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arXiv 0909.2530quant-ph
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利用玻色-爱因斯坦凝聚和测量反馈电路的优化

Optimization using Bose-Einstein condensation and measurement-feedback circuits

Tim Byrnes, Kai Yan, Yoshihisa Yamamoto

摘要:

我们研究了一种计算设备,利用玻色-爱因斯坦凝聚(BEC)的影响,以加快找到一个给定的优化问题的解决方案的速度。许多计算上困难的问题,包括NP完全问题,可以用公式表示为基态搜索问题。在BEC中,低于临界温度,玻色子粒子具有在基态中积累的自然趋势。此外,由于最终状态刺激,获得该配置的速度被增强。我们提出了一个物理设备,将这些基本属性的玻色子的优化问题,这样一个优化的解决方案是通过一个简单的冷却设备的物理温度。我们发现,收敛到基态的速度可以加快$ N$在一个给定的错误,其中N是每个站点的玻色子数的一个因素。

英文摘要:

We investigate a computational device that harnesses the effects of Bose-Einstein condensation (BEC) to accelerate the speed of finding the solution of a given optimization problem. Many computationally difficult problems, including NP-complete problems, can be formulated as a ground state search problem. In a BEC, below the critical temperature, bosonic particles have a natural tendency to accumulate in the ground state. Furthermore, the speed of attaining this configuration is enhanced as a result of final state stimulation. We propose a physical device that incorporates these basic properties of bosons into the optimization problem, such that an optimized solution is found by a simple cooling of the physical temperature of the device. We find that the speed of convergence to the ground state can be sped up by a factor of $ N$ at a given error, where N is the boson number per site.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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