Searcharxiv⌕ Search

arXiv subjects

Chen Shi

Publications and source records attributed to Chen Shi.

At least 19 recordsLinked to original sources
arXiv2026

Spherically Polarized Alfv\'en Waves and the Gosling Boost

Alfv\'en waves are thought to play critical roles in solar wind acceleration and plasma heating in the solar corona and inner heliosphere. Parker Solar Probe (PSP) has highlighted the role of large amplitude Spherically Polarized Alfv\'en Waves (SPAWs), where the locally constant magnetic field magnitude $|\mathbf{B}|$ together with outward propagation explains the observed one sided radial velocity enhancement - the Gosling boost. Starting from the MHD equations, we derive the modified wave pressure and Poynting flux under the SPAW condition, and demonstrate both are governed solely by the transverse magnetic fluctuations. Using PSP data from Encounters 6--25, we define an unperturbed velocity baseline from the lower 10th-percentile running average and statistically characterize the radial evolution of Alfv\'enic fluctuations. The background solar wind velocity shows clear radial acceleration, while the velocity perturbation amplitude $\delta v$ decreases with heliocentric distance. This decay is anisotropic between the radial and perpendicular directions, which is a direct consequence of the growing magnetic deflection angle related to the spherical polarization. Our results demonstrate that radial velocity enhancements in the young solar wind arise naturally from SPAWs rather than from localized velocity jets, and provide direct observational evidence for the anisotropic radial evolution of SPAWs in the inner heliosphere.

astro-ph.SR↗
arXiv2026

Radial Evolution of Near-Sun Magnetic Switchbacks Alfvenicity, Occurrence Rate, and Size

Magnetic switchbacks, characterized by reversals of magnetic field direction, are widely observed in the inner heliosphere by Parker Solar Probe (PSP). With PSP reaching perihelia near 10Rs, observations from the first 24 encounters enable studies of near-Sun switchback evolution at r > 10Rs. We construct a switchback catalog within 10 < r < 55Rs by identifying magnetic field reversals with stable field magnitude and strahl-electron polarity. Statistical analysis shows that switchback Alfvenicity decreases with increasing radial distance, consistent with solar wind evolution beyond the Alfven critical point. Meanwhile, switchback occurrence rate and spatial size increase with distance, suggesting continued generation and expansion during solar wind propagation. At a given radial distance, the fraction of solar wind containing switchbacks is positively correlated with background solar wind radial velocity (VR) and Alfven Mach number (MA), while the local occurrence rate is mainly controlled by MA. These results suggest that switchback patches preferentially form in faster and higher-MA solar wind. The spatial size of switchbacks shows no clear dependence on MA or VR, implying that their size evolution is probably not determined by source conditions. Solar activity influences switchback evolution through changes in background solar wind properties, with a larger fraction of higher-MA switchbacks during solar minimum. We further identify anisotropy relative to the background magnetic field direction: the local occurrence rate and spatial size are approximately 1.5 times as large in the perpendicular direction as in the parallel direction, indicating distinct magnetic topology of switchback patches

astro-ph.SR↗
arXiv2026

Evolution and Impact of Switchbacks Throughout the Heliosphere

Magnetic switchbacks are large-amplitude fluctuations in the interplanetary magnetic field, and appear frequently in the near-Sun solar wind explored recently by Parker Solar Probe: these new observations have prompted many new studies into their properties and origins. Here, we first review what is known about how switchbacks evolve as they travel away from the Sun: both in terms of their expansion-driven growth and their decay due to various processes like turbulence, reconnection, dispersion, parametric instability, and interaction with interplanetary shocks. We then review the current state of knowledge on how switchbacks impact the physics of the solar wind as a whole: in terms of the turbulent cascade, acceleration and heating of the wind, modification of the open solar flux and scattering of energetic particles. Finally, we suggest future studies to further our understanding of switchback evolution and impacts on the heliosphere.

