Many systems admit observables that can be decomposed into exponentially decaying modes. In such systems, the asymptotic exponential rate is not controlled by total amplitude, mode count, particle number, average rate, or any other aggregate that fails to determine the slowest nonvanishing decay component; it is controlled by the bottleneck mode. We formalize this as a finite-dimensional constraint theorem and prove a no-go result: any rate law that depends only on an aggregate that can be held fixed while the bottleneck changes cannot be a universal asymptotic rate predictor. We give a rigorous application to finite-dimensional Markovian dephasing, where the decay of supported coherences is governed by the minimum decoherence rate among them. An explicit n-qubit family |ψr⟩ = (|0 n⟩ + |1 r0 n−r ⟩)/ √ 2 with r = 1, . . . , n has identical particle count and asymptotic rates differing by a factor of n, falsifying particle-count-only predictors. We test the structural content of the constraint experimentally on ibm torino using full quantum state tomography of 3-qubit GHZ and Cluster states across five idle delays. The predicted leading-order law DM = AρW≤D∗ + O(W3/2 ) holds linearly to R2 > 0.999 on Cluster and R2 > 0.99 on GHZ; the calibration-independent ratio of regression slopes matches the parameter-free Kubo–Mori prediction to 9.1%, ruling out alternative monotone kernels in the Petz family. We then discuss collapse-type master equations as a conditional application and machine-learning settings as spectral analogues. The contribution is mathematical (a constraint theorem) and experimental (a structural demonstration on real quantum hardware), not a new dynamical mechanism.
Many systems admit observables that can be decomposed into exponentially decaying modes. In such systems, the asymptotic exponential rate is not controlled by total amplitude, mode count, particle number, average rate, or any other aggregate that fails to determine the slowest nonvanishing decay component; it is controlled by the bottleneck mode. We formalize this as a finite-dimensional constraint theorem and prove a no-go result: any rate law that depends only on an aggregate that can be held fixed while the bottleneck changes cannot be a universal asymptotic rate predictor. We give a rigorous application to finite-dimensional Markovian dephasing, where the decay of supported coherences is governed by the minimum decoherence rate among them. An explicit n-qubit family |ψr⟩ = (|0 n⟩ + |1 r0 n−r ⟩)/ √ 2 with r = 1, . . . , n has identical particle count and asymptotic rates differing by a factor of n, falsifying particle-count-only predictors. We test the structural content of the constraint experimentally on ibm torino using full quantum state tomography of 3-qubit GHZ and Cluster states across five idle delays. The predicted leading-order law DM = AρW≤D∗ + O(W3/2 ) holds linearly to R2 > 0.999 on Cluster and R2 > 0.99 on GHZ; the calibration-independent ratio of regression slopes matches the parameter-free Kubo–Mori prediction to 9.1%, ruling out alternative monotone kernels in the Petz family. We then discuss collapse-type master equations as a conditional application and machine-learning settings as spectral analogues. The contribution is mathematical (a constraint theorem) and experimental (a structural demonstration on real quantum hardware), not a new dynamical mechanism.
Despite two decades of work on decoherence and entanglement robustness, no quantitative principle explains why equally entangled quantum states decohere at radically different rates under identical noise. Here we identify the missing variable: a single integer D∗that measures the minimum geometric distance of quantum coherence in Hilbert space. We show that this spectral bottleneck controls irreversible entropy production, while entanglement depth, purity, and coherence norms do not. The principle emerges from an exact spectral decomposition of coherence under local noise, combined with a controlled asymptotic expansion of von Neumann entropy. States with identical entanglement but different D∗exhibit paramet-rically different collapse times—explaining the stark contrast between fragile GHZ states (D∗= n, fast collapse) and robust cluster states (D∗= 1, slow collapse). This upgrades previous empirical observations to a derived theorem, with a prefactor Acomputed exactly from the Kubo–Mori kernel rather than fitted. The spectral bottleneck is not a diagnostic but a control variable: it determines when classical statistics emerge from quantum superposition. This principle resolves a foundational gap in decoherence theory and identifies the correct macroscopic variable governing the quantum-to-classical transition under local noise.
