Stochastic modeling and analysis of methods and algorithms for quantum computing
Alexander S. Rumyantsev
In the emerging field of quantum computing, among the possible scenarios of quantum systems utilization are the hybrid quantum-classical systems that need corresponding software and algorithms. One of the important steps of such algorithms is complexity analysis which basically starts with convergence proof/evaluation. In the talk we will address the issues of algorithm convergence formal proof, convergence speed evaluation/estimation and performance evaluation of the quantum computing speedup methods in traditional fields, such as Monte-Carlo simulation, by means of applied probability and stochastic simulation.