Our work on hybrid quantum-classical algorithms is featured in news
The best of both worlds: how to solve real problems on modern quantum computers
We solve algorithmic, modeling and computational problems in AI, machine learning, quantum computing, network science, graphs, combinatorial scientific computing and more.
Our work on hybrid quantum-classical algorithms is featured in news
The best of both worlds: how to solve real problems on modern quantum computers
Our paper on hybrid quantum-classical algorithms is featured in IEEE Computer, the June's issue on quantum realism.
Ruslan Shaydulin, Hayato Ushijima-Mwesigwa, Christian F.A. Negre, Ilya Safro, Susan M. Mniszewski, Yuri Alexeev "Hybrid Approach for Solving Optimization Problems on Small Quantum Computers", IEEE Computer, vol. 52(6), pp. 18-26, 2019
Solving larger-sized problems is an important area of research in quantum computing. Designing hybrid quantum-classical algorithms is a promising approach to solving this. We discuss decomposition-based hybrid approaches for solving optimization problems and demonstrate them for applications related to community detection.
Quantum Computing Quantum computers are expected to accelerate scientific discovery spanning many different areas such as medicine, AI, ...