Atmospheric Circulation of Brown Dwarfs and Jupiter and Saturn-like Planets: Zonal Jets, Long-term Variability, and QBO-type Oscillations

Brown dwarfs and directly imaged giant planets exhibit significant evidence for active atmospheric circulation, which induces a large-scale patchiness in the cloud structure that evolves significantly over time, as evidenced by infrared light curves and Doppler maps. These observations raise critical questions about the fundamental nature of the circulation, its time variability, and the overall relationship to the circulation on Jupiter and Saturn. Jupiter and Saturn themselves exhibit numerous robust zonal (east-west) jet streams at the cloud level; moreover, both planets exhibit long-term stratospheric oscillations involving perturbations of zonal wind and temperature that propagate downward over time on timescales of ~4 years (Jupiter) and ~15 years (Saturn). These oscillations, dubbed the Quasi Quadrennial Oscillation (QQO) for Jupiter and the Semi-Annual Oscillation (SAO) on Saturn, are thought to be analogous to the Quasi-Biennial Oscillation (QBO) on Earth, which is driven by upward propagation of equatorial waves from the troposphere. To investigate these issues, we here present global, three-dimensional, high-resolution numerical simulations of the flow in the stratified atmosphere--overlying the convective interior--of brown dwarfs and Jupiter-like planets. The effect of interior convection is parameterized by inducing small-scale, randomly varying perturbations in the radiative-convective boundary at the base of the model. In the simulations, the convective perturbations generate atmospheric waves and turbulence that interact with the rotation to produce numerous zonal jets. Moreover, the equatorial stratosphere exhibits stacked eastward and westward jets that migrate downward over time, exactly as occurs in the terrestrial QBO, Jovian QQO, and Saturnian SAO. This is the first demonstration of a QBO-like phenomenon in 3D numerical simulations of a giant planet.Comment: 27 pages, 15 figures, in press at ApJ; this is the revised (accepted) version, which includes a major new section providing detailed analysis of the types of wave modes present in the model, and characterizing the wave-mean-flow interactions by which they generate the QBO-like oscillation

Bootstrapping One-Loop Inflation Correlators with the Spectral Decomposition

Phenomenological studies of cosmological collider physics in recent years have identified many 1-loop inflation correlators as leading channels for discovering heavy new particles around or above the inflation scale. However, complete analytical results for these massive 1-loop correlators are currently unavailable. In this work, we embark on a program of bootstrapping inflation correlators with massive exchanges at 1-loop order, with the input of tree-level inflation correlators and the techniques of spectral decomposition in dS. As a first step, we present for the first time the complete and analytical results for a class of 4-point and 3-point inflation correlators mediated by massive scalar fields at the 1-loop order. Using the full result, we provide simple and reliable analytical approximations for the signals and the background in the squeezed limit. We also identify configurations of the scalar trispectrum where the oscillatory signal from the loop is dominant over the background.Comment: 65 page

Community detection based on structural balance in signed networks

In signed networks, some existing community detection methods treat negative connections as intercommunity links and positive ones as intracommunity links. However, it is important to recognize that negative links on real-world networks also play a key role in maintaining community stability. In this work, our aim is to identify communities that are not only densely connected but also harmonious or balanced in terms of the nature of their relationships. Such communities are more likely to be stable over time and less prone to conflicts. Consequently, we propose a motif-based method to identify communities by quantifying the importance of links in the local structural balance. The results in synthetic and real-world networks show that the proposed method has a higher performance in identifying the community. In addition, it demonstrates strong robustness, i.e., remains insensitive to the balance of the network, and accurately classifies communities in real-world networks.Comment: 16 pages, 6 figure

Phase subdivision of absolute coding grating in displacement measurement

AbstractA phase subdivision of absolute coding grating is proposed to improve the resolution and precision of displacement measurement. The used grating consists of multiple code channel grating of Gray code, and the basic code channel is high frequency Rochi grating. Fourier analysis method is adopted to extract the phase value of grating in decoding, and the wrapped phase distribution of basic code channel is obtained by Fourier transform, filtering, and inverse Fourier transform, then the unwrapped phase distribution could be recovered using the phase order information of Gray code. High resolution of phase subdivision can be achieved via linear fitting of phase distribution. Analysis of the basic principle and the subdivision of the phase to improve the resolution of displacement measurement have also been described in this paper. Experimental results show that the resolution and precision of absolute coding grating is enhanced greatly after phase subdivision and calibration

The distribution of long-chain n-alkan-2-ones in peat can be used to infer past changes in pH

Long-chain (C21-C33) n-alkan-2-ones are biomarkers ubiquitous in peat deposits. However, their paleoenvironmental significance lacks constraints. Here we evaluate the influence pH exerts on the occurrence of long-chain n-alkan-2-ones in Chinese peats. A comparison of the distribution in a collection (n= 65) of modern peat samples with different pH (pH values 4.4-8.6) from China demonstrates that their distribution is significantly different in acid compared to alkaline peat. This difference can be explained by the pH control on the conversion of n-alkan-2-one precursor compounds (n-alkanes and fatty acids). Transfer functions between pH and n-alkan-2-one ratios were established using linear and logarithmic regression models. We then applied these proxies to reconstruct variations of paleo-pH in the Dajiuhu peat sequence to identify the history of peatland acidification over the last 13 kyr. We find significant changes in paleo-pH during the deglaciation/early Holocene and relate these to times of dry climate in the region. The drought-induced peat acidification is supported by observations from modern drying events in the peatland. We propose that long-chain n-alkan-2-ones in peats have potential to trace paleo-pH changes across the deglaciation and Holocene, although further research from different peatlands and time periods is still needed

EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution

Recently, convolutional networks have achieved remarkable development in remote sensing image Super-Resoltuion (SR) by minimizing the regression objectives, e.g., MSE loss. However, despite achieving impressive performance, these methods often suffer from poor visual quality with over-smooth issues. Generative adversarial networks have the potential to infer intricate details, but they are easy to collapse, resulting in undesirable artifacts. To mitigate these issues, in this paper, we first introduce Diffusion Probabilistic Model (DPM) for efficient remote sensing image SR, dubbed EDiffSR. EDiffSR is easy to train and maintains the merits of DPM in generating perceptual-pleasant images. Specifically, different from previous works using heavy UNet for noise prediction, we develop an Efficient Activation Network (EANet) to achieve favorable noise prediction performance by simplified channel attention and simple gate operation, which dramatically reduces the computational budget. Moreover, to introduce more valuable prior knowledge into the proposed EDiffSR, a practical Conditional Prior Enhancement Module (CPEM) is developed to help extract an enriched condition. Unlike most DPM-based SR models that directly generate conditions by amplifying LR images, the proposed CPEM helps to retain more informative cues for accurate SR. Extensive experiments on four remote sensing datasets demonstrate that EDiffSR can restore visual-pleasant images on simulated and real-world remote sensing images, both quantitatively and qualitatively. The code of EDiffSR will be available at https://github.com/XY-boy/EDiffSRComment: Submitted to IEEE TGR

Minimizing the Makespan for Scheduling Problems with General Deterioration Effects

This paper investigates the scheduling problems with general deterioration models. By the deterioration models, the actual processing time functions of jobs depend not only on the scheduled position in the job sequence but also on the total weighted normal processing times of the jobs already processed. In this paper, the objective is to minimize the makespan. For the single-machine scheduling problems with general deterioration effects, we show that the considered problems are polynomially solvable. For the flow shop scheduling problems with general deterioration effects, we also show that the problems can be optimally solved in polynomial time under the proposed conditions