Overview Systematic experimental characterization of Greenberger-Horne-Zeilinger (GHZ) states from N=2 to N=12 qubits on IBM Quantum's ibm_torino processor (133 qubits, Heron r2 architecture). Key Discovery The fidelity landscape exhibits unexpected non-monotonic behavior — contradicting the conventional expectation of monotonic decay with increasing qubit number. Five Distinct Regions Identified Region N Fidelity Characteristic Peak 3 0.951 Optimal qubit chain Valley 4, 5 ~0.14 Decoherence collapse Recovery 6–8 ~0.69 V-shaped recovery Cliff 9 0.40 Stabilization 10–12 ~0.33 Fidelity floor Principal Results V-shaped recovery: Fidelity increases from F=0.07 (N=5) to F=0.73 (N=6), demonstrating that qubit chain quality dominates over circuit depth Mermin violation: M₃ = 3.65 ± 0.01, exceeding the classical bound by 143 standard deviations Asymmetric decoherence: For N≥9, the |1⟩⊗N component vanishes entirely while |0⟩⊗N maintains ~30% probability Implications This 11-point dataset suggests that "fidelity phase diagrams" could serve as a new tool for quantum processor characterization, complementing existing benchmarks. Reproducibility All IBM Quantum Job IDs are provided for independent verification.
Overview Systematic experimental characterization of Greenberger-Horne-Zeilinger (GHZ) states from N=2 to N=12 qubits on IBM Quantum's ibm_torino processor (133 qubits, Heron r2 architecture). Key Discovery The fidelity landscape exhibits unexpected non-monotonic behavior — contradicting the conventional expectation of monotonic decay with increasing qubit number. Five Distinct Regions Identified Region N Fidelity Characteristic Peak 3 0.951 Optimal qubit chain Valley 4, 5 ~0.14 Decoherence collapse Recovery 6–8 ~0.69 V-shaped recovery Cliff 9 0.40 Stabilization 10–12 ~0.33 Fidelity floor Principal Results V-shaped recovery: Fidelity increases from F=0.07 (N=5) to F=0.73 (N=6), demonstrating that qubit chain quality dominates over circuit depth Mermin violation: M₃ = 3.65 ± 0.01, exceeding the classical bound by 143 standard deviations Asymmetric decoherence: For N≥9, the |1⟩⊗N component vanishes entirely while |0⟩⊗N maintains ~30% probability Implications This 11-point dataset suggests that "fidelity phase diagrams" could serve as a new tool for quantum processor characterization, complementing existing benchmarks. Reproducibility All IBM Quantum Job IDs are provided for independent verification.
We report experimental measurements comparing the coherence decay of three-qubit Greenberger-Horne-Zeilinger (GHZ) entangled states versus locally coherent product states (|+++⟩) under idle time evolution on IBM Heron quantum processors. Across three different processor generations (Heron r1, r2, r3), we consistently observe that the GHZ state maintains higher fidelity than the product state as idle delay increases. Decay rate analysis reveals that |+++⟩ decays 2.4–13.8× faster than GHZ depending on the backend. A control experiment with |000⟩ confirms the decay mechanism is dominated by dephasing (T₂-type noise) rather than energy relaxation (T₁) or readout errors. These results demonstrate a structural dependence of coherence stability on the topology of the quantum state. Backends: ibm_fez (Heron r2), ibm_torino (Heron r1), ibm_boston (Heron r3)Configuration: 3 qubits, 4000 shots, 20 repetitions per delay pointDelays: 0, 500, 1000, 2000, 4000 dt
Greenberger-Horne-Zeilinger (GHZ) states are a widely used benchmark for studying multipartite entanglement and coherence in quantum processors. In this work, GHZ states of increasing size were prepared on the 156-qubit IBM Quantum processor ibm_marrakesh and certified using a fidelity-based entanglement witness. State coherence was extracted from parity-oscillation measurements using the multiple-quantum-coherence method. The study investigates how a combination of practical error-reduction techniques affects the largest GHZ state that can be certified on open-access superconducting hardware. These techniques include depth-minimized entangling trees, calibration-aware qubit selection, dynamical decoupling with gate and measurement twirling, and matrix-free readout-error mitigation. A naive implementation fails at larger system sizes, while depth-optimized preparation certifies entanglement up to 14 qubits. Calibration-aware qubit selection extends this to 16 qubits, and readout-error mitigation enables certification of genuine multipartite entanglement up to 18 qubits with a measured fidelity exceeding the witness threshold. The results show that the achievable certification size is determined primarily by the quality of the selected qubit region rather than by the total number of qubits available on the processor. The observed non-monotonic dependence of fidelity on system size reflects variations in local device performance. These findings illustrate the impact of hardware-aware compilation and error-mitigation strategies on entanglement certification using publicly accessible quantum computing platforms.
