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Hidden User Oct. 5, 2018, 5:37 p.m.
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Individuals were represented in the model using two qubits. One qubit represented the individual’s genotype, the genetic code behind a certain trait, and the other its phenotype, or the physical expression of that trait.

To model self-replication, the algorithm copied the expectation value (the average of the probabilities of all possible measurements) of the genotype to a new qubit through entanglement, a process that links qubits so that information is instantaneously exchanged between them. To account for mutations, the researchers encoded random qubit rotations into the algorithm that were applied to the genotype qubits.

The algorithm then modeled the interaction between the individual and its environment, which represented aging and eventually death. This was done by taking the new genotype from the self-replicating action in the previous step and transferring it to another qubit via entanglement. The new qubit represented the individual’s phenotype. The lifetime of the individual—that is, how long it takes the information to degrade or dissipate through interaction with the environment—depends on the information coded in this phenotype.
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