Papers › Quantum algorithm for solving linear systems of equations

Quantum algorithm for solving linear systems of equations

19 Nov 2008arXiv:0811.3171links table onlyarchive 2025-07-28

Aram W. Harrow, Avinatan Hassidim, Seth Lloyd

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Solving linear systems of equations is a common problem that arises both on its own and as a subroutine in more complex problems: given a matrix A and a vector b, find a vector x such that Ax=b. We consider the case where one doesn't need to know the solution x itself, but rather an approximation of the expectation value of some operator associated with x, e.g., x'Mx for some matrix M. In this case, when A is sparse, N by N and has condition number kappa, classical algorithms can find x and estimate x'Mx in O(N sqrt(kappa)) time. Here, we exhibit a quantum algorithm for this task that runs in poly(log N, kappa) time, an exponential improvement over the best classical algorithm.

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StationQ/Liquid mentioned on GitHubNOASSERTION report
hhy37/Liquid mentioned on GitHubNOASSERTION report
marco-lewis/silq-hhl mentioned on GitHubMIT report
omalled/quantum-woodbury mentioned on GitHub report

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1ran · violated contract
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hadamard_test_expval omalled/quantum-woodbury/ex.py community (archive-listed) ran · fixture could not drive it licence not identified · pointer only · 5b9b489b2888bb61 · report
my_getcounts omalled/quantum-woodbury/ex.py community (archive-listed) ran · violated contract licence not identified · pointer only · cf6e5a95d758ef63 · report

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