Estimation of n non-identical unitary channels
  We investigate the simultaneous estimation of $n$ not necessarily identical unitary channels using multi-partite entanglement. We examine whether it is possible for the rate at which the mean square error decreases to be greater than that using the channels individually. For a reasonably general situation, in which there is no functional dependence between the channels, we show that this is not possible. We look at a case in which the channels are not necessarily identical but depend on a common variable. In this case, the mean square error decreases more rapidly using multi-partite entanglement. 
Caleb J O'Loan