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研究生： 呂曉南
Lu, Hsiao-Nan
論文名稱： 適用於近期量子電腦之自動化機率式誤差校正套件之開發
An Automated Probabilistic Error Cancellation Package for Near-Term Quantum Computers
指導教授： 陳宏斌
Chen, Hong-Bin
學位類別： 碩士
Master
系所名稱： 工學院 - 工程科學系
Department of Engineering Science
論文出版年： 2026
畢業學年度： 114
語文別： 英文
論文頁數： 55
中文關鍵詞： 量子誤差緩解 、機率式誤差校正
外文關鍵詞： Quantum Error Mitigation, Probabilistic Error Cancellation
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    • 機率式誤差校正（probabilistic error cancellation, PEC）目前帶雜訊中等規模量子裝置上最具潛力的量子誤差緩解技術之一，因為此方法在原理上能夠在不依賴完整容錯機制的情況下，消除由硬體雜訊所造成的偏差。然而，PEC 在實際部署上仍具有相當高的困難度，原因在於其流程同時涉及雜訊特性分析、準機率分解、取樣控制，以及與量子軟體工作流程的整合。本研究聚焦於自動化 PEC 套件之設計，目標是將使用者輸入的量子電路轉換為可進行誤差緩解的執行流程，並結合後端感知校正、閘級準機率建構、適應性取樣與標準化結果輸出等功能。

    本套件進一步將觀測量層級的讀出誤差緩解、以包立轉換矩陣為基礎的通道表示法、針對二量子位元閘雜訊的包立旋轉，以及基於截斷的取樣縮減策略整合為一套一致化的工作流程。由於在現今量子硬體上完整執行 PEC 往往需要極為龐大的電路數量與取樣資源，因此本架構採用以硬體資訊為基礎的模擬策略，將自 IBM 量子後端擷取之雜訊模型配置至對應的模擬器中。透過此一設計，本套件在保持面向真實量子硬體應用的同時，提供一個模組化且可重現的平台，用以在接近真實的雜訊條件下測試 PEC。

    Probabilistic error cancellation (PEC) is one of the most promising quantum error-mitigation techniques for noisy intermediate-scale quantum devices because it can, in principle, remove bias induced by hardware noise without requiring full fault tolerance. In practice, however, PEC is difficult to deploy: it requires noise characterization, quasi-probability decomposition, sampling control, and integration with quantum software workflows. This work focuses on the design of an automated PEC package that translates user circuits into mitigation-ready execution pipelines, combining backend-aware calibration, gate-level quasi-probability construction, adaptive sampling, and standardized reporting.

    The proposed package further integrates observable-level readout mitigation, Pauli-transfer-matrix-based channel representation, Pauli twirling for two-qubit gate noise, and truncation-based sampling reduction into a unified workflow. Because full PEC execution on present-day hardware can require prohibitive circuit and sampling resources, the framework adopts a hardware-informed simulation strategy in which noise models extracted from IBM quantum backends are assigned to corresponding simulators. Through this design, the package provides a modular and reproducible platform for testing PEC under realistic noisy conditions while remaining oriented toward future applications on real quantum hardware.

    Abstract (Chinese) i Abstract ii Acknowledgement (Chinese) iii Contents iv List of Figures vi List of Tables viii Chapter I Introduction 1 Introduction 1 Chapter II Background and General Framework 4 Background and General Framework 4 Basic Principle of Probabilistic Error Cancellation 4 Pauli Transfer Matrix Representation and Pauli Twirling 5 Observable-Level and Gate-Level Mitigation 7 General Framework of the Proposed Package 8 Chapter III Methodology of the Package 9 Methodology of the Package 9 Observable-Level Probabilistic Error Cancellation 9 Two-Qubit Gate Probabilistic Error Cancellation 10 Chapter IV Automated PEC Package Architecture 17 Automated PEC Package Architecture 17 Overall Workow of the Package 17 Readout Calibration Module 18 Two-Qubit-Gate Twirling Module 19 PEC Execution and Truncation Strategy 20 Chapter V Benchmark Results and Analysis 24 Benchmark Results and Analysis 24 Common Simulation Settings 24 CNOT Benchmark 25 Bell-State Benchmark 29 Quantum-Teleportation Benchmark 33 Overall Discussion 40 Chapter VI Conclusions and Future Work 41 Conclusions and Future Work 41 References 42

