This paper considers a version of the Wiener filtering problem for equalization of passive linear quantum systems. We demonstrate that taking into consideration the quantum nature of the signals involved leads to features typically not encountered in classical equalization problems. Most significantly, finding a mean-square optimal quantum equalizing filter amounts to solving a nonconvex constrained optimization problem. We discuss two approaches to solving this problem, both involving a relaxation of the constraint. In both cases, unlike classical equalization, there is a threshold on the variance of the noise below which an improvement of the mean-square error cannot be guaranteed.
The 2023 Boyer Lecture series is called 'The Atomic Revolution' and is presented by Professor Michelle Simmons AO, a pioneer in atomic electronics and global leader in quantum computing.READ
CQC2T Director Professor Michelle Simmons AO and Chief Investigator Professor Yuerui (Larry) Lui were recognised in the prestigious 2023 Prime Minister’s award ceremony held at Parliament House last nREAD
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