arXiv subjects

Li Feng

Publications and source records attributed to Li Feng.

At least 91 records · Page 5Linked to original sources

arXiv2022

The Large High Altitude Air Shower Observatory (LHAASO) Science Book (2021 Edition)

Since the science white paper of the Large High Altitude Air Shower Observatory (LHAASO) published on arXiv in 2019 [e-Print: 1905.02773 (astro-ph.HE)], LHAASO has completed the transition from a project to an operational gamma-ray astronomical observatory LHAASO is a new generation multi-component facility located in Daocheng, Sichuan province of China, at an altitude of 4410 meters. It aims at measuring with unprecedented sensitivity the spectrum, composition, and anisotropy of cosmic rays in the energy range between 10$^{12}$ and 10$^{18}$~eV, and acting simultaneously as a wide aperture (one stereoradiant) continuously operating gamma-ray telescope in the energy range between 10$^{11}$ and $10^{15}$~eV with the designed sensitivity of 1.3\% of the Crab Unit (CU) above 100 TeV. LHAASO's capability of measuring simultaneously different shower components (electrons, muons, and Cherenkov/fluorescence light), will allow it to investigate the origin, acceleration, and propagation of CR through measurement of the energy spectrum, elemental composition, and anisotropy with unprecedented resolution. The remarkable sensitivity of LHAASO will play a key role in CR physics and gamma-ray astronomy for a general and comprehensive exploration of the high energy universe and will allow important studies of fundamental physics (such as indirect dark matter search, Lorentz invariance violation, quantum gravity) and solar and heliospheric physics. The LHAASO Collaboration organized an editorial working group and finished all editorial work of this science book, to summarize the instrumental features and outline the prospects of scientific researches with the LHAASO experiment.

astro-ph.HE↗

arXiv2022

Three-dimensional analyses of an aspherical coronal mass ejection and its driven shock

Context. Observations reveal that shocks can be driven by fast coronal mass ejections (CMEs) and play essential roles in particle accelerations. A critical ratio, $δ$, derived from a shock standoff distance normalized by the radius of curvature (ROC) of a CME, allows us to estimate shock and ambient coronal parameters. However, true ROCs of CMEs are difficult to measure due to observed projection effects. Aims. We investigate the formation mechanism of a shock driven by an aspherical CME without evident lateral expansion. Through three-dimensional (3D) reconstructions without a priori assumptions of the object morphology, we estimate two principal ROCs of the CME surface and demonstrate how the difference between two principal ROCs of the CME affects the estimate of the coronal physical parameters. Methods. The CME was observed by the Sun Earth Connection Coronal and Heliospheric Investigation (SECCHI) instruments and the Large Angle and Spectrometric Coronagraph (LASCO). We used the mask-fitting method to obtain the irregular 3D shape of the CME and reconstructed the shock surface using the bow-shock model. Through smoothings with fifth-order polynomial functions and Monte Carlo simulations, we calculated the ROCs at the CME nose. Results. We find that (1) the maximal ROC is 2-4 times the minimal ROC of the CME. A significant difference between the CME ROCs implies that the assumption of one ROC of an aspherical CME could cause over-/under- estimations of the shock and coronal parameters. (2) The shock nose obeys the bow-shock formation mechanism, considering the constant standoff distance and the similar speed between the shock and CME around the nose. (3) With a more precise $δ$ calculated via 3D ROCs in space, we derive corona parameters at high latitudes of about -50$^{\circ}$, including the Alfv{é}n speed and the coronal magnetic field strength.

astro-ph.SR↗

arXiv2022

Observational Signatures of Tearing Instability in the Current Sheet of a Solar Flare

