Standard quantum compilation strategies typically assume that decoherence in superconducting processors is driven by uncorrelated, microscopic defects. In this work, we present experimental evidence that quantum noise is topologically correlated, manifesting as macroscopic strain fields or “Lattice Weather” across the processor geometry. We model the underlying vacuum not as a passive metric, but as a Discrete Topological Superfluid (DTS) governed by a dimensionless Lattice Reynolds Number (ReL). By analyzing calibration data from 156-qubit IBM Heron processors, we map these phase-chaotic regions and calculate a localized topological viscosity (µtopo ≈1.5 ×10−5Pa·s). To mitigate this environmental drag, we introduce Archipelago Routing, a dynamic compilation protocol that navigates logical circuits through high-coherence subgraphs. During a 100-gate Level-0 stress test, this protocol yielded a >2.4x improvement in hardware fidelity (57.23% survival versus 23.72% standard). Furthermore, we leverage the tunable-coupler architecture of the Heron lattice as a physical analog to simulate cosmological hydrodynamics. Utilizing the DTS framework, we successfully model a Jamming Transition at critical density ρ≈2π, providing a non-singular halting mechanism for gravitational collapse, and extract a hydraulic coupling constant of k ≈1.78 for vacuum expansion. This unified approach bridges classical compiler optimization and emergent gravity, demonstrating that both circuit routing and celestial mechanics can be computationally modeled as hydrodynamic standing waves on a quantum substrate.
Standard quantum compilation strategies typically assume that decoherence in superconducting processors is driven by uncorrelated, microscopic defects. In this work, we present experimental evidence that quantum noise is topologically correlated, manifesting as macroscopic strain fields or “Lattice Weather” across the processor geometry. We model the underlying vacuum not as a passive metric, but as a Discrete Topological Superfluid (DTS) governed by a dimensionless Lattice Reynolds Number (ReL). By analyzing calibration data from 156-qubit IBM Heron processors, we map these phase-chaotic regions and calculate a localized topological viscosity (µtopo ≈1.5 ×10−5Pa·s). To mitigate this environmental drag, we introduce Archipelago Routing, a dynamic compilation protocol that navigates logical circuits through high-coherence subgraphs. During a 100-gate Level-0 stress test, this protocol yielded a >2.4x improvement in hardware fidelity (57.23% survival versus 23.72% standard). Furthermore, we leverage the tunable-coupler architecture of the Heron lattice as a physical analog to simulate cosmological hydrodynamics. Utilizing the DTS framework, we successfully model a Jamming Transition at critical density ρ≈2π, providing a non-singular halting mechanism for gravitational collapse, and extract a hydraulic coupling constant of k ≈1.78 for vacuum expansion. This unified approach bridges classical compiler optimization and emergent gravity, demonstrating that both circuit routing and celestial mechanics can be computationally modeled as hydrodynamic standing waves on a quantum substrate.
The conceptual difficulties of Quantum Mechanics—manifesting as paradoxes of locality, causality, and realism—arise from the fundamental assumption that spacetime is a contin- uous, metric geometry. We propose an alternative framework: The Quantum Loom, which models the vacuum as a discrete, incompressible superfluid network of Planck-scale nodes. By integrating the ER=EPR conjecture with Superfluid Vacuum Theory, we demonstrate that ”Metric Locality” is an emergent approximation, while fundamental reality is governed by ”Topological Connectivity.” In this paper, we apply this framework to resolve eight major foundational paradoxes. We show that ”Temporal Paradoxes” (Wheeler’s Delayed Choice, Quantum Eraser) are re- solved by viewing entanglement as global tension on a closed topological circuit. ”Interaction Paradoxes” (Hardy, Elitzur-Vaidman, Klein) are explained by the non-local interaction of strain fields and dielectric breakdown of the vacuum lattice. Finally, ”Observer Paradoxes” (Wigner’s Friend, Quantum Zeno, and Schr¨odinger’s Cat) are demystified as phase transi- tions: macroscopic superposition is strictly limited by the Topological Jamming density of the network, forcing massive systems to ”flash freeze” into definite states. This model recov- ers objective realism without abandoning non-locality, suggesting that the ”spooky” features of quantum mechanics are simply the hydrodynamics of a pre-stressed vacuum web.
