Noise in quantum systems poses a challenge for both near term quantum devices as well as for future fault-tolerant quantum computers.

To tackle this challenge, this project will integrate a suite of techniques into a toolbox that leverages techniques from quantum characterization and control, probabilistic programming, and approximate computing to improve error robustness in quantum computing hardware.

We will integrate characterization and error mitigation strategies into the quantum software stack from the bottom up to optimize and enhance the robustness and scaling of noisy computation. From the top-down, we will investigate whether higher-level programming constructs from the classical domain, such as probabilistic programming or approximate computing, can extend into the quantum domain to further enhance the reliability of noisy quantum computation. While our efforts will focus on near-term noisy intermediate scale quantum (NISQ) computation, our approach will have direct applicability to future fault-tolerant quantum computers as well.

Achieving quantum supremacy in the NISQ-era and beyond will require continued reduction in noise levels and optimizations in quantum circuits that consider the underlying hardware constraints, including noise characteristics.