Optimization of a precise integration method for seismic modeling based on graphic processing unit

General purpose graphic processing unit （GPU） calculation technology is gradually widely used in various fields. Its mode of single instruction, multiple threads is capable of seismic numerical simulation which has a huge quantity of data and calculation steps. In this study, we introduce a GPU-based parallel calculation method of a precise integration method （PIM） for seismic forward modeling. Compared with CPU single-core calculation, GPU parallel calculating perfectly keeps the features of PIM, which has small bandwidth, high accuracy and capability of modeling complex substructures, and GPU calculation brings high computational efficiency, which means that high-performing GPU parallel calculation can make seismic forward modeling closer to real seismic records.

Pulsar Candidate Classification Using a Computer Vision Method from a Combination of Convolution and Attention

Artificial intelligence methods are indispensable to identifying pulsars from large amounts of candidates.We develop a new pulsar identification system that utilizes the CoAtNet to score two-dimensional features of candidates,implements a multilayer perceptron to score one-dimensional features,and relies on logistic regression to judge the corresponding scores.In the data preprocessing stage,we perform two feature fusions separately,one for one-dimensional features and the other for two-dimensional features,which are used as inputs for the multilayer perceptron and the CoAtNet respectively.The newly developed system achieves 98.77%recall,1.07%false positive rate(FPR)and 98.85%accuracy in our GPPS test set.

Cleaning Radio Frequency Interference in Pulsar-Folded Data Based on the Conditional Random Fields with an Adaptive Prior

Radio astronomy observations are frequently impacted by radio frequency interference(RFI).We propose a novel method,named 2σCRF,for cleaning RFI in the folded data of pulsar observations,utilizing a Bayesian-based model called conditional random fields(CRFs).This algorithm minimizes the“energy”of every pixel given an initial label.The standard deviations(i.e.,rms values)of the folded pulsar data are utilized as pixels for all subintegrations and channels.Non-RFI data without obvious interference is treated as“background noise,”while RFI-affected data have different classes due to their exceptional rms values.This initial labeling can be automated and is adaptive to the actual data.The CRF algorithm optimizes the label category for each pixel of the image with the prior initial labels.We demonstrate the efficacy of the proposed method on pulsar folded data obtained from Five-hundred-meter Aperture Spherical radio Telescope observations.It can effectively recognize and tag various categories of RFIs,including broadband or narrowband,constant or instantaneous,and even weak RFIs that are unrecognizable in some pixels but picked out based on their neighborhoods.The results are comparable to those obtained via manual labeling but without the need for human intervention,saving time and effort.

A coarse-to-fine strategy for the registration of the multi-wavelength high-resolution solar images

The registration of multi-wavelength high-resolution solar images is an important task in the research of solar physics. This paper proposed a coarse-to-fine strategy to realize the accurate registration of high-resolution photospheric images and chromospheric images observed by the New Vacuum Solar Telescope(NVST) whose field-of-view is about 2′~ 3′, and the spatial resolution can reach 0.1′′after image reconstruction. In this strategy, the full-disk solar images with relatively lower resolution taken by other space-or ground-based telescopes are taken as transition images, and the Fourier-Merlin transform,Template matching and a local statistical information based algorithm are used in combination. After registration, the geometric transformation between multi-wavelength images of NVST are corrected at the level of sub-arcseconds, including the rotation, scaling and translation relations. Two sets of data observed in active regions(i.e., the NOAA 11982 and the NOAA 12673) are used to illustrate our method step by step.The result shows that the registration accuracy can reach less than 1′′. Moreover, this work also has facilitated the combination of high-resolution observations of NVST with the continuum, ultraviolet passbands and magnetic field observations of the Solar Dynamic Observation(SDO), which is highly beneficial to the multi-instrument joint measurement of solar activities.

Precise Positions of Triton in 2010–2014 based on Gaia-DR2

With unique orbital and physical characteristics,Triton is a very important target because it may contain information of the origin and evolution of the solar system.Besides space explorations,ground-based observations over long time also play a key role on research of Triton.High-precision positions of Triton obtained from ground telescopes are of great significance for studying its orbital evolution and the physical properties of Neptune.As a long-term observational target,Triton has been observed by the 1.56 m telescope of Shanghai Astronomical Observatory since 1996.In this paper,based on our AAPPDI software and with Gaia DR2 as the reference catalog,604 positions of Triton during 2010–2014 are calculated,with standard errors of 19–88 mas.A comparison between our results and the ephemeris(DE431+nep096)is also given.

Early-fusion based pulsar identification with smart under-sampling

The discovery of pulsars is of great significance in the field of physics and astronomy.As the astronomical equipment produces a large number of pulsar data,an algorithm for automatically identifying pulsars becomes urgent.We propose a deep learning framework for pulsar recognition.In response to the extreme imbalance between positive and negative examples and the hard negative sample issue presented in the High Time Resolution Universe Medlat Training Data,there are two coping strategies in our framework:the smart under-sampling and the improved loss function.We also apply the early-fusion strategy to integrate features obtained from different attributes before classification to improve the performance.To our best knowledge,this is the first study that integrates these strategies and techniques in pulsar recognition.The experiment results show that our framework outperforms previous works with respect to either the training time or F 1 score.We can not only speed up the training time by 10×compared with the state-ofthe-art work,but also get a competitive result in terms of F1 score.

