论文标题
$β$ - 变量自动编码器作为纠缠分类器
$β$-Variational Autoencoder as an Entanglement Classifier
论文作者
论文摘要
我们专注于使用类似于$β$ - 变量自动编码器（$β$ -VAE）的体系结构来区分量子状态是否基于测量值将量子状态纠缠或可分离。我们将数据分为两组：局部和相关的测量集。使用潜在空间，这是数据的低维表示，我们表明将自己限制在一组本地数据中，不可能区分纠缠和可分离状态。同时，当考虑相关和局部测量值时，在潜在空间的结构中获得了超过80％的精度。
We focus on using an architecture similar to the $β$-Variational Autoencoder ($β$-VAE) to discriminate if a quantum state is entangled or separable based on measurements. We split the data into two sets, the set of local and correlated measurements. Using the latent space, which is a low dimensional representation of the data, we show that restricting ourselves to the set of local data it is not possible to distinguish between entangled and separable states. Meanwhile, when considering both correlated and local measurements, an accuracy of over 80% is attained in the structure of the latent space.
