  The circuit model of quantum computation is reformulated as a multilayer
network theory [3] called a Quantum Multiverse Network (QuMvN). The QuMvN
formulation allows us to interpret the quantum wave function as a combination
of ergodic Markov Chains where each Markov Chain occupies a different layer in
the QuMvN structure. Layers of a QuMvN are separable components of the
corresponding wave function. Single qubit measurement is defined as a state
transition of the Markov Chain that emits either a $0$ or $1$ making each layer
of the QuMvN a Discrete Information Source. A message is equivalent to a
possible measurement outcome and the message length is the number of qubits.
Therefore, the quantum wave function can be treated as a combination of
multiple discrete information sources analogous to what Shannon called a
"mixed" information source [18]. We show the QuMvN model has significant
advantages in the classical simulation of some quantum circuits by implementing
quantum gates as edge transformations on the QuMvNs. We implement a quantum
virtual machine capable of simulating quantum circuits using the QuMvN model
and use our implementation to classically simulate Shor's Algorithm [19]. We
present results from multiple simulations of Shor's Algorithm culminating in a
$70$ qubit simulation of Shor's Algorithm on a commodity cloud server with $96$
CPUS and $624$GB of RAM. Lastly, the source of quantum speedups is discussed in
the context of layers in the QuMvN framework and how randomized algorithms can
push the quantum supremacy boundary.