Two quantum states with identical entanglement, two neural networks with identical parameters, and two mass superpositions with identical constituents—in each case, one survives while the other is destroyed.We identify the single geometric variable that controls information survival across all three. For decades, information stability in quantum systems and machine learning has been analyzed through resource counting—particle number, entanglement magnitude, or parameter count—despite persistent, model-independent failures of these explanations. The most prominent examples are the exponential fragility of GHZ states relative to Cluster states under identical decoherence and the frequent breakdown of transfer in overparameterized neural networks. These phenomena were observed, quantified, and repeatedly labeled "surprising," yet no controlling variable or mechanism was identified. This work provides both. We identify a geometric invariant—the spectral bottleneck D*—and show that it induces a concrete mechanism of information loss: spectral peeling, in which coherence decays shell-by-shell in order of increasing spectral distance from the noise geometry. From first principles, we prove that under general Markovian dynamics the entropy gap obeys the asymptotic decay law D_M(t) = A · W_{≤D}(t) + O(W^{3/2})**, where D controls the decay exponent and the Kubo-Mori prefactor A controls the thermodynamic response. This yields the parameter-free prediction τ_Cluster/τ_GHZ = n, verified on IBM quantum hardware with sub-percent agreement, and predicts robustness inversions under correlated noise invisible to all entanglement measures. The framework extends in three directions: (i) to non-Markovian dynamics, where the static noise metric is replaced by an integrated metric Σ_d(t) = ∫₀ᵗ Σ_k γ_k(s) d_k ds and the bottleneck D* is preserved exactly; (ii) to machine learning, where the same structure governs transfer fidelity under domain shift; and (iii) to gravitational decoherence, where GHZ-like mass superpositions collapse as n² while cluster-like configurations remain robust, yielding a 10⁸× discriminant test between gravitational and environmental collapse. The conclusion is a structural principle: information persists when encoded at minimal spectral distance from the noise geometry. Noise destroys outer shells first—spectral peeling—and the innermost occupied shell controls survival.
We prove that a single abstract theorem governs information loss in quantum systems under Lindbladdynamics, in neural networks under domain shift, in gravitational decoherence, and in non-Markovian open systems. The theorem requires three objects: a metrized configuration space (X,d),a positive semidefinite operator ρ on X decomposed into shells by d, and a distance-monotone contraction—any completely positive map that suppresses off-diagonal elements monotonically in d.From these alone, we derive the spectral bottleneck D∗, the peeling order, the entropy–shell connectionvia the Kubo-Mori kernel, and the parameter-free collapse time ratio. Lindblad dephasing,gravitational self-energy channels, spectral projection in transfer learning, and time-dependentnon-Markovian dynamics are all shown to be instantiations of the same abstract structure, with D∗emerging from the same theorem in every case.
We show that any objective collapse model satisfying (i) Markovian dynamics, (ii) Lindblad consistency, and (iii) pointer-basis localization is necessarily geometry-dependent: collapse rates are controlled by the spectral bottleneck D∗Σ, not by particle number, entanglement, or Hilbert-space dimension. This follows from the structure of pointer-diagonal Lindblad generators and does not require interpretational assumptions. Building on this foundation, we develop a min-imal completion of quantum mechanics—in the same technical sense as GRW/CSL—with two additional physical commitments: (A) the noise record is ontologically real, making outcomes deterministic given the record; and (B) the noise metric has gravitational origin, Σ = Σ(G)/ℏ, where the 1/r spatial structure is derived from linearized quantum gravity and the amplitude is fixed up to order-unity regularization. This yields the Penrose-Di´osi timescale τ ∼ℏ/∆EG as a derived result rather than an ansatz. The framework predicts that GHZ and Cluster states with the same particle number collapse at rates differing by a factor of n—a ratio that constitutes a parameter-free experimental test. This prediction has been validated on IBM quantum hardware, with sub-percent prefactor agreement for the theorem applied to environmental noise. We iden-tify a window λ0 ∈[10−20,10−10] Hz for the fundamental collapse rate, consistent with current bounds. Applications include: intrinsic geometric robustness of quantum error-correcting codes,Noise Geometry Tomography for reverse-engineering transport coefficients, and testable cosmo-logical implications. Within the class of Markovian CPTP collapse models that localize in a pointer basis, geometry-dependence is a theorem; models outside this class (e.g., non-Markovian,Everettian, or contextual) are not constrained by our result.
