arXiv subjects

Jinyang Wang

Publications and source records attributed to Jinyang Wang.

10 recordsLinked to original sources

arXiv2026

Probing the Faint Outskirts of Star-Forming Galaxies with 1<z<9 Using Stacked Images

We present a systematic study of the faint outer light profiles of star-forming galaxies using deep JWST/NIRCam imaging from the CEERS, JADES, and PRIMER surveys. Our sample consists of 14,812 face-on disk galaxies at $1 8.5$, selected from the DAWN JWST Archive. To characterize the low-surface-brightness outskirts beyond the effective radius ($R_e$), we stack galaxies in bins of stellar mass and redshift, accounting for cosmological surface-brightness dimming, angular-size scaling, and PSF convolution, and estimate residual backgrounds from blank-sky stacks. The color profiles generally become bluer toward larger radii, indicating negative color gradients and supporting an inside-out growth scenario. Galaxies with $\log(M_*/M_{\odot}) < 9.5$ at $z>2.5$ exhibit a weak reversal in their outermost regions, suggesting more complex stellar population gradients at early times. The outer light profiles generally exhibit a good exponential decline with radius, and the outer scale lengths measured beyond $2R_e$ show mass and redshift dependences remarkably similar to those of the conventional mass-size relation. This similarity suggests that the extended outer light is closely linked to the same processes governing the growth of the inner galaxy, rather than providing a direct tracer of ex-situ stellar components in the early universe. We also find little wavelength dependence in the outer scale lengths, indicating that dust attenuation likely has a limited impact at these radii. These results provide new constraints on the buildup of extended stellar distributions during cosmic noon and at earlier epochs.

astro-ph.GA↗

arXiv2026

SV-WAM: An Efficient Surround-View World-Action Model for End-to-End Autonomous Driving

World models (WMs) have demonstrated strong potential for end-to-end autonomous driving by learning predictive representations of future scene dynamics. However, generating future videos during inference introduces substantial computational overhead, leading many recent driving WMs to adopt a single front camera as input for efficient deployment. This design restricts spatial coverage in safety-critical maneuvers such as lane changes, merges, and turns. To address this limitation, we propose SV-WAM, a surround-view world-action model (WAM) that preserves full six-camera observations while maintaining efficient inference. SV-WAM leverages future-video prediction as dense training supervision for action learning within a shared generative model, rather than as an inference-time output. At the core of this design is an action-centered causal mask that prevents action tokens from attending to future-video tokens during joint action-video denoising. Consequently, the video branch can be discarded at deployment, enabling efficient action-only planning. Furthermore, we introduce a differentiable drivable-area compliance regularizer that penalizes vehicle-footprint corners approaching or crossing drivable boundaries, improving planning safety and boundary awareness. Extensive experiments on the closed-loop NAVSIMv2 benchmark and the open-loop nuScenes benchmark demonstrate that SV-WAM achieves state-of-the-art planning performance with low inference latency and competitive zero-shot transfer capability.

cs.CV↗

arXiv2026

Transition from Outside-in to Inside-Out at $z\sim 2$: Evidence from Radial Profiles of Specific Star Formation Rate based on JWST/HST

By combining high-resolution observations from JWST and HST, we have measured the stellar masses, star formation rates (SFRs), and multi-wavelength morphologies of galaxies in the CANDELS fields. Furthermore, based on rest-frame 1 $μ$m morphologies, we have derived spatially resolved stellar mass and SFR surface density ($Σ_*$ and $Σ_{\rm SFR}$) profiles for 46,313 galaxies with reliable structural measurements at $0 8$, and provide the corresponding catalogue. For star-forming galaxies (SFGs), our results show excellent consistency with previous studies in terms of the star formation main sequence and the size-mass relation, demonstrating the robustness of our stellar mass and SFR measurements. For spatially resolved profiles, we find that at higher redshifts ($z>2.5$), the median radial profile of $Σ_{\rm SFR}$ is nearly parallel to but slightly steeper than that of $Σ_*$. This results in mildly negative gradients in the specific SFR (sSFR) profiles across all stellar mass bins considered. These findings indicate that galaxies at $z>2.5$ cannot grow in size via only in-situ star formation, challenging the understanding of galaxy size evolution beyond the cosmic noon. In contrast, at $z<2.0$, the sSFR profiles transition to exhibit more and more positive gradients at lower redshifts, consistent with an inside-out growth scenario where star formation preferentially expands the galactic outskirts.

astro-ph.GA↗

arXiv2026

First Statistical Detection of MgII-traced Cool Gas Outflows with JWST Towards Cosmic Dawn

