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Neural Computing and Applications

Quantum multiverse optimization algorithm for optimization problems

Gehad Ismail Sayed, Ashraf Darwish, Aboul Ella Hassanien

Published Nov 1, 2017• 72 citations
Publisher
DOI
10.1007/s00521-017-3228-9

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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 000 or 111 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 707070 qubit simulation of Shor's Algorithm on a commodity cloud server with 969696 CPUS and 624624624GB 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.
Current multiverse theories often lack a rigorous computational framework. We propose using quantum simulations to dynamically explore the possible configurations of a multiverse, identifying emergent patterns and constraints. This research explores a novel approach by implementing a quantum simulation algorithm that iteratively explores a vast state space, revealing patterns and constraints that arise from the interactions of multiple universes. The core mechanism involves a dynamic mapping of potential universes, guided by quantum principles, to identify underlying physical laws. This work aims to provide a computationally feasible model for investigating the potential existence of multiverse structures and their implications for fundamental physics.