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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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Energy per answer papers 37 papers
Platform builders, data-centre operators and energy analysts. What a correct answer costs in joules. Joules-per-Solution (JPCUB) definitions and measurements, Landauer and Margolus-Levitin limits, energy and power budgets, and energy benchmarking across quantum, HPC and AI hardware.
Thermodynamic Divergence of Active Quantum Error Correction Overhead: A Kapitza-Limited Feasibility Threshold for Gate-Based Architectures
Active quantum error correction (QEC) is conventionally analyzed as an algorithmic resource problem: how many physical qubits and gate cycles are needed per logical qubit. We propose a complementary thermodynamic feasibility criterion. In a gate-based architecture, every QEC cycle is driven by…
A Cost-Model Benchmark for Mixed-State Quantum Simulation Workloads: Entanglement-Cost Anchors and Reuse-Aware Re-Entry Metrics
Classical simulation of quantum circuits increasingly takes the form of repeated-run workloads—variational-parameter sweeps, noisy multishot studies, and error-correction cycles—rather than isolated executions, and the target states of such workloads are frequently mixed rather than pure. This paper…
Actual Demand of a Computational Substrate: A Reconciled Demand-Side and Allocation Framework for Physical Computing Platforms
Debates about novel computational substrates—reservoir systems, post-qubit quantum architectures, thermodynamically bounded devices—are usually conducted from the supply side: what can a given physical system compute? This paper asks the complementary question posed by the QNFO programme: what is…
The Switching Economics of Hamiltonian Re-Entry Computation: A Cost-Model Comparison with Stored-Program Architectures
Stored-program (von Neumann) architectures pay a per-operation switching cost for instruction fetch, decode, and memory traffic, while a proposed Hamiltonian-computation paradigm identifies computation with continuous dynamical trajectories that re-enter a designated operating region of phase space.…
Ultrametric p-Adic Arithmetic as Energy-Proportional Precision Computing: An Energy Model for Digit-Terminable Multiply-Accumulate
Fixed-width Archimedean floating-point arithmetic pays a constant energy cost per multiply-accumulate (MAC) regardless of the precision actually required by the computation. We conjecture and formalize an alternative: p-adic (ultrametric) number representations, whose digits are hierarchically…
The Resource Burden of Active Quantum Error Correction: A Scaling Analysis of Qubit, Bandwidth, and Energy Overheads
Active quantum error correction (QEC) protects quantum information only by continuously consuming physical resources: qubits, measurement bandwidth, classical processing, and energy. While the theoretical foundations of QEC are mature, the resource burden of running a code—rather than constructing…
QuWARP Reconciled: An Analytical Cost-Model Assessment of Workload-Level Reuse Planning for Quantum Circuit Simulation
Classical simulation of quantum circuits increasingly appears as repeated-run workloads — variational quantum eigensolver (VQE) sweeps, noisy multishot studies, and quantum error-correction (QEC) cycles — rather than isolated circuit executions. The QuWARP planner (arXiv:2609.23664v1) proposes…
Thermodynamic Budgeting for Hybrid Quantum-Classical Computing: A Three-Layer Energy Model with Explicit Arithmetic and a 15-Month Validation Roadmap
Hybrid quantum-classical (HQC) computing is the dominant near-term paradigm, yet its energy accounting is rarely made explicit: the classical control, readout, cryogenic, and orchestration hardware surrounding the quantum processing unit (QPU) can dominate the total power budget, eroding any…
Adiabatic Superconducting Spiking Architectures: A Reconciled Energy Budget for Quantum-Inspired Neuromorphic Computing
Neuromorphic computing promises order-of-magnitude energy savings over von Neumann processors, yet CMOS spiking hardware remains bounded by capacitive switching losses and transistor leakage. We present a reconciled analysis of a hybrid architecture that replaces the CMOS neuron with a…
Thermodynamic Trade-off Frontiers for Neuromorphic Processors: A Quantum-Inspired Non-Equilibrium Model of the Energy–Speed Boundary
