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After leaving the Sun's corona, the solar wind continues to accelerate and cools, but more slowly than expected for a freely expanding adiabatic gas. We use in situ measurements from the Parker Solar Probe and Solar Orbiter spacecrafts to investigate a stream of solar wind as it traverses the inner heliosphere. The observations show heating and acceleration of the the plasma between the outer edge of the corona and near the orbit of Venus, in connection to the presence of large amplitude Alfv\'en waves. Alfv\'en waves are perturbations in the interplanetary magnetic field that transport energy. Our calculations show the damping and mechanical work performed by the Alfv\'en waves is sufficient to power the heating and acceleration of the fast solar wind in the inner heliosphere., Comment: This is the author's version of the work. It is posted here by permission of the AAAS for personal use, not for redistribution. The definitive version was published in Science on August 30 2024, DOI: 10.1126/science.adk6953

Scale-Dependent Dynamic Alignment (SDDA) in Els\"asser field fluctuations is theorized to suppress nonlinearities and modulate the energy spectrum. Limited empirical evidence exists for SDDA within the solar wind turbulence's inertial range. We analyzed data from the WIND mission to assess the effects of compressibility, intermittency, and imbalance on SDDA. SDDA consistently appears at energy-containing scales, with a trend toward misalignment at inertial scales. Compressible fluctuations show no increased alignment; however, their impact on SDDA's overall behavior is minimal. The alignment angles inversely correlate with field gradient intensity, likely due to "anomalous" or "counterpropagating" wave packet interactions. This suggests that SDDA originates from mutual shearing of Els\"asser fields during imbalanced ($\delta \boldsymbol{z}^{\pm} \gg \delta \boldsymbol{z}^{\mp}$) interactions. Rigorous thresholding on field gradient intensity reveals SDDA signatures across much of the inertial range. The scaling of Els\"asser increments' alignment angle, $\Theta^{z}$, steepens with increasing global Alfv\'enic imbalance, while the angle between magnetic and velocity field increments, $\Theta^{ub}$, becomes shallower. $\Theta^{ub}$ only correlates with global Els\"asser imbalance, steepening as the imbalance increases. Furthermore, increasing alignment in $\Theta^{ub}$ persists deep into the inertial range of balanced intervals but collapses at large scales for imbalanced ones. Simplified theoretical analysis and modeling of high-frequency, low-amplitude noise in the velocity field indicate significant impacts on alignment angle measurements even at very low frequencies, with effects growing as global imbalance increases.

Recent observations of Parker Solar Probe (PSP) from around the Alfv\'en surface have shown that the trace magnetic power spectrum density (PSD) is often characterized by a shallow-inertial double power law, where in the low frequency energy injection range, the power spectrum is shallow (flatter than $1/f$), and in the inertial range the spectrum is steep, with a scaling index of [1.5, 1.67]. Consequently, close to the sun, the majority of the fluctuation energy concentrates in a small frequency range around the low frequency power spectral break. In this work, we conduct a systematic survey of PSP observations for the first 17 encounters to statistically study the energy behaviors of the magnetic fluctuations. Our results show that the center frequency of fluctuation energy systematically drifts to around 3-minute for the most pristine solar wind (smallest solar wind advection time). Moreover, the center frequency rapidly drifts to lower frequency as solar wind advection time increases, as expected for active turbulence. The concentration of fluctuation energy around 3-minutes suggests that Alfv\'enic fluctuations in solar wind might mostly be coming from resonant p-mode oscillations in the photosphere, though other potential sources are discussed.

The Extended Quantum Molecular Dynamics (EQMD) model is one of the few QMD-like transport approaches that can describe the $\alpha$-clustering structure with efficient computational power. However, compared to most QMD-like models, the choice of equation of state (EOS) for nuclear matter is very limited. In this work, a Monte Carlo integral method is employed to calculate the density integration with non-integer exponent. We demonstrate the superiority of our approach by studying the isovector giant dipole resonance (IVGDR). This improvement will be beneficial for the EQMD model to study more valuable effects for heavy ion collisions in the near future., Comment: 10 pages, 8 figures

The extended quantum molecular dynamics (EQMD) model is one of the few quantum molecular dynamics (QMD)-like transport approaches that can be used to study the effective clustering structure as well as heavily deformed nuclei in both ground state nuclei and nuclear reactions. However, there are only two parameter sets that lead to hard incompressibility for long times. The aim of the present work is to obtain a soft equation of state (EoS) in the EQMD model. In this context, we take the isoscalar giant monopole resonance (ISGMR), which is sensitive to the EoS, as an example to check our work. By introducing a kind of standard Skyrme energy density functional with different parameter sets, such as SkP, SkT1, and SKXce, whose incompressibility value ranges from 200 to 268 MeV, the ISGMR of $^{208}$Pb and other nuclei are studied. When the SkP parameter sets are adopted, our new soft interaction in the EQMD model gives reasonable agreement with the experimental data in the heavy ion regime., Comment: 10 pages, 8 figures

We analyze in-situ observations of imbalanced solar wind turbulence to evaluate MHD turbulence models grounded in "Critical Balance" (CB) and "Scale-Dependent Dynamic Alignment" (SDDA). At energy injection scales, both outgoing and ingoing modes exhibit a weak cascade; a simultaneous tightening of SDDA is noted. Outgoing modes persist in a weak cascade across the inertial range, while ingoing modes shift to a strong cascade at $\lambda \approx 3 \times 10^{4} d_i$, with associated spectral scalings deviating from expected behavior due to "anomalous coherence" effects. The inertial range comprises two distinct sub-inertial segments. Beyond $\lambda \gtrsim 100 d_i$, eddies adopt a field-aligned tube topology, with SDDA signatures mainly evident in high amplitude fluctuations. The scaling exponents $\zeta_{n}$ of the $n$-th order conditional structure functions, orthogonal to both the local mean field and fluctuation direction, align with the analytical models of Chandran et al. 2015 and Mallet et al. 2017, indicating "multifractal" statistics and strong intermittency; however, scaling in parallel and displacement components is more concave than predicted, possibly influenced by expansion effects. Below $\lambda \approx 100 d_i$, eddies become increasingly anisotropic, evolving into thin current sheet-like structures. Concurrently, $\zeta_{n}$ scales linearly with order, marking a shift towards "monofractal" statistics. At $\lambda \approx 8 d_i$, the increase in aspect ratio halts, and the eddies become quasi-isotropic. This change may signal tearing instability, leading to reconnection, or result from energy redirection into the ion-cyclotron wave spectrum, aligning with the "helicity barrier". Our analysis utilizes 5-point structure functions, proving more effective than the traditional 2-point method in capturing steep scaling behaviors at smaller scales.

