Nonlinear Quantum Fluids

S. M. Mahajan, Felipe A. Asenjo

Razvan Teodorescu

Javier Gonzalez-Conde, Dylan Lewis, Sachin S. Bharadwaj +1 more

Computational fluid dynamics (CFD) is a specialized branch of fluid mechanics that utilizes numerical methods and algorithms to solve and analyze fluid-flow problems. One promising avenue to enhance CFD is the use of quantum computing, which has the potential to resolve nonlinear differential equations more efficiently than classical computers. Here, we try to answer the question of which regimes of nonlinear partial differential equations for fluid dynamics can have an efficient quantum algorithm. We propose a connection between the numerical parameter R , which guarantees efficiency in the truncation of the Carleman linearization, and the physical parameters that describe the fluid flow. This link can be made thanks to the Kolmogorov scale, which determines the minimum size of the grid needed to properly resolve the energy cascade induced by the nonlinear term. Additionally, we introduce the formalism for vector field simulation in different spatial dimensions, providing the discretization of the operators and the boundary conditions.

Min Soe, George Vahala, Linda L. Vahala +3 more

Using the Madelung transformation on a generalized scalar Gross–Pitaevski equation, a nonlinear continuum fluid equations are derived for a classical fluid. A unitary quantum lattice algorithm is then determined as a second order discrete representation of this Gross–Pitaevski equation and the simulations are compared to those using classical fluid dynamic techniques.