Ambiguous optical illusions have been a paradigmatic object of fascination,
research and inspiration in arts, psychology and video games. However, accurate
computational models of perception of ambiguous figures have been elusive. In
this paper, we design and train a deep neural network model to simulate the
human's perception of the Necker cube, an ambiguous drawing with several
alternating possible interpretations. Defining the weights of the neural
network connection using a quantum generator of truly random numbers, in
agreement with the emerging concepts of quantum artificial intelligence and
quantum cognition we reveal that the actual perceptual state of the Necker cube
is a qubit-like superposition of the two fundamental perceptual states
predicted by classical theories. Our results will find applications in video
games and virtual reality systems employed for training of astronauts and
operators of unmanned aerial vehicles. They will also be useful for researchers
working in the fields of machine learning and vision, psychology of perception
and quantum-mechanical models of human mind and decision-making.

通过设计和训练深度神经网络模型，使用真正随机数的量子生成器作为神经网络连接的权重来模拟人类对多义性图形的感知，我们揭示了让克尔立方体的实际感知状态是由经典理论预测的两种基本感知状态的叠加态，这个研究结果将在训练宇航员和无人飞行器操作员的视频游戏和虚拟现实系统中得到应用，对从事机器学习、视觉、感知心理学以及人类思维和决策的量子力学模型的研究人员也将非常有用。