Centre for Quantum Computation and Communication Technology (Australian Research Council), Centre for Quantum Dynamics, Griffith University, Brisbane, Queensland 4111, Australia.
School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore 639673, Republic of Singapore.; Complexity Institute, Nanyang Technological University, 60 Nanyang View, Singapore 639673, Republic of Singapore.; Centre for Quantum Technologies, National University of Singapore, 3 Science Drive 2, Singapore, Republic of Singapore.
Sci Adv. 2017 Feb 3;3(2):e1601302. doi: 10.1126/sciadv.1601302. eCollection 2017 Feb.
Computer simulation of observable phenomena is an indispensable tool for engineering new technology, understanding the natural world, and studying human society. However, the most interesting systems are often so complex that simulating their future behavior demands storing immense amounts of information regarding how they have behaved in the past. For increasingly complex systems, simulation becomes increasingly difficult and is ultimately constrained by resources such as computer memory. Recent theoretical work shows that quantum theory can reduce this memory requirement beyond ultimate classical limits, as measured by a process' statistical complexity, . We experimentally demonstrate this quantum advantage in simulating stochastic processes. Our quantum implementation observes a memory requirement of = 0.05 ± 0.01, far below the ultimate classical limit of = 1. Scaling up this technique would substantially reduce the memory required in simulations of more complex systems.
计算机模拟可观察现象是工程新技术、理解自然界和研究人类社会不可或缺的工具。然而，最有趣的系统往往非常复杂，以至于要模拟它们未来的行为，就需要存储大量关于它们过去行为的信息。对于越来越复杂的系统，模拟变得越来越困难，最终受到计算机内存等资源的限制。最近的理论工作表明，量子理论可以将这种存储要求降低到超出经典极限的程度，这一极限可以通过过程的统计复杂度来衡量。我们在模拟随机过程方面实验性地证明了这种量子优势。我们的量子实现观察到的存储要求为 = 0.05 ± 0.01，远低于经典极限 = 1。这项技术的扩展将大大减少更复杂系统模拟所需的内存。
