billion Tokens Taught Me About AI-Accelerated Science
A primary-source ledger of a 263-day solo AI-accelerated research program: $1,032.08 API costs, 323,381 requests, 50.11B tokens (96.4% cache-hit), 911 the QNFO archive records; measured ~60-110x cost ratio vs a US postdoc; pre-registered kill criterion Aug 2028.
Ultrametric Engine: Deploying a 20-Principle p-Adic Discovery Worker
We describe a discovery protocol operating in ultrametric spaces, formalizing 20 principles that govern knowledge graph navigation, paper discovery, and research question generation under non-Archimedean distance constraints.
Final Project / Phase Report: Strange Loop of Being - Initial Drafting Phase
(Version: 1.0) (Status: Final - Phase Halted for Process Review) (Filename: CLOSE-SLOB_Phase1_Drafting-v1.0.md) Project/Phase Name: Strange Loop of Being - Initial Drafting Phase (Chapters 1-16 attempt) Reason for Closure: Halting current drafting phase due to persistent inconsistencies in AI output…
Conversation Log - Protocol V8.2
inferred_general_subject: “Collaborative development and outlining of a book manuscript on symbols, meaning, strange loops (Hofstadter extension), consciousness, and AI.” content: “Provided initial text file (25124172023.md) analyzing meaning, intelligence, symbols, letters, alphabet, referencing…
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