High-precision quantum algorithms for partial differential equations

Andrew M. Childs1,2,3, Jin-Peng Liu1,2,4, and Aaron Ostrander1,2,5

1Joint Center for Quantum Information and Computer Science, University of Maryland, MD 20742, USA
2Institute for Advanced Computer Studies, University of Maryland, MD 20742, USA
3Department of Computer Science, University of Maryland, MD 20742, USA
4Department of Mathematics, University of Maryland, MD 20742, USA
5Department of Physics, University of Maryland, MD 20742, USA

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Abstract

Quantum computers can produce a quantum encoding of the solution of a system of differential equations exponentially faster than a classical algorithm can produce an explicit description. However, while high-precision quantum algorithms for linear ordinary differential equations are well established, the best previous quantum algorithms for linear partial differential equations (PDEs) have complexity $\mathrm{poly}(1/\epsilon)$, where $\epsilon$ is the error tolerance. By developing quantum algorithms based on adaptive-order finite difference methods and spectral methods, we improve the complexity of quantum algorithms for linear PDEs to be $\mathrm{poly}(d, \log(1/\epsilon))$, where $d$ is the spatial dimension. Our algorithms apply high-precision quantum linear system algorithms to systems whose condition numbers and approximation errors we bound. We develop a finite difference algorithm for the Poisson equation and a spectral algorithm for more general second-order elliptic equations.

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[129] Soronzonbold Otgonbaatar and Dieter Kranzlmüller, "Exploiting the Quantum Advantage for Satellite Image Processing: Review and Assessment", IEEE Transactions on Quantum Engineering 5, 1 (2024).

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[133] Haoya Li, Hongkang Ni, and Lexing Ying, "On efficient quantum block encoding of pseudo-differential operators", Quantum 7, 1031 (2023).

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[135] Chenyi Zhang, Jiaqi Leng, and Tongyang Li, "Quantum algorithms for escaping from saddle points", Quantum 5, 529 (2021).

[136] Kenji Kubo, Koichi Miyamoto, Kosuke Mitarai, and Keisuke Fujii, "Pricing Multiasset Derivatives by Variational Quantum Algorithms", IEEE Transactions on Quantum Engineering 4, 1 (2023).

[137] Kai Li, Ming Zhang, Xiaowen Liu, Yong Liu, Hongyi Dai, Yijun Zhang, and Chen Dong, "Quantum Linear System Algorithm for General Matrices in System Identification", Entropy 24 7, 893 (2022).

[138] Lingxia Cui, Zongmin Wu, and Hua Xiang, "Quantum radial basis function method for the Poisson equation", Journal of Physics A: Mathematical and Theoretical 56 22, 225303 (2023).

[139] Abhijat Sarma, Thomas W. Watts, Mudassir Moosa, Yilian Liu, and Peter L. McMahon, "Quantum variational solving of nonlinear and multidimensional partial differential equations", Physical Review A 109 6, 062616 (2024).

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[142] Cheng Xue, Xiao-Fan Xu, Yu-Chun Wu, and Guo-Ping Guo, "Quantum algorithm for solving a quadratic nonlinear system of equations", Physical Review A 106 3, 032427 (2022).

[143] Nana Liu, Qisheng Wang, Mark M. Wilde, and Zhicheng Zhang, "Quantum algorithms for matrix geometric means", npj Quantum Information 11 1, 101 (2025).

[144] Alexander M. Dalzell, Sam McArdle, Mario Berta, Przemyslaw Bienias, Chi-Fang Chen, András Gilyén, Connor T. Hann, Michael J. Kastoryano, Emil T. Khabiboulline, Aleksander Kubica, Grant Salton, Samson Wang, and Fernando G. S. L. Brandão, "Quantum algorithms: A survey of applications and end-to-end complexities", arXiv:2310.03011, (2023).

[145] Jin-Peng Liu, Herman Øie Kolden, Hari K. Krovi, Nuno F. Loureiro, Konstantina Trivisa, and Andrew M. Childs, "Efficient quantum algorithm for dissipative nonlinear differential equations", Proceedings of the National Academy of Science 118 35, e2026805118 (2021).

[146] Oleksandr Kyriienko, Annie E. Paine, and Vincent E. Elfving, "Solving nonlinear differential equations with differentiable quantum circuits", Physical Review A 103 5, 052416 (2021).

[147] Hai-Ling Liu, Yu-Sen Wu, Lin-Chun Wan, Shi-Jie Pan, Su-Juan Qin, Fei Gao, and Qiao-Yan Wen, "Variational quantum algorithm for the Poisson equation", Physical Review A 104 2, 022418 (2021).

[148] Budinski Ljubomir, "Quantum algorithm for the Navier-Stokes equations by using the streamfunction-vorticity formulation and the lattice Boltzmann method", International Journal of Quantum Information 20 2, 2150039-27 (2022).

[149] David Jennings, Kamil Korzekwa, Matteo Lostaglio, Andrew T Sornborger, Yigit Subasi, and Guoming Wang, "Quantum algorithms for general nonlinear dynamics based on the Carleman embedding", arXiv:2509.07155, (2025).