Magnetic reconnection is a fundamental physical process converting magnetic energy into not only plasma energy but also particle energy in various astrophysical phenomena. In this letter, we show a unique dataset of a solar flare where various plasmoids were formed by a continually stretched current sheet. EUV images captured reconnection inflows, outflows, and particularly the recurring plasma blobs (plasmoids). X-ray images reveal nonthermal emission sources at the lower end of the current sheet, presumably as large plasmoids with a sufficiently amount of energetic electrons trapped in. In the radio domain, an upward slowly drifting pulsation structure, followed by a rare pair of oppositely drifting structures, was observed. These structures are supposed to map the evolution of the primary and the secondary plasmoids formed in the current sheet. Our results on plasmoids at different locations and scales shed important light on the dynamics, plasma heating, particle acceleration, and transport processes in the turbulent current sheet and provide observational evidence for the cascading magnetic reconnection process.

astro-ph.SR↗

arXiv2021

Learning Oculomotor Behaviors from Scanpath

Identifying oculomotor behaviors relevant for eye-tracking applications is a critical but often challenging task. Aiming to automatically learn and extract knowledge from existing eye-tracking data, we develop a novel method that creates rich representations of oculomotor scanpaths to facilitate the learning of downstream tasks. The proposed stimulus-agnostic Oculomotor Behavior Framework (OBF) model learns human oculomotor behaviors from unsupervised and semi-supervised tasks, including reconstruction, predictive coding, fixation identification, and contrastive learning tasks. The resultant pre-trained OBF model can be used in a variety of applications. Our pre-trained model outperforms baseline approaches and traditional scanpath methods in autism spectrum disorder and viewed-stimulus classification tasks. Ablation experiments further show our proposed method could achieve even better results with larger model sizes and more diverse eye-tracking training datasets, supporting the model's potential for future eye-tracking applications. Open source code: http://github.com/BeibinLi/OBF.

cs.CV↗

arXiv2021

Quasi-Periodic Pulsations Detected in Ly$α$ and Nonthermal Emissions During Solar Flares

We report quasi-periodic pulsations (QPPs) with double periods during three solar flares (viz. SOL2011-Feb-15T01:44, SOL2011-Sep-25T04:31, SOL2012-May-17T01:25). The flare QPPs were observed from light curves in Ly$α$, hard X-ray (HXR) and microwave emissions, with the Ly$α$ emission recorded by the Geostationary Operational Environmental Satellite, the HXR emission recorded by the Reuven Ramaty High-Energy Solar Spectroscopic Imager and the Fermi Gamma-ray Burst Monitor, and the microwave emission recorded by the Nobeyama Radio Polarimeters and Radioheliograph. By using the Markov chain Monte Carlo (MCMC) method, QPPs with double periods of about two minutes and one minute were first found in the Ly$α$ emission. Then using the same method, a QPP with nearly the same period of about two minutes was also found in HXR and microwave emissions. Considering the possible common origin (nonthermal electrons) between Ly$α$ and HXR/microwave emission, we suggest that the two-minute QPP results from the periodic acceleration of nonthermal electrons during magnetic reconnections. The ratio between the double periods in the Ly$α$ emission was found to be close to two, which is consistent with the theoretical expectation between the fundamental and harmonic modes. However, we cannot rule out other possible driving mechanisms for the one-minute QPPs in HXR/microwave emissions due to their relatively large deviations.

astro-ph.SR↗

arXiv2021

Analysis of type II and type III radio bursts associated with SEPs from non-interacting/interacting radio-loud CMEs

