Quantum Simulations is the craft of making quantum devices do one thing well. Among others, this can include the following tasks -

• Understanding the structure of complex molecules and materials.

• Learning classical data well, including images and sounds.

• Forecasting classical time-series data like stock market, neural signals etc.

Present quantum simulator platforms are noisy and relatively small-scale. Thus, the crucial question is - what can we do with these platforms for now ?

Visiting UCL during my PhD days, I met Abolfazl (then a postdoc there), and together with Saubhik, we started the study of magic, the ability of quantum systems to sustain beyond classical simulation capacity, as a diagnostic tool for many-body physics. This line has become quite popular in recent days. 

My current research is mostly on quantum reservoir learning, which does not require too much individual control over qubits. Using QRL, we are trying to find out ways of predicting classical time-series data like stock market volatility and chaotic nonlinear maps reasonably well.