arXiv subjects

Xia Hua

Publications and source records attributed to Xia Hua.

9 recordsLinked to original sources

arXiv2026

Disentangling chemical evolution histories with phylogenetic trees

Chemical abundances encode the fossil record of galaxy evolution in a complex and diverse way that requires innovative approaches to reconstruct galactic histories. We investigate the power of using phylogenetic methods to disentangle different evolutionary pathways in analytical chemical evolution models. We ran 1024 one-zone chemical evolution models using flexCE. The resulting chemical abundances are combined with those of two fiducial models, mw-fid and dw-fid, and then used both to determine which combinations produce two-branched phylogenetic trees, as well as how purely these trees split the two input models. We used random forests and Shapley analysis to predict which model combinations return well-separated trees and explain which input parameters are most important for this. We also studied the abundance patterns, as well as star formation rates, mass accumulation, and branch lengths. We found that {\eta}, the mass-loading outflow parameter in flexCE, had the largest impact in separating models into separate branches, due to its importance in driving the chemical enrichment rates and total abundances. Star formation rates and mass accumulation had some impact on {\eta}, but no direct relation between these quantities and the abundances was found. We also found that branches connected through the most metal rich tips in our trees, which is opposite to how phylogenetic trees connect in biological systems. Phylogenetic trees help to reconstruct histories when there is information that is inherited between generations, which is the case of the chemical elements in galaxy evolution. Branch topologies can provide information about the rates of evolutionary change of the various populations, and the connection between branches also contains information about their shared history. This work brings us a step further understanding galaxy evolution through cross-disciplinary research.

astro-ph.GA↗

arXiv2026

Reconstructing chemical enrichment pathways in disc galaxies: A phylogenetic approach

Phylogenetic methods, traditionally used in biology to trace the evolutionary relationships among species, are emerging as a powerful framework to reconstruct evolutionary processes in galaxies from chemical information. We apply galactic phylogenetics to study the chemical evolution of stellar populations in distinct regions of a simulated disc galaxy, assessing its capability to unveil assembly histories. We used a high-resolution simulation that follows the chemical enrichment of an isolated disc galaxy, by different stellar progenitors. We track gas particles as they turn into stars and inherit their parent gas chemical composition. Target particles are selected to store the chemical history of each chemical element considered in the simulation. Two regions were analysed: an inner ring, influenced by early bar-driven inflows, and an outer ring, shaped by spiral arms. We built phylogenetic trees for stellar populations in each region and quantified their structure using the Corrected Colless index, a standard metric of tree balance used in biology. The inner ring tree reveals a compact clade of old stars enriched by rapid SNII feedback, followed by a hierarchical sequence with increasing SNIa and AGB contributions. In contrast, the outer ring exhibits more symmetric, caterpillar-like trees with smoother abundance gradients, consistent with more prolonged star formation and efficient local mixing. Chemical enrichment rates corroborate these trends, showing fast early enrichment in the inner ring and gradual, spatially extended enrichment in the outer disc. The structural indices differ significantly between the two regions and converge robustly even for modest stellar samples (NSSP = 100). Galactic phylogenetics provides a novel and complementary tool to decode the fossil record of galaxies.

astro-ph.GA↗

arXiv2026

Beyond Pixels: Vector-to-Graph Transformation for Reliable Schematic Auditing

Multimodal Large Language Models (MLLMs) have shown remarkable progress in visual understanding, yet they suffer from a critical limitation: structural blindness. Even state-of-the-art models fail to capture topology and symbolic logic in engineering schematics, as their pixel-driven paradigm discards the explicit vector-defined relations needed for reasoning. To overcome this, we propose a Vector-to-Graph (V2G) pipeline that converts CAD diagrams into property graphs where nodes represent components and edges encode connectivity, making structural dependencies explicit and machine-auditable. On a diagnostic benchmark of electrical compliance checks, V2G yields large accuracy gains across all error categories, while leading MLLMs remain near chance level. These results highlight the systemic inadequacy of pixel-based methods and demonstrate that structure-aware representations provide a reliable path toward practical deployment of multimodal AI in engineering domains. To facilitate further research, we release our benchmark and implementation at https://github.com/gm-embodied/V2G-Audit.

cs.AI↗

arXiv2026

AugVLA-3D: Depth-Driven Feature Augmentation for Vision-Language-Action Models

Vision-Language-Action (VLA) models have recently achieved remarkable progress in robotic perception and control, yet most existing approaches primarily rely on VLM trained using 2D images, which limits their spatial understanding and action grounding in complex 3D environments. To address this limitation, we propose a novel framework that integrates depth estimation into VLA models to enrich 3D feature representations. Specifically, we employ a depth estimation baseline called VGGT to extract geometry-aware 3D cues from standard RGB inputs, enabling efficient utilization of existing large-scale 2D datasets while implicitly recovering 3D structural information. To further enhance the reliability of these depth-derived features, we introduce a new module called action assistant, which constrains the learned 3D representations with action priors and ensures their consistency with downstream control tasks. By fusing the enhanced 3D features with conventional 2D visual tokens, our approach significantly improves the generalization ability and robustness of VLA models. Experimental results demonstrate that the proposed method not only strengthens perception in geometrically ambiguous scenarios but also leads to superior action prediction accuracy. This work highlights the potential of depth-driven data augmentation and auxiliary expert supervision for bridging the gap between 2D observations and 3D-aware decision-making in robotic systems.

