
arXiv: 2402.18721
We introduce new methods for integrating nonlinear differential equations on low-rank manifolds. These methods rely on interpolatory projections onto the tangent space, enabling low-rank time integration of vector fields that can be evaluated entry-wise. A key advantage of our approach is that it does not require the vector field to exhibit low-rank structure, thereby overcoming significant limitations of traditional dynamical low-rank methods based on orthogonal projection. To construct the interpolatory projectors, we develop a sparse tensor sampling algorithm based on the discrete empirical interpolation method (DEIM) that parameterizes tensor train manifolds and their tangent spaces with cross interpolation. Using these projectors, we propose two time integration schemes on low-rank tensor train manifolds. The first scheme integrates the solution at selected interpolation indices and constructs the solution with cross interpolation. The second scheme generalizes the well-known orthogonal projector-splitting integrator to interpolatory projectors. We demonstrate the proposed methods with applications to several tensor differential equations arising from the discretization of partial differential equations.
31 pages, 8 figures
low-rank approximation, tensor cross approximation, Numerical linear algebra, Numerical & Computational Mathematics, Mathematical sciences, Numerical methods for low-rank matrix approximation; matrix compression, tensor differential equations, FOS: Physical sciences, Numerical Analysis (math.NA), Low-rank approximation, Tensor train format, time-dependent tensors, Computational Physics (physics.comp-ph), Tensor differential equations, Mathematical Sciences, Time-dependent tensors, Engineering, Information and Computing Sciences, Tensor cross approximation, Multilinear algebra, tensor calculus, FOS: Mathematics, Mathematics - Numerical Analysis, Physics - Computational Physics, Spectral, collocation and related methods for initial value and initial-boundary value problems involving PDEs, tensor train format
low-rank approximation, tensor cross approximation, Numerical linear algebra, Numerical & Computational Mathematics, Mathematical sciences, Numerical methods for low-rank matrix approximation; matrix compression, tensor differential equations, FOS: Physical sciences, Numerical Analysis (math.NA), Low-rank approximation, Tensor train format, time-dependent tensors, Computational Physics (physics.comp-ph), Tensor differential equations, Mathematical Sciences, Time-dependent tensors, Engineering, Information and Computing Sciences, Tensor cross approximation, Multilinear algebra, tensor calculus, FOS: Mathematics, Mathematics - Numerical Analysis, Physics - Computational Physics, Spectral, collocation and related methods for initial value and initial-boundary value problems involving PDEs, tensor train format
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