    [1] J. Preskill. Quantum computing in the NISQ era and beyond. Quantum, 2:79, Aug 2018. doi: 10.22331/q-2018-08-06-79.
    [2] F. Arute. Quantum supremacy using a programmable superconducting processor. Nature, 574:505510, Oct 2019. doi: 10.1038/s41586-019-1666-5.
    [3] R. J. Schoelkopf. Wiring up quantum systems. Nature, 451:664669, Feb 2008. doi: 10.1038/451664a.
    [4] S. Krinner. Realizing repeated quantum error correction in a distance-three surface code. Nature, 605:664670, May 2022. doi: 10.1038/s41586-022-04566-8.
    [5] M. Sarovar. Detecting crosstalk errors in quantum information processors. Quantum, 4:291, Jul 2020. doi: 10.22331/q-2020-09-11-321.
    [6] B. Nachman. Unfolding quantum computer readout errors. npj Quantum Inf., 6:84, Oct 2020. doi: 10.1038/s41534-020-00309-7.
    [7] A. Kandala. Error mitigation extends the computational reach of a noisy quantum processor. Nature, 567:491495, Mar 2019. doi: 10.1038/s41586-019-1040-7.
    [8] K. Bharti. Noisy intermediate-scale quantum algorithms. Rev. Mod. Phys., 94:015004, Feb 2022. doi: 10.1103/RevModPhys.94.015004.
    [9] Y. Kim. Evidence for the utility of quantum computing before fault tolerance. Nature, 618:500505, 2023. doi: 10.1038/s41586-023-06096-3.
    [10] L. Viola. Dynamical decoupling of open quantum systems. Phys. Rev. Lett., 82:24172421, Mar 1999. doi: 10.1103/PhysRevLett.82.2417.
    [11] B. M. Terhal. Quantum error correction for quantum memories. Rev. Mod. Phys., 87:307346, Apr 2015. doi: 10.1103/RevModPhys.87.307.
    [12] C. Gidney. How to factor 2048 bit RSA integers in 8 hours. Quantum, 5:433, Apr 2021. doi: 10.22331/q-2021-04-15-433.
    [13] K. Temme. Error mitigation for short-depth quantum circuits. Phys. Rev. Lett., 119:180509, Nov 2017. doi: 10.1103/PhysRevLett.119.180509.
    [14] S. Endo. Hybrid quantum-classical algorithms and quantum error mitigation. J. Phys. Soc. Jpn., 90:032001, Mar 2021. doi: 10.7566/JPSJ.90.032001.
    [15] Z. Cai. Quantum error mitigation. Rev. Mod. Phys., 95:045005, Dec 2023. doi: 10.1103/RevModPhys.95.045005.
    [16] X. Bonet-Monroig. Low-cost error mitigation by symmetry verication. Phys. Rev. A, 98:062339, Dec 2018. doi: 10.1103/PhysRevA.98.062339.
    [17] M. Huo. Dual-state purication for practical quantum error mitigation. Phys. Rev. A, 105:022427, Feb 2022. doi: 10.1103/PhysRevA.105.022427.
    [18] E. F. Dumitrescu. Cloud quantum computing of an atomic nucleus. Phys. Rev. Lett., 120:210501, May 2018. doi: 10.1103/PhysRevLett.120.210501.
    [19] A. He. Zero-noise extrapolation for quantum-gate error mitigation with identity insertions. Phys. Rev. A, 102:012426, Jul 2020. doi: 10.1103/PhysRevA.102.012426.
    [20] R. Takagi. Fundamental limits of quantum error mitigation. npj Quantum Inf., 8:114, Sep 2022. doi: 10.1038/s41534-022-00618-z.
    [21] Y. Quek. Exponentially tighter bounds on limitations of quantum error mitigation. Nat. Phys., Jul 2024. doi: 10.1038/s41567-024-02536-7.
    [22] K. Schultz. Impact of time-correlated noise on zero-noise extrapolation. Phys. Rev. A, 106:052406, Nov 2022. doi: 10.1103/PhysRevA.106.052406.
