The Change of Relationship between Real Estate and Stock Markets in China

The real estate market and stock market, as two major investment channels in China, had experienced dramatically skyrocketing and fluctuations. Especially, after 2008 financial crisis, the price index of these two asset markets tended to be alternately soaring and declining. It seems there is a new principle or new relationship generating between the real estate and stock markets. This study employs VAR model and on the base of data from 2003 January to 2013 December to explore and discuss whether the relationships between the real estate market and stock market changed after financial crisis in 2008 emerged in China. The results show that there is no significant relationship existing between the real estate market and stock market during 2003 to 2008; while there is a significantly negative long-term relationship after the financial crisis in 2008

Gravitational-wave Emission from a Primordial Black Hole Inspiraling inside a Compact Star: a Novel Probe for Dense Matter Equation of State

Primordial black holes of planetary masses captured by compact stars are widely studied to constrain their composition fraction of dark matter. Such a capture may lead to an inspiral process and be detected through gravitational wave signals. In this Letter, we study the post-capture inspiral process by considering two different kinds of compact stars, i.e., strange stars and neutron stars. The dynamical equations are numerically solved and the gravitational wave emission is calculated. It is found that the Advanced LIGO can detect the inspiraling of a $10^{-5}$ solar mass primordial black hole at a distance of 10 kpc, while a Jovian-mass case can even be detected at megaparsecs. Promisingly, the next generation gravitational wave detectors can detect the cases of $10^{-5}$ solar mass primordial black holes up to $\sim1$ Mpc, and can detect Jovian-mass cases at several hundred megaparsecs. Moreover, the kilohertz gravitational wave signal shows significant differences for strange stars and neutron stars, potentially making it a novel probe to the dense matter equation of state.Comment: 7 figures, 15 pages, match the accepted version, accepted by ApJ

Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition

This paper does not attempt to design a state-of-the-art method for visual recognition but investigates a more efficient way to make use of convolutions to encode spatial features. By comparing the design principles of the recent convolutional neural networks ConvNets) and Vision Transformers, we propose to simplify the self-attention by leveraging a convolutional modulation operation. We show that such a simple approach can better take advantage of the large kernels (>=7x7) nested in convolutional layers. We build a family of hierarchical ConvNets using the proposed convolutional modulation, termed Conv2Former. Our network is simple and easy to follow. Experiments show that our Conv2Former outperforms existent popular ConvNets and vision Transformers, like Swin Transformer and ConvNeXt in all ImageNet classification, COCO object detection and ADE20k semantic segmentation