The task of financial analysis primarily encompasses two key areas: stock trend prediction and the corresponding financial question answering. Currently, machine learning and deep learning algorithms (ML&DL) have been widely applied for stock trend predictions, leading to significant progress. However, these methods fail to provide reasons for predictions, lacking interpretability and reasoning processes. Also, they can not integrate textual information such as financial news or reports. Meanwhile, large language models (LLMs) have remarkable textual understanding and generation ability. But due to the scarcity of financial training datasets and limited integration with real-time knowledge, LLMs still suffer from hallucinations and are unable to keep up with the latest information. To tackle these challenges, we first release AlphaFin datasets, combining traditional research datasets, real-time financial data, and handwritten chain-of-thought (CoT) data. It has a positive impact on training LLMs for completing financial analysis. We then use AlphaFin datasets to benchmark a state-of-the-art method, called Stock-Chain, for effectively tackling the financial analysis task, which integrates retrieval-augmented generation (RAG) techniques. Extensive experiments are conducted to demonstrate the effectiveness of our framework on financial analysis., Comment: COLING 2024. The first three authors contributed equally. Project website: https://github.com/AlphaFin-proj/AlphaFin

Generative query rewrite generates reconstructed query rewrites using the conversation history while rely heavily on gold rewrite pairs that are expensive to obtain. Recently, few-shot learning is gaining increasing popularity for this task, whereas these methods are sensitive to the inherent noise due to limited data size. Besides, both attempts face performance degradation when there exists language style shift between training and testing cases. To this end, we study low-resource generative conversational query rewrite that is robust to both noise and language style shift. The core idea is to utilize massive unlabeled data to make further improvements via a contrastive co-training paradigm. Specifically, we co-train two dual models (namely Rewriter and Simplifier) such that each of them provides extra guidance through pseudo-labeling for enhancing the other in an iterative manner. We also leverage contrastive learning with data augmentation, which enables our model pay more attention on the truly valuable information than the noise. Extensive experiments demonstrate the superiority of our model under both few-shot and zero-shot scenarios. We also verify the better generalization ability of our model when encountering language style shift., Comment: Accepted to COLING 2024

The Aesthetics Assessment of Children's Paintings (AACP) is an important branch of the image aesthetics assessment (IAA), playing a significant role in children's education. This task presents unique challenges, such as limited available data and the requirement for evaluation metrics from multiple perspectives. However, previous approaches have relied on training large datasets and subsequently providing an aesthetics score to the image, which is not applicable to AACP. To solve this problem, we construct an aesthetics assessment dataset of children's paintings and a model based on self-supervised learning. 1) We build a novel dataset composed of two parts: the first part contains more than 20k unlabeled images of children's paintings; the second part contains 1.2k images of children's paintings, and each image contains eight attributes labeled by multiple design experts. 2) We design a pipeline that includes a feature extraction module, perception modules and a disentangled evaluation module. 3) We conduct both qualitative and quantitative experiments to compare our model's performance with five other methods using the AACP dataset. Our experiments reveal that our method can accurately capture aesthetic features and achieve state-of-the-art performance., Comment: AAAI 2024

Parker Solar Probe observations reveal that the near-Sun space is almost filled with magnetic switchbacks (``switchbacks'' hereinafter), which may be a major contributor to the heating and acceleration of solar wind. Here, for the first time, we develop an analytic model of an axisymmetric switchback with uniform magnetic field strength. In this model, three parameters control the geometry of the switchback: height (length along the background magnetic field), width (thickness along radial direction perpendicular to the background field), and the radial distance from the center of switchback to the central axis, which is a proxy of the size of the switchback along the third dimension. We carry out three-dimensional magnetohydrodynamic simulations to investigate the dynamic evolution of the switchback. Comparing simulations conducted with compressible and incompressible codes, we verify that compressibility, i.e. parametric decay instability, is necessary for destabilizing the switchback. Our simulations also reveal that the geometry of the switchback significantly affects how fast the switchback destabilizes. The most stable switchbacks are 2D-like (planar) structures with large aspect ratios (length to width), consistent with the observations. We show that when plasma beta ($\beta$) is smaller than one, the switchback is more stable as $\beta$ increases. However, when $\beta$ is greater than one, the switchback becomes very unstable as the pattern of the growing compressive fluctuations changes. Our results may explain some of the observational features of switchbacks, including the large aspect ratios and nearly constant occurrence rates in the inner heliosphere.

One of the primary science objectives of Parker Solar Probe (PSP) is to determine the structures and dynamics of the plasma and magnetic fields at the sources of the solar wind. However, establishing the connection between {\it in situ} measurements and structures and dynamics in the solar atmosphere is challenging: most of the magnetic footpoint mapping techniques have significant uncertainties in the source localization of a plasma parcel observed {\it in situ}, and the PSP plasma measurements suffer from a limited field of view. Therefore it is of interest to investigate whether {\it in situ} measurements can be used on their own to identify streams originating from the same structures in the corona more finely than the well known fast wind-coronal hole, slow wind-elsewhere distinction. Here we develop a novel time series visualization method \textcolor{red}{(time-frequency representation or TFR)} named Gaussianity Scalogram. Utilizing this method, by analyzing the magnetic magnitude data from both PSP and Ulysses, we successfully identify {\it in situ} structures that are possible remnants of solar atmospheric and magnetic structures spanning more than seven orders of magnitude, from years to seconds, including polar and mid-latitude coronal holes, as well as structures compatible with super-granulation , ``jetlets'' and ``picoflares''. \textcolor{red}{Furthermore, computer simulations of Alfv\'enic turbulence successfully reproduce the Gaussianization of the magnetic magnitude for locally homogeneous structures.} Building upon these discoveries, the Gaussianity Scalogram can help future studies to reveal the fractal-like fine structures in the solar wind time series from both PSP and decades-old data archive., Comment: Accepted by ApJL

In this paper, we present DreaMoving, a diffusion-based controllable video generation framework to produce high-quality customized human videos. Specifically, given target identity and posture sequences, DreaMoving can generate a video of the target identity moving or dancing anywhere driven by the posture sequences. To this end, we propose a Video ControlNet for motion-controlling and a Content Guider for identity preserving. The proposed model is easy to use and can be adapted to most stylized diffusion models to generate diverse results. The project page is available at https://dreamoving.github.io/dreamoving, Comment: 5 pages, 5 figures, Tech. Report

