论文标题
协调的推理，全息神经网络和量子误差校正
Coordinated inference, Holographic neural networks, and quantum error correction
论文作者
论文摘要
正在引入协调的推理问题，以作为全息批量中位置问题神经网络表示的基础。有人认为，源自“囚犯和帽子”困境中的一种问题涉及在广告/CFT二重性中可以找到的某些非本地结构。该问题的神经网络解决方案引入了一种新方法，该方法可以灵活地识别ADS/CFT以外的全息二元性。证明神经网络在批量与边界之间的联系中具有重要作用，能够推断出能够解释散装中可观察物的预处理的足够信息，从而导致边界中的非本地前体前体操作员。
Coordinated inference problems are being introduced as a basis for a neural network representation of the locality problem in the holographic bulk. It is argued that a type of problem originating in the "prisoners and hats" dilemma involves certain non-local structures to be found in the AdS/CFT duality. The neural network solution to this problem introduces a new approach that can be flexible enough to identify holographic dualities beyond AdS/CFT. Neural networks are shown to have a significant role in the connection between the bulk and the boundary, being capable of inferring sufficient information capable of explaining the pre-arrangement of observables in the bulk that would lead to non-local precursor operators in the boundary.
