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Qiang Hu

Publications and source records attributed to Qiang Hu.

At least 127 records · Page 7Linked to original sources
arXiv2023

VideoRF: Rendering Dynamic Radiance Fields as 2D Feature Video Streams

Neural Radiance Fields (NeRFs) excel in photorealistically rendering static scenes. However, rendering dynamic, long-duration radiance fields on ubiquitous devices remains challenging, due to data storage and computational constraints. In this paper, we introduce VideoRF, the first approach to enable real-time streaming and rendering of dynamic radiance fields on mobile platforms. At the core is a serialized 2D feature image stream representing the 4D radiance field all in one. We introduce a tailored training scheme directly applied to this 2D domain to impose the temporal and spatial redundancy of the feature image stream. By leveraging the redundancy, we show that the feature image stream can be efficiently compressed by 2D video codecs, which allows us to exploit video hardware accelerators to achieve real-time decoding. On the other hand, based on the feature image stream, we propose a novel rendering pipeline for VideoRF, which has specialized space mappings to query radiance properties efficiently. Paired with a deferred shading model, VideoRF has the capability of real-time rendering on mobile devices thanks to its efficiency. We have developed a real-time interactive player that enables online streaming and rendering of dynamic scenes, offering a seamless and immersive free-viewpoint experience across a range of devices, from desktops to mobile phones.

cs.CV↗
arXiv2023

Revisit to the yield ratio of triton and $^3$He as an indicator of neutron-rich neck emission

The neutron rich neck zone created in heavy ion reaction is experimentally probed by the production of the $A=3$ isobars. The energy spectra and angular distributions of triton and $^3$He are measured with the CSHINE detector in $^{86}$Kr +$^{208}$Pb reactions at 25 MeV/u. While the energy spectrum of $^{3}$He is harder than that of triton, known as "$^{3}$He-puzzle", the yield ratio $R({\rm t/^3He})$ presents a robust rising trend with the polar angle in laboratory. Using the fission fragments to reconstruct the fission plane, the enhancement of out-plane $R({\rm t/^3He})$ is confirmed in comparison to the in-plane ratios. Transport model simulations reproduce qualitatively the experimental trends, but the quantitative agreement is not achieved. The results demonstrate that a neutron rich neck zone is formed in the reactions. Further studies are called for to understand the clustering and the isospin dynamics related to neck formation.

nucl-ex↗
arXiv2023

A Black-Box Attack on Code Models via Representation Nearest Neighbor Search

Existing methods for generating adversarial code examples face several challenges: limted availability of substitute variables, high verification costs for these substitutes, and the creation of adversarial samples with noticeable perturbations. To address these concerns, our proposed approach, RNNS, uses a search seed based on historical attacks to find potential adversarial substitutes. Rather than directly using the discrete substitutes, they are mapped to a continuous vector space using a pre-trained variable name encoder. Based on the vector representation, RNNS predicts and selects better substitutes for attacks. We evaluated the performance of RNNS across six coding tasks encompassing three programming languages: Java, Python, and C. We employed three pre-trained code models (CodeBERT, GraphCodeBERT, and CodeT5) that resulted in a cumulative of 18 victim models. The results demonstrate that RNNS outperforms baselines in terms of ASR and QT. Furthermore, the perturbation of adversarial examples introduced by RNNS is smaller compared to the baselines in terms of the number of replaced variables and the change in variable length. Lastly, our experiments indicate that RNNS is efficient in attacking defended models and can be employed for adversarial training.

cs.CR↗
arXiv2023

Magnetic Reconnection as the Key Mechanism in Sunspot Rotation Leading to Solar Eruption

The rotation of sunspots around their umbral center has long been considered as an important process in leading to solar eruptions, but the underlying mechanism remains unclear. A prevailing physical picture on how sunspot rotation leads to eruption is that, by twisting the coronal magnetic field lines from their footpoints, the rotation can build up a magnetic flux rope and drive it into some kinds of ideal magnetohydrodynamics (MHD) instabilities which initiate eruptions. Here with a data-inspired MHD simulation we studied the rotation of a large sunspot in solar active region NOAA 12158 leading to a major eruption, and found that it is distinct from prevailing theories based on ideal instabilities of twisted flux rope. The simulation suggests that, through successive rotation of the sunspot, the coronal magnetic field is sheared with a central current sheet created progressively within the sheared arcade before the eruption, but without forming a flux rope. Then the eruption is instantly triggered once fast reconnection sets in at the current sheet, while a highly twisted flux rope is created during the eruption. Furthermore, the simulation reveals an intermediate evolution stage between the quasi-static energy-storage phase and the impulsive eruption-acceleration phase. This stage may correspond to the slow-rise phase in observation and it enhances building up of the current sheet.