Semantic segmentation tasks naturally require high-resolution information for pixel-wise segmentation and global context information for class prediction. While existing vision transformers demonstrate promising performance, they often utilize high resolution context modeling, resulting in a computational bottleneck. In this work, we challenge conventional wisdom and introduce the Low-Resolution Self-Attention (LRSA) mechanism to capture global context at a significantly reduced computational cost. Our approach involves computing self-attention in a fixed low-resolution space regardless of the input image's resolution, with additional 3x3 depth-wise convolutions to capture fine details in the high-resolution space. We demonstrate the effectiveness of our LRSA approach by building the LRFormer, a vision transformer with an encoder-decoder structure. Extensive experiments on the ADE20K, COCO-Stuff, and Cityscapes datasets demonstrate that LRFormer outperforms state-of-the-art models. The code will be made available at https://github.com/yuhuan-wu/LRFormer., Comment: 11 pages, 11 tables, 6 figures

We conduct 3D magnetohydrodynamic (MHD) simulations of decaying turbulence in the solar wind context. To account for the spherical expansion of the solar wind, we implement the expanding box model. The initial turbulence comprises uncorrelated counter-propagating Alfv\'en waves and exhibits an isotropic power spectrum. Our findings reveal the consistent generation of negative residual energy whenever nonlinear interactions are present, independent of the normalized cross helicity $\sigma_c$. The spherical expansion facilitates this process. The resulting residual energy is primarily distributed in the perpendicular direction, with $[S_2(\mathbf{b})-S_2(\mathbf{u})] \propto l_\perp$ or equivalently $-E_r \propto k_\perp^{-2}$. Here $S_2(\mathbf{b})$ and $S_2(\mathbf{u})$ are second-order structure functions of magnetic field and velocity respectively. In most runs, $S_2(\mathbf{b})$ develops a scaling relation $S_2(\mathbf{b}) \propto l_\perp^{1/2}$ ($E_b \propto k_\perp^{-3/2}$). In contrast, $S_2(\mathbf{u})$ is consistently shallower than $S_2(\mathbf{b})$, which aligns with in-situ observations of the solar wind. We observe that the higher-order statistics of the turbulence, which act as a proxy for intermittency, are strongly affected by the expansion effect but have weak dependence on the initial $\sigma_c$. Generally, the intermittency is more pronounced when the expansion effect is present. Finally, we find that in our simulations although the negative residual energy and intermittency grow simultaneously as the turbulence evolves, there is no obvious causal relation between them because they are generated on different scales.

Tuberculosis (TB) is a major global health threat, causing millions of deaths annually. Although early diagnosis and treatment can greatly improve the chances of survival, it remains a major challenge, especially in developing countries. Recently, computer-aided tuberculosis diagnosis (CTD) using deep learning has shown promise, but progress is hindered by limited training data. To address this, we establish a large-scale dataset, namely the Tuberculosis X-ray (TBX11K) dataset, which contains 11,200 chest X-ray (CXR) images with corresponding bounding box annotations for TB areas. This dataset enables the training of sophisticated detectors for high-quality CTD. Furthermore, we propose a strong baseline, SymFormer, for simultaneous CXR image classification and TB infection area detection. SymFormer incorporates Symmetric Search Attention (SymAttention) to tackle the bilateral symmetry property of CXR images for learning discriminative features. Since CXR images may not strictly adhere to the bilateral symmetry property, we also propose Symmetric Positional Encoding (SPE) to facilitate SymAttention through feature recalibration. To promote future research on CTD, we build a benchmark by introducing evaluation metrics, evaluating baseline models reformed from existing detectors, and running an online challenge. Experiments show that SymFormer achieves state-of-the-art performance on the TBX11K dataset. The data, code, and models will be released at https://github.com/yun-liu/Tuberculosis., Comment: Accepted by IEEE TPAMI; 17 pages

This Letter reports the first observational estimate of the heating rate in the slowly expanding solar corona. The analysis exploits the simultaneous remote and local observations of the same coronal plasma volume with the Solar Orbiter/Metis and the Parker Solar Probe instruments, respectively, and relies on the basic solar wind magnetohydrodynamic equations. As expected, energy losses are a minor fraction of the solar wind energy flux, since most of the energy dissipation that feeds the heating and acceleration of the coronal flow occurs much closer to the Sun than the heights probed in the present study, which range from 6.3 to 13.3 solar radii. The energy deposited to the supersonic wind is then used to explain the observed slight residual wind acceleration and to maintain the plasma in a non-adiabatic state. As derived in the Wentzel-Kramers-Brillouin limit, the present energy transfer rate estimates provide a lower limit, which can be very useful in refining the turbulence-based modeling of coronal heating and subsequent solar wind acceleration.

Determining the mechanism responsible for the plasma heating and particle acceleration is a fundamental problem in the study of the heliosphere. Due to efficient wave-particle interactions of ion-scale waves with charged particles, these waves are widely believed to be a major contributor to ion energization, and their contribution considerably depends on the wave occurrence rate. By analyzing the radial distribution of quasi-monochromatic ion-scale waves observed by the Parker Solar Probe, this work shows that the wave occurrence rate is significantly enhanced in the near-Sun solar wind, specifically 21%$-$29% below 0.3 au, in comparison to 6%$-$14% beyond 0.3 au. The radial decrease of the wave occurrence rate is not only induced by the sampling effect of a single spacecraft detection, but also by the physics relating to the wave excitation, such as the enhanced ion beam instability in the near-Sun solar wind. This work also shows that the wave normal angle $\theta$, the absolute value of ellipticity $\epsilon$, the wave frequency $f$ normalized by the proton cyclotron frequency $f_{\mathrm{cp}}$, and the wave amplitude $\delta B$ normalized by the local background magnetic field $B_0$ slightly vary with the radial distance. The median values of $\theta$, $|\epsilon|$, $f$, and $\delta B$ are about $9^\circ$, $0.73$, $3f_{\mathrm{cp}}$, and $0.01B_0$, respectively. Furthermore, this study proposes that the wave mode nature of the observed left-handed and right-handed polarized waves corresponds to the Alfv\'en ion cyclotron mode wave and the fast-magnetosonic whistler mode wave, respectively., Comment: Accepted for publication by The Astrophysical Journal (ApJ)

The trace magnetic power spectrum in the solar wind is known to be characterized by a double power law at scales much larger than the proton gyro-radius, with flatter spectral exponents close to -1 found at the lower frequencies below an inertial range with indices closer to $[-1.5,-1.6]$. The origin of the $1/f$ range is still under debate. In this study, we selected 109 magnetically incompressible solar wind intervals ($\delta |\boldsymbol B|/|\boldsymbol B| \ll 1$) from Parker Solar Probe encounters 1 to 13 which display such double power laws, with the aim of understanding the statistics and radial evolution of the low frequency power spectral exponents from Alfv\'en point up to 0.3 AU. New observations from closer to the sun show that in the low frequency range solar wind turbulence can display spectra much shallower than $1/f$, evolving asymptotically to $1/f$ as advection time increases, indicating a dynamic origin for the $1/f$ range formation. We discuss the implications of this result on the Matteini et al. (2018) conjecture for the $1/f$ origin as well as example spectra displaying a triple power law consistent with the model proposed by Chandran et al. (2018), supporting the dynamic role of parametric decay in the young solar wind. Our results provide new constraints on the origin of the $1/f$ spectrum and further show the possibility of the coexistence of multiple formation mechanisms., Comment: Accepted by ApJL

