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728 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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Results for “joules” 6 papers
Energy benchmarking. Measuring energy per result Tagged papers: 27.
The Trapped-Ion Ultrametric Testbed: A Falsifiability Register for Testing p-Adic Structure in Quantum Dynamics
Twenty-one published records from a single research program, spanning December 2025 to August 2026, are here organized into one testable claim: trapped-ion quantum simulators are the first near-term platform on which ultrametric (p-adic) structure in quantum dynamics can be accepted or rejected by…
Joules-per-Solution for Stochastic and Agentic Inference: Benchmarking Frontier and Agentic LLMs Against the Human Brain
The joules-per-solution (J/S) metric, introduced in JPCUB P0 as a universal, physics-grounded measure of computational efficiency, assumed deterministic solvers: one run yields one solution. Large language models (LLMs) violate that assumption twice over: they are stochastic samplers whose outputs…
QWAV Strategy v2.4.1: The Energy-Standard Playbook — Consortium Governance, Verified Precedents, and the JPCUB Road to a Quantum Computing Energy Benchmark
Quantum computation is known to possess theoretical energy-consumption advantages over classical computation — Meier and Yamasaki proved an exponential energy advantage on Simon's problem (arXiv:2305.11212), and Fellous-Asiani et al. demonstrated full-stack resource-efficiency optimization regimes…
JPCUB Competitive Landscape v2.0: System-Level Joules-per-Solution Estimates for 17 Quantum Computing Platforms from Published Specifications
The JPCUB P0 protocol (https://papers.qnfo.org/papers/joules-per-solution-metric/) defines the joules-per-solution metric — total system energy per correct answer — as a universal, physics-grounded benchmark for computational platforms. The qwav.tech competitive landscape displays six platforms with…
JPCUB as a Leading Indicator of Computing Paradigm Shifts: Retrospective Validation and Prospective Forecast
The computing industry lacks a single, cross-domain metric that can compare energy efficiency across fundamentally different paradigms — CPU, GPU, neuromorphic processor, in-memory accelerator, or spintronic logic. Traditional metrics (FLOPS, MIPS, transistor count) describe what already exists;…
The Joules-per-Solution Metric: Definition, Measurement Protocol, and Anti-Gaming Provisions for Honest Computational Benchmarking
The global computational infrastructure spans seven distinct paradigms — from classical CPUs to quantum processors, from AI accelerators to neuromorphic chips — yet no universal metric exists for comparing their computational value. Every paradigm benchmarks itself on its own terms: quantum volume…
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