标题： 纠缠熵的对偶几何通过深度学习 显示英文标题

标题： Dual Geometry of Entanglement Entropy via Deep Learning

摘要： 对于给定的量子场论的纠缠熵，我们研究了如何通过应用 Ryu-Takayanagi 公式和深度学习方法来重构其对偶几何。在全息设定下，对偶几何的径向方向被识别为对偶量子场论的能量尺度。因此，全息对偶几何能够描述量子场论沿着重整群流的变化。有趣的是，我们展示了仅从纠缠熵数据重构出的几何可以给我们提供更多关于红外区域的其他物理性质的信息，比如热力学量。 显示英文摘要

摘要： For a given entanglement entropy of QFT, we investigate how to reconstruct its dual geometry by applying the Ryu-Takayanagi formula and the deep learning method. In the holographic setup, the radial direction of the dual geometry is identified with the energy scale of the dual QFT. Therefore, the holographic dual geometry can describe how the QFT changes along the RG flow. Intriguingly, we show that the reconstructed geometry only from the entanglement entropy data can give us more information about other physical properties like thermodynamic quantities in the IR region.