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Title: Interfering trajectories in experimental quantum-enhanced stochastic simulation
Authors: Ghafari, Farzad
Tischler, Nora
Di Franco, Carlo
Thompson, Jayne
Gu, Mile
Pryde, Geoff J.
Keywords: Quantum
Stochastic Simulation
Issue Date: 2019
Source: Ghafari, F., Tischler, N., Di Franco, C., Thompson, J., Gu, M., & Pryde, G. J. (2019). Interfering trajectories in experimental quantum-enhanced stochastic simulation. Nature Communications, 10, 1630-. doi:10.1038/s41467-019-08951-2
Series/Report no.: Nature Communications
Abstract: Simulations of stochastic processes play an important role in the quantitative sciences, enabling the characterisation of complex systems. Recent work has established a quantum advantage in stochastic simulation, leading to quantum devices that execute a simulation using less memory than possible by classical means. To realise this advantage it is essential that the memory register remains coherent, and coherently interacts with the processor, allowing the simulator to operate over many time steps. Here we report a multi-time-step experimental simulation of a stochastic process using less memory than the classical limit. A key feature of the photonic quantum information processor is that it creates a quantum superposition of all possible future trajectories that the system can evolve into. This superposition allows us to introduce, and demonstrate, the idea of comparing statistical futures of two classical processes via quantum interference. We demonstrate interference of two 16-dimensional quantum states, representing statistical futures of our process, with a visibility of 0.96 ± 0.02.
DOI: 10.1038/s41467-019-08951-2
Rights: © 2019 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit
Fulltext Permission: open
Fulltext Availability: With Fulltext
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