Quantum Spectral Methods for Differential Equations

Recently developed quantum algorithms address computational challenges in numerical analysis by performing linear algebra in Hilbert space. Such algorithms can produce a quantum state proportional to the solution of a d-dimensional system of linear equations or linear differential equations with complexity $${{\,\mathrm{poly}\,}}(\log d)$$. While several of these algorithms approximate the solution to within $$\epsilon $$ with complexity $${{\,\mathrm{poly}\,}}(\log (1/\epsilon ))$$, no such algorithm was previously known for differential equations with time-dependent coefficients. Here we develop a quantum algorithm for linear ordinary differential equations based on so-called spectral methods, an alternative to finite difference methods that approximates the solution globally. Using this approach, we give a quantum algorithm for time-dependent initial and boundary value problems with complexity $${{\,\mathrm{poly}\,}}(\log d, \log (1/\epsilon ))$$.