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Main Authors: Yang, Jiahua, Lu, Zhen, Yang, Yue
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2512.22559
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author Yang, Jiahua
Lu, Zhen
Yang, Yue
author_facet Yang, Jiahua
Lu, Zhen
Yang, Yue
contents Quantum computing holds potential for accelerating the simulation of fluid dynamics. However, hardware noise in the noisy intermediate-scale quantum era significantly distorts simulation accuracy. Although error magnitudes are frequently quantified, the specific physical effects of quantum noise on flow simulation results remain largely uncharacterized. We investigate the influence of gate noise on the quantum simulation of one-dimensional scalar convection. By employing a quantum spectral algorithm where ideal time advancement affects only Fourier phases, we isolate and analyze noise-induced artifacts in spectral magnitudes. We derive a theoretical transition matrix based on Hamming distances between computational basis states to predict spectral decay, and then validate this model against density-matrix simulations and experiments on a superconducting quantum processor. Furthermore, using data-driven sparse regression, we demonstrate that quantum noise manifests in the effective partial differential equation primarily as artificial diffusion and nonlinear source terms. These findings suggest that quantum errors can be modeled as deterministic physical terms rather than purely stochastic perturbations.
format Preprint
id arxiv_https___arxiv_org_abs_2512_22559
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Modeling Noise in Quantum Computing of Scalar Convection
Yang, Jiahua
Lu, Zhen
Yang, Yue
Quantum Physics
Fluid Dynamics
Quantum computing holds potential for accelerating the simulation of fluid dynamics. However, hardware noise in the noisy intermediate-scale quantum era significantly distorts simulation accuracy. Although error magnitudes are frequently quantified, the specific physical effects of quantum noise on flow simulation results remain largely uncharacterized. We investigate the influence of gate noise on the quantum simulation of one-dimensional scalar convection. By employing a quantum spectral algorithm where ideal time advancement affects only Fourier phases, we isolate and analyze noise-induced artifacts in spectral magnitudes. We derive a theoretical transition matrix based on Hamming distances between computational basis states to predict spectral decay, and then validate this model against density-matrix simulations and experiments on a superconducting quantum processor. Furthermore, using data-driven sparse regression, we demonstrate that quantum noise manifests in the effective partial differential equation primarily as artificial diffusion and nonlinear source terms. These findings suggest that quantum errors can be modeled as deterministic physical terms rather than purely stochastic perturbations.
title Modeling Noise in Quantum Computing of Scalar Convection
topic Quantum Physics
Fluid Dynamics
url https://arxiv.org/abs/2512.22559