physics.space-ph↗
arXiv2026

Plasma Instabilities in Arbitrary Distributions: Comparison between ALPS and BO

Determining accurate wave dispersion relations is a central problem in plasma physics. Recent advances have enabled the numerical computation of linear dispersion relation in plasmas with arbitrary particle velocity distribution functions (VDFs), using two distinct solvers, BO and ALPS. Their reliability and mutual consistency, however, have not been systematically tested for a broad range of VDFs. Here we compare the dispersion relations obtained from BO and ALPS for several representative distributions. We find that the two solvers give consistent unstable modes for kappa distributions with large values of $\kappa$, as well as for ring-beam, shell, and proton core-beam distributions. BO, however, becomes unreliable for kappa distributions with $\kappa < 4$. For an observationally derived VDF, the two solvers give similar real frequencies for the unstable waves but substantially different growth rates. This difference is mainly caused by the imperfect fitting of the input distribution required by BO. Despite this limitation, BO has a clear computational advantage because it can obtain all roots in a single run. Considering the complementary strengths of the two solvers, their combined use can provide a more reliable and effective framework for investigating instabilities in non-Maxwellian plasma environments.

physics.plasm-ph↗
arXiv2026

Denoising Tells When to Replan: Denoising-Variance Adaptive Chunking for Flow-Based Robot Policies

Action chunking has become a common inference strategy for flow-based robot policies, improving action coherence by modeling multi-step temporal dependencies in demonstrations. However, the execution horizon is still typically set as an empirical fixed value, overlooking that predictable free-space motions and precision-critical interaction phases often require different replanning frequencies. In this work, we first show that the denoising process of flow-based policies contains an intrinsic signal of task phases: clean-action estimates remain stable during predictable motion phases, but fluctuate more strongly around contact-rich or precision-sensitive operations. Motivated by this observation, we propose DVAC (Denoising-Variance Adaptive Chunking), a test-time method that adaptively determines how many actions to execute from each predicted chunk. DVAC measures the variance of clean-action estimates over the final denoising steps, executes the stable low-variance prefix, and replans before high-variance future actions are committed. To transfer across tasks and rollouts, DVAC further calibrates the threshold with a rolling estimate of the local variance scale. Experiments on LIBERO, RoboTwin, CALVIN, and real-world manipulation show that DVAC improves task success while reducing replanning frequency. With a $\pi_{0.5}$-based policy, DVAC improves LIBERO success from 94.75% to 98.00% and reduces replanning by 43.0%, while also yielding aggregate gains on RoboTwin and CALVIN and improving real-world execution efficiency.

cs.RO↗
arXiv2026

DriveWAM: Video Generative Priors Enable Scalable World-Action Modeling for Autonomous Driving

Pretrained foundation models have become an important basis for end-to-end autonomous driving. In contrast to vision-language models pretrained primarily on static image-text pairs, video generative models capture temporal dynamics and motion priors that are naturally suited for driving. We present DriveWAM, a driving world-action model that adapts a pretrained video diffusion transformer into an autoregressive video-action policy. DriveWAM organizes video and action streams into a unified temporal token sequence and trains them under a joint flow-matching objective, preserving the pretrained video-generation architecture while adapting its large-scale video priors to action generation. To incorporate high-level scene understanding, we introduce scene-evolving driving guidance, where a frozen VLM produces chunk-specific semantic intent to guide video-action generation. To keep long-horizon rollout bounded, we further introduce selective KV memory, which maintains bounded modality-aware video and action memory pools through relevance-redundancy cache selection at inference time. Experiments on NAVSIM and the PhysicalAI-Autonomous-Vehicles benchmark show that DriveWAM achieves strong planning performance, and a data-scaling study from 4k to 100k driving clips further confirms the scaling potential of world-action modeling for end-to-end autonomous driving.

