I work on novel applications for quantum computers and on assesssing/benchmarking their properties and performance. In particular, I work on how to model and simulate the behaviour of physical systems inside quantum computers and on harnessing quantum algorithms to accelerate the inference of properties of these physical systems. This leads to applications such as accelerated inference of structure and trends in high dimensional time-series data, design of interactive quantum agents which are deployable towards reinforcement learning and sequence-to-sequence modelling tasks. It also leads to benchmarking of quantum computers and quantum memory based on capacity to reproduce desired input-output relation behaviour.
Selected publications:
- Quantum adaptive agents with efficient long-term memories, Physical Review X 12, 011007 (2022)
- Universal and operational benchmarking of quantum memories, Nature Partner Journal: Quantum Information 7, 108 (2021)
- Modular quantum computation in a trapped ion system, Nature Communications 10, 469 (2019)
- Causal Asymetry in a Quantum World, Physical Review X 8, 031013 (2018)
- Practical Unitary Simulator for Non-Markovian Complex Processes, Physical Review Letters 120, 240502 (2018)
