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A Probabilistic Quantum Algorithm For Lyapunov Equations And Matrix Inversion

Abstract

We present a probabilistic quantum algorithm for preparing mixed states which, in expectation, are proportional to the solutions of Lyapunov equations -- linear matrix equations ubiquitous in the analysis of classical and quantum dynamical systems. Building on previous results by Zhang et al., arXiv:2304.04526, at each step the algorithm either returns the current state, applies a trace non-increasing completely positive map, or restarts depending on the outcomes of a biased coin flip and an ancilla measurement. We introduce a deterministic stopping rule which leads to an efficient algorithm with a bounded expected number of calls to a block-encoding and a state preparation circuit representing the two input matrices of the Lyapunov equations. We also consider approximating the normalized inverse of a positive definite matrix with condition number up to trace distance error . For this special case the algorithm requires, in expectation, at most \(\lceil \ka

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