astro-ph.SR↗
arXiv2023

Characterization of Magnetic Flux Contents for Flux Transfer Events and its Implications for Flux Rope Formation at the Earth's Magnetopause

Flux transfer events (FTEs) are a type of magnetospheric phenomena that exhibit distinctive observational signatures from the in-situ spacecraft measurements across the Earth's magnetopause. They are generally believed to possess a magnetic field configuration of a magnetic flux rope and formed through magnetic reconnection at the dayside magnetopause, sometimes accompanied with enhanced plasma convection in the ionosphere. We examine two FTE events under the condition of southward interplanetary magnetic field (IMF) with a dawn-dusk component at the magnetopause by applying the Grad-Shafranov (GS) reconstruction method to the in-situ measurements by the Magnetospheric Multiscale (MMS) spacecraft to derive the magnetic flux contents associated with the FTE flux ropes. In particular, given a cylindrical magnetic flux rope configuration derived from the GS reconstruction, the magnetic flux content can be characterized by both the toroidal (axial) and poloidal fluxes. We then estimate the amount of magnetic flux (i.e., the reconnection flux) encompassed by the area ``opened" in the ionosphere, based on the ground-based Super Dual Auroral Radar Network (SuperDARN) observations. We find that for event 1, the FTE flux rope is oriented in the approximate dawn-dusk direction, and the amount of its poloidal magnetic flux agrees with the corresponding reconnection flux. For event 2, the agreement among the estimates of the magnetic fluxes is uncertain. We provide a detailed description about our interpretation for the topological features of the FTE flux ropes, based on a formation scenario of sequential magnetic field reconnection between adjacent field lines, consistent with our results.

physics.space-ph↗
arXiv2023

Data-driven MHD simulation of a sunspot rotating active region leading to solar eruption

Solar eruptions are the leading driver of space weather, and it is vital for space weather forecast to understand in what conditions the solar eruptions can be produced and how they are initiated. The rotation of sunspots around their umbral center has long been considered as an important condition in causing solar eruptions. To unveil the underlying mechanisms, here we carried out a data-driven magnetohydrodynamics simulation for the event of a large sunspot with rotation for days in solar active region NOAA 12158 leading to a major eruption. The photospheric velocity as recovered from the time sequence of vector magnetograms are inputted directly at the bottom boundary of the numerical model as the driving flow. Our simulation successfully follows the long-term quasi-static evolution of the active region until the fast eruption, with magnetic field structure consistent with the observed coronal emission and onset time of simulated eruption matches rather well with the observations. Analysis of the process suggests that through the successive rotation of the sunspot the coronal magnetic field is sheared with a vertical current sheet created progressively, and once fast reconnection sets in at the current sheet, the eruption is instantly triggered, with a highly twisted flux rope originating from the eruption. This data-driven simulation stresses magnetic reconnection as the key mechanism in sunspot rotation leading to eruption.

astro-ph.SR↗
arXiv2023

Sequential Small Coronal Mass Ejections Observed In~situ and in White-Light Images by Parker Solar Probe

We reconstruct the morphology and kinematics of a series of small transients that erupt from the Sun on 2021 April 24 using observations primarily from Parker Solar Probe (PSP). These sequential small coronal mass ejections (CMEs) may be the product of continuous reconnection at a current sheet, a macroscopic example of the more microscopic reconnection activity that has been proposed to accelerate the solar wind more generally. These particular CMEs are of interest because they are the first CMEs to hit PSP and be simultaneously imaged by it, using the Wide-field Imager for Solar Probe (WISPR) instrument. Based on imaging from WISPR and STEREO-A, we identify and model six discrete transients, and determine that it is the second of them (CME2) that first hits PSP, although PSP later more obliquely encounters the third transient as well. Signatures of these encounters are seen in the PSP in situ data. Within these data, we identify six candidate magnetic flux ropes (MFRs), all but one of which are associated with the second transient. The five CME2 MFRs have orientations roughly consistent with PSP encountering the right sides of roughly E-W oriented MFRs, which are sloping back towards the Sun.

