Abstract

We present and experimentally realize a quantum algorithm for efficiently solving the following problem: given an N×NN\times N matrix M\mathcal{M}, an NN-dimensional vector b\textbf{\emph{b}}, and an initial vector x(0)\textbf{\emph{x}}(0), obtain a target vector x(t)\textbf{\emph{x}}(t) as a function of time tt according to the constraint dx(t)/dt=Mx(t)+bd\textbf{\emph{x}}(t)/dt=\mathcal{M}\textbf{\emph{x}}(t)+\textbf{\emph{b}}. We show that our algorithm exhibits an exponential speedup over its classical counterpart in certain circumstances. In addition, we demonstrate our quantum algorithm for a 4×44\times4 linear differential equation using a 4-qubit nuclear magnetic resonance quantum information processor. Our algorithm provides a key technique for solving many important problems which rely on the solutions to linear differential equations.

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