Entanglement Enhanced Technologies

We work on the theory and applications of entanglement enhanced technologies in communications and computing. We focus on two main ideas: Quantum networks and Quantum Optimization.

Quantum networks provide entanglement between distributed quantum systems as a resource to perform communication, sensing or computational tasks.  A quick introduction to quantum networks can be found here. Environmental interactions during transport of the flying qubits in the network degrades the quality of distributed entanglement. Thus, to obtain high-quality, long-range entangled quantum states efficient entanglement purification and distribution protocols are required.  Currently, we are working on techniques for efficient entanglement routing, i.e. optimal paths for entanglement distribution, by developing routing algebras for quantum networks. For large-scale quantum networks regions with interesting multipartite entanglement patterns can develop. We are interested in studying the emergence and properties of such entanglement structures in large scale quantum networks.

Quantum optimization promises quicker and/or more optimal solutions for certain classes of computational problems where classical stochastic algorithms are inefficient. Quantum optimization subroutines can be used in settings ranging from direct applications in quadratic binary optimization problems on one hand; to efficiently train neural networks for supervised learning applications on the other hand. We are studying the use of quantum and quantum-inspired algorithms for direct applications in vehicular hardware design. Further, we are studying the use of entanglement in obtaining better learning models. Since, for the current noisy quantum hardware the reliability of the returned solutions is questionable, we are also interested in techniques that mitigate the errors in the hardware-returned solutions.