Harnessing Randomized Measurements for Near-Term Quantum Algorithms

The rapid development of modern quantum devices offers new opportunities to explore quantum algorithms that operate on current hardware and investigate complex quantum many-body phenomena. In this talk, I will discuss advanced measurement techniques that are crucial for unlocking the potential of these devices. I will give an overview of recent progress enhancing the randomized measurement toolbox, including the efficient utilization of approximate classical knowledge and robust estimation schemes. I will present how this enables algorithms for learning properties of quantum dynamics such as conservation laws. Additionally, I will introduce RandomMeas.jl, an open-source Julia package that provides accessible tools for implementing these techniques. Finally, I will discuss new approaches to understanding—and experimentally probing—the classical complexity of quantum experiments, with the aim to better map the boundaries between classical and quantum computational capabilities, guiding the development of algorithms that achieve genuine quantum advantage.