Automated closed-loop hardware optimization

This webinar will demonstrate how new features in Boulder Opal allow you to automate performance enhancement in quantum hardware through closed-loop experimental optimization. Whether you build quantum computers or quantum sensors, or you perform basic physics research, it’s simple to use closed-loop optimization to deliver greater performance from hardware even when there are major uncertainties in your system. We will present a variety of experimental case studies including demonstrations on ultra-cold atoms, quantum memories, and superconducting quantum computers. And look out for a sneak peak of our results using closed-loop optimization to improve the performance of two-qubit gates on IBM-Q.