We investigate dispersive and kinetic effects on the evolution of a two-dimensional kinked Alfv\'en wave packet by comparing results from MHD, Hall-MHD and hybrid simulations of a low-$\beta$ plasma. We find that the Hall term determines the overall evolution of the wave packet over a characteristic time $\tau^*=\tau_a\ell/d_i$ in both fluid and hybrid models. Dispersion of the wave packet leads to the conversion of the wave energy into internal plasma energy. When kinetic protons are considered, the proton internal energy increase has contributions from both plasma compressions and phase space mixing. The latter occurs in the direction parallel to the guiding mean magnetic field, due to protons resonating at the Alfv\'en speed with a compressible mode forced by the wave packet. Implications of our results for switchbacks observations and solar wind energetics are discussed., Comment: In press at PoP for the Special Collection on the Plasma Physics of the Sun in Honor of Eugene Parker

Designing an efficient yet deployment-friendly 3D backbone to handle sparse point clouds is a fundamental problem in 3D perception. Compared with the customized sparse convolution, the attention mechanism in Transformers is more appropriate for flexibly modeling long-range relationships and is easier to be deployed in real-world applications. However, due to the sparse characteristics of point clouds, it is non-trivial to apply a standard transformer on sparse points. In this paper, we present Dynamic Sparse Voxel Transformer (DSVT), a single-stride window-based voxel Transformer backbone for outdoor 3D perception. In order to efficiently process sparse points in parallel, we propose Dynamic Sparse Window Attention, which partitions a series of local regions in each window according to its sparsity and then computes the features of all regions in a fully parallel manner. To allow the cross-set connection, we design a rotated set partitioning strategy that alternates between two partitioning configurations in consecutive self-attention layers. To support effective downsampling and better encode geometric information, we also propose an attention-style 3D pooling module on sparse points, which is powerful and deployment-friendly without utilizing any customized CUDA operations. Our model achieves state-of-the-art performance with a broad range of 3D perception tasks. More importantly, DSVT can be easily deployed by TensorRT with real-time inference speed (27Hz). Code will be available at \url{https://github.com/Haiyang-W/DSVT}., Comment: Accepted by CVPR2023

We analyze a merged Parker Solar Probe ($PSP$) and Solar Orbiter ($SO$) dataset covering heliocentric distances $13 \ R_{\odot} \lesssim R \lesssim 220$ $R_{\odot}$ to investigate the radial evolution of power and spectral-index anisotropy in the wavevector space of solar wind turbulence. Our results show that anisotropic signatures of turbulence display a distinct radial evolution when fast, $V_{sw} \geq ~ 400 ~km ~s^{-1}$, and slow, $V_{sw} \leq ~ 400 ~km ~s^{-1}$, wind streams are considered. The anisotropic properties of slow wind in Earth orbit are consistent with a ``critically balanced'' cascade, but both spectral-index anisotropy and power anisotropy diminish with decreasing heliographic distance. Fast streams are observed to roughly retain their near-Sun anisotropic properties, with the observed spectral index and power anisotropies being more consistent with a ``dynamically aligned'' type of cascade, though the lack of extended fast-wind intervals makes it difficult to accurately measure the anisotropic scaling. A high-resolution analysis during the first perihelion of PSP confirms the presence of two sub-ranges within the inertial range, which may be associated with the transition from weak to strong turbulence. The transition occurs at $\kappa d_{i} \approx 6 \times 10^{-2}$, and signifies a shift from -5/3 to -2 and -3/2 to -1.57 scaling in parallel and perpendicular spectra, respectively. Our results provide strong observational constraints for anisotropic theories of MHD turbulence in the solar wind., Comment: Accepted to APJ

The heating and acceleration of the solar wind remains one of the fundamental unsolved problems in heliophysics. It is usually observed that the proton temperature $T_i$ is highly correlated with the solar wind speed $V_{SW}$, while the electron temperature $T_e$ shows anti-correlation or no clear correlation with the solar wind speed. Here we inspect both Parker Solar Probe (PSP) and WIND data and compare the observations with simulation results. PSP observations below 30 solar radii clearly show a positive correlation between proton temperature and wind speed and a negative correlation between electron temperature and wind speed. One year (2019) of WIND data confirm that proton temperature is positively correlated with solar wind speed, but the electron temperature increases with the solar wind speed for slow wind while it decreases with the solar wind speed for fast wind. Using a one-dimensional Alfv\'en-wave-driven solar wind model with different proton and electron temperatures, we for the first time find that if most of the dissipated Alfv\'en wave energy heats the ions instead of electrons, a positive $T_i-V_{SW}$ correlation and a negative $T_e-V_{SW}$ correlation arise naturally. If the electrons gain a small but finite portion of the dissipated wave energy, the $T_e-V_{SW}$ correlation evolves with radial distance to the Sun such that the negative correlation gradually turns positive. The model results show that Alfv\'en waves are one of the possible explanations of the observed evolution of proton and electron temperatures in the solar wind.

The task of query rewrite aims to convert an in-context query to its fully-specified version where ellipsis and coreference are completed and referred-back according to the history context. Although much progress has been made, less efforts have been paid to real scenario conversations that involve drawing information from more than one modalities. In this paper, we propose the task of multimodal conversational query rewrite (McQR), which performs query rewrite under the multimodal visual conversation setting. We collect a large-scale dataset named McQueen based on manual annotation, which contains 15k visual conversations and over 80k queries where each one is associated with a fully-specified rewrite version. In addition, for entities appearing in the rewrite, we provide the corresponding image box annotation. We then use the McQueen dataset to benchmark a state-of-the-art method for effectively tackling the McQR task, which is based on a multimodal pre-trained model with pointer generator. Extensive experiments are performed to demonstrate the effectiveness of our model on this task\footnote{The dataset and code of this paper are both available in \url{https://github.com/yfyuan01/MQR}, Comment: Accepted by EMNLP22

The acceleration of the solar coronal plasma to supersonic speeds is one of the most fundamental yet unresolved problem in heliophysics. Despite the success of Parker's pioneering theory on an isothermal solar corona, the realistic solar wind is observed to be non-isothermal, and the decay of its temperature with radial distance usually can be fitted to a polytropic model. In this work, we use Parker Solar Probe data from the first nine encounters to estimate the polytropic index of solar wind protons. The estimated polytropic index varies roughly between 1.25 and 1.5 and depends strongly on solar wind speed, faster solar wind on average displaying a smaller polytropic index. We comprehensively analyze the 1D spherically symmetric solar wind model with polytropic index $\gamma \in [1,5/3]$. We derive a closed algebraic equation set for transonic stellar flows, i.e. flows that pass the sound point smoothly. We show that an accelerating wind solution only exists in the parameter space bounded by $C_0/C_g < 1$ and $(C_0/C_g)^2 > 2(\gamma-1)$ where $C_0$ and $C_g$ are the surface sound speed and one half of the escape velocity of the star, and no stellar wind exists for $\gamma > 3/2$. With realistic solar coronal temperatures, the observed solar wind with $\gamma \gtrsim 1.25$ cannot be explained by the simple polytropic model. We show that mechanisms such as strong heating in the lower corona that leads to a thick isothermal layer around the Sun and large-amplitude Alfv\'en wave pressure are necessary to remove the constraint in $\gamma$ and accelerate the solar wind to high speeds.