cs.CV↗
arXiv2026

Magnetic switchback formation: a review of proposed mechanisms

Magnetic switchbacks are large amplitude deflections of the magnetic field within the solar wind. They are Alfv\'enic in character and so are associated with a spike in velocity and a generally small variation in local plasma density. Early orbits of Parker Solar Probe revealed that the solar wind near the Sun is dominated by these structures, and therefore, they may be playing an important role in the energy budget and acceleration of the young solar wind. In this review, we present an overview of different mechanisms that have been proposed for how switchbacks could be formed. We group the mechanisms by whether they predominantly act in the low solar atmosphere or within the solar wind (in situ). We focus on mechanisms that can create reversals of the ambient magnetic field direction and, thus, account for the most extreme perturbations. The general consensus is that mechanisms in the lower solar atmosphere do not form such reversals on their own but provide the seed perturbations, flows, or particle beams necessary for in situ mechanisms to create switchbacks within the solar wind. Switchback observations thus likely contain an imprint of the coronal source of the seed perturbation or flow, which is evolved further locally by one of several plausible in situ mechanisms. We discuss the strengths and weaknesses of each mechanism and outline future observational and theoretical tests that could help differentiate between them.

astro-ph.SR↗
arXiv2026

ESCAPE: Episodic Spatial Memory and Adaptive Execution Policy for Long-Horizon Mobile Manipulation

Coordinating navigation and manipulation with robust performance is essential for embodied AI in complex indoor environments. However, as tasks extend over long horizons, existing methods often struggle due to catastrophic forgetting, spatial inconsistency, and rigid execution. To address these issues, we propose ESCAPE (Episodic Spatial Memory Coupled with an Adaptive Policy for Execution), operating through a tightly coupled perception-grounding-execution workflow. For robust perception, ESCAPE features a Spatio-Temporal Fusion Mapping module to autoregressively construct a depth-free, persistent 3D spatial memory, alongside a Memory-Driven Target Grounding module for precise interaction mask generation. To achieve flexible action, our Adaptive Execution Policy dynamically orchestrates proactive global navigation and reactive local manipulation to seize opportunistic targets. ESCAPE achieves state-of-the-art performance on the ALFRED benchmark, reaching 65.09% and 60.79% success rates in test seen and unseen environments with step-by-step instructions. By reducing redundant exploration, our ESCAPE attains substantial improvements in path-length-weighted metrics and maintains robust performance (61.24% / 56.04%) even without detailed guidance for long-horizon tasks.

cs.CV↗
arXiv2026

Factor-Adjusted Multiple Testing for High-Dimensional Individual Mediation Effects

Identifying individual mediators is a central goal of high-dimensional mediation analysis, yet pervasive dependence among mediators can invalidate standard debiased inference and lead to substantial false discovery rate (FDR) inflation. We propose a Factor-Adjusted Debiased Mediation Testing (FADMT) framework that enables large-scale inference for individual mediation effects with FDR control under complex dependence structures. Our approach posits an approximate factor structure on the unobserved errors of the mediator model, extracts common latent factors, and constructs decorrelated pseudo-mediators for the subsequent inferential procedure. We establish the asymptotic normality of the debiased estimator and develop a multiple testing procedure with theoretical FDR control under mild high-dimensional conditions. By adjusting for latent factor induced dependence, FADMT also improves robustness to spurious associations driven by shared latent variation in observational studies. Extensive simulations demonstrate the superior finite-sample performance across a wide range of correlation structures. Applications to TCGA-BRCA multi-omics data and to China's stock connect study further illustrate the practical utility of the proposed method.

stat.ME↗
arXiv2026

Generation and Expansion-Driven Growth of Switchbacks in the Outer Solar Corona and Solar Wind

