论文标题
使用贝叶斯绝症量子退火多个目标跟踪和过滤
Multiple Target Tracking and Filtering using Bayesian Diabatic Quantum Annealing
论文作者
论文摘要
在本文中，我们提出了一种混合量子/经典算法，以解决称为多重目标数据关联（MTDA）和跟踪问题的NP-硬化组合问题。我们使用绝绝载量子退火（DQA）来列举低能量或高概率，可行的分配，我们使用经典的计算机来查找贝叶斯预期的平均轨道估计，以求和这些作业。我们在一个简单的示例中演示了混合量子/经典方法。这可能是贝叶斯杂种量子型多重目标跟踪滤波器的首次演示。我们将DQA方法与绝热量子计算（AQC）方法进行了对比。我们给出了DQA的理论概述，并描述了在这种新型的绝绝植物方式中使用量子退火器的一些技术局限性。
In this paper, we present a hybrid quantum/classical algorithm to solve an NP-hard combinatorial problem called the multiple target data association (MTDA) and tracking problem. We use diabatic quantum annealing (DQA) to enumerate the low energy, or high probability, feasible assignments, and we use a classical computer to find the Bayesian expected mean track estimate by summing over these assignments. We demonstrate our hybrid quantum/classical approach on a simple example. This may be the first demonstration of a Bayesian hybrid quantum-classical multiple target tracking filter. We contrast our DQA method with the adiabatic quantum computing (AQC) approach to MTDA. We give a theoretical overview of DQA and characterize some of the technical limitations of using quantum annealers in this novel diabatic modality.