Parker Solar Probe and Solar Orbiter data are used to investigate the radial evolution of magnetic turbulence between $0.06 ~ \lesssim R ~\lesssim 1$ au. The spectrum is studied as a function of scale, normalized to the ion inertial scale $d_{i}$. In the vicinity of the Sun, the inertial range is limited to a narrow range of scales and exhibits a power-law exponent of, $\alpha_{B} = -3/2$, independent of plasma parameters. The inertial range grows with distance, progressively extending to larger spatial scales, while steepening towards a $\alpha_{B} =-5/3$ scaling. It is observed that spectra for intervals with large magnetic energy excesses and low Alfv\'enic content steepen significantly with distance, in contrast to highly Alfv\'enic intervals that retain their near-Sun scaling. The occurrence of steeper spectra in slower wind streams may be attributed to the observed positive correlation between solar wind speed and Alfv\'enicity., Comment: Accepted to APJ letters with minor revisions

3D object detection has achieved remarkable progress by taking point clouds as the only input. However, point clouds often suffer from incomplete geometric structures and the lack of semantic information, which makes detectors hard to accurately classify detected objects. In this work, we focus on how to effectively utilize object-level information from images to boost the performance of point-based 3D detector. We present DeMF, a simple yet effective method to fuse image information into point features. Given a set of point features and image feature maps, DeMF adaptively aggregates image features by taking the projected 2D location of the 3D point as reference. We evaluate our method on the challenging SUN RGB-D dataset, improving state-of-the-art results by a large margin (+2.1 mAP@0.25 and +2.3mAP@0.5). Code is available at https://github.com/haoy945/DeMF.

The solar wind undergoes significant heating as it propagates away from the Sun; the exact mechanisms responsible for this heating remain unclear. Using data from the first perihelion of the Parker Solar Probe mission, we examine the properties of proton and electron heating occurring within magnetic coherent structures identified by means of the Partial Variance of Increments (PVI) method. Statistically, regions of space with strong gradients in the magnetic field, $PVI \geq 1$, are associated with strongly enhanced proton but only slightly elevated electron temperatures. Our analysis indicates a heating mechanism in the nascent solar wind environment facilitated by a nonlinear turbulent cascade that preferentially heats protons over electrons.

We investigate the transverse momentum weighted Sivers asymmetries in the processes with transversely polarized proton target, including the $\frac{P_{hT}}{zM_p}\sin (\phi_h-\phi_S)$ weighted asymmetry in charged hadron production in semi-inclusive deeply inelastic scattering (SIDIS) and the $\frac{q_T}{M_p}\sin (\phi_S)$ weighted asymmetry in $\pi^- p$ Drell-Yan process. Due to the integration over the transverse momentum, the weighted asymmetries can be expressed as the product of the transverse-moments of the transverse momentum dependent (TMD) parton distribution functions (PDFs) and fragmentation functions (FFs). Using the parametrization for the Sivers function of the proton, the unpolarized PDFs of proton and pion, and the unpolarized FF of charged hadron, we present the numerical calculation for weighted Sivers asymmetries in SIDIS and Drell-Yan processes at the kinematics of COMPASS, and compare them with experimental data. We find that our prediction on the weighted Sivers asymmetry in SIDIS process is in agreement with the recent COMPASS measurement. Due to the relatively large uncertainties of the preliminary data from COMPASS Drell-Yan program, high precision experimental data are needed to test the sign change property of the Sivers function between SIDIS and Drell-Yan processes and to constrain the sea quark Sivers function., Comment: 10 pages, 4 figures

Parker Solar Probe (PSP) has shown that the solar wind in the inner heliosphere is characterized by the quasi omni-presence of magnetic switchbacks ("switchback" hereinafter), local backward-bends of magnetic field lines. Switchbacks also tend to come in patches, with a large-scale modulation that appears to have a spatial scale size comparable to supergranulation on the Sun. Here we inspect data from the first ten encounters of PSP focusing on different time intervals when clear switchback patches were observed by PSP. We show that the switchbacks modulation, on a timescale of several hours, seems to be independent of whether PSP is near perihelion, when it rapidly traverses large swaths of longitude remaining at the same heliocentric distance, or near the radial-scan part of its orbit, when PSP hovers over the same longitude on the Sun while rapidly moving radially inwards or outwards. This implies that switchback patches must also have an intrinsically temporal modulation most probably originating at the Sun. Between two consecutive patches, the magnetic field is usually very quiescent with weak fluctuations. We compare various parameters between the quiescent intervals and the switchback intervals. The results show that the quiescent intervals are typically less Alfv\'enic than switchback intervals, and the magnetic power spectrum is usually shallower in quiescent intervals. We propose that the temporal modulation of switchback patches may be related to the "breathing" of emerging flux that appears in images as the formation of "bubbles" below prominences in the Hinode/SOT observations.

We study the stability problem of a magnetohydrodynamic current sheet with the presence of a plasma jet. The flow direction is perpendicular to the normal of the current sheet and we analyze two cases: (1) The flow is along the anti-parallel component of the magnetic field; (2) The flow is perpendicular to the anti-parallel component of the magnetic field. A generalized equation set with the condition of incompressibility is derived and solved as a boundary-value-problem. For the first case, we show that, the streaming kink mode is stabilized by the magnetic field at $V_0/B_0 \lesssim 2$, where $V_0$ and $B_0$ are the jet speed and upstream Alfv\'en speed, and it is not affected by resistivity significantly. The streaming sausage mode is stabilized at $V_0/B_0 \lesssim 1$, and it can transit to the streaming tearing mode with a finite resistivity. The streaming tearing mode has larger growth rate than the pure tearing mode, though the scaling relation between the maximum growth rate and the Lundquist number remains unchanged. When the jet is perpendicular to the anti-parallel component of the magnetic field, the most unstable sausage mode is usually perpendicular (wave vector along the jet) without a guide field. But with a finite guide field, the most unstable sausage mode can be oblique, depending on the jet speed and guide field strength.

