arXiv subjects

Haoxuan Sun

Publications and source records attributed to Haoxuan Sun.

6 recordsLinked to original sources

arXiv2025

The Tianlai-WIYN North Celestial Cap Redshift Survey

We present the results of a small, low redshift spectroscopic survey of galaxies within 3 degrees of the North Celestial Pole (NCP) selected using V-band photometry obtained from the North Celestial Cap Survey (NCCS) (Gorbikov & Brosch 2014). The purpose of the current survey is to create a redshift space template for 21 cm emission from neutral hydrogen with which to correlate radio line intensity observations by the Tianlai dish and cylinder interferometers. A total of 898 redshifts were obtained from the 2102 extended objects in the NCCS with m_V < 19 in the survey area. After accounting for extinction, the survey geometry and selection effects, the number density and clustering pattern of galaxies in the redshift catalog are consistent with other low redshift surveys. We were also able to identify 11 galaxy cluster candidates from this redshift catalog.

astro-ph.CO↗

arXiv2025

HistRetinex: Optimizing Retinex model in Histogram Domain for Efficient Low-Light Image Enhancement

Retinex-based low-light image enhancement methods are widely used due to their excellent performance. However, most of them are time-consuming for large-sized images. This paper extends the Retinex model from the spatial domain to the histogram domain, and proposes a novel histogram-based Retinex model for fast low-light image enhancement, named HistRetinex. Firstly, we define the histogram location matrix and the histogram count matrix, which establish the relationship among histograms of the illumination, reflectance and the low-light image. Secondly, based on the prior information and the histogram-based Retinex model, we construct a novel two-level optimization model. Through solving the optimization model, we give the iterative formulas of the illumination histogram and the reflectance histogram, respectively. Finally, we enhance the low-light image through matching its histogram with the one provided by HistRetinex. Experimental results demonstrate that the HistRetinex outperforms existing enhancement methods in both visibility and performance metrics, while executing 1.86 seconds on 1000*664 resolution images, achieving a minimum time saving of 6.67 seconds.

cs.CV↗

arXiv2024

The Impact of Initial Composition on Massive Star Evolution and Nucleosynthesis

We study the sensitivity of presupernova evolution and supernova nucleosynthesis yields of massive stars to variations of the initial composition. We use the solar abundances from Lodders (2009), and compute two different initial stellar compositions: i) scaled solar abundances, and ii) the isotopic galactic chemical history model (GCH) developed by West and Heger (2013b). We run a grid of models using the KEPLER stellar evolution code, with 7 initial stellar masses, 12 initial metallicities, and two for each scaling method to explore the effects on nucleosynthesis over a metallicity range of $-4.0\leq[Z]\leq+0.3$. We find that the compositions from the GCH model better reproduce the weak \emph{s}-process peak than the scaled solar models. The model yields are then used in the OMEGA Galactic Chemical Evolution (GCE) code to assess this result further. We find that initial abundances used in computing stellar structure have more of an impact on GCE results than initial abundances used in the burn network, with the GCH model again being favored when compared to observations. Lastly, a machine learning algorithm was used to verify the free parameter values of the GCH model, which were previously found by West and Heger (2013b) using a stochastic fitting process. The updated model is provided as an accessible tool for further nucleosynthesis studies.

astro-ph.SR↗

arXiv2024

Self-Supervised Vision Transformer for Enhanced Virtual Clothes Try-On

Virtual clothes try-on has emerged as a vital feature in online shopping, offering consumers a critical tool to visualize how clothing fits. In our research, we introduce an innovative approach for virtual clothes try-on, utilizing a self-supervised Vision Transformer (ViT) coupled with a diffusion model. Our method emphasizes detail enhancement by contrasting local clothing image embeddings, generated by ViT, with their global counterparts. Techniques such as conditional guidance and focus on key regions have been integrated into our approach. These combined strategies empower the diffusion model to reproduce clothing details with increased clarity and realism. The experimental results showcase substantial advancements in the realism and precision of details in virtual try-on experiences, significantly surpassing the capabilities of existing technologies.

cs.CV↗

arXiv2024

Renormalizable Cosmology Based on Gauss-Bonnet Theory with Torsion

This paper focuses on renormalizable cosmology based on the Gauss-Bonnet theory with torsion. Within the framework of renormalizable quantum field theory, we study the matter field containing the Gauss-Bonnet correction term. By modifying the gauge model, which includes a charged scalar field and two families of fermions, and introducing torsion and Gauss-Bonnet corrections, we analyze the field equations in the super-symmetric hybrid inflation model, investigate the properties of torsion in a flat universe, the characteristics of the energy-momentum tensor, and the sensitivity of the theoretical model to correction parameters. This study shows that the Gauss-Bonnet correction term can directly affect the Hubble constant through the Einstein equations, providing a new observational perspective. This paper proposes a cosmological model that can be adjusted according to different Gauss-Bonnet correction models, providing a theoretical reference for future observational verification of various Gauss-Bonnet models.

gr-qc↗

arXiv2024

Machine Learning Refinements to Metallicity-Dependent Isotopic Abundances

The project aims to use machine learning algorithms to fit the free parameters of an isotopic scaling model to elemental observations. The processes considered are massive star nucleosynthesis, Type Ia SNe, the s-process, the r-process, and p-isotope production. The analysis on the successful fits seeks to minimize the reduced chi squared between the model and the data. Based upon the successful refinement of the isotopic parameterized scaling model, a table providing the 287 stable isotopic abundances as a function of metallicity, separated into astrophysical processes, is useful for identifying the chemical history of them. The table provides a complete averaged chemical history for the Galaxy, subject to the underlying model constraints.

astro-ph.IM↗