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Register a new userLong-Term Tracking of Corotating Density Structures using Heliospheric Imaging
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The systematic monitoring of the solar wind in high-cadence and high-resolution heliospheric images taken by the Solar-Terrestrial Relation Observatory (STEREO) spacecraft permits the study of the spatial and temporal evolution of variable solar wind flows from the Sun out to 1~AU, and beyond. As part of the EU Framework 7 (FP7) Heliospheric Cataloguing, Analysis and Techniques Service (HELCATS) project, we have generated a catalogue listing the properties of 190 corotating structures well-observed in images taken by the Heliospheric Imager instruments on-board STEREO-A. We present here one of very few long-term analyses of solar wind structures advected by the background solar wind. This analysis confirms that most of the corotating density structures detected by the heliospheric imagers comprises a series of density inhomogeneities advected by the slow solar wind that eventually become entrained by stream interaction regions. We have derived the spatial-temporal evolution of each of these corotating density structures by using a well-established fitting technique. The mean radial propagation speed of the corotating structures is found to be $311 pm 31$ km~s$^{-1}$. We predicted the arrival time of each corotating density structure at different probes. We show that the speeds of the corotating density structures derived using our fitting technique track well the long-term variation of the radial speed of the slow solar wind during solar minimum years (2007--2008). Furthermore, we demonstrate that these features originate near the coronal neutral line that eventually becomes the heliospheric current sheet.
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A Coronal Mass Ejection (CME) is an inhomogeneous structure consisting of different features which evolve differently with the propagation of the CME. Simultaneous heliospheric tracking of different observed features of a CME can improve our understanding about relative forces acting on them. It also helps to estimate accurately their arrival times at the Earth and identify them in in- situ data. This also enables to find association between remotely observed features and in-situ observations near the Earth. In this paper, we attempt to continuously track two density enhanced features, one at the front and another at the rear edge of the 6 October 2010 CME. This is achieved by using time-elongation maps constructed from STEREO/SECCHI observations. We derive the kinematics of the tracked features using various reconstruction methods. The estimated kinematics are used as inputs in the Drag Based Model (DBM) to estimate the arrival time of the tracked features of the CME at L1. On comparing the estimated kinematics as well as the arrival times of the remotely observed features with in-situ observations by ACE and Wind, we find that the tracked bright feature in the J-map at the rear edge of 6 October 2010 CME corresponds most probably to the enhanced density structure after the magnetic cloud detected by ACE and Wind. In-situ plasma and compositional parameters provide evidence that the rear edge density structure may correspond to a filament associated with the CME while the density enhancement at the front corresponds to the leading edge of the CME. Based on this single event study, we discuss the relevance and significance of heliospheric imager (HI) observations in identification of the three-part structure of the CME.
Typical reconstructions of historic heliospheric magnetic field (HMF) $B_{rm HMF}$ are based on the analysis of the sunspot activity, geomagnetic data or on measurement of cosmogenic isotopes stored in terrestrial reservoirs like trees ($^{14}$C) and ice cores ($^{10}$Be). The various reconstructions of $B_{rm HMF}$ are however discordant both in strength and trend. Cosmogenic isotopes, which are produced by galactic cosmic rays (GCRs) impacting on meteoroids and whose production rate is modulated by the varying HMF convected outward by the solar wind, may offer an alternative tool for the investigation of the HMF in the past centuries. In this work, we aim to evaluate the long-term evolution of $B_{rm HMF}$ over a period covering the past twenty-two solar cycles by using measurements of the cosmogenic $^{44}$Ti activity ($tau_{1/2} = 59.2 pm 0.6$ yr) measured in 20 meteorites which fell between 1766 and 2001. Within the given uncertainties, our result is compatible with a HMF increase from $4.87^{+0.24}_{-0.30}$ nT in 1766 to $6.83^{+0.13}_{-0.11}$ nT in 2001, thus implying an overall average increment of $1.96^{+0.43}_{-0.35}$ nT over 235 years since 1766 reflecting the modern Grand maximum. The $B_{rm HMF}$ trend thus obtained is then compared with the most recent reconstructions of the near-Earth heliospheric magnetic field strength based on geomagnetic, sunspot number and cosmogenic isotope data.
We use The Sun Watcher with Active Pixel System detector and Image Processing (SWAP) imager onboard the Project for Onboard Autonomy 2 (PROBA2) mission to study the evolution of large-scale EUV structures in the solar corona observed throughout Solar Cycle 24 (from 2010 to 2019). We discuss the evolution of the on-disk coronal features and at different heights above the solar surface based on EUV intensity changes. We also look at the evolution of the corona in equatorial and polar regions and compare them at different phases of the solar cycle, as well as with sunspot number evolution and with the PROBA2/Lyman-Alpha Radiometer (LYRA) signal. The main results are as follows: The three time series (SWAP on-disk average brightness, sunspot number and LYRA irradiance) are very well correlated, with correlation coefficients around 0.9. The average rotation rate of bright features at latitudes of +15, 0, and -15 degrees was around 15 degree/day throughout the period studied. A secondary peak in EUV averaged intensity at the Poles was observed on the descending phase of SC24. These peaks (at North and South poles respectively) seem to be associated with the start of the development of the (polar) coronal holes. Large-scale off-limb structures were visible from around March 2010 to around March 2016, meaning that they were absent at the minimum phase of solar activity. A fan at the North pole persisted for more than 11 Carrington rotations (February 2014 to March 2015), and it could be seen up to altitudes of 1.6 Rs.
Monitor of All-sky X-ray Image (MAXI) on the International Space Station has been observing the X-ray sky since 2009 August 15. It has accumulated the X-ray data for about four years, so far. X-ray objects are usually variable and their variability can be studied by the power spectrum density (PSD) of the X-ray light curves.We applied our method to calculate PSDs of several kinds of objects observed with MAXI. We obtained significant PSDs from 16 Seyfert galaxies.For blackhole binary Cygnus X-1 there was a difference in the shape of PSD between the hard state and the soft state. For high mass X-ray binaries, Cen X-3, SMC X-1, and LMC X-4, there were several peaks in the PSD corresponding to the orbital period and the superorbital period.
Long-term visual tracking has drawn increasing attention because it is much closer to practical applications than short-term tracking. Most top-ranked long-term trackers adopt the offline-trained Siamese architectures, thus, they cannot benefit from great progress of short-term trackers with online update. However, it is quite risky to straightforwardly introduce online-update-based trackers to solve the long-term problem, due to long-term uncertain and noisy observations. In this work, we propose a novel offline-trained Meta-Updater to address an important but unsolved problem: Is the tracker ready for updating in the current frame? The proposed meta-updater can effectively integrate geometric, discriminative, and appearance cues in a sequential manner, and then mine the sequential information with a designed cascaded LSTM module. Our meta-updater learns a binary output to guide the trackers update and can be easily embedded into different trackers. This work also introduces a long-term tracking framework consisting of an online local tracker, an online verifier, a SiamRPN-based re-detector, and our meta-updater. Numerous experimental results on the VOT2018LT, VOT2019LT, OxUvALT, TLP, and LaSOT benchmarks show that our tracker performs remarkably better than other competing algorithms. Our project is available on the website: https://github.com/Daikenan/LTMU.
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