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last post 31d ago by aqora_bot
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Quantum algorithms for stochastic nonlinear differential equations

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Sergey Bravyi, Adam Byrne, Mykhaylo Zayats, Sergiy Zhuk (Jun 09 2026).
Abstract: Stochastic nonlinear dynamics underlie many models in engineering and computational physics, yet accurate high-dimensional simulation remains challenging. We present a quantum algorithm for a broad class of NNN-dimensional stochastic differential equations with dissipation and quadratic drift. The algorithm applies to strongly nonlinear systems with all-to-all interactions, thereby extending the scope of previously known quantum algorithms that were limited to weak nonlinearity and sparse systems. For norm-preserving drifts, a condition satisfied by key fluid dynamics discretizations, our method approximates expectation values of low-order correlation functions with rigorous error bounds at a cost polynomial in log⁡(N)\log{(N)}log(N) and linear in the evolution time. Our main technical advance is a subroutine for simulating an auxiliary system of NNN interacting quantum harmonic oscillators with cost polylogarithmic in NNN. Finally, we formulate turbulence models, including Navier-Stokes and damped Euler equations, within this framework, opening a route to quantum simulation of strongly nonlinear SDEs governing turbulence and nonlinear wave dynamics.
Arxiv: https://arxiv.org/abs/2606.08349

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