Using non-homogeneous point process statistics to find multi-species event clusters in an implanted semiconductor

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Abstract

The Poisson distribution of event-to-ith-nearest-event radial distances is well known for homogeneous processes that do not depend on location or time. Here we investigate the case of a non-homogeneous point process where the event probability (and hence the neighbour configuration) depends on location within the event space. The particular non-homogeneous scenario of interest to us is ion implantation into a semiconductor for the purposes of studying interactions between the implanted impurities. We calculate the probability of a simple cluster based on nearest neighbour distances, and specialise to a particular two-species cluster of interest for qubit gates. We show that if the two species are implanted at different depths there is a maximum in the cluster probability and an optimum density profile.

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Stockbridge, K., Chick, S., Crane, E., Fisher, A., & Murdin, B. N. (2020). Using non-homogeneous point process statistics to find multi-species event clusters in an implanted semiconductor. Journal of Physics Communications, 4(1). https://doi.org/10.1088/2399-6528/ab6049

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