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This study demonstrates a practical advancement in near-term quantum computing by using partially fault-tolerant encoding to improve simulation accuracy on noisy hardware without the overhead of full error correction. By leveraging IBM's ibm_boston processor and introducing Observable-Ranked Postselection, researchers achieved significant gains in estimating local observables for Ising model simulations across different dimensions. The approach validates that strategic use of quantum error-detecting codes can effectively mitigate device errors while maintaining lower circuit depths than unencoded implementations.
Realizing Error Suppression in Partially Fault-Tolerant Quantum Simulations with IBM Quantum Computers
arXiv:2607.24947v1 Announce Type: new Abstract: Quantum error-detecting codes offer a near-term path for improving the performance of quantum simulations on noisy hardware. Using IBM's superconducting quantum computer ibm_boston, we show that partially fault-tolerant encoded quantum simulations of the Ising model in 1+1D and 2+1D outperform their unencoded counterparts in estimating local observables. To represent 42 logical qubits on the heavy-hex quantum processor, 21 blocks of the [[4, 2, 2]] Iceberg code and up to 136 physical qubits are used. By pairing fault-tolerant syndrome extraction with non-fault-tolerant logical operations, this scheme preserves many of the benefits of error detection while avoiding the overhead typically required for a fully fault-tolerant logical gate set. The encoding's square logical connectivity, together with the freedom to place logical qubits within each block, enables simulations of a 2D spatial lattice with lower circuit depth than the unencoded implementation requires. We introduce Observable-Ranked Postselection, a selective-filtering technique based on syndrome correlations that recovers reliable results without the prohibitive shot loss of full syndrome postselection. Under the cumulative effect of device errors, this encoding improves local-observable accuracy over the unencoded baseline by 2-6% at intermediate times in 1+1D simulations, growing with circuit depth to over 200% in 2+1D at the latest times studied.
Authors:Henry Froland, Dorota M. Grabowska, Sebastian Grieninger, Jeremy Hartse, Anne L. Lashbrook, Zhiyao Li, Ziyuan Li, Sarah J. M. Powell, Martin J. Savage, Xiaojun Yao, Nikita A. Zemlevskiy
Abstract:Quantum error-detecting codes offer a near-term path for improving the performance of quantum simulations on noisy hardware. Using IBM's superconducting quantum computer ibm_boston, we show that partially fault-tolerant encoded quantum simulations of the Ising model in 1+1D and 2+1D outperform their unencoded counterparts in estimating local observables. To represent 42 logical qubits on the heavy-hex quantum processor, 21 blocks of the [[4, 2, 2]] Iceberg code and up to 136 physical qubits are used. By pairing fault-tolerant syndrome extraction with non-fault-tolerant logical operations, this scheme preserves many of the benefits of error detection while avoiding the overhead typically required for a fully fault-tolerant logical gate set. The encoding's square logical connectivity, together with the freedom to place logical qubits within each block, enables simulations of a 2D spatial lattice with lower circuit depth than the unencoded implementation requires. We introduce Observable-Ranked Postselection, a selective-filtering technique based on syndrome correlations that recovers reliable results without the prohibitive shot loss of full syndrome postselection. Under the cumulative effect of device errors, this encoding improves local-observable accuracy over the unencoded baseline by 2-6% at intermediate times in 1+1D simulations, growing with circuit depth to over 200% in 2+1D at the latest times studied.
arXiv:2607.24947 [quant-ph]
(or arXiv:2607.24947v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2607.24947 arXiv-issued DOI via DataCite (pending registration)
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