[150] Yuxuan Du, Xinbiao Wang, Naixu Guo, Zhan Yu, Yang Qian, Kaining Zhang, Min-Hsiu Hsieh, Patrick Rebentrost, and Dacheng Tao, "Quantum Machine Learning: A Hands-on Tutorial for Machine Learning Practitioners and Researchers", arXiv:2502.01146, (2025).

[151] Xi-Ning Zhuang, Zhao-Yun Chen, Yu-Chun Wu, and Guo-Ping Guo, "Quantum computational quantitative trading: high-frequency statistical arbitrage algorithm", New Journal of Physics 24 7, 073036 (2022).

[152] Shantanav Chakraborty, Soumyabrata Hazra, Tongyang Li, Changpeng Shao, Xinzhao Wang, and Yuxin Zhang, "Quantum singular value transformation without block encodings: Near-optimal complexity with minimal ancilla", arXiv:2504.02385, (2025).

[153] Arthur G. Rattew, Po-Wei Huang, Naixu Guo, Lirandë Pira, and Patrick Rebentrost, "Accelerating Inference for Multilayer Neural Networks with Quantum Computers", arXiv:2510.07195, (2025).

[154] Mohsen Bagherimehrab, Yuval R. Sanders, Dominic W. Berry, Gavin K. Brennen, and Barry C. Sanders, "Nearly Optimal Quantum Algorithm for Generating the Ground State of a Free Quantum Field Theory", PRX Quantum 3 2, 020364 (2022).

[155] Osama Muhammad Raisuddin and Suvranu De, "Quantum Multigrid Algorithm for Finite Element Problems", arXiv:2404.07466, (2024).

[156] André Großardt, "Nonlinear-ancilla aided quantum algorithm for nonlinear Schrödinger equations", arXiv:2403.10102, (2024).

[157] Zhenning Liu, Xiantao Li, Chunhao Wang, and Jin-Peng Liu, "Toward end-to-end quantum simulation for protein dynamics", arXiv:2411.03972, (2024).

[158] Ismail Yunus Akhalwaya, Adam Connolly, Roland Guichard, Steven Herbert, Cahit Kargi, Alexandre Krajenbrink, Michael Lubasch, Conor Mc Keever, Julien Sorci, Michael Spranger, and Ifan Williams, "A Modular Engine for Quantum Monte Carlo Integration", arXiv:2308.06081, (2023).

[159] Cheng Xue, Yu-Chun Wu, and Guo-Ping Guo, "Quantum homotopy perturbation method for nonlinear dissipative ordinary differential equations", New Journal of Physics 23 12, 123035 (2021).

[160] S. Biedron, L. Brouwer, D. L. Bruhwiler, N. M. Cook, A. L. Edelen, D. Filippetto, C.-K. Huang, A. Huebl, T. Katsouleas, N. Kuklev, R. Lehe, S. Lund, C. Messe, W. Mori, C.-K. Ng, D. Perez, P. Piot, J. Qiang, R. Roussel, D. Sagan, A. Sahai, A. Scheinker, M. Thévenet, F. Tsung, J.-L. Vay, D. Winklehner, and H. Zhang, "Snowmass21 Accelerator Modeling Community White Paper", arXiv:2203.08335, (2022).

[161] Rundi Lu, Hao-En Li, Zhengwei Liu, and Jin-Peng Liu, "Infinite-dimensional Extension of the Linear Combination of Hamiltonian Simulation: Theorems and Applications", arXiv:2502.19688, (2025).

[162] Souichi Takahira, Asuka Ohashi, Tomohiro Sogabe, and Tsuyoshi Sasaki Usuda, "Quantum Algorithms based on the Block-Encoding Framework for Matrix Functions by Contour Integrals", arXiv:2106.08076, (2021).

[163] Xinchi Huang, Hirofumi Nishi, Taichi Kosugi, Yoshifumi Kawada, and Yu-ichiro Matsushita, "A probabilistic imaginary-time evolution quantum algorithm for advection-diffusion equation: Explicit gate-level implementation and comparisons to quantum linear system algorithms", arXiv:2409.18559, (2024).

[164] Óscar Amaro and Diogo Cruz, "A Living Review of Quantum Computing for Plasma Physics", arXiv:2302.00001, (2023).

[165] Wolfgang Maass, Ankit Agrawal, Alessandro Ciani, Sven Danz, Alejandro Delgadillo, Philipp Ganser, Pascal Kienast, Marco Kulig, Valentina König, Nil Rodellas-Gràcia, Rivan Rughubar, Stefan Schröder, Marc Stautner, Hannah Stein, Tobias Stollenwerk, Daniel Zeuch, and Frank K. Wilhelm, "Quantum Computing Enhanced Service Ecosystem for Simulation in Manufacturing", arXiv:2401.10623, (2024).

[166] Songqinghao Yang and Jin-Peng Liu, "Circuit-Efficient Randomized Quantum Simulation of Non-Unitary Dynamics with Observable-Driven and Symmetry-Aware Designs", arXiv:2509.08030, (2025).

