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Jean-Baptiste Waring

Publications and source records attributed to Jean-Baptiste Waring.

4 recordsLinked to original sources

Robust GHZ State Preparation via Majority-Voted Boundary Measurements

Preparing high-fidelity Greenberger-Horne-Zeilinger (GHZ) states on noisy quantum hardware remains challenging due to cumulative gate errors and decoherence. We introduce Group-Majority-Voting (Group-MV), a dynamic-circuit protocol that partitions arbitrary coupling graphs, prepares local GHZ states in parallel, and fuses them via majority-voted mid-circuit measurements. The majority vote over redundant boundary links mitigates measurement errors that would otherwise propagate through classical feedforward. We evaluate Group-MV on simulated Heavy-hex and Grid topologies for 30 through 60 qubits under a realistic noise regime. Group-MV generalizes to arbitrary GHZ sizes on arbitrary coupling topologies, achieving 2.4x higher fidelity than the Line Dynamic method while tracking the unitary baseline within 3%.

quant-ph

CHSH Violations using Dynamic Circuits

Scalable quantum computing relies on high-quality, long-range entanglement, a challenge on noisy, near-term devices. The need for practical insights for near-term algorithm design calls for trade-offs exploration in implementing dynamic circuits on current hardware. In this work, we experimentally compare three CNOT implementations for generating Bell states across varying qubit separations on a 127-qubit IBM Quantum Eagle processor (ibm_quebec): a unitary (SWAP-based) approach, a dynamic approach with mid-circuit measurements and classical feedforward, and a post-processed approach. We use Clauser-Horne-Shimony-Holt (CHSH) inequality violations to quantify entanglement quality. We observe that, beyond 10 qubits, dynamic circuits lead to higher |S| values than the unitary approach, demonstrating improved distance-dependent entanglement preservation. The post-processed approach yields the highest CHSH values, reaching |S| > 2 up to 13 qubits. Our results underscore the critical need for faster classical feedforward and higher readout fidelity.

quant-ph

Noise Aware Utility Optimization of NISQ Devices

In order to enter the era of utility, noisy intermediate-scale quantum (NISQ) devices need to enable long-range entanglement of large qubit chains. However, due to the limited connectivity of superconducting NISQ devices, long-range entangling gates are realized in linear depth. Furthermore, a time-dependent degradation of the average CNOT gate fidelity is observed. Likely due to aging, this phenomenon further degrades entanglement capabilities. Our aim is to help in the current efforts to achieve utility and provide an opportunity to extend the utility lifespan of current devices --albeit by selecting fewer, high quality resources. To achieve this, we provide a method to transform user-provided CNOT and readout error requirements into a compliant partition onto which circuits can be executed. We demonstrate an improvement of up to 52% in fidelity for a random CNOT chain of length 50 qubits and consistent improvements between 11.8% and 47.7% for chains between 10 and 40 in varying in increments of 10, respectively.

quant-ph

XGSwap: eXtreme Gradient boosting Swap for Routing in NISQ Devices

In the current landscape of noisy intermediate-scale quantum (NISQ) computing, the inherent noise presents significant challenges to achieving high-fidelity long-range entanglement. Furthermore, this challenge is amplified by the limited connectivity of current superconducting devices, necessitating state permutations to establish long-distance entanglement. Traditionally, graph methods are used to satisfy the coupling constraints of a given architecture by routing states along the shortest undirected path between qubits. In this work, we introduce a gradient boosting machine learning model to predict the fidelity of alternative--potentially longer--routing paths to improve fidelity. This model was trained on 4050 random CNOT gates ranging in length from 2 to 100+ qubits. The experiments were all executed on ibm_quebec, a 127-qubit IBM Quantum System One. Through more than 200+ tests run on actual hardware, our model successfully identified higher fidelity paths in approximately 23% of cases.

quant-ph