The conservation of wave action in moving plasmas has been well-known for over half a century. However, wave action is not conserved when multiple wave modes propagate and coexist close to degeneration condition (Sound speed equals Alfv\'en speed, i.e. plasma $\beta \sim 1$). Here we show that the violation of conservation is due to wave mode conversion, and that the total wave action summed over interacting modes is still conserved. Though the result is general, we focus on MHD waves and identify three distinctive mode conversion mechanisms, i.e. degeneracy, linear mode conversion, and resonance, and provide an intuitive physical picture for the mode conversion processes. We use 1D MHD simulations with the Expanding Box Model to simulate the nonlinear evolution of monochromatic MHD waves in the expanding solar wind. Simulation results validate the theory; total wave action therefore remains an interesting diagnostic for studies of waves and turbulence in the solar wind., Comment: Accepted by ApJ

$PSP$ and $SolO$ data are utilized to investigate magnetic field intermittency in the solar wind (SW). Small-scale intermittency $(20-100d_{i})$ is observed to radially strengthen when methods relying on higher-order moments are considered ($SF_q$, $SDK$), but no clear trend is observed at larger scales. However, lower-order moment-based methods (e.g., PVI) are deemed more appropriate for examining the evolution of the bulk of Coherent Structures (CSs), $PVI \ge 3$. Using PVI, we observe a scale-dependent evolution in the fraction of the dataset occupied by CSs, $f_{PVI \ge 3}$. Specifically, regardless of the SW speed, a subtle increase is found in $f_{PVI\ge3}$ for $\ell =20 d_i$, in contrast to a more pronounced radial increase in CSs observed at larger scales. Intermittency is investigated in relation to plasma parameters. Though, slower SW speed intervals exhibit higher $f_{PVI \geq 6}$ and higher kurtosis maxima, no statistical differences are observed for $f_{PVI \geq 3}$. Highly Alfv\'enic intervals, display lower levels of intermittency. The anisotropy with respect to the angle between the magnetic field and SW flow, $\Theta_{VB}$ is investigated. Intermittency is weaker at $\Theta_{VB} \approx 0^{\circ}$ and is strengthened at larger angles. Considering the evolution at a constant alignment angle, a weakening of intermittency is observed with increasing advection time of the SW. Our results indicate that the strengthening of intermittency in the inner heliosphere is driven by the increase in comparatively highly intermittent perpendicular intervals sampled by the probes with increasing distance, an effect related directly to the evolution of the Parker spiral.

The success of Pre-Trained Models (PTMs) has reshaped the development of Natural Language Processing (NLP). Yet, it is not easy to obtain high-performing models and deploy them online for industrial practitioners. To bridge this gap, EasyNLP is designed to make it easy to build NLP applications, which supports a comprehensive suite of NLP algorithms. It further features knowledge-enhanced pre-training, knowledge distillation and few-shot learning functionalities for large-scale PTMs, and provides a unified framework of model training, inference and deployment for real-world applications. Currently, EasyNLP has powered over ten business units within Alibaba Group and is seamlessly integrated to the Platform of AI (PAI) products on Alibaba Cloud. The source code of our EasyNLP toolkit is released at GitHub (https://github.com/alibaba/EasyNLP)., Comment: 8 pages

We use data from the first six encounters of Parker Solar Probe and employ the Partial Variance of Increments ($PVI$) method to study the statistical properties of coherent structures in the inner heliosphere with the aim of exploring physical connections between magnetic field intermittency and observable consequences such as plasma heating and turbulence dissipation. Our results support proton heating localized in the vicinity of, and strongly correlated with, magnetic structures characterized by $PVI \geq 1$. We show that on average, such events constitute $\approx 19\%$ of the dataset, though variations may occur depending on the plasma parameters. We show that the waiting time distribution ($WT$) of identified events is consistent across all six encounters following a power-law scaling at lower $WTs$. This result indicates that coherent structures are not evenly distributed in the solar wind but rather tend to be tightly correlated and form clusters. We observe that the strongest magnetic discontinuities, $PVI \geq 6$, usually associated with reconnection exhausts, are sites where magnetic energy is locally dissipated in proton heating and are associated with the most abrupt changes in proton temperature. However, due to the scarcity of such events, their relative contribution to energy dissipation is minor. Taking clustering effects into consideration, we show that smaller scale, more frequent structures with PVI between, $1\lesssim PVI \lesssim 6$, play the major role in magnetic energy dissipation. The number density of such events is strongly associated with the global solar wind temperature, with denser intervals being associated with higher $T_{p}$., Comment: Accepted for publication in APJ

The effects of the heliospheric current sheet (HCS) on the evolution of Alfv\'enic turbulence in the solar wind are studied using MHD simulations incorporating the expanding-box-model (EBM). The simulations show that near the HCS, the Alfv\'enicity of the turbulence decreases as manifested by lower normalized cross helicity and larger excess of magnetic energy. The numerical results are supported by a superposed-epoch analysis using OMNI data, which shows that the normalized cross helicity decreases inside the plasma sheet surrounding HCS, and the excess of magnetic energy is significantly enhanced at the center of HCS. Our simulation results indicate that the decrease of Alfv\'enicity around the HCS is due to the weakening of radial magnetic field and the effects of the transverse gradient in the background magnetic field. The magnetic energy excess in the turbulence may be a result of the loss of Alfv\'enic correlation between velocity and magnetic field and the faster decay of transverse kinetic energy with respect to magnetic energy in a spherically expanding solar wind.

Named entity recognition (NER) models generally perform poorly when large training datasets are unavailable for low-resource domains. Recently, pre-training a large-scale language model has become a promising direction for coping with the data scarcity issue. However, the underlying discrepancies between the language modeling and NER task could limit the models' performance, and pre-training for the NER task has rarely been studied since the collected NER datasets are generally small or large but with low quality. In this paper, we construct a massive NER corpus with a relatively high quality, and we pre-train a NER-BERT model based on the created dataset. Experimental results show that our pre-trained model can significantly outperform BERT as well as other strong baselines in low-resource scenarios across nine diverse domains. Moreover, a visualization of entity representations further indicates the effectiveness of NER-BERT for categorizing a variety of entities.