Neuromorphic processors promise order-of-magnitude gains in energy efficiency, but no predictive framework currently connects device-level dissipation to system-level computational throughput. We develop a non-equilibrium thermodynamic model in which a neuromorphic processor is treated as a driven,…
The Margolus-Levitin Bound and Energy-Time Limits for Quantum Computation at the Landauer Scale
The Margolus-Levitin (ML) bound establishes a fundamental limit on the speed of quantum evolution, stating that a system with mean energy $\langle H \rangle$ above its ground state requires a minimum time $\tau \ge \pi\hbar/(2\langle H\rangle)$ to evolve between orthogonal states. This preprint…
Quantum Computation Latency-Energy Tradeoff and the JPCUB Metric
Fault-tolerant quantum computation trades latency against energy through the code distance: a larger distance d costs more syndrome rounds and more physical gates per logical operation, lengthening every operation and raising its energy. This paper computes that tradeoff for the rotated surface code…
Revising the Joules-per-Compute (JPCUB) Benchmark: Normalizing Energy Efficiency by Logical-Qubit Operations
Energy benchmarks for quantum processors are usually quoted per physical gate or per physical qubit, figures that hide the dominant cost of a fault-tolerant machine: the error-correction overhead that multiplies physical work by a distance-dependent factor before any logical operation is delivered.…
Landauer-Limit Energy Floor and JPCUB Normalization for Cryogenic Quantum Control Electronics
Cryogenic quantum control electronics dissipate energy many orders of magnitude above the thermodynamic minimum implied by Landauer's principle, and the gap matters for the joules-per-compute economics of fault-tolerant machines. This paper computes the Landauer floor for a rotated surface-code…
A Lower Bound on Energy Cost per Logical-Qubit Operation in Surface-Code Quantum Error Correction
Surface-code quantum error correction translates one logical qubit into a two-dimensional array of physical qubits, and the energy cost of that translation is rarely quantified at the level of a logical operation. This paper specifies a minimal, convention-explicit energy model for a rotated…
Error Correction Is a Landauer Machine: The Thermodynamic Floor of Quantum Error-Correction Overhead
Every cycle of active (measurement-based) quantum error correction is an erasure process priced by Landauer's principle at no less than kT ln 2 per erased bit; correction overhead therefore converges to a positive thermodynamic floor, (n-k)/k * kT ln 2 per logical qubit per round for an n,k…
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
QWAV Quantum Software possesses a validated technical differentiator in JPCUB, but the SaaS go-to-market model carries a structural weakness. This paper proposes the JPCUB Consortium model combined with grant-funded core R&D, transforming JPCUB from a single-vendor product into a multi-stakeholder…
The Qudit Advantage: System-Level Joules-per-Solution Comparison of a Qudit Architecture Against 17 Conventional Qubit Quantum Computing Platforms
The JPCUB Competitive Landscape v2.0 benchmarked 17 qubit-based quantum computing platforms across a single system-level energy-efficiency metric: joules per solution (J/sol). All 17 platforms use two-level quantum systems (qubits). This paper extends the JPCUB framework to qudit architectures —…
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
Abstract 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…
The QWAV Decade: Enterprise p-Adic Computing 2025-2035
Computing efficiency — measured by Joules Per Computational Unit (JPCUB †) — will be the dominant competitive axis in enterprise computing by 2035. This document forecasts the JPCUB ecosystem's evolution across three eras. Era 1: Benchmark (2025-2028) — JPCUB is validated against public hardware…
The Joules-per-Solution Metric: Definition, Measurement Protocol, and Anti-Gaming Provisions for Honest Computational Benchmarking
We define and formalize the joules-per-solution (J/S) metric as a universal, cross-domain measure of computational energy efficiency. The metric accounts for six energy components: computation, memory, I/O, cooling, power conversion, and amortized manufacturing. We provide a closed-form definition,…
The BQNN Classical Baseline: Constructive Falsification of Near-Term Quantum Advantage at a Fifteen-Million-to-One Energy Disadvantage
Classical BinaryConnect ensemble achieves 92.73% accuracy vs BQNN quantum inference (~82-85%) at 0.0365 J vs 550,000 J (ratio 1.5x10^7). CAL-BQNN-05 confirmed one year early.