astro-ph.SR↗
arXiv2023

Evaluating the Robustness of Test Selection Methods for Deep Neural Networks

Testing deep learning-based systems is crucial but challenging due to the required time and labor for labeling collected raw data. To alleviate the labeling effort, multiple test selection methods have been proposed where only a subset of test data needs to be labeled while satisfying testing requirements. However, we observe that such methods with reported promising results are only evaluated under simple scenarios, e.g., testing on original test data. This brings a question to us: are they always reliable? In this paper, we explore when and to what extent test selection methods fail for testing. Specifically, first, we identify potential pitfalls of 11 selection methods from top-tier venues based on their construction. Second, we conduct a study on five datasets with two model architectures per dataset to empirically confirm the existence of these pitfalls. Furthermore, we demonstrate how pitfalls can break the reliability of these methods. Concretely, methods for fault detection suffer from test data that are: 1) correctly classified but uncertain, or 2) misclassified but confident. Remarkably, the test relative coverage achieved by such methods drops by up to 86.85%. On the other hand, methods for performance estimation are sensitive to the choice of intermediate-layer output. The effectiveness of such methods can be even worse than random selection when using an inappropriate layer.

cs.LG↗
arXiv2023

CodeLens: An Interactive Tool for Visualizing Code Representations

Representing source code in a generic input format is crucial to automate software engineering tasks, e.g., applying machine learning algorithms to extract information. Visualizing code representations can further enable human experts to gain an intuitive insight into the code. Unfortunately, as of today, there is no universal tool that can simultaneously visualise different types of code representations. In this paper, we introduce a tool, CodeLens, which provides a visual interaction environment that supports various representation methods and helps developers understand and explore them. CodeLens is designed to support multiple programming languages, such as Java, Python, and JavaScript, and four types of code representations, including sequence of tokens, abstract syntax tree (AST), data flow graph (DFG), and control flow graph (CFG). By using CodeLens, developers can quickly visualize the specific code representation and also obtain the represented inputs for models of code. The Web-based interface of CodeLens is available at http://www.codelens.org. The demonstration video can be found at http://www.codelens.org/demo.

cs.SE↗
arXiv2023

Probing high-momentum component in nucleon momentum distribution by neutron-proton bremsstrahlung γ-rays in heavy ion reactions

The high momentum tail (HMT) of nucleons, as a signature of the short-range correlations in nuclei, has been investigated by the high-energy bremsstrahlung $γ$ rays produced in $^{86}$Kr + $^{124}$Sn at 25 MeV/u. The energetic photons are measured by a CsI(Tl) hodoscope mounted on the spectrometer CSHINE. The energy spectrum above 30 MeV can be reproduced by the IBUU model calculations incorporating the photon production channel from $np$ process in which the HMTs of nucleons is considered. A non-zero HMT ratio of about $15\%$ is favored by the data. The effect of the capture channel $np \to dγ$ is demonstrated.

nucl-ex↗
arXiv2023

Formation of an observed eruptive flux rope above the torus instability threshold through tether-cutting magnetic reconnection

Erupting magnetic flux ropes (MFRs) play a crucial role in producing solar flares. However, the formation of erupting MFRs in complex coronal magnetic configurations and their subsequent evolution in the flaring events are not fully understood. We performed an MHD simulation of active region NOAA 12241 to understand the formation of a rising MFR during the onset of an M6.9 flare on 2014 December 18, around 21:41 UT. The MHD simulation was initialised with an extrapolated non-force-free magnetic field generated from the photospheric vector magnetogram of the active region taken a few minutes before the flare. The initial magnetic field topology displays a pre-existing sheared arcade enveloping the polarity inversion line. The simulated dynamics exhibit the movement of the oppositely directed legs of the sheared arcade field lines towards each other due to the converging Lorentz force, resulting in the onset of tether-cutting magnetic reconnection that produces an underlying flare arcade and flare ribbons. Concurrently, an MFR above the flare arcade develops inside the sheared arcade and shows a rising motion. The MFR is found to be formed in a torus-unstable region, thereby explaining its eruptive nature. Interestingly, the location and rise of the rope are in good agreement with the corresponding observations seen in EUV channels. Furthermore, the foot points of the simulation's flare arcade match well with the location of the observed parallel ribbons of the flare. The presented simulation supports the development of the MFR by the tether-cutting magnetic reconnection inside the sheared coronal arcade during flare onset. The MFR is then found to extend along the polarity inversion line (PIL) through slip-running reconnection. The MFR's eruptive nature is ascribed both to its formation in the torus-unstable region and also to the runaway tether-cutting reconnection.

