Implementing quantum dimensionality reduction for non-Markovian stochastic simulation.

Complex systems are embedded in our everyday experience. Stochastic modelling enables us to understand and predict the behaviour of such systems, cementing its utility across the quantitative sciences. Accurate models of highly non-Markovian processes - where the future behaviour depends on events that happened far in the past - must track copious amounts of information about past observations, requiring high-dimensional memories. Quantum technologies can ameliorate this cost, allowing models of the same processes with lower memory dimension than corresponding classical models. Here we implement such memory-efficient quantum models for a family of non-Markovian processes using a photonic setup. We show that with a single qubit of memory our implemented quantum models can attain higher precision than possible with any classical model of the same memory dimension. This heralds a key step towards applying quantum technologies in complex systems modelling.

Experimental quantification of dynamical coherence via entangling two qubits.

Coherence and entanglement are both the fundamental properties which quantify the degree of nonclassicality possessed in a quantum state. Recently coherence and entanglement are considered as a dynamical resource where the nonclassicality is strongly related to the amount of the static resources which can be generated in a quantum process. In [Phys. Rev. Lett.125, 130401 (2020)10.1103/PhysRevLett.125.130401], for the first time, the authors study the interconvertability of these two kinds of dynamical resources. Here, we demonstrate this resource conversion in an all optical setup, and successfully observe the dynamical resource conversion. The experimental observation prove the ability of manipulating dynamical resource within current quantum photonic technologies.