The Physics of Computation: Fundamental Limits and the Honest Boundaries of Post-Classical Computing
Phase III of the Qubit Delusion series. Examines fundamental physical limits on computation: Landauer bound, Margolus-Levitin theorem, Bremermann limit, Bekenstein bound. Shows that quantum error-correction overhead (1e2-1e3 physical operations per logical operation) multiplies thermodynamic cost…
Quantum Abacus
The scalability of active, gate-based quantum computers is fundamentally challenged by the “Thermodynamic Wall,” where the heat from control electronics becomes prohibitive. This study computationally investigates the “Quantum Abacus,” a passive quantum computing architecture that circumvents this…
Spectral Dynamics and Thermodynamic Stability in the Arithmetic Quantum Framework
The scalability of fault-tolerant quantum computing is currently obstructed by a “Thermodynamic Wall,” where the entropy generated by active error correction (QEC) cycles scales exponentially with the number of logical qubits. This research addresses the crisis by proposing a transition from active,…
Autonomous Dissipative Quantum Processing
Current quantum computing architectures face a thermodynamic bottleneck where the energy cost of classical error correction scales superlinearly with system size. Reliance on exogenous classical control imposes a latency and power penalty that renders hybrid paradigms unscalable for exascale…
Thermodynamic Veto
The realization of commercially viable, fault-tolerant quantum computing is precluded not by engineering immaturity but by a fundamental percolation phase transition driven by correlated noise and thermodynamic constraints, which render the required system scales physically uncorrectable. The status…
Escaping the Millikelvin Death Spiral
Standard quantum architectures rely on dilution refrigeration to suppress thermal noise, tethering the industry to a non-scalable 20 mK thermal floor. The cooling power at millikelvin temperatures scales poorly, creating a “mainframe constraint” that limits widespread deployment. Here, a 4-Kelvin…
Thermodynamic and Informational Bottlenecks of Scalable Fault-Tolerant Quantum Computation
The promise of fault-tolerant quantum computation rests on its ability to solve certain intractable problems exponentially faster than classical computers. However, this theoretical promise is challenged by a cascade of interconnected physical bottlenecks, where the act of scaling quantum resources…
THERMODYNAMIC AND TOPOLOGICAL CONSTRAINTS ON BIOLOGICAL QUANTUM PROCESSING
This study establishes a rigorous quantitative boundary between engineered quantum systems and biological matter, defined by the thermodynamic cost of information protection. By benchmarking the 2025 Google “Willow” superconducting processor—which requires cryogenic isolation (20 mK) and active…
Thermodynamic and Quantum Constraints on Scalable Quantum Computing
The central tension in scalable quantum computing lies between the exponential growth of quantum information density and the polynomial limits of cryogenic heat extraction. This thermodynamic bottleneck motivates an architectural inversion, where high-power control and readout electronics are…
Thermodynamic Imperative
Standard quantum computing paradigms assume that minimizing temperature is the primary pathway to coherence, driving massive investment in millikelvin dilution refrigeration. However, a fundamental thermodynamic paradox remains unsolved: cooling capacity scales superlinearly with temperature…
Thermodynamic Scaling of 4-Kelvin Topological Processors
Standard superconducting quantum processors are currently constrained by the thermodynamic bottleneck of millikelvin dilution refrigeration, which precludes the integration of high-speed control logic and limits scalability. This reliance on the 20 mK regime creates a “mainframe constraint” where…
Thermodynamic Viability and the Universality of Feynman Matter
The dominant paradigm for universal quantum computation, predicated on active error correction, is fundamentally constrained by a thermodynamic wall, a phase transition where the entropy produced by control operations catastrophically overwhelms the system. This study quantifies this constraint,…
Thermodynamics of Structural Persistence (Topological Memory)
The prevailing paradigm in quantum information preservation—active intervention—relies on continuous, energy-intensive error correction cycles to suppress entropic decay. This approach faces a fundamental scaling limitation: the latency horizon, where the time delay of the control loop exceeds the…
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