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.
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Autonomous systems papers 16 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.
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, differing only in a parameter, that 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
V8.2 # Optimized for Machine Parsing and downstream AI Analysis # Emphasizes Explicit Extraction, Structural Representation, and Embedded Schema # Default Scope is Entire Available History unless Specified Otherwise by User # —- SCHEMA DEFINITION (v8.2) —- # Root Keys: Metadata, initial_trigger,…
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