Postselection

In probability theory, to postselect is to condition a probability space upon the occurrence of a given event. In symbols, once we postselect for an event E , the probability of some other event F changes from \operatorname{Pr}[F] to the conditional probability \operatorname{Pr}[F\, |\, E] . For a discrete probability space, \operatorname{Pr}[F\, |\, E] = \frac{\operatorname{Pr}[F \, \cap \, E]}{\operatorname{Pr}[E]} , and thus we require that \operatorname{Pr}[E] be strictly positive in order for the postselection to be well-defined. See also PostBQP, a complexity class defined with postselection. Using postselection it seems quantum Turing machines are much more powerful: Scott Aaronson proved PostBQP is equal to PP. Some quantum experiments use post-selection after the experiment as a replacement for communication during the experiment, by post-selecting the communicated value into a constant.

In probability theory, to postselect is to condition a probability space upon the occurrence of a given event. In symbols, once we postselect for an event E , the probability of some other event F changes from \operatorname{Pr}[F] to the conditional probability \operatorname{Pr}[F\, |\, E] . For a discrete probability space, \operatorname{Pr}[F\, |\, E] = \frac{\operatorname{Pr}[F \, \cap \, E]}{\operatorname{Pr}[E]} , and thus we require that \operatorname{Pr}[E] be strictly positive in order for the postselection to be well-defined. See also PostBQP, a complexity class defined with postselection. Using postselection it seems quantum Turing machines are much more powerful: Scott Aaronson proved PostBQP is equal to PP. Some quantum experiments use post-selection after the experiment as a replacement for communication during the experiment, by post-selecting the communicated value into a constant.

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