I report a hands-on, systematic investigation of Greenberger–Horne–Zeilinger (GHZ) state generation on a 127-qubit supercon-ducting quantum processor, covering system sizes from 4 to 80 qubits. I measured both computational-basis populations andglobal Pauli-X parity oscillations to decompose the state fidelity into its population purity and phase-coherence components. Mydata reveal an exponential collapse of fidelity with qubit number: a 4-qubit GHZ state achieves a fidelity of F = 0.9307, wellabove the threshold for entanglement-based quantum key distribution, yet by 32 qubits the fidelity has plummeted to 0.0963 andthe parity signal is extinguished. At 80 qubits, the state is indistinguishable from a maximally mixed state (F = 0.0453). I isolatethe dominant noise channels—CNOT gate errors, dephasing, readout crosstalk—and map the current usability frontier for rawmultipartite entanglement. I then contrast my results with mitigation-enhanced benchmarks from other platforms, showing thatadaptive compilation and dynamical decoupling can recover fidelity above the genuine multipartite entanglement (GME) thresholdeven at 120 qubits. This work provides a deeply personal, quantitative perspective on the challenges and near-term solutions forscaling entanglement in quantum communication, sensing, and error-mitigated computation.
We present an empirical study of circuit-depth thresholds on IBM Quantum Heron-class hardware using 4- and 5-qubit GHZ-state preparation circuits with logical depths from 2 to 20. On ibm_torino, we observe qubit-count-dependent depth limits: 4-qubit circuits reach a fidelity plateau near 88% beyond depth 10, while 5-qubit circuits show continued decay from 89.4% to 83.7% over the same range. The observed fidelity at depth 20 substantially exceeds predictions from an independent gate-error model (88% vs. 61%), indicating coherent error effects and partial error cancellation not captured by simple accumulation models. These results provide hardware-specific depth bounds for near-term quantum circuits and support calibration-based depth selection over fixed heuristics. We recommend a maximum depth ≤ 10 for applications requiring >85% fidelity on this hardware.
TECHNICAL REPORT: HEURISTIC DESCENDING LIMIT FOR GENUINE MULTIPARTITE ENTANGLEMENT SCALABILITY IN GHZ STATES Executive Summary The long-term viability of fault-tolerant quantum computing depends on the scalability of Genuine Multipartite Entanglement (GME), commonly evaluated through Greenberger-Horne-Zeilinger (GHZ) states. Current orthodoxy assumes that decoherence is a purely environmental issue mitigable through thermal isolation and Quantum Error Correction (QEC) schemes. In this report, we introduce a proprietary topological saturation algorithmic model that evaluates the maximum concurrent information load. By fitting this model to the most recent empirical data from superconducting processors and trapped ions, we identify a fundamental collapse asymptote. We formally predict that state fidelity (F) will inevitably cross the critical failure threshold (F < 0.5) before reaching 141 monolithically entangled qubits, marking a strict hardware limit independent of local noise mitigation architectures. 1. Introduction and Empirical Context Advancing toward "quantum advantage" requires the creation and maintenance of highly entangled states. To certify genuine multipartite entanglement in a GHZ state, the system must exceed the strict fidelity threshold of F > 0.5. Historically, scalability has shown an exponential degradation of fidelity as the number of qubits (N) increases. Recent industry reports demonstrate this extreme tension at the upper limit of current hardware: · Quantinuum (Trapped Ion Architecture): Reported stabilization of N = 56 qubits with a fidelity of F approx 0.61. · IBM Quantum (Superconducting Architecture): Achieved a milestone in GHZ state preparation with N = 120 qubits, reporting a fidelity of F approx 0.56. Despite the immense resources invested, at 120 qubits the system is on the edge of the viability limit. The industry assumes that incremental refinements will allow for linear scaling toward thousands of logical qubits. Our model demonstrates that this assumption is topologically incorrect. 2. Methodology: The Entanglement Saturation Limit Using a proprietary algorithmic model designed to map informational bandwidth constraints onto discrete multidimensional meshes, we have derived a strict scalar limit for concurrent entanglement. The model assumes that entanglement is not a "free" resource in Hilbert space; rather, it incurs an informational density cost (Shannon Tax) that saturates the system's transverse capacity. By projecting an asymptotic curve adjusted to current resource loss friction, we determined a critical overflow point defined as Qmax. Formal Prediction Milestones: · Early Warning (N = 130): We predict that the next attempts to scale to 130 qubits will show a marginal fidelity of F approx 0.51, exhibiting noise levels unmanageable by software. · Structural Collapse (Qmax = 141): The model predicts that it is physically impossible to sustain a monolithic GHZ state equal to or greater than 141 qubits. At this point, fidelity will drop below 0.5, resulting in irreversible and instantaneous system decoherence, fragmenting the entanglement into smaller clusters. 4. Conclusion and Industry Implications Traditional Quantum Error Correction (QEC) is based on the premise that local errors are independent and stochastic. If our prediction of Qmax = 141 holds in the next iterations of commercial quantum processors, it will imply that large-scale decoherence is a systemic limiting effect (a structural bottleneck), not a simple thermal engineering failure. Overcoming this "141-Qubit Wall" will require abandoning brute-force scalability methodologies and adopting routing modulation and phase cancellation architectures that address the geometric root of information saturation.
Abstract We report on the coherence of Greenberger–Horne–Zeilinger (GHZ) states comprised of up to 8 qubits in the IBM ibmqx5 16-qubit quantum processor. In particular, we evaluate the coherence of GHZ states with N = 1, …, 8 qubits 4 , as a function of a delay time between state creation and measurement. We find that the decay in coherence occurs at a rate that is linear in the number of qubits. This is consistent with a model in which the dominant noise affecting the system is uncorrelated across qubits.