@article {1605, title = {Quantum algorithm for systems of linear equations with exponentially improved dependence on precision}, journal = {SIAM Journal on Computing}, volume = {46}, year = {2017}, month = {2017/12/21}, pages = {1920-1950}, abstract = {
Harrow, Hassidim, and Lloyd showed that for a suitably specified N\×N matrix A and N-dimensional vector b⃗ , there is a quantum algorithm that outputs a quantum state proportional to the solution of the linear system of equations Ax⃗ =b⃗ . If A is sparse and well-conditioned, their algorithm runs in time poly(logN,1/ϵ), where ϵ is the desired precision in the output state. We improve this to an algorithm whose running time is polynomial in log(1/ϵ), exponentially improving the dependence on precision while keeping essentially the same dependence on other parameters. Our algorithm is based on a general technique for implementing any operator with a suitable Fourier or Chebyshev series representation. This allows us to bypass the quantum phase estimation algorithm, whose dependence on ϵ is prohibitive.
}, doi = {10.1137/16M1087072}, url = {http://epubs.siam.org/doi/10.1137/16M1087072}, author = {Andrew M. Childs and Robin Kothari and Rolando D. Somma} }