9 September 2021, 13:15 (EET), online seminar

• Hristo Tonchev (ISSP and INRNE-BAS)
• Title: Optimizing the walk coin of Quantum random walk search algorithm through neural network
• Abstract: In the talk I will explain the quantum random walk search (QRWS) algorithm with walk coin constructed by Householder reflection with additional phase. Functional dependence between the coin parameters is searched for. The walk coin is optimized by Monte Carlo simulations and supervised machine learning in a way that increases the robustness of the QRWS algorithm, against inaccuracies in the phases used to construct the coin. Examples of numerical simulations for coin consisting of one, two and three qubits will also be shown.
• The presentation is based on the preprint “Optimizing the walk coin in the quantum random walk search algorithm through machine learning”, with authors Hristo Tonchev and Petar Danev: arXiv:2105.08020.