    [23] S. Endo. Practical quantum error mitigation for near-future applications. Phys. Rev. X, 8:031027, Jul 2018. doi: 10.1103/PhysRevX.8.031027.
    [24] E. v. d. Berg. Probabilistic error cancellation with sparse Pauli-Lindblad models on noisy quantum processors. Nat. Phys., 19:11161121, Sep 2023. doi: 10.1038/s41567-023-02042-2.
    [25] W. J. Huggins. Virtual distillation for quantum error mitigation. Phys. Rev. X, 11:041036, 2021. doi: 10.1103/PhysRevX.11.041036.
    [26] P. Czarnik. Error mitigation with cliord data regression. Quantum, 5:592, Dec 2021. doi: 10.22331/q-2021-12-08-592.
    [27] D. Bultrini. Unifying and benchmarking state-of-the-art quantum error mitigation techniques. Quantum, 7:1034, 2023. doi: 10.22331/q-2023-06-06-1034.
    [28] A. Strikis. Learning-based quantum error mitigation. PRX Quantum, 2:040330, Nov 2021. doi: 10.1103/PRXQuantum.2.040330.
    [29] C. Kim. Quantum error mitigation with articial neural network. IEEE Access, 8:188853188860, 2020. doi: 10.1109/ACCESS.2020.3031607.
    [30] H. Liao. Machine learning for practical quantum error mitigation. Nat. Mach. Intell., 6:14781486, 2024. doi: 10.1038/s42256-024-00927-2.
    [31] S. Bravyi. Mitigating measurement errors in multiqubit experiments. Phys. Rev. A, 103:042605, Apr 2021. doi: 10.1103/PhysRevA.103.042605.
    [32] R. LaRose. Mitiq: A software package for error mitigation on noisy quantum computers. Quantum, 6:774, Sep 2022. doi: 10.22331/q-2022-08-11-774.
    [33] C. Song. Quantum computation with universal error mitigation on a superconducting quantum processor. Sci. Adv., 5(9):eaaw5686, 2019. doi: 10.1126/sciadv.aaw5686.
    [34] S. Zhang. Error-mitigated quantum gates exceeding physical delities in a trapped-ion system. Nat. Commun., 11:587, 2020. doi: 10.1038/s41467-020-14376-z.
    [35] D. Qin. Error statistics and scalability of quantum error mitigation formulas. npj Quantum Inf., 9:35, Apr 2023. doi: 10.1038/s41534-023-00707-7.
    [36] Steven T. Flammia and Joel J. Wallman. Ecient estimation of pauli channels. ACM Trans. Quantum Comput., 1(1):3:13:32, Dec 2020. doi: 10.1145/3408039.
    [37] E. van den Berg. Model-free readout-error mitigation for quantum expectation values. Phys. Rev. A, 105:032620, 2022. doi: 10.1103/PhysRevA.105.032620.
    [38] A. S. Aasen. Readout error mitigated quantum state tomography tested on superconducting qubits. Commun. Phys., 7:301, 2024. doi: 10.1038/s42005-024-01790-8.
    [39] K. Tsubouchi. Symmetric cliord twirling for cost-optimal quantum error mitigation in early FTQC regime. npj Quantum Inf., 11:104, 2025. doi: 10.1038/s41534-025-01050-9.
    [40] I. Henao. Adaptive quantum error mitigation using pulse-based inverse evolutions. npj Quantum Inf., 9:120, 2023. doi: 10.1038/s41534-023-00785-7.
    [41] T. B. Adeniyi. Adaptive neural network for quantum error mitigation. Quantum Mach. Intell., 7:13, 2025. doi: 10.1007/s42484-024-00234-4.

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