Galactic-scale outflows are a crucial component of galaxy evolution, yet their properties in the early universe remain poorly constrained. We present the first statistical investigation of \ion{Mg}{2}-traced cool gas outflows in galaxies spanning a wide cosmic timeline from $z \approx 1$ to $z > 6$ (with sample coverage extending to $z \sim 10$). Using thousands of public JWST/NIRSpec spectra, we employ a signal-to-noise weighted spectral stacking technique on the \ion{Mg}{2} $λ\lambda2796, 2803$ absorption doublet. We robustly detect blueshifted \ion{Mg}{2} absorption in nearly all stellar mass and redshift bins, with the exception of the lowest-mass systems at $z \sim 1-2$. The outflow equivalent width exhibits a positive correlation with stellar mass ($M_*$) at all epochs, with the fitted slope of $1.21 \pm 0.35$. Our work provides the first statistical constraints on \ion{Mg}{2}-traced cool outflows in the low-mass ($M_* \lesssim 10^{9.5} \, \mathrm{M}_\odot$), high-redshift ($z > 3$) regime. We also find that the outflow velocities generally remain below the host halo escape velocities, consistent with a galactic fountain scenario. The consistency of the stellar mass-outflow equivalent width relation across $z \sim 2-6$ suggests a persistent, unevolving feedback mechanism governing the baryon cycle towards cosmic dawn.

astro-ph.GA↗

arXiv2025

Central Concentration and Escape of Ionizing Photons in Galaxies at the Epoch of Reionization

Compact, low-mass galaxies with strong nebular emission are considered promising candidates for efficient ionizing photon production and escape. We present a spatially resolved analysis of 189 galaxies at redshifts $z \sim 6.7-7.6$ in JADES GOODS-N and GOODS-S fields and selected via JWST/NIRCam F410M filter. By employing annular photometry and spectral energy distribution fitting across rest-frame UV to optical wavelengths, we investigate the internal structure of star formation, ionizing photon production and escape, as well as the resolved star formation histories within these galaxies. We find that these galaxies exhibit compact, centrally concentrated, and bursty star formation, especially in lower-mass systems ($\log(M_*/{\rm M_{\odot}}) <9.0$). The central regions of them display extreme [OIII]+H$β$ equivalent widths ($>$1000 Å), high ionizing photon production efficiencies ($ξ_{\text{ion}} \sim 10^{25.6}$ Hz erg$^{-1}$), steep UV slopes ($\sim -2.3$), and elevated escape fractions ($f_{\text{esc}} > 0.08$), with all these properties peaking in the inner regions. These findings reveal outside-in growth and rising star formation histories at $z\sim 7$, with the central regions of them playing a pivotal role in driving cosmic reionization.

astro-ph.GA↗

arXiv2025

Impact of Spinning Droplets onto Superhydrophobic Surfaces: Asymmetric Tumbling Rapid Rebound

The impact dynamics of spinning droplets onto superhydrophobic surfaces was studied by using Volume-of-Fluid simulations, covering broad ranges of Weber number ($We$) and dimensionless angular velocity ($\mathitΩ$). The omputational results were validated by high-speed imaging experiments, with particular focus on the types of rebound, asymmetric deformation, and droplet-wall contact time. Results show that, the spinning motion of droplets leads to two novel rebound scenarios. Specificially, the front-raise tumbling rebound occurs at a lower $\mathitΩ$ and is caused by the unsymmetrical Laplace pressure, while the rear-raise tumbling rebound emerges at a higher $\mathitΩ$ and is attributed to the rotational inertia. The angular momentum of the spinning droplet is dissipated or even reversed, while its direction upon detachment is inconsistent with the visually observed spinning motion. With the increase of the angular velocity, the droplet-wall contact time is largely reduced, which is attributed to the asymmetric spreading by the spinning motion rather than the increased kinetic energy. A theoretical model was also established to predict asymmetric spreading and the contact time and validated against numerical results in wide ranges of $We$ and $\mathitΩ$.

physics.flu-dyn↗

arXiv2025

Potential-Driven Metal Cycling: JADES Census of Gas-Phase Metallicity for galaxies at 1 < z < 7