Preprint: This paper derives quantitative bounds on measurement windows for finite-capacity observers extracting information from decohering quantum systems, extending standard decoherence theory to realistic experimental constraints. Main Result: For Gaussian-Markovian decoherence with exponential information decay I(t) = I₀ exp(-2Γt), bounded-capacity observers lose access to system distinctions when mutual information drops below detection threshold ε, yielding measurement window: τ_c = (1/2Γ) log(α C_A / ε) where Γ is decoherence rate [s⁻¹], C_A is observer capacity [bits] defined via Shannon formula (bandwidth × log₂(SNR) × integration time), ε is detection threshold [bits], and α ~ 0.1-1 is a model-dependent constant from spectral decomposition of environmental information. This establishes logarithmic capacity-scaling: doubling detector quality extends measurement windows by only ~0.35/Γ seconds, implying diminishing returns from capacity improvements. Experimental Predictions: For state-of-the-art circuit QED (superconducting transmon qubits, T₁ = 100 μs, bandwidth Δf = 10 MHz, SNR = 10), the framework predicts τ_c ~ 4-10 μs. Varying bandwidth from 1-30 MHz (capacity C_A ∈ [3, 90] bits) produces measurable Δτ_c ≈ 1.7 μs variation (5-10% of coherence time). Five experimental tests discriminate capacity-scaling from standard decoherence: ∙ Tests 1-3: Verify logarithmic capacity-scaling, inverse rate-dependence, threshold-dependence ∙ Test 4: Multi-observer non-redundancy (at most one narrowband detector succeeds) ∙ Test 5: Capacity-dependent redundancy buildup (primary discriminating signature) Key Contributions: ∙ First quantitative analysis of Zurek's pre-objective phase under explicit finite-resource constraints ∙ Capacity-scaling law connecting Shannon information theory to quantum measurement dynamics ∙ Operational definitions ensuring falsifiability (capacity, threshold, mutual information defined via measurement protocols) ∙ Concrete numerical predictions for three platforms (circuit QED, spin qubits, optomechanics) with resource estimates ∙ Design principle: environmental shielding (linear benefit in τ_c) outperforms detector improvement (logarithmic benefit) when both options available Technical Approach: The bound follows from threshold-crossing analysis of exponential decay with capacity-limited initial information I₀ = α C_A, justified via spectral decomposition of environmental information under flat-spectrum approximation for narrowband observation. All parameters (Γ, C_A, ε) are operationally defined and independently measurable, avoiding circularity. Extensions to non-Markovian dynamics (memory kernels), scrambling systems (black holes, many-body chaos), and non-Gaussian noise (Lévy flights, 1/f noise) are discussed with conjectured scaling laws. Scope: The bound applies specifically to Gaussian-Markovian systems (harmonic oscillators, qubits in dispersive limit, weak continuous measurement with memoryless baths). Circuit QED provides optimal testbed due to tunable Purcell filters (bandwidth control), high coherence times (T₁ > 300 μs achieved), and multiplexed readout infrastructure (5+ independent detectors demonstrated). Validity requires α C_A > ε (initial information exceeds threshold); domain violations occur when capacity too small, threshold too high, or coupling too weak. Relation to Prior Work: Zurek's Quantum Darwinism (2003-2009) explains asymptotic objectivity emergence through environmental redundancy but assumes unbounded observers (C_A → ∞, t → ∞). This work analyzes the complementary finite-resource regime (C_A < ∞, t ~ τ_c), providing first capacity-parameterized bound on pre-objective phase duration. Framework is interpretation-neutral—compatible with Copenhagen, Many-Worlds, Bohmian mechanics, and relational quantum mechanics. Philosophical implications (process ontology, observer-dependent reality, impermanence) are explored but clearly separated from testable predictions. Methods: Open quantum systems theory, Shannon information theory, operational quantum measurement, circuit QED experimental physics, numerical prediction for realistic parameters. Content: Complete 90-page manuscript with axiomatic framework (§2), narrowband observation model (§3), main theorem with proof (§4), numerical predictions (§5), five experimental falsification tests (§6), detailed Quantum Darwinism comparison (§7), extensions and limitations (§8), interpretive options (§9), and honest assessment (§10). Includes 77 references and operational definitions for all information-theoretic quantities. Target Audience: Quantum foundations researchers, experimental quantum physicists (circuit QED, trapped ions, quantum dots), quantum information theorists, philosophers of physics interested in measurement and objectivity.
Efforts to scale quantum hardware are commonly framed as a challenge of suppressing local decoherence and stochastic noise through improved physical qubits and quantum error correction. Yet large-scale devices routinely exhibit performance degradation inconsistent with bounded-complexity local noise models, including nonstationary drift, bursty correlated events, and long-range crosstalk. We propose a constraint-based scaling framework in which the dominant limitation to scalability is not local error amplitude but the accumulation of constraint geometry: structured, correlated degrees of freedom that grow with system size and cannot be absorbed by standard endogenous noise models. We formalize this via (i) a bounded-complexity endogenous model class, (ii) a structured residual observable isolating unexplained degradation, and (iii) a coherence budget comparing effective control capacity to constraint burden. We identify a regime transition-the coherence wall-at which constraint burden outpaces control capacity, leading to rapid performance collapse despite stable local fidelities. We provide operational measurement protocols for extracting structured residual scaling, correlated dimensionality, and perturbation sensitivity from standard benchmarking data. The framework yields falsifiable architectural predictions and offers a diagnostic layer bridging quantum theory and scalable quantum engineering.