One of the most important problems of magnetotail dynamics is the substorm onset and the related instability of the magneotail current sheet. Since the simplest 2D current sheet configuration with monotonic $B_z$ was proven to be stable to the tearing mode, the focus of the instability investigation moved to more specific configurations, e.g. kinetic current sheets with strong transient ion currents and current sheets with non-monotonic $B_z$ (local $B_z$ minima or/and peaks). Stability of the latter current sheet configuration has been studied both within kinetic and fluid approaches, whereas the investigation of the transient ion effects were limited to kinetic models only. This paper aims to provide detailed analysis of stability of a multi-fluid current sheet configuration that mimics current sheets with transient ions. Using the system with two field-aligned ion flows that mimic the effect of pressure non-gyrotropy, we construct 1D current sheet with a finite $B_z$. This model describes well recent findings of very thin intense magnetotail current sheets. The stability analysis of this two-ion model confirms the stabilizing effect of finite $B_z$ and shows that the most stable current sheet is the one with exactly counter-streaming ion flows and zero net flow. Such field-aligned flows may substitute the contribution of the pressure tensor nongyrotropy to the stress balance, but cannot overtake the stabilizing effect of $B_z$. Obtained results are discussed in the context of magnetotail dynamical models and spacecraft observations.

In this work, we reconstruct the $\gamma$-photon energy spectrum which is in good agreement with the experimental data of $^{86}$Kr + $^{12}$C at $E/A$ = 44 MeV in the framework of our modified EQMD model. The directed flow and elliptic flow of free protons and direct photons have been investigated by taking $\alpha$-clustering structure of $^{12}$C into account. Comparing with the free proton, the direct photon flows give a clearer information about early stage of nuclear reaction. Difference of collective flows between different configurations of $^{12}$C is observed in this work. This indicates that collective flows of direct photons are sensitive to the initial configuration, therefore the $\gamma$ bremsstrahlung process might be taken as an alternative probe to investigate $\alpha$-clustering structure in light nucleus from heavy ion collisions at Fermi-energy region., Comment: 10 pages, 9 figures

We analyze magnetic field data from the first six encounters of PSP, three Helios fast streams and two Ulysses south polar passes covering heliocentric distances $0.1\lesssim R\lesssim 3$ au. We use this data set to statistically determine the evolution of switchbacks of different periods and amplitudes with distance from the Sun. We compare the radial evolution of magnetic field variances with that of the mean square amplitudes of switchbacks, and quantify the radial evolution of the cumulative counts of switchbacks per km. We find that the amplitudes of switchbacks decrease faster than the overall turbulent fluctuations, in a way consistent with the radial decrease of the mean magnetic field. This could be the result of a saturation of amplitudes and may be a signature of decay processes of large amplitude Alfv\'enic fluctuations in the solar wind. We find that the evolution of switchback occurrence in the solar wind is scale-dependent: the fraction of longer duration switchbacks increases with radial distance whereas it decreases for shorter switchbacks. This implies that switchback dynamics is a complex process involving both decay and in-situ generation in the inner heliosphere. We confirm that switchbacks can be generated by the expansion although other type of switchbacks generated closer to the sun cannot be ruled out., Comment: Accepted for publication on ApJL

Task-oriented dialogue (ToD) benchmarks provide an important avenue to measure progress and develop better conversational agents. However, existing datasets for end-to-end ToD modeling are limited to a single language, hindering the development of robust end-to-end ToD systems for multilingual countries and regions. Here we introduce BiToD, the first bilingual multi-domain dataset for end-to-end task-oriented dialogue modeling. BiToD contains over 7k multi-domain dialogues (144k utterances) with a large and realistic bilingual knowledge base. It serves as an effective benchmark for evaluating bilingual ToD systems and cross-lingual transfer learning approaches. We provide state-of-the-art baselines under three evaluation settings (monolingual, bilingual, and cross-lingual). The analysis of our baselines in different settings highlights 1) the effectiveness of training a bilingual ToD system compared to two independent monolingual ToD systems, and 2) the potential of leveraging a bilingual knowledge base and cross-lingual transfer learning to improve the system performance under low resource condition., Comment: 22 pages

Representation of semantic context and local details is the essential issue for building modern semantic segmentation models. However, the interrelationship between semantic context and local details is not well explored in previous works. In this paper, we propose a Dynamic Dual Sampling Module (DDSM) to conduct dynamic affinity modeling and propagate semantic context to local details, which yields a more discriminative representation. Specifically, a dynamic sampling strategy is used to sparsely sample representative pixels and channels in the higher layer, forming adaptive compact support for each pixel and channel in the lower layer. The sampled features with high semantics are aggregated according to the affinities and then propagated to detailed lower-layer features, leading to a fine-grained segmentation result with well-preserved boundaries. Experiment results on both Cityscapes and Camvid datasets validate the effectiveness and efficiency of the proposed approach. Code and models will be available at \url{x3https://github.com/Fantasticarl/DDSM}., Comment: accepted by ICIP-2021

In this paper, we propose an effective method for fast and accurate scene parsing called Bidirectional Alignment Network (BiAlignNet). Previously, one representative work BiSeNet~\cite{bisenet} uses two different paths (Context Path and Spatial Path) to achieve balanced learning of semantics and details, respectively. However, the relationship between the two paths is not well explored. We argue that both paths can benefit each other in a complementary way. Motivated by this, we propose a novel network by aligning two-path information into each other through a learned flow field. To avoid the noise and semantic gaps, we introduce a Gated Flow Alignment Module to align both features in a bidirectional way. Moreover, to make the Spatial Path learn more detailed information, we present an edge-guided hard pixel mining loss to supervise the aligned learning process. Our method achieves 80.1\% and 78.5\% mIoU in validation and test set of Cityscapes while running at 30 FPS with full resolution inputs. Code and models will be available at \url{https://github.com/jojacola/BiAlignNet}., Comment: accepted by ICIP-2021

We investigate the transverse momentum weighted azimuthal asymmetry with a $\sin\left(3\phi_h -\phi_S\right)$ modulation in electroproduction of charged pion production off the transversely polarized proton. The asymmetry is contributed by the product of the second transverse-moment of the pretzelosity distribution function and the first transverse-moment of the Collins function. Using the extracted result for the proton pretzelosity and the available parametrization for the pion Collins function, we numerically predict the $P_{hT}^3$-weighted $\sin\left(3\phi_h -\phi_S\right)$ asymmetry for charged pion production at electron ion colliders (EICs). It is found that the weighted asymmetry is around 2 percent in the kinematics region of EICs. Our results show that the planned high luminosity electron ion colliders could be feasible to access pretzelosity in the near future., Comment: 8 page, 2 figures

We make use of the Parker Solar Probe (PSP) data to explore the nature of solar wind turbulence focusing on the Alfv\'enic character and power spectra of the fluctuations and their dependence on distance and context (i.e. large scale solar wind properties), aiming to understand the role that different effects such as source properties, solar wind expansion, stream interaction might play in determining the turbulent state. We carry out a statistical survey of the data from the first five orbits of PSP with a focus on how the fluctuation properties at the large, MHD scales, vary with different solar wind streams and distance from the Sun. A more in-depth analysis from several selected periods is also presented. Our results show that as fluctuations are transported outward by the solar wind, the magnetic field spectrum steepens while the shape of the velocity spectrum remains unchanged. The steepening process is controlled by the "age" of the turbulence, determined by the wind speed together with the radial distance. Statistically, faster solar wind has higher "Alfv\'enicity", with more dominant outward propagating wave component and more balanced magnetic/kinetic energies. The outward wave dominance gradually weakens with radial distance, while the excess of magnetic energy is found to be stronger as we move closer toward the Sun. We show that the turbulence properties can vary significantly stream to stream even if these streams are of similar speed, indicating very different origins of these streams. Especially, the slow wind that originates near the polar coronal holes has much lower Alfv\'enicity compared with the slow wind that originates from the active regions/pseudostreamers. We show that structures such as heliospheric current sheets and velocity shears can play an important role in modifying the properties of the turbulence.