We analyze radio bursts observed in events with interacting/non-interacting CMEs that produced major SEPs (Ip $>$ 10 MeV) fromApril 1997 to December 2014.We compare properties of meter (m), deca-hectometer (DH) type II as well as DH type III bursts, and time lags for interacting-CME-associated (IC) events and non-interacting-CME-associated (NIC) events. About 70\% of radio emissions were observed in events of both types from meters to kilometers. We found high correlations between the drift rates and mid-frequencies of type II radio bursts calculated as the mean geometric between their starting and ending frequencies for both NIC and IC-associated events (Correlation coefficient \textit{R}$^{2}$ = 0.98, power-law index $\varepsilon$ = 1.68 $\pm $ 0.16 and \textit{R}$^{2}$ = 0.93, $\varepsilon$ = 1.64 $\pm $ 0.19 respectively).We also found a correlation between the frequency drift rates of DH type II bursts and space speeds of CMEs in NIC-associated events. The absence of such correlation for IC-associated events confirms that the shock speeds changed in CME--CME interactions. For the events with western source locations, the mean peak intensity of SEPs in IC-associated events is four times larger than that in NIC-associated SEP events. From the mean time lags between the start times of SEP events and the start of m, DH type II, and DH type III radio bursts, we inferred that particle enhancements in NIC-associated SEP events occurred earlier than in IC-associated SEP events. The difference between NIC events and IC events in the mean values of parameters of type II and type III bursts is statistically insignificant.

astro-ph.SR↗

arXiv2021

Interaction Detection Between Vehicles and Vulnerable Road Users: A Deep Generative Approach with Attention

Intersections where vehicles are permitted to turn and interact with vulnerable road users (VRUs) like pedestrians and cyclists are among some of the most challenging locations for automated and accurate recognition of road users' behavior. In this paper, we propose a deep conditional generative model for interaction detection at such locations. It aims to automatically analyze massive video data about the continuity of road users' behavior. This task is essential for many intelligent transportation systems such as traffic safety control and self-driving cars that depend on the understanding of road users' locomotion. A Conditional Variational Auto-Encoder based model with Gaussian latent variables is trained to encode road users' behavior and perform probabilistic and diverse predictions of interactions. The model takes as input the information of road users' type, position and motion automatically extracted by a deep learning object detector and optical flow from videos, and generates frame-wise probabilities that represent the dynamics of interactions between a turning vehicle and any VRUs involved. The model's efficacy was validated by testing on real--world datasets acquired from two different intersections. It achieved an F1-score above 0.96 at a right--turn intersection in Germany and 0.89 at a left--turn intersection in Japan, both with very busy traffic flows.

cs.CV↗

arXiv2021

On Lambda Function and a Quantification of Torhorst Theorem

To any compact $K\subset\hat{\mathbb{C}}$ we associate a map $λ_K: \hat{\mathbb{C}}\rightarrow\mathbb{N}\cup\{\infty\}$ -- the lambda function of $K$ -- such that a planar continuum $K$ is locally connected if and only if $Λ_K(x)\equiv0$. We establish basic methods of determining the lambda function $λ_K$ for specific compacta $K\subset\hat{\mathbb{C}}$, including a gluing lemma for lambda functions and some inequalities. One of these inequalities comes from an interplay between the topological difficulty of a planar compactum $K$ and that of a sub-compactum $L\subset K$, lying on the boundary of a component of $\hat{\mathbb{C}}\setminus K$. It generalizes and quantifies the result of Torhorst Theorem, a fundamental result from plane topology. We also find three conditions under which this inequality is actually an equality. Under one of these conditions, this equality provides a quantitative version for Whyburn's Theorem, which is a partial converse to Torhorst Theorem.

math.GN↗

arXiv2021

Few-Shot Meta-Learning on Point Cloud for Semantic Segmentation

The promotion of construction robots can solve the problem of human resource shortage and improve the quality of decoration. To help the construction robots obtain environmental information, we need to use 3D point cloud, which is widely used in robotics, autonomous driving, and so on. With a good understanding of environmental information, construction robots can work better. However, the dynamic changes of 3D point cloud data may bring difficulties for construction robots to understand environmental information, such as when construction robots renovate houses. The paper proposes a semantic segmentation method for point cloud based on meta-learning. The method includes a basic learning module and a meta-learning module. The basic learning module is responsible for learning data features and evaluating the model, while the meta-learning module is responsible for updating the parameters of the model and improving the model generalization ability. In our work, we pioneered the method of producing datasets for meta-learning in 3D scenes, as well as demonstrated that the Model-Agnostic Meta-Learning (MAML) algorithm can be applied to process 3D point cloud data. At the same time, experiments show that our method can allow the model to be quickly applied to new environments with a few samples. Our method has important applications.

