Coherent heteronuclear spin dynamics in an ultracold spin-1 mixture

We report the observation of coherent heteronuclear spin dynamics driven by inter-species spin-spin interaction in an ultracold spinor mixture, which manifests as periodical and well correlated spin oscillations between two atomic species. In particular, we investigate the magnetic field dependence of the oscillations and find a resonance behavior which depends on {\em both} the linear and quadratic Zeeman effects and the spin-dependent interaction. We also demonstrate a unique knob for controlling the spin dynamics in the spinor mixture with species-dependent vector light shifts. Our finds are in agreement with theoretical simulations without any fitting parameters.Comment: 13 pages including the supplementary materia

Molecular dynamics simulation of flow around a circular nano-cylinder

In this study, the wake flow around a circular nano-cylinder is numerically investigated with molecular dynamics simulation to reveal the micro/nano size effect on the wake flow. The cavitation occurring when Reynolds number (Re) > 101 can effectively influence the wake flow. The Strouhal number (St) of the wake flow increases with the Re at low Re, but steadily decreases with the Re after the cavitation appears. The dominant frequency of the lift force fluctuation can be higher than that of the velocity fluctuation, and be drowned in the chaotic fluctuating background of the Brownian forces when Re {\geq} 127. Also because of the strong influence of the Brownian forces, no dominant frequency of the drag force fluctuation can be observed. The Jz number, which is defined as the ratio between the mean free path {\lambda} of the fluid molecules and the equilibrium distance of potential energy {\sigma}, is newly introduced in order to consider the internal size effect of fluid. The St of the wake flow increases with the Jz until it falls to zero sharply when Jz {\approx} 1.7. It denotes the discontinuity of the fluid can eventually eliminate the vortex generation and shedding. Meanwhile, the St decreases with the Kn because of the intensification of the cavitation.Comment: 17 pages, 17 figures, 37 conference

Rural financial development, spatial spillover, and poverty reduction: evidence from China

Rural financial development is deemed essential for eliminating poverty. In China, successive governments have initiated a series of financial development plans to reduce poverty since the launch of economic reform in the late 1970s. However, there is a rising concern about whether financial development can reduce poverty in China. This study uses a panel dataset of 30 provinces (out of 31) in mainland China from 1997 to 2015 to examine the effect of rural financial development on poverty reduction. We employ a spatial panel model to investigate whether rural financial development has a positive spatial spillover effect. Moreover, we use the instrumental variable method to address the possible bidirectional causal effect between rural financial development and poverty reduction. Our study confirms that rural financial development does reduce poverty and simultaneously widen the urban-rural income gap. We further find that rural financial development has a positive spatial spillover effect on poverty alleviation and that the conventional panel model (e.g., fixed effects method) may underestimate the effect of rural financial development, as it ignores the spatial spillover effect

OrdinalCLIP: Learning Rank Prompts for Language-Guided Ordinal Regression

This paper presents a language-powered paradigm for ordinal regression. Existing methods usually treat each rank as a category and employ a set of weights to learn these concepts. These methods are easy to overfit and usually attain unsatisfactory performance as the learned concepts are mainly derived from the training set. Recent large pre-trained vision-language models like CLIP have shown impressive performance on various visual tasks. In this paper, we propose to learn the rank concepts from the rich semantic CLIP latent space. Specifically, we reformulate this task as an image-language matching problem with a contrastive objective, which regards labels as text and obtains a language prototype from a text encoder for each rank. While prompt engineering for CLIP is extremely time-consuming, we propose OrdinalCLIP, a differentiable prompting method for adapting CLIP for ordinal regression. OrdinalCLIP consists of learnable context tokens and learnable rank embeddings; The learnable rank embeddings are constructed by explicitly modeling numerical continuity, resulting in well-ordered, compact language prototypes in the CLIP space. Once learned, we can only save the language prototypes and discard the huge language model, resulting in zero additional computational overhead compared with the linear head counterpart. Experimental results show that our paradigm achieves competitive performance in general ordinal regression tasks, and gains improvements in few-shot and distribution shift settings for age estimation. The code is available at https://github.com/xk-huang/OrdinalCLIP.Comment: Accepted by NeurIPS2022. Code is available at https://github.com/xk-huang/OrdinalCLI