The tearing mode instability is one important mechanism that may explain the triggering of fast magnetic reconnection in astrophysical plasmas such as the solar corona and the Earth's magnetosphere. In this paper, the linear stability analysis of the tearing mode is carried out for a current sheet in the presence of a guide field, including the Hall effect. We show that the presence of a strong guide field does not modify the most unstable mode in the two-dimensional wave vector space orthogonal to the current gradient direction, which remains the fastest growing parallel mode. With the Hall effect, the inclusion of a guide field turns the non-dispersive propagation along the guide field direction to a dispersive one. The oblique modes have a wave-like structure along the normal direction of the current sheet and a strong guide field suppresses this structure while making the eigen-functions asymmetric.

In contrast with the fast solar wind, that originates in coronal holes, the source of the slow solar wind is still debated. Often intermittent and enriched with low FIP elements -- akin to what is observed in closed coronal loops -- the slow wind could form in bursty events nearby helmet streamers. Slow winds also exhibit density perturbations which have been shown to be periodic and could be associated with flux ropes ejected from the tip of helmet streamers, as shown recently by the WISPR white light imager onboard Parker Solar Probe (PSP). In this work, we propose that the main mechanism controlling the release of flux ropes is a flow-modified tearing mode at the heliospheric current sheet (HCS). We use MHD simulations of the solar wind and corona to reproduce realistic configurations and outflows surrounding the HCS. We find that this process is able to explain long ($\sim 10-20$h) and short ($\sim 1-2$h) timescales of density structures observed in the slow solar wind. This study also sheds new light on the structure, topology and composition of the slow solar wind, and could be, in the near future, compared with white light and in situ PSP observations., Comment: 8 pages, 5 figures, accepted for publication in ApJL

We apply the transverse momentum dependent factorization formalism to investigate the transverse single spin dependent Collins asymmetry with a $\sin(\phi_h+\phi_s)$ modulation in the semi-inclusive production of Kaon meson in deep inelastic scattering process. The asymmetry is contributed by the convolutions of the transversity distribution function $h_1(x)$ of the target proton and the Collins function of the Kaon in the final state. We adopt the available parametrization of $h_1(x)$ as well as the recent extracted result for the Kaon Collins function. To perform the transverse momentum dependent evolution, the parametrization of the nonperturbative Sudakov form factor of the proton and final state Kaon are utilized. We numerically predict the Collins asymmetry for charged Kaon production at the electron ion colliders within the accuracy of next-to-leading-logarithmic order. It is found that the asymmetry is sizable and could be measured. We emphasize the importance of planned electron ion colliders in the aspect of constraining sea quark distribution functions as well as accessing the information of the nucleon spin structure and the hadronization mechanism.

During Parker Solar Probe's first orbit, the solar wind plasma has been observed in situ closer than ever before, the perihelion on November 6th 2018 revealing a flow that is constantly permeated by large amplitude Alfv\'enic fluctuations. These include radial magnetic field reversals, or switchbacks, that seem to be a persistent feature of the young solar wind. The measurements also reveal a very strong, unexpected, azimuthal velocity component. In this work, we numerically model the solar corona during this first encounter, solving the MHD equations and accounting for Alfv\'en wave transport and dissipation. We find that the large scale plasma parameters are well reproduced, allowing the computation of the solar wind sources at Probe with confidence. We try to understand the dynamical nature of the solar wind to explain both the amplitude of the observed radial magnetic field and of the azimuthal velocities., Comment: Accepted Erratum includeded as an appendix. Updated references. 17 pages, 9 figures total

Parker Solar Probe (PSP) observations during its first encounter at 35.7 $R_\odot$ have shown the presence of magnetic field lines which are strongly perturbed to the point that they produce local inversions of the radial magnetic field, known as switchbacks. Their counterparts in the solar wind velocity field are local enhancements in the radial speed, or jets, displaying (in all components) the velocity-magnetic field correlation typical of large amplitude Alfv\'en waves propagating away from the Sun. Switchbacks and radial jets have previously been observed over a wide range of heliocentric distances by Helios, WIND and Ulysses, although they were prevalent in significantly faster streams than seen at PSP. Here we study via numerical MHD simulations the evolution of such large amplitude Alfv\'enic fluctuations by including, in agreement with observations, both a radial magnetic field inversion and an initially constant total magnetic pressure. Despite the extremely large excursion of magnetic and velocity fields, switchbacks are seen to persist for up to hundreds of Alfv\'en crossing times before eventually decaying due to the parametric decay instability. Our results suggest that such switchback/jet configurations might indeed originate in the lower corona and survive out to PSP distances, provided the background solar wind is sufficiently calm, in the sense of not being pervaded by strong density fluctuations or other gradients, such as stream or magnetic field shears, that might destabilize or destroy them over shorter timescales., Comment: Accepted for publication on APJ PSP special issue

We carry out two-dimensional magnetohydrodynamic (MHD) simulations of an ensemble of Alfv\'enic fluctuations propagating in a structured, expanding solar wind including the presence of fast and slow solar wind streams. Using an appropriate expanding box model, the simulations incorporate the effects of fast-slow stream shear and compression and rarefaction self-consistently. We investigate the radial and longitudinal evolution of the cross-helicity, the total and residual energies and the power spectra of outward and inward Alfv\'enic fluctuations. The stream interaction is found to strongly affect the radial evolution of Alfv\'enic turbulence. The total energy in the Alfv\'en waves is depleted within the velocity shear regions, accompanied by the decrease of the normalized cross-helicity. The presence of stream-compression facilitates this process. Residual energy fluctuates around zero due to the correlation and de-correlation between the inward/outward waves but no net growth or decrease of the residual energy is observed. The radial power spectra of the inward/outward Alfv\'en waves show significant longitudinal variations. Kolmogorov-like spectra are developed only inside the fast and slow streams and when both the compression and shear are present. On the other hand, the spectra along the longitudinal direction show clear Kolmogorov-like inertial ranges in all cases.