cs.RO↗

arXiv2021

Population of Bright Plume Threads in Solar Polar Coronal Holes

Coronal holes are well accepted to be source regions of the fast solar wind. As one of the common structures in coronal holes, coronal plumes might contribute to the origin of the nascent solar wind. To estimate the contribution of coronal plumes to the nascent solar wind, we make the first attempt to estimate their populations in solar polar coronal holes. By comparing the observations viewed from two different angles taken by the twin satellites of STEREO and the results of Monte Carlo simulations, we estimate about 16--27 plumes rooted in an area of $4\times10^4$ arcsec$^2$ of the polar coronal holes near the solar minimum, which occupy about 2--3.4% of the area. Based on these values, the contribution of coronal plumes to the nascent solar wind has also been discussed. A further investigation indicates that more precise number of coronal plumes can be worked out with observations from three or more viewing angles.

astro-ph.SR↗

arXiv2020

Methodology for In-flight Flat-field Calibration of the Lyman-alpha Solar Telescope (LST)

Flat-field reflects the non-uniformity of the photometric response at the focal plane of an instrument, which uses digital image sensors, such as Charge Coupled Device (CCD) and Complementary Metal-Oxide-Semiconductor (CMOS). This non-uniformity must corrected before being used for scientific research. In this paper, we assess various candidate methods via simulation using available data so as to figure the in-flight flat-field calibration methodology for the Lyman-alpha Solar Telescope (LST). LST is one of the payloads for the Advanced Space-based Solar Observatory (ASO-S) mission and consists of three instruments: a White-light Solar Telescope (WST), a Solar Disk Imager (SDI) and a dual-waveband Solar Corona Imager (SCI). In our simulations, data from the Helioseismic and Magnetic Imager (HMI) and Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) mission are used. Our results show that the normal KLL method is appropriate for in-flight flat-field calibration of WST and implementing a transmissive diffuser is applicable for SCI. For the in-flight flat-field calibration of SDI, we recommend the KLL method with off-pointing images with defocused resolution of around 18", and use the local correlation tracking (LCT) algorithm instead of limb-fitting to determine the relative dis-placements between different images.

astro-ph.SR↗

arXiv2020

Three-Dimensional Reconstructions of Coronal Wave Surfaces Using a New Mask-Fitting Method

Coronal waves are large-scale disturbances often driven by coronal mass ejections (CMEs). We investigate a spectacular wave event on 7 March 2012, which is associated with an X5.4 flare (SOL2012-03-07). By using a running center-median (RCM) filtering method for the detection of temporal variations in extreme ultraviolet (EUV) images, we enhance the EUV disturbance observed by the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) and the Sun Watcher using Active Pixel System detector and Image Processing (SWAP) onboard the PRoject for Onboard Autonomy 2 (PROBA2). In coronagraph images, a halo front is observed to be the upper counterpart of the EUV disturbance. Based on the EUV and coronagraph images observed from three different perspectives, we have made three-dimensional (3D) reconstructions of the wave surfaces using a new mask-fitting method. The reconstructions are compared with those obtained from forward-fitting methods. We show that the mask fitting method can reflect the inhomogeneous coronal medium by capturing the concave shape of the shock wave front. Subsequently, we trace the developing concave structure and derive the deprojected wave kinematics. The speed of the 3D-wave nose increases from a low value below a few hundred $\mathrm{km\,s^{-1}}$ to a maximum value of about 3800 $\mathrm{km\,s^{-1}}$, and then slowly decreases afterwards. The concave structure starts to decelerate earlier and has significantly lower speeds than those of the wave nose. We also find that the 3D-wave in the extended corona has a much higher speed than the speed of EUV disturbances across the solar disk.