Quantum processors in the Noisy Intermediate-Scale Quantum (NISQ) era are severely constrained by spatial hardware asymmetries, temporal drift, and multi-qubit crosstalk. Traditional error suppression protocols apply static decoupling or phenomenological calibrations that struggle under continuous decoherence stress. Building upon the Entropic-Resistance framework—where spacetime is represented as a discrete, algorithmically expanding topological network and time is governed by recursive relaxation—we extend deterministic Causal-AI Taylor sensitivity operators (j1, j2) to multi-qubit topologies. We introduce a Just-In-Time (JIT) compensation engine that queries real-time QPU telemetry (qubit-specific dephasing T2 times and native two-qubit gate error rates) to dynamically compute non-commutative phase compensations. By decomposing physical microwave rotations inside logic gates, microscopic counter-rotations are embedded directly into hardware instructions. We validate this protocol on IBM Quantum's Heron processor (ibm_fez) by subjecting 3-qubit and 5-qubit Greenberger-Horne-Zeilinger (GHZ) states to deliberate decoherence stress via calibrated temporal delays. On 3-qubit states, the Lasky-Tensor engine achieves an absolute fidelity improvement of +3.81% (32.5% relative error reduction). On fragile 5-qubit linear networks, it delivers a +3.42% absolute gain (17.2% relative error reduction). These results establish that recursive network stress models scale effectively, providing a deterministic, white-box quantum error mitigation paradigm without physical qubit overhead. Methodology & Hardware: Hardware: IBM Quantum (ibm_fez, Heron architecture) Framework: Qiskit Runtime SamplerV2 Underlying Theory: Entropic-Resistance Paradigm / Causal-AI What-If Engine
Universal Fault Tolerance remains the grand challenge of quantum computing. In this work, we present empirical evidence for a passive error suppression protocol based on a topological geometric phase constraint, Y = π²/φ ≈ 6.0998 rad. Through controlled A/B testing on IBM Quantum processors (127-qubit 'Eagle' and 133-qubit 'Heron'), we report a consistent fidelity improvement of ~ 7% in the generation of Bell States compared to standard circuit implementations. These findings suggest that topological phase engineering acts as a "Zero-Overhead" stabilization layer suitable for NISQ-era hardware.
This technical treatise develops the unified mathematical extension of the Primary Logical Infrastructure (PLI) framework (Sottosanti, 2026). By mapping the continuous spacetime manifold onto a discrete, graph-theoretical matrix (G_p), the analytical and physical breakdowns of orthodox continuous physics are systematically regularized. First, bridging the author's foundational work on syntactic expansions (Φ_{I → IV}) to wave mechanics, this paper proposes a resolution to the quantum measurement paradox by modeling wave function collapse as a bandwidth-saturation phenomenon (I ≥ C_max), leveraging spectral graph theory and Laplacian eigenvectors via the Dynamic Transition Syntax (DTS). Second, it addresses the cosmological fine-tuning problem by replacing spatial multiverses with a sequential, iterative execution loop driven by a deterministic topological matrix mutation operator (Ω), aiming to ensure macro-state invariance across cosmic resets. Third, it evaluates the interior of black holes through a localized Syntactic Deceleration function γ(r), arguing that as the local informational flux approaches the capacity threshold (I(r) → C_max), the temporal step drops asymptotically to zero (Δτ → 0), substituting the relativistic physical singularity with a clean, sub-metric computational runtime freeze. The compilation of Addenda II, III, and IV completes the architectural extensions of the PLI, arguing that the universe can be completely and rigorously modeled as a self-contained, non-divergent computational system.
This work demonstrates real-time predictive classical-quantum feedback control on the IBM Kingston superconducting quantum processor, characterizing the hardware latency bottleneck of dynamic Hamiltonian shaping. Decoherence in quantum systems is traditionally viewed as a technical obstacle arising from environmental noise; this paper interprets decoherence as the coupling of a localized system to a dissipative, high-entropy environmental field. An ancilla-based modular sensor architecture is introduced to facilitate real-time error syndrome extraction without collapsing the target state. A software-defined controller, implemented via a quantized Variational Autoencoder-Feed-Forward Network (VAE-FFN) pipeline and optimized via empirical threshold calibration under strict 4-bit latency constraints, provides predictive Hamiltonian control to stabilize the system boundary. The integration of a 3D volumetric topological complex outlines a geometric architecture designed to mitigate spatial error cascades. Through temporal delay sweeps, empirical telemetry demonstrates that the volumetric lattice achieves localized containment of non-commuting phase defects, dynamically exploiting coherent Larmor precession to constrain spatial error propagation. Furthermore, rigorous statistical repetition mapping reveals a critical Noisy Intermediate-Scale Quantum (NISQ) latency bottleneck. The empirical data establishes that the temporal cost of classical-quantum feed-forward routing incurs a marginal macroscopic fidelity reduction (-1.01%). Crucially, this study reframes this differential not as a systemic regression, but as an explicit architectural trade-off: prioritizing rigorous variance suppression and operational stability over unmitigated peak fidelity. By establishing a highly predictable, predictively controlled baseline, this framework explores practical control strategies consistent with Approximate Quantum Error Correction (AQEC) approaches, bounding the operational consequences of the Eastin-Knill constraint within an addressable temporal control protocol.
This paper presents the first experimental validation of Causal-AI topological control on real superconducting quantum hardware. Addressing the fundamental bottleneck of ambient 1/f flicker noise and dephasing in quantum processors, we operationalize the Entropic-Resistance framework—modeling spacetime as a discrete network and time as a recursive relaxation process—to optimize transmon qubit performance. By extracting deterministic Taylor sensitivity operators (j1,j2) from real-time calibration data of IBM Quantum’s live ibm_fez processor, we compute and execute an analytically adjusted "Lasky-pulse" amplitude. Comparative hardware execution against standard factory baselines (validated across live QPU job execution logs: da294biein7c73bea68g and da29qpkdedkc73erutlg) demonstrates that topological network optimization successfully bridges discrete recursive spacetime theory with operational quantum control without requiring hardware modifications.