[167] Jaewoo Joo and Hyungil Moon, "Quantum variational PDE solver with machine learning", arXiv:2109.09216, (2021).

[168] Zhao-Yun Chen, Cheng Xue, Si-Ming Chen, Bing-Han Lu, Yu-Chun Wu, Ju-Chun Ding, Sheng-Hong Huang, and Guo-Ping Guo, "Quantum Finite Volume Method for Computational Fluid Dynamics with Classical Input and Output", arXiv:2102.03557, (2021).

[169] Paula García-Molina, Luca Tagliacozzo, and Juan José García-Ripoll, "Comparative study of matrix product state/quantized tensor-train algorithms for solving time-independent partial differential equations", arXiv:2303.09430, (2023).

[170] Guillermo González, Rahul Trivedi, and J. Ignacio Cirac, "Quantum algorithms for powering stable Hermitian matrices", Physical Review A 103 6, 062420 (2021).

[171] Osama Muhammad Raisuddin and Suvranu De, "FEqa: Finite element computations on quantum annealers", Computer Methods in Applied Mechanics and Engineering 395, 115014 (2022).

[172] Cheng Xue, Yuchun Wu, and Guoping Guo, "Quantum Newton’s Method for Solving the System of Nonlinear Equations", Spin 11 3, 2140004 (2021).

[173] Dylan Herman, Yue Sun, Jin-Peng Liu, Marco Pistoia, Charlie Che, Rob Otter, Shouvanik Chakrabarti, and Aram Harrow, "Quantum Speedups for Derivative Pricing Beyond Black-Scholes", arXiv:2602.03725, (2026).

[174] Xinchi Huang, Hirofumi Nishi, Yoshifumi Kawada, Tomofumi Zushi, and Yu-ichiro Matsushita, "Fourier space readout method for efficiently recovering functions encoded in quantum states", arXiv:2507.20599, (2025).

[175] Osama Muhammad Raisuddin and Suvranu De, "Quantum Relaxation for Linear Systems in Finite Element Analysis", arXiv:2308.01377, (2023).

[176] Changpeng Shao and Jin-Peng Liu, "Solving generalized eigenvalue problems by ordinary differential equations on a quantum computer", arXiv:2010.15027, (2020).

[177] Matthias Deiml and Daniel Peterseim, "Quantum Sampling and Moment Estimation for Transformed Gaussian Random Fields", arXiv:2508.13879, (2025).

[178] Shengbin Wang, Zhimin Wang, Wendong Li, Lixin Fan, Guolong Cui, Zhiqiang Wei, and Yongjian Gu, "A quantum Poisson solver implementable on NISQ devices (improved version)", arXiv:2005.00256, (2020).

[179] Paul Over, Sergio Bengoechea, Thomas Rung, Francesco Clerici, Leonardo Scandurra, Eugene de Villiers, and Dieter Jaksch, "Boundary Treatment for Variational Quantum Simulations of Partial Differential Equations on Quantum Computers", arXiv:2402.18619, (2024).

[180] Miriam Goldack, Yosi Atia, Ori Alberton, and Karl Jansen, "Computing Statistical Properties of Velocity Fields on Current Quantum Hardware", arXiv:2601.10166, (2026).

[181] Yolanne Yi Ran Lee, "Autoregressive Renaissance in Neural PDE Solvers", arXiv:2310.19763, (2023).

[182] Carlos Outeiral, Martin Strahm, Jiye Shi, Garrett M. Morris, Simon C. Benjamin, and Charlotte M. Deane, "The prospects of quantum computing in computational molecular biology", arXiv:2005.12792, (2020).

[183] Hari Krovi, "Quantum algorithms to simulate quadratic classical Hamiltonians and optimal control", arXiv:2404.07303, (2024).

[184] Xinchi Huang, Hirofumi Nishi, Yoshifumi Kawada, Tomofumi Zushi, and Yu-ichiro Matsushita, "Real and Fourier space readout methods: Comparison of complexity and applications to CFD problems", arXiv:2511.20017, (2025).

[185] Nikolaos Cheimarios, "Solving nonlinear PDEs with Quantum Neural Networks: A variational approach to the Bratu Equation", arXiv:2601.04372, (2026).

[186] Haoya Li, Hongkang Ni, and Lexing Ying, "On efficient quantum block encoding of pseudo-differential operators", arXiv:2301.08908, (2023).

[187] Kazue Kudo, "Annealing-based approach to solving partial differential equations", arXiv:2406.17364, (2024).

[188] Mohammed Bediche, Matthijs van Waveren, Denis Ricot, and Pierre Sagaut, "Fully Quantum Algorithm for the 1-dimensional linear Lattice Boltzmann Method", arXiv:2606.16514, (2026).

[189] Xiantao Li, "A Quantum Path to Partial Differential Equations", arXiv:2607.09639, (2026).

The above citations are from Crossref's cited-by service (last updated successfully 2026-07-17 05:34:05) and SAO/NASA ADS (last updated successfully 2026-07-16 16:29:22). The list may be incomplete as not all publishers provide suitable and complete citation data.

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