Evidence for collapsing fields in corona and photosphere during the 15 February 2011 X2.2 flare: SDO AIA and HMI Observations

We use high-resolution images of the sun obtained by the SDO/AIA instrument to study the evolution of the coronal loops in a flaring solar active region. During 15 February 2011 a X-2.2 class flare occurred in NOAA 11158, a $\beta\gamma\delta$ sunspot complex. We identify three distinct phases of the coronal loop dynamics during this event: (i) {\it Slow rise phase}: slow rising motion of the loop-tops prior to the flare in response to slow rise of the underlying flux rope, (ii) {\it Collapse phase}: sudden contraction of the loop-tops with lower loops collapsing earlier than the higher loops, and (iii) {\it Oscillation phase}: the loops exhibit global kink oscillations after the collapse phase at different periods, with period decreasing with decreasing height of the loops. The period of these loop oscillations is used to estimate the field strength in the coronal loops of different loop lengths in this active region. Further, we also use SDO/HMI observations to study the photospheric changes close to the polarity inversion line (PIL). The longitudinal magnetograms show step-wise permanent decrease in the magnetic flux after the flare over a coherent patch along the PIL. Further, we examine the HMI Stokes I,Q,U,V profiles over this patch and find that the Stokes-V signal systematically decreases while the Stokes-Q and U signal increases after the flare. These observations suggest that close to the PIL the field configuration became more horizontal after the flare. We also use HMI vector magnetic field observations to quantify the changes in the field inclination angle and found an inward collapse of the field lines towards the polarity inversion line (PIL) by $\sim$ 10$^\circ$. These observations are consistent with the "coronal implosion" scenario and its predictions about flare related photospheric field changes.Comment: 27 pages, 7 figures, in press (Astrophysical Journal

Multiwavelength observations of a partially eruptive filament on 2011 September 8

In this paper, we report our multiwavelength observations of a partial filament eruption event in NOAA active region 11283 on 2011 September 8. A magnetic null point and the corresponding spine and separatrix surface are found in the active region. Beneath the null point, a sheared arcade supports the filament along the highly complex and fragmented polarity inversion line. After being activated, the sigmoidal filament erupted and split into two parts. The major part rose at the speeds of 90$-$150 km s$^{-1}$ before reaching the maximum apparent height of $\sim$115 Mm. Afterwards, it returned to the solar surface in a bumpy way at the speeds of 20$-$80 km s$^{-1}$. The rising and falling motions were clearly observed in the extreme-ultravoilet (EUV), UV, and H$\alpha$ wavelengths. The failed eruption of the main part was associated with an M6.7 flare with a single hard X-ray source. The runaway part of the filament, however, separated from and rotated around the major part for $\sim$1 turn at the eastern leg before escaping from the corona, probably along large-scale open magnetic field lines. The ejection of the runaway part resulted in a very faint coronal mass ejection (CME) that propagated at an apparent speed of 214 km s$^{-1}$ in the outer corona. The filament eruption also triggered transverse kink-mode oscillation of the adjacent coronal loops in the same AR. The amplitude and period of the oscillation were 1.6 Mm and 225 s. Our results are important for understanding the mechanisms of partial filament eruptions and provide new constraints to theoretical models. The multiwavelength observations also shed light on space weather prediction.Comment: 46 pages, 17 figures, 1 table, accepted for publication in Ap

Slow and steady feature analysis: higher order temporal coherence in video

How can unlabeled video augment visual learning? Existing methods perform "slow" feature analysis, encouraging the representations of temporally close frames to exhibit only small differences. While this standard approach captures the fact that high-level visual signals change slowly over time, it fails to capture *how* the visual content changes. We propose to generalize slow feature analysis to "steady" feature analysis. The key idea is to impose a prior that higher order derivatives in the learned feature space must be small. To this end, we train a convolutional neural network with a regularizer on tuples of sequential frames from unlabeled video. It encourages feature changes over time to be smooth, i.e., similar to the most recent changes. Using five diverse datasets, including unlabeled YouTube and KITTI videos, we demonstrate our method's impact on object, scene, and action recognition tasks. We further show that our features learned from unlabeled video can even surpass a standard heavily supervised pretraining approach.Comment: in Computer Vision and Pattern Recognition (CVPR) 2016, Las Vegas, NV, June 201

