Quantum-Fluctuation-Driven Coherent Spin Dynamics in Small Condensates

We have studied quantum spin dynamics of small condensates of cold sodium atoms. For a condensate initially prepared in a mean field ground state, we show that coherent spin dynamics are {\em purely} driven by quantum fluctuations of collective spin coordinates and can be tuned by quadratic Zeeman coupling and magnetization. These dynamics in small condensates can be probed in a high-finesse optical cavity where temporal behaviors of excitation spectra of a coupled condensate-photon system reveal the time evolution of populations of atoms at different hyperfine spin states.Comment: 4 pages, 3 figure

Resonance Scattering in Optical Lattices and Molecules: Interband versus Intraband Effects

We study the low-energy two-body scattering in optical lattices with all higher-band effects included in an effective potential, using a renormalization group approach. As the potential depth reaches a certain value, a resonance of low energy scattering occurs even when the negative s-wave scattering length $(a_s)$ is much shorter than the lattice constant. These resonances can be mainly driven either by interband or intraband effects or by both, depending on the magnitude of $a_s$. Furthermore the low-energy scattering matrix in optical lattices has a much stronger energy-dependence than that in free space. We also investigate the momentum distribution for molecules when released from optical lattices.Comment: 4 figures, version accepted for publication in PR

Urban Renovation and the Simulation Evaluation of Urban Climate Change in Residential and Commercial Districts: A Case of Xi’an, China

The urban heat island (UHI) effect has drawn attention to monitor and evaluate outdoor thermal comfort in cities worldwide. The rapid, large-scale urban development in China is producing urban climate change in large cities, creating other urban environmental problems such as haze weather, which is one of the most important environmental issues in China. High-density building development will change the urban typology, leading to changes in the urban sky view factor (SVF) and microclimate. Since the energy consumed by indoor heating and air conditioning is highly related to the outdoor mean air temperature, a high SVF should be considered in the planning period. In this chapter, the typical urban planning styles in China are evaluated. Four microscaled residential and three commercial districts in Xi’an city are selected, to represent the typical urban typology of residential and commercial districts that developed during different historical periods and used the urban simulation system scSTREAM to evaluate the impact of urban renovation types on urban climate change

MaskDiffusion: Boosting Text-to-Image Consistency with Conditional Mask

Recent advancements in diffusion models have showcased their impressive capacity to generate visually striking images. Nevertheless, ensuring a close match between the generated image and the given prompt remains a persistent challenge. In this work, we identify that a crucial factor leading to the text-image mismatch issue is the inadequate cross-modality relation learning between the prompt and the output image. To better align the prompt and image content, we advance the cross-attention with an adaptive mask, which is conditioned on the attention maps and the prompt embeddings, to dynamically adjust the contribution of each text token to the image features. This mechanism explicitly diminishes the ambiguity in semantic information embedding from the text encoder, leading to a boost of text-to-image consistency in the synthesized images. Our method, termed MaskDiffusion, is training-free and hot-pluggable for popular pre-trained diffusion models. When applied to the latent diffusion models, our MaskDiffusion can significantly improve the text-to-image consistency with negligible computation overhead compared to the original diffusion models

Pressure induced superconductivity bordering a charge-density-wave state in NbTe4 with strong spinorbit coupling

Transition-metal chalcogenides host various phases of matter, such as charge-density wave (CDW), superconductors, and topological insulators or semimetals. Superconductivity and its competition with CDW in low-dimensional compounds have attracted much interest and stimulated considerable research. Here we report pressure induced superconductivity in a strong spin-orbit (SO) coupled quasi-one-dimensional (1D) transition-metal chalcogenide NbTe$_4$, which is a CDW material under ambient pressure. With increasing pressure, the CDW transition temperature is gradually suppressed, and superconducting transition, which is fingerprinted by a steep resistivity drop, emerges at pressures above 12.4 GPa. Under pressure $p$ = 69 GPa, zero resistance is detected with a transition temperature $T_c$ = 2.2 K and an upper critical field $H_{c2}$= 2 T. We also find large magnetoresistance (MR) up to 102\% at low temperatures, which is a distinct feature differentiating NbTe$_4$ from other conventional CDW materials.Comment: https://rdcu.be/LX8

DPF: Learning Dense Prediction Fields with Weak Supervision

Nowadays, many visual scene understanding problems are addressed by dense prediction networks. But pixel-wise dense annotations are very expensive (e.g., for scene parsing) or impossible (e.g., for intrinsic image decomposition), motivating us to leverage cheap point-level weak supervision. However, existing pointly-supervised methods still use the same architecture designed for full supervision. In stark contrast to them, we propose a new paradigm that makes predictions for point coordinate queries, as inspired by the recent success of implicit representations, like distance or radiance fields. As such, the method is named as dense prediction fields (DPFs). DPFs generate expressive intermediate features for continuous sub-pixel locations, thus allowing outputs of an arbitrary resolution. DPFs are naturally compatible with point-level supervision. We showcase the effectiveness of DPFs using two substantially different tasks: high-level semantic parsing and low-level intrinsic image decomposition. In these two cases, supervision comes in the form of single-point semantic category and two-point relative reflectance, respectively. As benchmarked by three large-scale public datasets PASCALContext, ADE20K and IIW, DPFs set new state-of-the-art performance on all of them with significant margins. Code can be accessed at https://github.com/cxx226/DPF

Effect of Mn Addition and Heat Treatment on the Corrosion Behaviour of Mg–Ag–Mn Alloy

The high corrosion sensitivity and the potential bio-toxicity of Mg-Ag alloys limit their wide applications for the production of implanted devices. In the present work, Mn is added into the Mg-Ag alloy to optimize its corrosion behaviour. The corrosion behaviour of Mg-Ag-Mn alloys is investigated with the underlying microstructural factors examined. The Mg-Ag alloy with 2 wt. % Mn exhibits the highest corrosion resistance after post-casting heat treatment at 440 ⁰C. The addition of Mn results in α-Mn phase with the incorporation of Fe, which suppresses the cathodic activity of impurity Fe. Further, heat treatment of the cast alloys homogenizes the distribution of Ag and promotes the precipitation of α-Mn phase. The former removes Ag segregations as potential cathodes; the latter promotes a more uniform distribution of cathodes and, therefore, prevents localized corrosion.<br/