23 citations · 28 across the 2 of their papers we have counts for
7 papers
Provable superior accuracy in machine learned quantum models
Chengran Yang, Andrew Garner, Feiyang Liu +5
In modelling complex processes, the potential past data that influence future expectations are immense. Models that track all this data are not only computationally wasteful but al…
Bandwidth control of the biphoton wavefunction exploiting spatio-temporal correlations
J. J. Miguel Varga, Jon Lasa-Alonso, Martín Molezuelas-Ferreras +2
In this work we study the spatio-temporal correlations of photons produced by spontaneous parametric down conversion. In particular, we study how the waists of the detection and pu…
Interfering trajectories in experimental quantum-enhanced stochastic simulation
Farzad Ghafari, Nora Tischler, Carlo Di Franco +3
Simulations of stochastic processes play an important role in the quantitative sciences, enabling the characterisation of complex systems. Recent work has established a quantum adv…
Single-shot quantum memory advantage in the simulation of stochastic processes
Farzad Ghafari, Nora Tischler, Jayne Thompson +7
Stochastic processes underlie a vast range of natural and social phenomena. Some processes such as atomic decay feature intrinsic randomness, whereas other complex processes, e.g.…
Experimental Quantum Switching for Exponentially Superior Quantum Communication Complexity
Kejin Wei, Nora Tischler, Si-Ran Zhao +13
Finding exponential separation between quantum and classical information tasks is like striking gold in quantum information research. Such an advantage is believed to hold for quan…
Experimental Realization of a Quantum Autoencoder: The Compression of Qutrits via Machine Learning
Alex Pepper, Nora Tischler, Geoff J. Pryde
With quantum resources a precious commodity, their efficient use is highly desirable. Quantum autoencoders have been proposed as a way to reduce quantum memory requirements. Genera…