Visual Dynamics: Stochastic Future Generation via Layered Cross Convolutional Networks

We study the problem of synthesizing a number of likely future frames from a single input image. In contrast to traditional methods that have tackled this problem in a deterministic or non-parametric way, we propose to model future frames in a probabilistic manner. Our probabilistic model makes it possible for us to sample and synthesize many possible future frames from a single input image. To synthesize realistic movement of objects, we propose a novel network structure, namely a Cross Convolutional Network; this network encodes image and motion information as feature maps and convolutional kernels, respectively. In experiments, our model performs well on synthetic data, such as 2D shapes and animated game sprites, and on real-world video frames. We present analyses of the learned network representations, showing it is implicitly learning a compact encoding of object appearance and motion. We also demonstrate a few of its applications, including visual analogy-making and video extrapolation.Comment: Journal preprint of arXiv:1607.02586 (IEEE TPAMI, 2019). The first two authors contributed equally to this work. Project page: http://visualdynamics.csail.mit.ed

A Decoupled 3D Facial Shape Model by Adversarial Training

Data-driven generative 3D face models are used to compactly encode facial shape data into meaningful parametric representations. A desirable property of these models is their ability to effectively decouple natural sources of variation, in particular identity and expression. While factorized representations have been proposed for that purpose, they are still limited in the variability they can capture and may present modeling artifacts when applied to tasks such as expression transfer. In this work, we explore a new direction with Generative Adversarial Networks and show that they contribute to better face modeling performances, especially in decoupling natural factors, while also achieving more diverse samples. To train the model we introduce a novel architecture that combines a 3D generator with a 2D discriminator that leverages conventional CNNs, where the two components are bridged by a geometry mapping layer. We further present a training scheme, based on auxiliary classifiers, to explicitly disentangle identity and expression attributes. Through quantitative and qualitative results on standard face datasets, we illustrate the benefits of our model and demonstrate that it outperforms competing state of the art methods in terms of decoupling and diversity.Comment: camera-ready version for ICCV'1

Parallel Evolution of Quasi-separatrix Layers and Active Region Upflows

Persistent plasma upflows were observed with Hinode's EUV Imaging Spectrometer (EIS) at the edges of active region (AR) 10978 as it crossed the solar disk. We analyze the evolution of the photospheric magnetic and velocity fields of the AR, model its coronal magnetic field, and compute the location of magnetic null-points and quasi-sepratrix layers (QSLs) searching for the origin of EIS upflows. Magnetic reconnection at the computed null points cannot explain all of the observed EIS upflow regions. However, EIS upflows and QSLs are found to evolve in parallel, both temporarily and spatially. Sections of two sets of QSLs, called outer and inner, are found associated to EIS upflow streams having different characteristics. The reconnection process in the outer QSLs is forced by a large-scale photospheric flow pattern which is present in the AR for several days. We propose a scenario in which upflows are observed provided a large enough asymmetry in plasma pressure exists between the pre-reconnection loops and for as long as a photospheric forcing is at work. A similar mechanism operates in the inner QSLs, in this case, it is forced by the emergence and evolution of the bipoles between the two main AR polarities. Our findings provide strong support to the results from previous individual case studies investigating the role of magnetic reconnection at QSLs as the origin of the upflowing plasma. Furthermore, we propose that persistent reconnection along QSLs does not only drive the EIS upflows, but it is also responsible for a continuous metric radio noise-storm observed in AR 10978 along its disk transit by the Nan\c{c}ay Radio Heliograph.Comment: 29 pages, 10 figure