Provably unbounded memory advantage in stochastic simulation using quantum mechanics

• Main Authors: Garner, Andrew J. P., Liu, Qing, Thompson, Jayne, Vedral, Vlatko, Gu, Mile
• Other Authors: School of Physical and Mathematical Sciences
• Format: Article
• Language: English
• Published: 2018
• Subjects: Quantum Advantage; Quantum Information
• Online Access: https://hdl.handle.net/10356/87218; http://hdl.handle.net/10220/44337
• Institution: Nanyang Technological University

Simulating the stochastic evolution of real quantities on a digital computer requires a trade-off between the precision to which these quantities are approximated, and the memory required to store them. The statistical accuracy of the simulation is thus generally limited by the internal memory available to the simulator. Here, using tools from computational mechanics, we show that quantum processors with a fixed finite memory can simulate stochastic processes of real variables to arbitrarily high precision. This demonstrates a provable, unbounded memory advantage that a quantum simulator can exhibit over its best possible classical counterpart.