Abstract: An ability to run unstructured search algorithm (by Grover) on actual quantum hardware is crucial for the assessment of viability of Quantum Computing as a solution to hard business problems in warehousing, logistics, finance, risk management and manufacturing. Running any meaningful unstructured search on NISQ machines, limited to circuit depths of low tens, is hard. This effect has been demonstrated in 2018 by a team using IBM Q quantum computer solving, with probability better than 60%, a search of one out of 8 states. 

So far, nobody has been able to show a Grover search on real hardware even with N as low as 16. Dr Wojciech Burkot will talk about a family of algorithms especially constructed for NISQ computers promising much better results at currently available qubit counts and circuit depths and the consequences of having a hardware able to running them.

Short Bio: Previously, Chief Technology Officer at Grupa Allegro, Dr Burkot was responsible for Marketplace, focused on Mobile and Big Data. Before Allegro, he had started and run Google R&D Center in Krakow as a Site Lead and Engineering Director between 2006-2014. Prior to Google, he worked in several roles at Motorola. Earlier in his career, he was an Assistant Professor of Computer Science at AGH in Kraków and a researcher at Institute of Nuclear Physics.

The main goal of Beit is to design and implement an algorithm for solving an all-relevant NP-complete class of problems using Quantum Computers effectively, i.e. getting speedups better than quadratic, guaranteed by theory. Beit focuses on Hamiltonian cycle problem, but since there are known reductions between different problems inside NP-complete class, Beit are working on all of them at the same time. As we know, NP-complete problems are abstractions relevant for many real-world problems encountered in logistics, manufacturing and warehousing at scale.

For further information please see Beit website and its publications.