cs.CV↗

arXiv2024

Dynamic laser ablation loading of a linear Paul trap

We present a detailed method for accumulating Ca$^{+}$ ions controllably in a linear Paul trap. The ions are generated by pulsed laser ablation and dynamically loaded into the ion trap by switching the trapping potential on and off. The loaded ions are precooled by buffer gas and then laser-cooled to form Coulomb crystals for verifying quantity. The number of ions is controlled by manipulating the trapping potential of the ion trap, partial pressure of buffer gas and turn-on time of the entrance end cap voltage. With single-pulse laser ablation, the number of trapped ions ranges from tens to ten thousand. The kinetic energy of loaded ions can be selected via the optimal turn-on time of the entrance end cap. Using multiple-pulse laser ablation, the number is further increased and reaches about $4 \times 10^{4}$. The dynamic loading method has wide application for accumulating low-yielding ions via laser ablation in the ion trap.

physics.atom-ph↗

arXiv2024

Assembling a high-precision abundance catalogue of solar twins in GALAH for phylogenetic studies

Stellar chemical abundances have proved themselves a key source of information for understanding the evolution of the Milky Way, and the scale of major stellar surveys such as GALAH have massively increased the amount of chemical data available. However, progress is hampered by the level of precision in chemical abundance data as well as the visualization methods for comparing the multidimensional outputs of chemical evolution models to stellar abundance data. Machine learning methods have greatly improved the former; while the application of tree-building or phylogenetic methods borrowed from biology are beginning to show promise with the latter. Here we analyse a sample of GALAH solar twins to address these issues. We apply The Cannon algorithm to generate a catalogue of about 40,000 solar twins with 14 high precision abundances which we use to perform a phylogenetic analysis on a selection of stars that have two different ranges of eccentricities. From our analyses we are able to find a group with mostly stars on circular orbits and some old stars with eccentric orbits whose age-[Y/Mg] relation agrees remarkably well with the chemical clocks published by previous high precision abundance studies. Our results show the power of combining survey data with machine learning and phylogenetics to reconstruct the history of the Milky Way.

astro-ph.GA↗

arXiv2023

On the evolutionary history of a simulated disc galaxy as seen by phylogenetic trees

Phylogenetic methods have long been used in biology, and more recently have been extended to other fields - for example, linguistics and technology - to study evolutionary histories. Galaxies also have an evolutionary history, and fall within this broad phylogenetic framework. Under the hypothesis that chemical abundances can be used as a proxy for interstellar medium's DNA, phylogenetic methods allow us to reconstruct hierarchical similarities and differences among stars - essentially a tree of evolutionary relationships and thus history. In this work, we apply phylogenetic methods to a simulated disc galaxy obtained with a chemo-dynamical code to test the approach. We found that at least 100 stellar particles are required to reliably portray the evolutionary history of a selected stellar population in this simulation, and that the overall evolutionary history is reliably preserved when the typical uncertainties in the chemical abundances are smaller than 0.08 dex. The results show that the shape of the trees are strongly affected by the age-metallicity relation, as well as the star formation history of the galaxy. We found that regions with low star formation rates produce shorter trees than regions with high star formation rates. Our analysis demonstrates that phylogenetic methods can shed light on the process of galaxy evolution.

astro-ph.GA↗

arXiv2023

Dynamic Scene Deblurring Based on Continuous Cross-Layer Attention Transmission

The deep convolutional neural networks (CNNs) using attention mechanism have achieved great success for dynamic scene deblurring. In most of these networks, only the features refined by the attention maps can be passed to the next layer and the attention maps of different layers are separated from each other, which does not make full use of the attention information from different layers in the CNN. To address this problem, we introduce a new continuous cross-layer attention transmission (CCLAT) mechanism that can exploit hierarchical attention information from all the convolutional layers. Based on the CCLAT mechanism, we use a very simple attention module to construct a novel residual dense attention fusion block (RDAFB). In RDAFB, the attention maps inferred from the outputs of the preceding RDAFB and each layer are directly connected to the subsequent ones, leading to a CCLAT mechanism. Taking RDAFB as the building block, we design an effective architecture for dynamic scene deblurring named RDAFNet. The experiments on benchmark datasets show that the proposed model outperforms the state-of-the-art deblurring approaches, and demonstrate the effectiveness of CCLAT mechanism.

cs.CV↗

arXiv2022

A scheme for excitation of thorium-229 nuclei based on the electronic bridge excitaion

Thorium-229 possesses the lowest nuclear first excited state with an energy of about 8 eV. The extremely narrow linewidth of the nuclear first excited state with the uncertainty of 53 THz prevents the direct laser excitation and the realization of the nuclear clock. We present a proposal using the Coulomb crystal of a linear chain formed by the $^{229}$Th$^{3+}$ ions, the nuclei of $^{229}$Th$^{3+}$ ions in the ion trap are excited by the electronic bridge (EB) process. The 7$P_{1/2}$ state of the thorium-229 nuclear ground state is chosen for the EB excitation. Using the two-level optical Bloch equation under experimental conditions, we calculate that 2 out of 36 prepared thorium ions in the Coulomb crystal can be excited to the nuclear first excited state, and it takes about 2 hours to scan over the uncertainty of 0.22 eV. Taking the advantage of transition enhancement of the EB and the long stability of the Coulomb crystal, the energy uncertainty of the first excited state can be limited to the order of 1 GHz.

physics.atom-ph↗