Information Scrambling in Quantum Neural Networks

The quantum neural network is one of the promising applications for near-term noisy intermediate-scale quantum computers. A quantum neural network distills the information from the input wave function into the output qubits. In this Letter, we show that this process can also be viewed from the opposite direction: the quantum information in the output qubits is scrambled into the input. This observation motivates us to use the tripartite information—a quantity recently developed to characterize information scrambling—to diagnose the training dynamics of quantum neural networks. We empirically find strong correlation between the dynamical behavior of the tripartite information and the loss function in the training process, from which we identify that the training process has two stages for randomly initialized networks. In the early stage, the network performance improves rapidly and the tripartite information increases linearly with a universal slope, meaning that the neural network becomes less scrambled than the random unitary. In the latter stage, the network performance improves slowly while the tripartite information decreases. We present evidences that the network constructs local correlations in the early stage and learns large-scale structures in the latter stage. We believe this two-stage training dynamics is universal and is applicable to a wide range of problems. Our work builds bridges between two research subjects of quantum neural networks and information scrambling, which opens up a new perspective to understand quantum neural networks

Observing Schr\"odinger's Cat with Artificial Intelligence: Emergent Classicality from Information Bottleneck

We train a generative language model on the randomized local measurement data collected from Schr\"odinger's cat quantum state. We demonstrate that the classical reality emerges in the language model due to the information bottleneck: although our training data contains the full quantum information about Schr\"odinger's cat, a weak language model can only learn to capture the classical reality of the cat from the data. We identify the quantum-classical boundary in terms of both the size of the quantum system and the information processing power of the classical intelligent agent, which indicates that a stronger agent can realize more quantum nature in the environmental noise surrounding the quantum system. Our approach opens up a new avenue for using the big data generated on noisy intermediate-scale quantum (NISQ) devices to train generative models for representation learning of quantum operators, which might be a step toward our ultimate goal of creating an artificial intelligence quantum physicist.Comment: 17 pages, 9 figure

Dipolar effect in coherent spin mixing of two atoms in a single optical lattice site

We show that atomic dipolar effects are detectable in the system that recently demonstrated two-atom coherent spin dynamics within individual lattice sites of a Mott state. Based on a two-state approximation for the two-atom internal states and relying on a variational approach, we have estimated the spin dipolar effect. Despite the absolute weakness of the dipole-dipole interaction, it is shown that it leads to experimentally observable effects in the spin mixing dynamics.Comment: 4 pages, 3 color eps figures, to appear in Phys. Rev. Let

Regional Economic Vitality Based on Weighted Grey Relational Analysis

Abstract: The future development of cities has a great relationship with economic vitality. To determine the size of the economic vitality and its main influencing factors. This article takes some cities in China as examples. First, determine the main factors. Aiming at many factors, this paper starts from the perspective of population changes in different cities and changes in corporate vitality. After applying the rough set theory to objectively evaluate index weights, the main factors are screened out. Then, the weights of the corresponding evaluation indexes of each group of cities are calculated by a multiple linear regression to a weighted index system, and then the cities are ranked using the gray correlation analysis method. Finally, we get the ranking of the economic vitality level of different cities. Finally, suggestions are made based on the weighting factors of major factors and economic vitality