18 July 2022, 13:15 (EET), Hall 300, INRNE

• Petar Danev (INRNE-BAS)
• Title: Study of quantum random walk search algorithm with qudit Householder traversing coin
• Abstract: The discrete time quantum random walk search (DTQRWS) algorithm uses quantum walk to find elements in an unordered database. It is quadratically faster than the corresponding classical counterpart. I will present a modification of DTQRWS, constructed by qudit Householder traversing coin, making the algorithm extremely robust to inaccuracies in the coin parameters if a proper relation between them is maintained. Optimal functional dependencies and parameter values are derived for walk coin with size up to one qudit with eleven states. By applying deep neural network, we extrapolate the results for walk coin with arbitrary dimension.
• The presentation is based on the preprint “High robustness quantum walk search algorithm with qudit Householder traversing coin, machine learning study”, with authors Hristo Tonchev and Petar Danev: arXiv:2111.10926
• Slides: pdf-format, 3MB and pptx-format, 20MB