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 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.
Decoherence in quantum systems is traditionally viewed as a technical obstacle arising from environmental noise. This paper presents a hierarchical active inference framework, interpreting 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 active Hamiltonian control to stabilize the system boundary. The integration of a 3D volumetric topological complex outlines a geometric architecture designed to mitigate the Eastin-Knill constraint. Empirical execution on the bare-metal IBM Kingston processor evaluates this framework against unmitigated hardware baselines. 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 stabilization over unmitigated peak fidelity. By establishing a highly predictable, actively governed baseline, this framework represents a highly sophisticated application of classical-quantum error mitigation, re-framing the Eastin-Knill restriction from an absolute homological barrier into an addressable temporal control protocol.
Quantum state decoherence and thermal relaxation remain critical bottlenecks in Near-Intermediate Scale Quantum (NISQ) architectures. This paper introduces a co-designed 5-qubit pentagonal hardware topology integrated with an ultra-fast active FPGA feedback loop (< 50 ns) to suppress phase-kickback and environmental thermal degradation. Experimental field verification was conducted on the IBM Quantum platform using the 156-qubit ibm_fez physical processor (Job ID: d9ku512br2fc73e7t730). Under an unmitigated physical delay of 125,000 dt (~562.5 us), the proposed 5-qubit core maintained a state fidelity of 84% (860/1024 shots) in the dominant target state (|00001>). The architecture demonstrates that tight topology loop-backs combined with sub-microsecond feedback pipelines provide robust thermal stabilization without incurring massive error-correction pulse overheads.
We present hereby a high-level hardware-agnostic framework for a resonant-control-based approach to stabilizing quantum processors. The method improves coherence and logical error performance by aligning control operations with intrinsic system response features through generalized resonance and quasi-aperiodic timing. This paper intentionally omits implementation details, proprietary algorithms, and confidential calibration methods to avoid prejudicing ongoing patent proceedings. Instead, we focus on conceptual formalism, theoretical motivation, and simulated indicators of performance improvement. Detailed implementation remains confidential pending patent issuance and licensing discussions. Patent pending (U.S. Provisional Application filed November 2025). All specific resonant carrier frequencies, base timing periods, numerical ratio scaling constants, envelope-shaping functions, and adaptive feedback algorithms are trade secrets of Dubito Inc. and are not disclosed in this work The resonant-control architecture (RCA) introduced in this work suggests a conceptual shift in how quantum decoherence and control noise are addressed at scale. Rather than treating decoherence purely as a consequence of microscopic material limitations or stochastic fluctuations, RCA frames the problem in terms of macroscopic dynamical structure, namely, the presence of device-specific resonance features and stability basins embedded within the quantum system’s effective response landscape. By aligning control pulses with these structural features, one can reduce sensitivity to low-frequency drift and non-Markovian disturbances without requiring explicit modeling of their origins. From a theoretical standpoint, RCA generalizes the idea behind dynamical-decoupling and filter-function approaches, but differs critically in its departure from strict periodicity or analytically prescribed timing sequences. Whereas classical decoupling protocols rely on precise, regular intervals with well-defined spectral notches, our resonant alignment leverages quasi-aperiodic intervals to avoid aliasing while maintaining coherence with intrinsic dynamical modes. This opens a pathway to more stable long-time behavior, especially under significant drift or structured noise. Another key implication concerns scalability. Fault-tolerant quantum computing requires the ability to sustain high-rate syndrome extraction and realtime feedback, not only sufficiently low physical error rates. A reduction in effective sensitivity to slow drifts or burst-like errors directly impacts the stability of logical operations, potentially easing the overhead associated with syndrome cycles and decoder latency. Though we intentionally avoid specifying exact performance metrics, simulation trends indicate that RCA can modify the effective scaling constants governing logical error suppression, providing a complementary layer to code-level corrections. Because RCA is hardware-agnostic, its implications extend across modalities, including superconducting qubits, bosonic encodings, trapped ions, and photonic platforms. Each modality has distinct noise profiles, yet all exhibit some form of internal dynamical structure that can be harnessed for resonant alignment. This offers a unifying perspective that could aid in cross-platform benchmarking and co-design strategies between hardware and control layers. Finally, RCA opens conceptual avenues for understanding the interplay between classical control and quantum dynamics. By abstracting away implementation details while emphasizing structural alignment, it establishes a theoretical foundation for future studies on stability