We analyze \emph{Parker Solar Probe} and \emph{Solar Orbiter} measurements of magnetic-field reversals (``switchbacks'') across the Alfv\'en surface ($M_a\simeq 1$), where $M_a$ is the Alfv\'en Mach number. The reported ``sub-Alfv\'enic switchback dropout'' follows from two diagnostic biases: conditioning on an instantaneous $M_a$, which is transiently elevated above unity by radial-velocity enhancements during large-amplitude Alfv\'enic rotations, and short-window local-mean backgrounds that partially track these rotations and suppress deflection angles. Treating $M_a$ as a bulk-stream property via rolling medians and referencing deflections to event-independent backgrounds -- a Parker-spiral direction or a sufficiently long rolling median -- recovers sub-Alfv\'enic switchbacks systematically. The mean deflection $\langle \theta \rangle$ separates into two regimes with $M_a$. For $M_a \lesssim 1$, $\langle \theta \rangle$ rises rapidly with weak dependence on the background window, consistent with expansion-driven amplification of Alfv\'enic fluctuations. For $M_a \gtrsim 1$, the evolution becomes scale dependent: large-scale $\langle \theta \rangle$ continues to grow with $M_a$ at reduced rate, while small-scale growth saturates, consistent with turbulent decay and dissipation. Collectively, these results indicate that switchbacks need not originate only in the super-Alfv\'enic solar wind. Instead, they are consistent with a formation pathway in which coronal fluctuations are amplified by large-scale expansion through the sub-Alfv\'enic regime, with subsequent propagation into the super-Alfv\'enic wind where turbulent decay modifies their scale-dependent properties.

physics.space-ph↗
arXiv2026

Conversion Layer Controls the Evolution of Magnetic Deflections Near the Alfven Surface

We examine the statistics of Alfvenic deflections in both sub-Alfvenic and super-Alfvenic solar wind with particular focus on a common parameter that underlies the definition of switchbacks: the magnetic deflection angle. Our findings are in general agreement with earlier studies that suggest magnetic deflection angles > 90 degrees are very unlikely to occur in sub-Alfvenic regimes. We find that their upper limit exhibits an identifiable trend with the Alfven Mach number Ma, suggesting that gradual steepening of Alfvenic deflections with increasing Ma is a plausible mechanism controlling deflection angles in the young solar wind. Further analysis reveals that large velocity fluctuations tend to be important in the largest sub-Alfvenic magnetic deflections with increasing contributions from the parallel component very close to Ma = 1, while virtually no magnetic deflections in the super-Alfvenic regime exhibit such large velocity perturbations. We also determine the local ratio of radial Poynting flux SR to kinetic energy flux KR and find that large sub-Alfvenic deflection angles tend to be dominated by SR, while super-Alfvenic deflections are eventually dominated by the KR associated with the radial solar wind flow. Our results show that within the vicinity of the Alfven surface (where Ma = 1), there is a critical region of parameter space within which velocity deflections approach the Alfven velocity and KR/SR is close to unity. We refer to this region (where | log10(Ma)| < 0.2) as the conversion layer. The conversion layer may play a significant role in the evolution of magnetic defections by providing the medium for converting magnetic energy to particle energy and likely driving the formation of magnetic switchbacks in super-Alfvenic solar wind.

astro-ph.SR↗
arXiv2025

GeoPredict: Leveraging Predictive Kinematics and 3D Gaussian Geometry for Precise VLA Manipulation

Vision-Language-Action (VLA) models achieve strong generalization in robotic manipulation but remain largely reactive and 2D-centric, making them unreliable in tasks that require precise 3D reasoning. We propose GeoPredict, a geometry-aware VLA framework that augments a continuous-action policy with predictive kinematic and geometric priors. GeoPredict introduces a trajectory-level module that encodes motion history and predicts multi-step 3D keypoint trajectories of robot arms, and a predictive 3D Gaussian geometry module that forecasts workspace geometry with track-guided refinement along future keypoint trajectories. These predictive modules serve exclusively as training-time supervision through depth-based rendering, while inference requires only lightweight additional query tokens without invoking any 3D decoding. Experiments on RoboCasa Human-50, LIBERO, and real-world manipulation tasks show that GeoPredict consistently outperforms strong VLA baselines, especially in geometry-intensive and spatially demanding scenarios.

