Quantum processes: a novel optimization for quantum simulation

The simulation of quantum algorithms in classical computers demands high processingand storing capabilities. However, optimizations to reduce temporal and spatial complexities are promising and capable of improving the overall performance of simulators. The main contribution of this work consists in designing optimizations to describe quantum transformations using Quantum Processes and Partial Quantum Processes, as conceived in the qGM theoretical model. These processes, when computed on the VPE-qGM execution environment, reduce the execution time of the simulation. The performance evaluation of this proposal was carried out by benchmarks that include sequential simulation of quantum algorithms up to 24 qubits and instances of Grover's Algorithm. The results show improvements in the simulation of general, controled transformations since their execution time was significantly low, even for systems with several qubits. Furthermore, a solution based on GPU computing for dealing with transformations that still have a high simulation cost in the VPE-qGM is also discussed.