basins, quasi-periodic scheduling, and adaptive resonance identification in noisy quantum systems. The RCA framework generalizes known dynamical-decoupling and frequency-modulated approaches while remaining distinct in its treatment of internal resonance and adaptive quasi-aperiodicity. Because implementation-specific algorithms are withheld, the paper serves as a conceptual introduction rather than a disclosure of patent-sensitive information. We have outlined a resonant-control framework that enhances quantum coherence and suppresses logical error accumulation by exploiting intrinsic dynamical structure within quantum hardware. The approach is fundamentally architecture-neutral and can be integrated into existing control stacks without requiring modifications to qubit design or measurement infrastructure. While the specific algorithms and calibration methods are withheld to preserve ongoing patent protections, the conceptual and theoretical basis presented here provides a foundation for future analyses and controlled experimental evaluations. This work suggests that progress toward scalable quantum computation may depend as much on control-level innovation as on hardware improvements. Resonant alignment and quasi-aperiodic timing sequences offer a pathway for mitigating drift sensitivity and noise coupling, potentially reducing the resource overhead associated with quantum error correction. Future research will focus on detailed modeling, cross-platform validation, and integration with advanced decoding and feedback systems. In summary, the resonant-control architecture represents a promising direction for improving quantum system stability and should be considered an essential component of next-generation quantum control and fault tolerance. We present a trade-secret-safe exposition of a resonant-control approach to improving quantum coherence and logical error performance. Detailed mechanisms remain proprietary pending patent review. Nov. 25, 2025, Daniel Solis Dubito Inc. www.dubito-ergo.com
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
This review synthesizes current understanding of decoherence pathways across leading hardware platforms and explains why several experimentally observed noise features—drift, burst events, coherent components, correlated and non-Markovian structure, and leakage—can be disproportionately damaging for QEC. Decoherence remains the dominant impediment to scalable quantum computing because it is not a single error mechanism but a system-level phenomenon arising from materials defects, electromagnetic loss, control electronics, measurement backaction, and the broader environment in which a processor operates. Quantum error correction (QEC) is designed to algorithmically suppress physical noise, yet its practical success depends on how closely real devices satisfy the assumptions under which fault tolerance is proved: approximate locality, weak temporal correlations, sufficiently stochastic error statistics, low leakage, and reliable syndrome extraction. We then evaluate fundamental and engineering challenges that shape the viability of QEC at scale: syndrome measurement fidelity, correlated error suppression, decoding latency and classical co-processing, architectural constraints (connectivity, crosstalk, calibration overhead), and the resource cost of implementing a universal fault-tolerant gate set. Recent demonstrations of below-threshold behaviour and “break-even” regimes show that QEC is transitioning from theory to practice, but also clarify what remains unresolved: maintaining stable noise below fault-tolerance targets over long times, scaling to many logical qubits with low correlated-error rates, and integrating hardware-aware codes and decoders. We conclude with research priorities that treat decoherence and QEC as part of a co-designed stack spanning device physics, control, architecture, and algorithms.
Abstract: The scalability of Noisy Intermediate-Scale Quantum (NISQ) devices remains fundamentally limited by stochastic decoherence, which traditional passive shielding and resource-heavy quantum error correction (QEC) struggle to overcome. Here, we propose a paradigm shift from passive noise mitigation to active internal phase stabilization. By integrating the Lie-algebraic renormalization (LA-ODR) framework with a dynamic model of temporal susceptibility (χ_τ), we derive a nonlinear control law for quantum coherence. We demonstrate that decoherence can be treated as a deterministic dynamical process governed by the feedback equation dχ_τ / dt = −α · Γ_τ · χ_τ + λ · (1 − χ_τ). Our numerical simulations confirm the formation of metastable coherence plateaus, where the effective qubit lifetime is extended significantly beyond the standard Lindbladian limit (e.g., from 100 µs to 1.5 ms in transmon-based models). We further specify a hardware-ready Temporal Phase-Locked Loop (TPLL) architecture, proving that with control latencies below 500 ns, active synchronization of the temporal metric becomes feasible on modern FPGA-based controllers. This framework provides a path toward fault-tolerant quantum computing by enabling fidelity-by-design at the physical layer, potentially providing a substantial reduction in QEC overhead by maintaining high physical fidelity prior to logical encoding. Keywords nonlinear phase stabilization; temporal susceptibility χτ; Lie-observable-dependent renormalization (LA-ODR); fixed-point Lindbladian; quantum decoherence; active feedback control; temporal phase-locked loop (TPLL); NISQ devices; superconducting qubits; cold atom arrays