Aug 2026· Zenodo (CERN European Organization for Nuclear Research)
Quantum Mechanics and Applications
Abstract
This paper establishes the observer as a physical node embedded in the causal graph and resolves the conceptual relation between General Relativity and Quantum Mechanics within the N.E.A. (Network Emergent Architecture) framework. The Mens Protocol defines the observer as a self-referential sampling operator, subject to the same finite bandwidth B=1 as every other node. The Stride-10 sampling window imposes a Nyquist limit on perceptual resolution. An SVD spectral audit reveals that over 95% of perceptual energy is concentrated in a single dominant mode across all tested lattice sizes — the topological origin of the subjective flow of time. This dominant mode is not a saturation plateau claim; the trend is monotonic and robust, with verification on larger lattices left as future numerical work. Three spatial dimensions are inherited from the d=3 efficiency plateau (H); the temporal dimension is inherited from the dominant singular mode of the directed sampling operator. Special and General Relativity are shown to be the geometry of bandwidth allocation on the causal graph (hardware). Motion is defined as the re-indexing of adjacency edges; the Pythagorean constraint f_int^2 + f_ext^2 = B^2 yields time dilation as an algebraic necessity. The 1/r gravitational potential is the Discrete Green's Function of the 3D graph Laplacian — a topological fingerprint of three-dimensional space. Quantum Mechanics describes the information-theoretic limits of observing that hardware with finite resources (software). The wavefunction arises as a beat envelope from aliased sampling, inheriting linearity from hardware unitarity. Measurement collapse is bandwidth hijacking. The uncertainty principle is the Nyquist limit, with a dimensionless uncertainty floor from the bandwidth constraint. Pauli exclusion is buffer-overflow protection with spin-±1/2 as time-division multiplexing. Entanglement is interpreted as a candidate topological trace on the 1D causal skeleton mandated by the Being Tax — a hypothesis, not yet a derivation. These two descriptions are not contradictory but are descriptively orthogonal, dynamically coupled layers of a single computational stack governed by the Pythagorean bandwidth constraint. The contradiction dissolves upon recognizing that physicists have been attempting to locate hardware bus specifications within software rendering algorithms. The observer's sampling rent is quantitatively denominated in Zhangyu (ZY): H_obs ≈ 1.0117 ZY as a preliminary numerical estimate. The hydrogen atom spectrum is reproduced on the discrete C8 lattice, converging to the continuum Schrödinger limit with 0.0024% deviation. ħ is demoted from fundamental status: ħ = Z × t_Tick, the product of bandwidth currency and the Tick. The preferred basis problem (OP-8), the first-principles derivation of the GR coefficient 2GM/c² (OP-O1), and Bell statistics for skeletal entanglement (OP-24) are honestly marked as open problems. The Born rule is identified as a maximum-entropy hypothesis, not yet a formal derivation from graph topology. A complete Scope and Logical Boundaries declaration is included, alongside extended classical references (Nyquist, Shannon, Born, Einstein, Bell).
MAGE explains how externalized knowledge, bounded action, independent evaluation, and retained human authority can compose into a governed engineering environment, and proposes tests of when that environment turns commodity intelligence into durable engineering progress.
James C. Davis, Kelechi G. Kalu, Huiyun Peng et al.· 1 citation
LLMs are increasingly used for code generation, yet they frequently hallucinate non-existent software packages, creating exploitable entry points into the software supply chain. We make four contributions to this problem. First, we show that prior evaluation methodologies systematically inflate hallucination rates by misclassifying standard-library modules as hallucinations in some languages. For Python, the overestimation reaches 9.4 percentage points. Second, we evaluate seven inference-time defenses for mitigating package hallucinations, including five guided decoding strategies (Greedy, Contrastive, DoLa, Nudging, and Active Layer-Contrastive Decoding), an iterative self-refinement approach (Self-Refine), and a Retrieval-Augmented Generation (RAG)-based defense.. Across eight models spanning five families and four programming languages (Python, JavaScript, Ruby, Rust), RAG reduces the package hallucination rate (PHR) in 18 of 32 model--language configurations. Third, we introduce Package Utility (PU) to assess whether defenses preserve valid and task-relevant recommendations. Among strategies evaluated, Greedy decoding provides the strongest average mitigation--utility trade-off. Fourth, we stress-test all strategies under adversarial prompts seeded with fabricated package names and find that PHR surges by up to 45 percentage points relative to standard prompts, with Ruby consistently the most vulnerable language (80.9--95.2\%). Under adversarial conditions, RAG and Self-Refine outperform all decoding-only strategies, indicating that robust defense requires either external grounding or iterative self-verification when prompts are actively hostile. Our results recast package hallucination as both a measurement problem and a decoding-time control problem, and they demonstrate that the choice of defense must be matched to the threat model and recommendation utility.
Albérick Euraste Djiré, Iyiola E. Olatunji, Melissa Tessa et al.· 1 citation
HawkEye is introduced, a modular, web-based vulnerability auditing platform designed to streamline security analysis by integrating multiple scanning tools within a unified dashboard and illustrates how consolidated reporting improves vulnerability prioritization for development teams.
D. R. Patil, Varad Salgare, Devaj Arya et al.· International Journal for Re...· 0 citations
By streamlining workflows and fostering collaboration, this platform offers a scalable, cost- effective solution for SMEs and contributes to software engineering by demonstrating how integrated technologies can modernize development processes in resource limited contexts, with potential for broader adoption in Albania and beyond.
OBJECTIVE
To prospectively evaluate whether modifying DSL version 5-based hearing aid (HA) fittings by adjusting gain on HA fitting software so that measured functional gain (FG) approached a one-third gain (1/3G) target could provide appropriate fitting outcomes in patients with sensorineural hearing loss.
METHODS
Twenty-four patients (48 ears) with bilateral sensorineural hearing loss underwent initial HA fitting using the DSL version 5 prescription formula. FG was measured at 250-4000 Hz, and HA gain was adjusted on HA fitting software so that FG approached the target 1/3 G. Speech discrimination scores at 65 and 80 dB SPL were evaluated after a two-week trial period using the 67-S Japanese monosyllable word list. Based on speech discrimination test results, ears were classified as well-fitting or non-well-fitting. FG values were compared between the two groups.
RESULTS
Twenty-one patients (42 ears) completed the study. Thirty-one ears (73%) were classified as well-fitting. Although HA gain was adjusted toward the target 1/3 G, measured FG values at 250 and 500 Hz remained lower than the target values. In well-fitting ears, low-frequency FG values were lower than the target 1/3 G, whereas FG at 2000 Hz was close to the target value. In contrast, non-well-fitting ears showed low-frequency FG values closer to the target 1/3 G, whereas FG values at 2000 and 4000 Hz remained below the target values.
CONCLUSIONS
Although HAs adjusted toward a 1/3 G target did not achieve the intended FG values, particularly at low frequencies, relatively favorable fitting outcomes were obtained in approximately three-quarters of the ears. In well-fitting ears, low-frequency FG remained below the target 1/3 G, whereas FG in the mid-frequency range around 2000 Hz was close to the target value. These findings provide a basis for future prospective studies to clarify how these FG characteristics should be applied to optimize HA adjustment.
A USAF cadet and a Lincoln Laboratory researcher found AI chatbots can help nontechnical service members produce viable software applications for their unique problems.