New Webpage
I’m very excited to have this new webpage running. The webpage uses Jekyll and the Minimal Mistakes theme.
Research
Hybrid quantum-classical generative models
Generative models are machine learning models that can be used to efficiently generate new data (for e.g. see DALLE-2, StyleGAN2).
We recently explored how deep generative models can be used to simulate sub-atomic interaction of high-energy particles produced at the Large Hadron Collider. In addition, we explored how we can use superconducting quantum annealers in a hybrid quantum-classical setting to improve on existing classical generative models and potentially demonstrate a quantum advantage 🥳 .
Differentiable quantum transforms
Diffentiable quantum transforms are meta-programs that can modify quantum circuits in a differentiable manner. We’re currently exploring their applications to quantum gradients, compilation and error mitigation.