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Physical Review Letters

Full Characterization of Genuine 17-qubit Entanglement on the Superconducting Processor

Chang-Kang Hu, Yong Wang, YuXuan Zhou, C. L. Liu, Gui-Xu Xie, Ruiyang Zhou, HaoLan Yuan, Lijun Liu, Li Li, Song Liu, Dian Tan, Shuming Cheng, Dapeng Yu

Published Jul 7, 2025• 2 citations
Publisher

Abstract

We present a least square state estimator regularized by state purity to accomplish the task of quantum state tomography and entanglement verification, and report an experimental validation on a superconducting processor. First, a scalable full-state tomography is achieved with state fidelity 0.8217(1) for the 9-qubit W state and 0.6817(1) for the 17-qubit Greenberger-Horne-Zeilinger state, with the latter reaching 0.7587(1) under a pure-state assumption. Then, the presence of genuine multiqubit entanglement in the majority of generated states is conclusively certified by violating the corresponding entanglement witness. Finally, it is demonstrated that our method can achieve superior tomography accuracy with limited measurement settings and that mitigating error is essential for leveraging noisy quantum systems in quantum processing tasks. Our results pave the way for more accurate full characterization of larger-scale many-body quantum systems.

DOI
10.1103/qy9y-7ywp

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We present a least square state estimator regularized by state purity to accomplish the task of quantum state tomography and entanglement verification, and report an experimental validation on a superconducting processor. First, a scalable full-state tomography is achieved with state fidelity 0.8217(1) for the 9-qubit W state and 0.6817(1) for the 17-qubit Greenberger-Horne-Zeilinger state, with the latter reaching 0.7587(1) under a pure-state assumption. Then, the presence of genuine multiqubit entanglement in the majority of generated states is conclusively certified by violating the corresponding entanglement witness. Finally, it is demonstrated that our method can achieve superior tomography accuracy with limited measurement settings and that mitigating error is essential for leveraging noisy quantum systems in quantum processing tasks. Our results pave the way for more accurate full characterization of larger-scale many-body quantum systems.
Abstract Generating and detecting genuine multipartite entanglement (GME) of sizeable quantum states prepared on physical devices is an important benchmark for highlighting the progress of near-term quantum computers. A common approach to certify GME is to prepare a Greenberger-Horne-Zeilinger (GHZ) state and measure a GHZ fidelity of at least 0.5. We measure the fidelities using multiple quantum coherences of GHZ states on 11 to 27 qubits prepared on the IBM Quantum ibmq_montreal device. Combinations of quantum readout error mitigation (QREM) and parity verification error detection are applied to the states. A fidelity of 0.546 ± 0.017 was recorded for a 27-qubit GHZ state when QREM was used, demonstrating GME across the full device with a confidence level of 98.6%. We benchmarked the effect of parity verification on GHZ fidelity for two GHZ state preparation embeddings on the heavy-hexagon architecture. The results show that the effect of parity verification, while relatively modest, led to a detectable improvement of GHZ fidelity.
Introduction: The scalability of superconducting quantum processors is fundamentally limited by environmental noise and the exponential measurement overhead required for multi-qubit entanglement verification. Methods: In this work, we introduce a hybrid machine learning (ML) framework utilizing convolutional neural networks (CNNs) to simultaneously characterize decoherence channels and verify multipartite entanglement. The model is trained on synthetic noisy syndrome measurement data augmented with empirical SPAM models and applied to a 5-qubit superconducting device, where the neural network acts as a non-linear entanglement witness. Results: sweeps. Furthermore, it successfully verifies genuine multipartite entanglement with a fidelity prediction of 99.1%, while requiring only 12% of the measurement bases demanded by full quantum state tomography (QST). Discussion: Crucially, our methodology bypasses two distinct challenges: it drastically reduces the measurement complexity inherent in multi-qubit entanglement verification, and it inherently filters out state preparation and measurement (SPAM) errors without requiring noise-amplifying matrix inversions. These numerical results demonstrate that ML-assisted protocols provide a highly resource-efficient pathway for the characterization of noisy intermediate-scale quantum (NISQ) devices.
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.
Here we report on the production and tomography of genuinely entangled Greenberger-Horne-Zeilinger states with up to ten qubits connecting to a bus resonator in a superconducting circuit, where the resonator-mediated qubit-qubit interactions are used to controllably entangle multiple qubits and to operate on different pairs of qubits in parallel. The resulting 10-qubit density matrix is probed by quantum state tomography, with a fidelity of 0.668±0.025. Our results demonstrate the largest entanglement created so far in solid-state architectures and pave the way to large-scale quantum computation.
Characterizing quantum states is essential for validating quantum devices, yet conventional quantum state tomography becomes prohibitively expensive as system size grows. Direct tomography offers a distinct route by enabling selective access to individual complex density-matrix elements, with a particular advantage for sparse target states and some verification tasks. Here we introduce a direct quantum state tomography scheme combining strong-measurement estimation with a fan-out coupling architecture. It enables mutually commuting interactions between system qubits and a single meter qubit, thereby achieving constant circuit depth, independent of system size. Notably, the involutory fan-out coupling reduces to the identity under repetition, enabling straightforward noise scaling for quantum error mitigation. We experimentally validate the scheme on a superconducting quantum processor via the IBM Quantum Platform, demonstrating four-qubit state reconstruction and single-circuit GHZ-state fidelity estimation up to 20 qubits with error mitigation. Consistent results with standard tomography and improved efficiency establish our scheme as a promising approach to reconstructing full quantum states and scalable verification tasks.
Genuine multipartite entanglement represents the strongest type of entanglement, which is an essential resource for quantum information processing. Standard methods to detect genuine multipartite entanglement, e.g., entanglement witnesses, state tomography, or quantum state verification, require full knowledge of the Hilbert space dimension and precise calibration of measurement devices, which are usually difficult to acquire in an experiment. The most radical way to overcome these problems is to detect entanglement solely based on the Bell-like correlations of measurement outcomes collected in the experiment, namely, device independently. However, it is difficult to certify genuine entanglement of practical multipartite states in this way, and even more difficult to quantify it, due to the difficulty in identifying optimal multipartite Bell inequalities and protocols tolerant to state impurity. In this Letter, we explore a general and robust device-independent method that can be applied to various realistic multipartite quantum states in arbitrary finite dimension, while merely relying on bipartite Bell inequalities. Our method allows us both to certify the presence of genuine multipartite entanglement and to quantify it. Several important classes of entangled states are tested with this method, leading to the detection of genuinely entangled states. We also certify genuine multipartite entanglement in weakly entangled Greenberger-Horne-Zeilinger states, showing that the method applies equally well to less standard states.