astro-ph.SR↗

arXiv2020

Extensive Study of a Coronal Mass Ejection with UV and WL coronagraphs: the need for multi-wavelength observations

Coronal Mass Ejections (CMEs) often show different features in different band-passes. By combining data in white-light (WL) and ultraviolet (UV) bands, we have applied different techniques to derive plasma temperatures, electron density, internal radial speed, etc, within a fast CME. They serve as extensive tests of the diagnostic capabilities, developed for the observations provided by future multi-channel coronagraphs (such as Solar Orbiter/Metis, ASO-S/LST, PROBA-3/ASPIICS). The involved data include WL images acquired by SOHO/LASCO coronagraphs, and intensities measured by SOHO/UVCS at 2.45 R$_{\odot}$ in the UV (H I Ly$α$ and O VI 1032 {AA} lines) and WL channels. Data from the UVCS WL channel have been employed for the first time to measure the CME position angle with polarization-ratio technique. Plasma electron and effective temperatures of the CME core and void are estimated by combining UV and WL data. Due to the CME expansion and the possible existence of prominence segments, the transit of the CME core results in decreases of the electron temperature down to $10^{5}$ K. The front is observed as a significant dimming in the Ly$α$ intensity, associated with a line broadening due to plasma heating and flows along the line-of-sight. The 2D distribution of plasma speeds within the CME body is reconstructed from LASCO images and employed to constrain the Doppler dimming of Ly$α$ line, and simulate future CME observations by Metis and LST.

astro-ph.SR↗

arXiv2020

Spatiotemporal Flexible Sparse Reconstruction for Rapid Dynamic Contrast-enhanced MRI

Dynamic Contrast-enhanced magnetic resonance imaging (DCE-MRI) is a tissue perfusion imaging technique. Some versatile free-breathing DCE-MRI techniques combining compressed sensing (CS) and parallel imaging with golden-angle radial sampling have been developed to improve motion robustness with high spatial and temporal resolution. These methods have demonstrated good diagnostic performance in clinical setting, but the reconstruction quality will degrade at high acceleration rates and overall reconstruction time remains long. In this paper, we proposed a new parallel CS reconstruction model for DCE-MRI that enforces flexible weighted sparse constraint along both spatial and temporal dimensions. Weights were introduced to flexibly adjust the importance of time and space sparsity, and we derived a fast thresholding algorithm which was proven to be simple and efficient for solving the proposed reconstruction model. Results on in vivo liver DCE datasets show that the proposed method outperforms the state-of-the-art methods in terms of visual image quality assessment and reconstruction speed without introducing significant temporal blurring.

physics.med-ph↗

arXiv2020

A Fast Radio Burst discovered in FAST drift scan survey

We report the discovery of a highly dispersed fast radio burst, FRB~181123, from an analysis of $\sim$1500~hr of drift-scan survey data taken using the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The pulse has three distinct emission components, which vary with frequency across our 1.0--1.5~GHz observing band. We measure the peak flux density to be $>0.065$~Jy and the corresponding fluence $>0.2$~Jy~ms. Based on the observed dispersion measure of 1812~cm$^{-3}$~pc, we infer a redshift of $\sim 1.9$. From this, we estimate the peak luminosity and isotropic energy to be $\lesssim 2\times10^{43}$~erg~s$^{-1}$ and $\lesssim 2\times10^{40}$~erg, respectively. With only one FRB from the survey detected so far, our constraints on the event rate are limited. We derive a 95\% confidence lower limit for the event rate of 900 FRBs per day for FRBs with fluences $>0.025$~Jy~ms. We performed follow-up observations of the source with FAST for four hours and have not found a repeated burst. We discuss the implications of this discovery for our understanding of the physical mechanisms of FRBs.

