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arXiv:2511.13532

Measurement-based Dynamical Decoupling for Fidelity Preservation on Large-scale Quantum Processors

Jeongwoo Jae, Changwon Lee, Juzar Thingna, Yeong-Dae Kwon, Daniel K. Park

quant-phSubmitted Nov 17, 2025• Announced Nov 18, 2025• 0 citations
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Abstract

Dynamical decoupling (DD) is a key technique for suppressing decoherence and preserving the performance of quantum algorithms. We introduce a measurement-based DD (MDD) protocol that determines control unitary gates from partial measurements of noisy subsystems, with measurement overhead scaling linearly with the number of subsystems. We prove that, under local energy relaxation and dephasing noise, MDD achieves the maximum entanglement fidelity attainable by any DD scheme based on bang-bang operations to first order in evolution time. On the IBM Eagle processor, MDD achieved up to a $450$-fold improvement in the success probability of a $14$-qubit quantum Fourier transform, and improved the accuracy of ground-state energy estimation for $N_2$ in the $56$-qubit sample-based quantum diagonalization compared with the standard XX-pulse DD. These results establish MDD as a scalable and effective approach for suppressing decoherence in large-scale quantum algorithms.

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22 pages, 15 figures

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Dynamical decoupling (DD) is a key technique for suppressing decoherence and preserving the performance of quantum algorithms. We introduce a measurement-based DD (MDD) protocol that determines control unitary gates from partial measurements of noisy subsystems, with measurement overhead scaling linearly with the number of subsystems. We prove that, under local energy relaxation and dephasing noise, MDD achieves the maximum entanglement fidelity attainable by any DD scheme based on bang-bang operations to first order in evolution time. On the IBM Eagle processor, MDD achieved up to a 450450450-fold improvement in the success probability of a 141414-qubit quantum Fourier transform, and improved the accuracy of ground-state energy estimation for N2N_2N2​ in the 565656-qubit sample-based quantum diagonalization compared with the standard XX-pulse DD. These results establish MDD as a scalable and effective approach for suppressing decoherence in large-scale quantum algorithms.
Quantum computers must be able to function in the presence of decoherence. The simplest strategy for decoherence reduction is dynamical decoupling (DD), which requires no encoding overhead and works by converting quantum gates into decoupling pulses. Here, using the IBM and Rigetti platforms, we demonstrate that the DD method is suitable for implementation in today's relatively noisy and small-scale cloud-based quantum computers. Using DD, we achieve substantial fidelity gains relative to unprotected, free evolution of individual superconducting transmon qubits. To a lesser degree, DD is also capable of protecting entangled two-qubit states. We show that dephasing and spontaneous emission errors are dominant in these systems, and that different DD sequences are capable of mitigating both effects. Unlike previous work demonstrating the use of quantum error correcting codes on the same platforms, we make no use of postselection and hence report unconditional fidelity improvements against natural decoherence.
Dynamic quantum circuits integrate unitary evolution with mid-circuit measurement and feedforward, enabling conditional operations essential for efficient quantum algorithms and foundational for fault-tolerant quantum computation. However, such operations introduce measurement-induced errors and control constraints that are not addressed by conventional error-suppression techniques. Here, we introduce an empirical learning framework that optimizes dynamical decoupling (DD) sequences for dynamic circuits at the level of circuit subintervals and qubit subregisters. Applying empirically learned DD sequences, we achieve a three-fold reduction in average dynamic circuit error rates as measured via randomized benchmarking. We apply the learned strategies to the dynamic circuit implementation of the quantum Fourier transform with measurement (QFT+M), demonstrating nontrivial process fidelity on connected chains of up to 20 qubits. Applying the resulting enhancement, we perform a high signal-to-noise QFT immediately following the preparation of a 10-qubit entangled state. Our results demonstrate that empirically optimized DD systematically outperforms theoretically derived sequences for dynamic circuits, establishing it as an efficient approach for error suppression in dynamic quantum circuits, with direct relevance to applications requiring measurement and feedback such as quantum error correction.