cs.CV↗
arXiv2025

Solitary Alfv\'en Waves

We present the solitary Alfv\'en wave as an ideal nonlinear Alfv\'enic solution in the solitary far-field limit and construct a three-dimensional numerical model -- an \emph{Alfv\'enon}. The model is characterized by an unperturbed far field, quasi-constant $|\boldsymbol{B}|$, and open field-line topology. Direct MHD simulations of the Alfv\'enon show coherent finite-time propagation, confirming that it behaves as a nonlinear solitary Alfv\'enic solution under ideal MHD evolution.

astro-ph.SR↗
arXiv2025

In situ Evidence of 5-minute Oscillations from Parker Solar Probe

The Sun's surface vibrates in characteristic 5-minute oscillations, known as p-modes, generated by sound waves trapped within the convection zone. Although these oscillations have long been hypothesized to reach into the solar wind, direct in situ evidence has remained elusive, even during previous close encounters by Parker Solar Probe (PSP). Here, we present the first promising in situ detection of 5-minute oscillations in the upper solar corona, based on observations from PSP's three closest perihelia. In two events at 9.9 solar radii, we identify statistically significant ($\sim$ 6 $\sigma$) 3.1-3.2 mHz peaks in the magnetic field power spectrum, each appearing as a large-amplitude, spherically polarized Alfv\'enic wave train lasting approximately 35 minutes. These results demonstrate that global solar oscillations can reach and potentially influence the solar wind.

astro-ph.SR↗
arXiv2025

UniSplat: Unified Spatio-Temporal Fusion via 3D Latent Scaffolds for Dynamic Driving Scene Reconstruction

Feed-forward 3D reconstruction for autonomous driving has advanced rapidly, yet existing methods struggle with the joint challenges of sparse, non-overlapping camera views and complex scene dynamics. We present UniSplat, a general feed-forward framework that learns robust dynamic scene reconstruction through unified latent spatio-temporal fusion. UniSplat constructs a 3D latent scaffold, a structured representation that captures geometric and semantic scene context by leveraging pretrained foundation models. To effectively integrate information across spatial views and temporal frames, we introduce an efficient fusion mechanism that operates directly within the 3D scaffold, enabling consistent spatio-temporal alignment. To ensure complete and detailed reconstructions, we design a dual-branch decoder that generates dynamic-aware Gaussians from the fused scaffold by combining point-anchored refinement with voxel-based generation, and maintain a persistent memory of static Gaussians to enable streaming scene completion beyond current camera coverage. Extensive experiments on real-world datasets demonstrate that UniSplat achieves state-of-the-art performance in novel view synthesis, while providing robust and high-quality renderings even for viewpoints outside the original camera coverage.

cs.CV↗
arXiv2025

Properties of current sheets in two-dimensional tearing-mediated incompressible magnetohydrodynamic turbulence

It is well known that the nonlinear evolution of magnetohydrodynamic (MHD) turbulence generates current sheets. In the solar wind turbulence, current sheets are frequently observed and they are believed to be an important pathway for the turbulence energy to dissipate and heat the plasma. In this study, we perform a comprehensive analysis of current sheets in a high-resolution two-dimensional simulation of balanced, incompressible MHD turbulence. The simulation parameters are selected such that tearing mode instability is triggered and plasmoids are generated throughout the simulation domain. We develop an automated method to identify current sheets and accurately quantify their key parameters including thickness ($a$), length ($L$), and Lundquist number ($S$). Before the triggering of tearing instability, the current sheet lengths are mostly comparable to the energy injection scale. After the tearing mode onsets, smaller current sheets with lower Lundquist numbers are generated. While power-law scaling relations between $L$ and $a$ and between $a/L$ and $S$ are observed, no clear correlation is found between the upstream magnetic field strength and thickness $a$. Finally, although the turbulence energy shows anisotropy between the directions parallel and perpendicular to the local magnetic field increment, we do not observe a direct correspondence between the shape of the current sheets and that of the turbulence ``eddies.'' These results suggest that one needs to be cautious when applying the scale-dependent dynamic alignment model to the analysis of current sheets in MHD turbulence.