astro-ph.SR↗
arXiv2023

Neural Residual Radiance Fields for Streamably Free-Viewpoint Videos

The success of the Neural Radiance Fields (NeRFs) for modeling and free-view rendering static objects has inspired numerous attempts on dynamic scenes. Current techniques that utilize neural rendering for facilitating free-view videos (FVVs) are restricted to either offline rendering or are capable of processing only brief sequences with minimal motion. In this paper, we present a novel technique, Residual Radiance Field or ReRF, as a highly compact neural representation to achieve real-time FVV rendering on long-duration dynamic scenes. ReRF explicitly models the residual information between adjacent timestamps in the spatial-temporal feature space, with a global coordinate-based tiny MLP as the feature decoder. Specifically, ReRF employs a compact motion grid along with a residual feature grid to exploit inter-frame feature similarities. We show such a strategy can handle large motions without sacrificing quality. We further present a sequential training scheme to maintain the smoothness and the sparsity of the motion/residual grids. Based on ReRF, we design a special FVV codec that achieves three orders of magnitudes compression rate and provides a companion ReRF player to support online streaming of long-duration FVVs of dynamic scenes. Extensive experiments demonstrate the effectiveness of ReRF for compactly representing dynamic radiance fields, enabling an unprecedented free-viewpoint viewing experience in speed and quality.

cs.CV↗
arXiv2023

Production of exotic electromagnetic bound systems in ultra-peripheral heavy ion collisions with two-photon processes

We calculate the production of exotic electromagnetic bound systems, which ia an consisting of a ($l^{+}l^{-}$) bound state system such as positronium, dimuonium, and ditauonium, by photon-photon interaction with the equivalent photon approximation in ultra-peripheral heavy ion collisions considering the nuclear form factor. The numerical results demonstrate that the experimental study of positronium, dimuonium, and ditauonium in ultra-peripheral collisions is feasible at Relativistic Heavy Ion Collider (RHIC) and Large Hadron Collider (LHC) energies.

hep-ph↗
arXiv2023

Coronal Magnetic Field Extrapolation and Topological Analysis of Fine-Scale Structures during Solar Flare Precursors

Magnetic field plays an important role in various solar eruptions like flares, coronal mass ejections, etc. The formation and evolution of characteristic magnetic field topology in solar eruptions are critical problems that will ultimately help us understand the origination of these eruptions in the solar source regions. With the development of advanced techniques and instruments, observations with higher resolutions in different wavelengths and fields of view have provided more quantitative information for finer structures. So it is essential to improve our method to study the magnetic field topology in the solar source regions by taking advantage of high-resolution observations. In this study, we employ a nonlinear force-free field (NLFFF) extrapolation method based on a nonuniform grid setting for an M-class flare eruption event (SOL2015-06-22T17:39) with embedded magnetograms from the Solar Dynamics Observatory (SDO) and the Goode Solar Telescope (GST). The extrapolation results employing the embedded magnetogram for the bottom boundary are obtained by maintaining the native resolutions of the corresponding GST and SDO magnetograms. We compare the field line connectivity with the simultaneous GST/H$α$ and SDO/AIA observations for fine-scale structures associated with precursor brightenings. Then we perform a topological analysis of the field line connectivity corresponding to fine-scale magnetic field structures based on the extrapolation results. The results indicate that by combining the high-resolution GST magnetogram with a larger HMI magnetogram, the derived magnetic field topology is consistent with a scenario of magnetic reconnection among sheared field lines across the main polarity inversion line during solar flare precursors.

astro-ph.SR↗
arXiv2023

Active Code Learning: Benchmarking Sample-Efficient Training of Code Models

The costly human effort required to prepare the training data of machine learning (ML) models hinders their practical development and usage in software engineering (ML4Code), especially for those with limited budgets. Therefore, efficiently training models of code with less human effort has become an emergent problem. Active learning is such a technique to address this issue that allows developers to train a model with reduced data while producing models with desired performance, which has been well studied in computer vision and natural language processing domains. Unfortunately, there is no such work that explores the effectiveness of active learning for code models. In this paper, we bridge this gap by building the first benchmark to study this critical problem - active code learning. Specifically, we collect 11 acquisition functions~(which are used for data selection in active learning) from existing works and adapt them for code-related tasks. Then, we conduct an empirical study to check whether these acquisition functions maintain performance for code data. The results demonstrate that feature selection highly affects active learning and using output vectors to select data is the best choice. For the code summarization task, active code learning is ineffective which produces models with over a 29.64\% gap compared to the expected performance. Furthermore, we explore future directions of active code learning with an exploratory study. We propose to replace distance calculation methods with evaluation metrics and find a correlation between these evaluation-based distance methods and the performance of code models.