Dynamical decoupling (DD) and Decoherence free subspace (DFS) are powerful techniques in quantum computing aimed at enhancing fidelity by mitigating the detrimental effects of noise and environmental interactions. In quantum systems, noise and decoherence can degrade the coherence of quantum states, leading to errors and reduced computational accuracy. DD employs carefully designed sequences of control pulses to periodically intervene and counteract these undesired interactions, while DFS utilizes subspace encoding techniques to protect quantum information from decoherence. To evaluate and compare the fidelity achieved by DD and DFS, this paper presents a series of experiments considering the effect of time and the number of qubits. The experiments provide valuable insights into the performance of both methods under different conditions. By systematically examining the fidelity results, the impact of time and the scaling behavior with increasing qubits can be assessed. The experimental findings showcase the effectiveness of DD in reducing the impact of noise and extending the coherence time of quantum states. By strategically manipulating the quantum system, DD minimizes error accumulation and preserves the integrity of fragile quantum information. It is observed that the decrease in fidelity with increasing t is relatively small and gradual. Despite being outperformed by DD, the DFS method exhibits robustness and maintains a high degree of fidelity even in the presence of extended time durations.
Dynamical decoupling (DD) is a widely-used quantum control technique that takes advantage of temporal symmetries in order to partially suppress quantum errors without the need resource-intensive error detection and correction protocols. This and other open-loop error mitigation techniques are critical for quantum information processing in the era of Noisy Intermediate-Scale Quantum technology. However, despite its utility, dynamical decoupling does not address errors which occur at unstructured times during a circuit, including certain commonly-encountered noise mechanisms such as cross-talk and imperfectly calibrated control pulses. Here, we introduce and demonstrate an alternative technique - `quantum measurement emulation' (QME) - that effectively emulates the measurement of stabilizer operators via stochastic gate application, leading to a first-order insensitivity to coherent errors. The QME protocol enables error suppression based on the stabilizer code formalism without the need for costly measurements and feedback, and it is particularly well-suited to discrete coherent errors that are challenging for DD to address.
Dynamical decoupling (DD) is a low-overhead method for quantum error suppression. Despite extensive work in DD design, finding pulse sequences that optimally decouple computational qubits is not well understood. Using IBM’s superconducting-qubit-based quantum processors, we demonstrate how to empirically tailor DD strategies for an arbitrary quantum circuit and device. These learned DD strategies significantly improve error suppression relative to canonical sequences, with relative improvement increasing with problem size and circuit sophistication. We leverage this to study mirror randomized benchmarking on 100 qubits, Greenberger-Horne-Zeilinger state preparation on 50 qubits, and the Bernstein-Vazirani algorithm on 27 qubits. Our empirical learning method finds strategies, in constant time independent of circuit width and depth, provides stable performance over long time periods without retraining, and generalizes to larger circuits when trained on small subcircuit structures.
We demonstrate a hardware-agnostic protocol for realizing fast, high-fidelity gates through dynamical decoupling (DD) pulse sequences applied to a central qubit coupled to target qubits. The target qubits are controlled by leveraging their intrinsic interaction with the central qubit, eliminating the need for slow, error-prone direct control. We develop and implement the DD-gate protocol within two distinct frameworks: a general model with minimal assumptions, benchmarked on a gate-based digital quantum simulator given by the IBM quantum (IBMQ) platforms; and an experimentally realistic case with a N 15 -vacancy center ( NV 15 ) in diamond. Using IBMQ, we are able to elucidate the underlying quantum dynamics of the DD gates and test them, independently of experimental constraints. For NV 15 , we realize the protocol considering system-specific properties, which could represent a significant reduction in gate duration and improved technological scalability compared with current dynamical-decoupling-based control. We also propose a simple application for high-efficiency polarization of the N 15 nuclear spin that could potentially be less technically demanding than current methods. Altogether, this work provides a robust strategy for quantum control that can be implemented in arbitrary systems fitting the central-target qubit architecture. Beyond these results, our open-source simulations and implementations for both platforms provide a practical framework for simulating time-dependent qubit dynamics on noisy intermediate-scale quantum era gate-based quantum processors.