The gravitational potential is established as a critical determinant of gas-phase metallicity (12+log(O/H)) in low-redshift galaxies, whereas its influence remains unconfirmed at high redshifts. We investigate the correlation between gas-phase metallicity and effective radius ($R_{\rm e}$) for a sample of galaxies with redshifts ranging from 1 to 7, drawn from JADES (JWST Advanced Deep Extragalactic Survey) Data Release 3. We calculate the metallicities using four strong-line methods: ${\rm N2S2Hα}$, ${\rm R23}$, ${\rm N2}$, and ${\rm O3N2}$, respectively. After taking out the evolution of size, we find that the offsets of mass-size relation ($Δ\log R_{\rm e}$) are significantly negatively correlated with the offset of mass-metallicity relation ($Δ\log({\rm O/H})$) for the four metallicity tracers. Regardless of the metallicity tracer used, we obtain Spearman rank $p-$values much less than 0.01, rejecting the null hypothesis that the observed correlation is statistically nonsignificant and attributable to random chance. This is also true for galaxies with $z>3$, with $p-$values less than 0.05 for the four metallicity tracers. We for the first time find evidence of size playing a key role in determining gas-phase metallicity towards cosmic dawn, suggesting that the gravitational potential influences their material-exchange processes with the surrounding environment at very early universe.

astro-ph.GA↗

arXiv2024

Computational Realization of Popping Impinging Sprays of Hypergolic Bipropellants by a Eulerian-Lagrangian Approach

This work adopts a Eulerian-Lagrangian approach to numerically simulate the spray impingement of MMH (Monomethyl hydrazine)/NTO (nitrogen tetroxide), which are prevalent rocket engine bipropellants for deep space missions and satellite orbital maneuvers. The emphasis of the work is to computationally realize the popping phenomenon and to study its parametric dependence on liquid and gas-phase reaction rates. The liquid-phase reaction of MMH/NTO is realized based on the extended spray equation, incorporating the additional independent variable, propellant mass fraction, to account for the mixing of droplets. The spray popping can be computationally reproduced over wide ranges of Damköhler numbers for both liquid- and gas-phase reactions. Furthermore, the computational results have been validated through qualitative comparison with experimental images and quantitative comparison with experimental frequencies. The present results verify our hypothesis that the heat release from the liquid-phase reaction enhances the evaporation of MMH and NTO so that the intense gas-phase reaction zone around the spray impingement point periodically separates the MMH and NTO impinging sprays to cause the popping phenomenon. Furthermore, it was found that the popping phenomenon can be suppressed by reducing the Damköhler numbers of liquid-phase reaction and therefore to suppress the evaporation of the propellants. This work is believed to provide valuable understanding for avoiding the off-design popping phenomenon that may reduce combustion efficiency and increase the risk of combustion instability in rocket engines.

physics.flu-dyn↗

arXiv2023

Few-shot Class-Incremental Semantic Segmentation via Pseudo-Labeling and Knowledge Distillation

We address the problem of learning new classes for semantic segmentation models from few examples, which is challenging because of the following two reasons. Firstly, it is difficult to learn from limited novel data to capture the underlying class distribution. Secondly, it is challenging to retain knowledge for existing classes and to avoid catastrophic forgetting. For learning from limited data, we propose a pseudo-labeling strategy to augment the few-shot training annotations in order to learn novel classes more effectively. Given only one or a few images labeled with the novel classes and a much larger set of unlabeled images, we transfer the knowledge from labeled images to unlabeled images with a coarse-to-fine pseudo-labeling approach in two steps. Specifically, we first match each labeled image to its nearest neighbors in the unlabeled image set at the scene level, in order to obtain images with a similar scene layout. This is followed by obtaining pseudo-labels within this neighborhood by applying classifiers learned on the few-shot annotations. In addition, we use knowledge distillation on both labeled and unlabeled data to retain knowledge on existing classes. We integrate the above steps into a single convolutional neural network with a unified learning objective. Extensive experiments on the Cityscapes and KITTI datasets validate the efficacy of the proposed approach in the self-driving domain. Code is available from https://github.com/ChasonJiang/FSCILSS.

cs.CV↗

arXiv2023

Robust Remote Sensing Scene Classification with Multi-View Voting and Entropy Ranking

Deep convolutional neural networks have been widely used in scene classification of remotely sensed images. In this work, we propose a robust learning method for the task that is secure against partially incorrect categorization of images. Specifically, we remove and correct errors in the labels progressively by iterative multi-view voting and entropy ranking. At each time step, we first divide the training data into disjoint parts for separate training and voting. The unanimity in the voting reveals the correctness of the labels, so that we can train a strong model with only the images with unanimous votes. In addition, we adopt entropy as an effective measure for prediction uncertainty, in order to partially recover labeling errors by ranking and selection. We empirically demonstrate the superiority of the proposed method on the WHU-RS19 dataset and the AID dataset.

cs.CV↗