Quantum Error Mitigation Strategies for Variational PDE-Constrained Circuits on Noisy Hardware
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arXiv:2604.10099v1 Announce Type: new Abstract: Variational quantum circuits (VQCs) solving partial differential equations (PDEs) on near-term quantum hardware face a critical challenge: hardware noise degrades solution fidelity and disrupts convergence. We present a systematic study of three noise channels; depolarizing, amplitude damping, and bit-flip on VQCs constrained by PDE residual loss functions for the heat equation, Burgers' equation, and the Saint-Venant shallow water equations. We be
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Quantum Physics
[Submitted on 11 Apr 2026]
Quantum Error Mitigation Strategies for Variational PDE-Constrained Circuits on Noisy Hardware
Prasad Nimantha Madusanka Ukwatta Hewage, Midhun Chakkravarthy, Ruvan Kumara Abeysekara
Variational quantum circuits (VQCs) solving partial differential equations (PDEs) on near-term quantum hardware face a critical challenge: hardware noise degrades solution fidelity and disrupts convergence. We present a systematic study of three noise channels; depolarizing, amplitude damping, and bit-flip on VQCs constrained by PDE residual loss functions for the heat equation, Burgers' equation, and the Saint-Venant shallow water equations. We benchmark three error mitigation strategies: zero-noise extrapolation (ZNE) via Richardson polynomial fitting, probabilistic error cancellation (PEC), and measurement error mitigation through inverse confusion matrices. Our numerical experiments on 6-qubit, 4-layer circuits demonstrate that ZNE reduces absolute error by 82-96% at low noise (p = 0.001), with effectiveness degrading gracefully at higher noise strengths. We prove analytically and confirm numerically that physics-constrained circuits exhibit inherent noise resilience: at p = 0.01, constrained circuits maintain 25-47% higher fidelity than unconstrained counterparts, with the advantage scaling with PDE complexity. PEC provides near-exact correction at low gate counts but incurs exponential sampling overhead, rendering it impractical beyond ~60 gates at p >= 0.02. Error budget decomposition reveals that systematic errors dominate at all noise levels (43-58%), while the PDE residual component grows from ~10% to ~31% as noise increases, indicating that physics constraints absorb noise through structured gradient information. These results establish practical guidelines for deploying variational PDE solvers on NISQ hardware.
Comments: 15 pages, 6 figures, 5 tables Github Repo: git@github.com:nimanpra/quantum_error_mitigation_strategies.git
Subjects: Quantum Physics (quant-ph)
MSC classes: 81Q80, 65M99, 81P68
Cite as: arXiv:2604.10099 [quant-ph]
(or arXiv:2604.10099v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2604.10099
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Submission history
From: Prasad Nimantha Madusanka Ukwatta Hewage [view email]
[v1] Sat, 11 Apr 2026 08:45:08 UTC (71 KB)
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