Formation of hot subdwarf B stars with neutron star components

Binary population synthesis predicts the existence of subdwarf B stars (sdBs) with neutron star (NS) or black hole (BH) companions. We systematically investigate the formation of sdB+NS binaries from binary evolution and aim to obtain some clues for a search for such systems. We started from a series of MS+NS systems and determined the parameter spaces for producing sdB+NS binaries from the stable Roche-lobe overflow (RLOF) channel and from the common envelope (CE) ejection channel. Various NS accretion efficiencies and NS masses were examined to investigate the effects they have. We show the characteristics of the produced sdB+NS systems, such as the mass of components, orbital period, the semi-amplitude of the radial velocity (K), and the spin of the NS component. In the stable RLOF channel, the orbital period of sdB+NS binaries produced in this way ranges from several days to more than 1000 days and moves toward the short-period (~ hr) side with increasing initial MS mass. the sdB+NS systems that result from CE ejection have very short orbital periods and then high values of K (up to 800km s^-1). Such systems are born in very young populations (younger than 0.3 Gyr) and are potential gravitational wave sources that might be resolved by the Laser Interferometer Space Antenna (LISA) in the future. Gravitational wave radiation may again bring them into contact on a timescale of only ~Myr. As a consequence, they are rare and hard to discover. The pulsar signal is likely a feature of sdB+NS systems caused by stable RLOF, and some NS components in sdB binaries may be millisecond pulsars.Comment: 12 pages, 6 figures, 4 tables. Accepted for publication in A&

H→e+e−H \rightarrow e^+ e^- at CEPC: ISR effect with MadGraph

The Circular Electron Positron Collider (CEPC) is a future Higgs factory proposed by the Chinese high energy physics community. It will operate at a center-of-mass energy of 240-250 GeV. The CEPC will accumulate an integrated luminosity of 5 ab$^{\rm{-1}}$ in ten years' operation. With GEANT4-based full simulation samples for CEPC, Higgs boson decaying into electron pair is studied at the CEPC. The upper limit of ${\cal B}(H \rightarrow e^+ e^-)$ could reach 0.024\% at 95\% confidence level. The signal process is generated by MadGraph, with Initial State Radiation (ISR) implemented, as a first step to adjust MadGraph for a electron positron Collider.Comment: Accepted version by J.P.

Effects of fan volute structure on airflow characteristics in rice combine harvesters

Aim of study: Selecting a proper fan for the rice combine harvesters to get a good cleaning performance when harvesting high yield rice. Area of study: Jiangsu Province, China.Material and methods: Three potential multi-duct fans were designed, and the computational fluid dynamics and hot wire anemometer technology were utilized to learn the airflow and pressure variation inside the fan with perforated plates at the outlet ducts as cleaning loads. Then, the fan with the best performance was selected and a multi-duct cleaning test-bed was developed. The variation of the corresponding airflow velocity in the cleaning system was analyzed and the ideal airflow velocity in different section of the sieve was clarified. Finally, a field experiment was carried out.Main results: For a rice combine harvester with a feed rate of 7 kg/s (material other than grain + grain), the requested airflow rates inside the cleaning shoe was about 3.0 m3/s. The ideal airflow velocity in different section of the cleaning shoe was 8-9 m/s at upper duct, 4-6 m/s at the middle section, and 3-4 m/s at the tail section; large improvement in cleaning performance was achieved with the designed fan.Research highlights: The airflow velocity decreased as the cleaning loads at the duct increased. The fan with the averaged airflow velocity ≥7 m/s at the upper duct under different cleaning loads, and the airflow velocity at the lowest duct ≥ 9 m/s, is favorable for forming a blowing airflow in the tail sieve and is good for grain stratification

Deconfinement Phase Transition in an Expanding Quark system in Relaxation Time Approximation

We investigated the effects of nonequilibrium and collision terms on the deconfinement phase transition of an expanding quark system in Friedberg-Lee model in relaxation time approximation. By calculating the effective quark potential, the critical temperature of the phase transition is dominated by the mean field, while the collisions among quarks and mesons change the time structure of the phase transition significantly.Comment: 7 pages, 7 figure

DeepInteraction: 3D Object Detection via Modality Interaction

Existing top-performance 3D object detectors typically rely on the multi-modal fusion strategy. This design is however fundamentally restricted due to overlooking the modality-specific useful information and finally hampering the model performance. To address this limitation, in this work we introduce a novel modality interaction strategy where individual per-modality representations are learned and maintained throughout for enabling their unique characteristics to be exploited during object detection. To realize this proposed strategy, we design a DeepInteraction architecture characterized by a multi-modal representational interaction encoder and a multi-modal predictive interaction decoder. Experiments on the large-scale nuScenes dataset show that our proposed method surpasses all prior arts often by a large margin. Crucially, our method is ranked at the first position at the highly competitive nuScenes object detection leaderboard.Comment: To appear at NeurIPS 2022. 16 pages, 7 figur

UMIFormer: Mining the Correlations between Similar Tokens for Multi-View 3D Reconstruction

In recent years, many video tasks have achieved breakthroughs by utilizing the vision transformer and establishing spatial-temporal decoupling for feature extraction. Although multi-view 3D reconstruction also faces multiple images as input, it cannot immediately inherit their success due to completely ambiguous associations between unstructured views. There is not usable prior relationship, which is similar to the temporally-coherence property in a video. To solve this problem, we propose a novel transformer network for Unstructured Multiple Images (UMIFormer). It exploits transformer blocks for decoupled intra-view encoding and designed blocks for token rectification that mine the correlation between similar tokens from different views to achieve decoupled inter-view encoding. Afterward, all tokens acquired from various branches are compressed into a fixed-size compact representation while preserving rich information for reconstruction by leveraging the similarities between tokens. We empirically demonstrate on ShapeNet and confirm that our decoupled learning method is adaptable for unstructured multiple images. Meanwhile, the experiments also verify our model outperforms existing SOTA methods by a large margin. Code will be available at https://github.com/GaryZhu1996/UMIFormer.Comment: Accepted by ICCV 202