astro-ph.SR↗
arXiv2025

On the Propagation and Damping of Alfvenic Fluctuations in the Outer Solar Corona and Solar Wind

We analyze \textit{Parker Solar Probe} and \textit{Solar Orbiter} observations to investigate the propagation and dissipation of Alfv\'enic fluctuations from the outer corona to 1~AU. Conservation of wave-action flux provides the theoretical baseline for how fluctuation amplitudes scale with the Alfv\'en Mach number $M_a$, once solar-wind acceleration is accounted for. Departures from this scaling quantify the net balance between energy injection and dissipation. Fluctuation amplitudes follow wave-action conservation for $M_a < M_a^{b}$ but steepen beyond this break point, which typically lies near the Alfv\'en surface ($M_a \approx 1$) yet varies systematically with normalized cross helicity $\sigma_c$ and fluctuation scale. In slow, quasi-balanced streams, the transition occurs at $M_a \lesssim 1$; in fast, imbalanced wind, WKB-like scaling persists to $M_a \gtrsim 1$. Outer-scale fluctuations maintain wave-action conservation to larger $M_a$ than inertial-range modes. The turbulent heating rate $Q$ is largest below $M_a^{b}$, indicating a preferential heating zone shaped by the degree of imbalance. Despite this, the Alfv\'enic energy flux $F_a$ remains elevated, and the corresponding damping length $\Lambda_d = F_a/Q$ remains sufficiently large to permit long-range propagation before appreciable damping occurs. Normalized damping lengths $\Lambda_d/H_A$, where $H_A$ is the inverse Alfv\'en-speed scale height, are near unity for $M_a \lesssim M_a^{b}$ but decline with increasing $M_a$ and decreasing $U$, implying that incompressible reflection-driven turbulence alone cannot account for the observed dissipation. Additional damping mechanisms -- such as compressible effects -- are likely required to account for the observed heating rates across much of the parameter space.

astro-ph.SR↗
arXiv2025

CX-Mind: A Pioneering Multimodal Large Language Model for Interleaved Reasoning in Chest X-ray via Curriculum-Guided Reinforcement Learning

Chest X-ray (CXR) imaging is one of the most widely used diagnostic modalities in clinical practice, encompassing a broad spectrum of diagnostic tasks. Recent advancements have seen the extensive application of reasoning-based multimodal large language models (MLLMs) in medical imaging to enhance diagnostic efficiency and interpretability. However, existing multimodal models predominantly rely on "one-time" diagnostic approaches, lacking verifiable supervision of the reasoning process. This leads to challenges in multi-task CXR diagnosis, including lengthy reasoning, sparse rewards, and frequent hallucinations. To address these issues, we propose CX-Mind, the first generative model to achieve interleaved "think-answer" reasoning for CXR tasks, driven by curriculum-based reinforcement learning and verifiable process rewards (CuRL-VPR). Specifically, we constructed an instruction-tuning dataset, CX-Set, comprising 708,473 images and 2,619,148 samples, and generated 42,828 high-quality interleaved reasoning data points supervised by clinical reports. Optimization was conducted in two stages under the Group Relative Policy Optimization framework: initially stabilizing basic reasoning with closed-domain tasks, followed by transfer to open-domain diagnostics, incorporating rule-based conditional process rewards to bypass the need for pretrained reward models. Extensive experimental results demonstrate that CX-Mind significantly outperforms existing medical and general-domain MLLMs in visual understanding, text generation, and spatiotemporal alignment, achieving an average performance improvement of 25.1% over comparable CXR-specific models. On real-world clinical dataset (Rui-CXR), CX-Mind achieves a mean recall@1 across 14 diseases that substantially surpasses the second-best results, with multi-center expert evaluations further confirming its clinical utility across multiple dimensions.

cs.LG↗