cs.SE↗
arXiv2023

The Structure and Origin of Switchbacks: Parker Solar Probe Observations

Switchbacks are rapid magnetic field reversals that last from seconds to hours. Current Parker Solar Probe (PSP) observations pose many open questions in regard to the nature of switchbacks. For example, are they stable as they propagate through the inner heliosphere, and how are they formed? In this work, we aim to investigate the structure and origin of switchbacks. In order to study the stability of switchbacks, we suppose the small-scale current sheets therein are generated by magnetic braiding, and they should work to stabilize the switchbacks. With more than one thousand switchbacks identified with PSP observations in seven encounters, we find many more current sheets inside than outside switchbacks, indicating that these microstructures should work to stabilize the S-shaped structures of switchbacks. Additionally, we study the helium variations to trace the switchbacks to their origins. We find both helium-rich and helium-poor populations in switchbacks, implying that the switchbacks could originate from both closed and open magnetic field regions in the Sun. Moreover, we observe that the alpha-proton differential speeds also show complex variations as compared to the local Alfvén speed. The joint distributions of both parameters show that low helium abundance together with low differential speed is the dominant state in switchbacks. The presence of small-scale current sheets in switchbacks along with the helium features are in line with the hypothesis that switchbacks could originate from the Sun via interchange reconnection process. However, other formation mechanisms are not excluded.

physics.space-ph↗
arXiv2023

NEPHELE: A Neural Platform for Highly Realistic Cloud Radiance Rendering

We have recently seen tremendous progress in neural rendering (NR) advances, i.e., NeRF, for photo-real free-view synthesis. Yet, as a local technique based on a single computer/GPU, even the best-engineered Instant-NGP or i-NGP cannot reach real-time performance when rendering at a high resolution, and often requires huge local computing resources. In this paper, we resort to cloud rendering and present NEPHELE, a neural platform for highly realistic cloud radiance rendering. In stark contrast with existing NR approaches, our NEPHELE allows for more powerful rendering capabilities by combining multiple remote GPUs and facilitates collaboration by allowing multiple people to view the same NeRF scene simultaneously. We introduce i-NOLF to employ opacity light fields for ultra-fast neural radiance rendering in a one-query-per-ray manner. We further resemble the Lumigraph with geometry proxies for fast ray querying and subsequently employ a small MLP to model the local opacity lumishperes for high-quality rendering. We also adopt Perfect Spatial Hashing in i-NOLF to enhance cache coherence. As a result, our i-NOLF achieves an order of magnitude performance gain in terms of efficiency than i-NGP, especially for the multi-user multi-viewpoint setting under cloud rendering scenarios. We further tailor a task scheduler accompanied by our i-NOLF representation and demonstrate the advance of our methodological design through a comprehensive cloud platform, consisting of a series of cooperated modules, i.e., render farms, task assigner, frame composer, and detailed streaming strategies. Using such a cloud platform compatible with neural rendering, we further showcase the capabilities of our cloud radiance rendering through a series of applications, ranging from cloud VR/AR rendering.

cs.GR↗
arXiv2023

CodeS: Towards Code Model Generalization Under Distribution Shift

Distribution shift has been a longstanding challenge for the reliable deployment of deep learning (DL) models due to unexpected accuracy degradation. Although DL has been becoming a driving force for large-scale source code analysis in the big code era, limited progress has been made on distribution shift analysis and benchmarking for source code tasks. To fill this gap, this paper initiates to propose CodeS, a distribution shift benchmark dataset, for source code learning. Specifically, CodeS supports two programming languages (Java and Python) and five shift types (task, programmer, time-stamp, token, and concrete syntax tree). Extensive experiments based on CodeS reveal that 1) out-of-distribution detectors from other domains (e.g., computer vision) do not generalize to source code, 2) all code classification models suffer from distribution shifts, 3) representation-based shifts have a higher impact on the model than others, and 4) pre-trained bimodal models are relatively more resistant to distribution shifts.

cs.SE↗