Automated removal of stripe interference in full-disk solar images

The quality of full-disk solar Hα images is significantly degraded by stripe interference. In this paper, to improve the analysis of morphological evolution, a robust solution for stripe interference removal in a partial full-disk solar Hα image is proposed. The full-disk solar image is decomposed into a set of support value images on different scales by convolving the image with a sequence of multiscale support value filters, which are calculated from the mapped least-squares support vector machines （LS-SVMs）. To match the resolution of the support value images, a scale-adaptive LS-SVM regression model is used to remove stripe interference from the support value images. We have demonstrated the advantages of our method on solar Hα images taken in 2001-2002 at the Huairou Solar Observing Station. Our experimental results show that our method can remove the stripe interference well in solar Hα images and the restored image can be used in morphology researches.

A small electron beam ion trap/source facility for electron/neutral-ion collisional spectroscopy in astrophysical plasmas

Spectra are fundamental observation data used for astronomical research,but understanding them strongly depends on theoretical models with many fundamental parameters from theoretical calculations.Different models give different insights for understanding a specific object.Hence,laboratory benchmarks for these theoretical models become necessary.An electron beam ion trap is an ideal facility for spectroscopic benchmarks due to its similar conditions of electron density and temperature compared to astrophysical plasmas in stellar coronae,supernova remnants and so on.In this paper,we will describe the performance of a small electron beam ion trap/source facility installed at National Astronomical Observatories,Chinese Academy of Sciences.We present some preliminary experimental results on X-ray emission,ion production,the ionization process of trapped ions as well as the effects of charge exchange on the ionization.

关于编绘县级土地利用现状图的几个问题

本文根据制图实践经验，比较全面地论述了编绘县土地利用图的几个主要问题：比例尺和编绘底图、土地利用现状分类和图例设计、编图的过程和方法、县土地利用图的制图综合等．

大比例尺地形图缩编流程与方法

介绍了大比例尺地形图缩编的主要流程,研究了缩编方法的实际应用,并实现了房屋和植被自动化处理算法。

Accelerating fully resolved simulation of particle-laden flows on heterogeneous computer architectures

An efficient computing framework,namely PFlows,for fully resolved-direct numerical simulations of particle-laden flows was accelerated on NVIDIA General Processing Units(GPUs)and GPU-like accelerator(DCU)cards.The framework is featured as coupling the lattice Boltzmann method for fluid flow with the immersed boundary method for fluid-particle interaction,and the discrete element method for particle collision,using two fixed Eulerian meshes and one moved Lagrangian point mesh,respectively.All the parts are accelerated by a fine-grained parallelism technique using CUDA on GPUs,and further using HIP on DCU cards,i.e.,the calculation on each fluid grid,each immersed boundary point,each particle motion,and each pair-particle collision is responsible by one computer thread,respectively.Coalesced memory accesses to LBM distribution functions with the data layout of Structure of Arrays are used to maximize utilization of hardware bandwidth.Parallel reduction with shared memory for data of immersed boundary points is adopted for the sake of reducing access to global memory when integrate particle hydrodynamic force.MPI computing is further used for computing on heterogeneous architectures with multiple CPUs-GPUs/DCUs.The communications between adjacent processors are hidden by overlapping with calculations.Two benchmark cases were conducted for code validation,including a pure fluid flow and a particle-laden flow.The performances on a single accelerator show that a GPU V100 can achieve 7.1–11.1 times speed up,while a single DCU can achieve 5.6–8.8 times speed up compared to a single Xeon CPU chip(32 cores).The performances on multi-accelerators show that parallel efficiency is 0.5–0.8 for weak scaling and 0.68–0.9 for strong scaling on up to 64 DCU cards even for the dense flow(φ=20%).The peak performance reaches 179 giga lattice updates per second(GLUPS)on 256 DCU cards by using 1 billion grids and 1 million particles.At last,a large-scale simulation of a gas-solid flow with 1.6 billion grids and 1.6 million particles was conducted using only 32 DCU cards.This simulation shows that the present framework is prospective for simulations of large-scale particle-laden flows in the upcoming exascale computing era.

Investigating species boundaries in Colletotrichum

Colletotrichum is one of the most important plant pathogenic genera that is responsible for numerous diseases which can have a profound impact on the agricultural sector.Species delineation is difficult due to a lack of distinctive phenotypic vari-ation.Therefore,in this study three different genomic approaches based on phylogenetic,evolutionary and coalescent-based methods are applied to establish robust species boundaries.The reliability of five different DNA barcodes was also assessed to provide further insights into species delineation.The ITS region can resolve the placement of taxa up to the species complex level.The GAPDH and TUB2 markers are determined to be the most informative for most complexes.However,no single marker could discriminate between species in all complexes,therefore different molecular approaches based on multi-locus datasets are recommended.This is the first study to provide an estimated divergence time for all species complexes in Colle-totrichum.The estimated divergence time for species complexes ranged between 4.8 to 32.2 MYA.Based on the high level of congruent results obtained from the different molecular approaches,a new species complex,the Colletotrichum agaves complex is introduced.This complex consists of five taxa which are characterised by the presence of straight or slightly curved conidia with obtuse apices.This study shows that coalescent approaches and multi-locus phylogeny are crucial to establish species boundaries in Colletotrichum.The taxonomic placement of three singleton taxa Colletotrichum axonopodi,C.cariniferi and C.parallelophorum is revised.We accept 248 species and provide recommendations regarding species boundaries in the graminicola-caudatum complex.

Binary Logic State Transition Oriented Formal General Reliability Model

There were various conventional modeling techniques with varied semantics for system reliability assessment, such as fault trees(FT), Markov process(MP), and Petri nets. However, it is strenuous to construct and to maintain models utilizing these formalisms throughout the life cycle of system under development. This paper proposes a unified formal modeling language to build a general reliability model. The method eliminates the gap between the actual system and reliability model and shows details of the system clearly. Furthermore,the model could be transformed into FT and MP through specific rules defined by a formal language to assess system-level reliability.