astro-ph.HE↗

arXiv2020

Quasi-periodic pulsation detected in Lyman-alpha emission during solar flares

We investigated the quasi-periodic pulsation (QPP) in Lyman-alpha, X-ray and extreme-ultraviolet (EUV) emissions during two solar flares, i.e., an X-class (SOL2012-01-27T) and a C-class (SOL2016-02-08T). The full-disk Lyman-alpha and X-Ray flux during these solar flares were recorded by the EUV Sensor and X-Ray Sensor on board the Geostationary Operational Environmental Satellite. The °are regions were located from the EUV images measured by the Atmospheric Imaging Assembly. The QPP could be identified as a series of regular and periodic peaks in the light curves, and its quasi-periodicity was determined from the global wavelet and Fourier power spectra. A quasi-periodicity at about 3 minutes is detected during the impulsive phase of the X-class flare, which could be explained as the acoustic wave in the chromosphere (e.g., Milligan et al. 2017). Interestingly, a quasi-periodicity at roughly 1 minute is discovered during the entire evolutionary phases of solar flares, including the precursor, impulsive, and gradual phases. This is the first report of 1-minute QPP in the Lyman-alpha emission during solar flares, in particular during the flare precursor. It may be interpreted as a self-oscillatory regime of the magnetic reconnection, such as magnetic dripping.

astro-ph.SR↗

arXiv2019

Spectroscopic and Stereoscopic Observations of the Solar Jets

We present a comprehensive study of a series of recurrent jets that occurred at the periphery of the NOAA active region 12114 on 2014 July 7. These jets were found to share the same source region and exhibited rotational motions as they propagated outward. The multi-wavelength imaging observations made by the AIA and {\it IRIS} telescopes reveal that some of the jets contain cool plasma only, while some others contain not only cool but also hot plasma. The Doppler velocities calculated from the {\it IRIS} spectra show a continuous evolution from blue to red shifts as the jet motions change from upward to downward. Additionally, some jets exhibit opposite Doppler shifts on their both sides, indicative of rotating motions along their axes. The inclination angle and three-dimensional velocity of the largest jet were inferred from the imaging and spectroscopic observations, which show a high consistence with those derived from the stereoscopic analysis using dual-perspective observations by {\it SDO}/AIA and {\it STEREO}-B/EUVI. By relating the jets to the local UV/EUV and full-disk {\it GOES} X-ray emission enhancements, we found that the previous five small-scale jets were triggered by five bright points while the last/largest one was triggered by a C1.6 solar flare. Together with a number of type III radio bursts generated during the jet eruptions as well as a weak CME that was observed in association with the last jet, our observations provide evidences in support of multi-scale magnetic reconnection processes being responsible for the production of jet events.

astro-ph.SR↗

arXiv2019

A New Automatic Tool for CME Detection and Tracking with Machine Learning Techniques

With the accumulation of big data of CME observations by coronagraphs, automatic detection and tracking of CMEs has proven to be crucial. The excellent performance of convolutional neural network in image classification, object detection and other computer vision tasks motivates us to apply it to CME detection and tracking as well. We have developed a new tool for CME Automatic detection and tracking with MachinE Learning (CAMEL) techniques. The system is a three-module pipeline. It is first a supervised image classification problem. We solve it by training a neural network LeNet with training labels obtained from an existing CME catalog. Those images containing CME structures are flagged as CME images. Next, to identify the CME region in each CME-flagged image, we use deep descriptor transforming to localize the common object in an image set. A following step is to apply the graph cut technique to finely tune the detected CME region. To track the CME in an image sequence, the binary images with detected CME pixels are converted from cartesian to polar coordinate. A CME event is labeled if it can move in at least two frames and reach the edge of coronagraph field of view. For each event, a few fundamental parameters are derived. The results of four representative CMEs with various characteristics are presented and compared with those from four existing automatic and manual catalogs. We find that CAMEL can detect more complete and weaker structures, and has better performance to catch a CME as early as possible.

astro-ph.SR↗