Complete characterization of states and processes that occur within quantum devices is crucial for understanding and testing their potential to outperform classical technologies for communications and computing. However, this task becomes unwieldy for large and complex quantum systems. Here we realize and experimentally demonstrate a method for complete characterization of a harmonic oscillator based on an artificial neural network known as the restricted Boltzmann machine. We apply the method to experimental balanced homodyne tomography and show it to allow full estimation of quantum states based on a smaller amount of experimental data. Although our experiment is in the optical domain, our method provides a way of exploring quantum resources in a broad class of physical systems, such as superconducting circuits, atomic and molecular ensembles, and optomechanical systems.
翻译:量子装置内发生的状态和过程的完整定性对于理解和测试其超常通信和计算古典技术的潜力至关重要。 但是,这项任务对于大型和复杂的量子系统来说变得不易操作。 在这里,我们发现并实验性地展示了一种基于被称为限制的波尔茨曼机器的人工神经网络的声波振荡器的全面定性方法。我们将这种方法应用于实验平衡的同子体摄影,并显示它能够根据较少的实验数据对量子状态进行全面估计。虽然我们的实验是在光学领域,但我们的方法提供了一种在广泛的物理系统中探索量子资源的方法,例如超导电路、原子和分子组合以及机能系统。