发表机构
Kavli Institute for Astronomy and Astrophysics, Peking University; Department of Astronomy, School of Physics, Peking University; Department of Astronomy, School of Physics and Astronomy, Shanghai Jiao Tong University; Key Laboratory for Particle Astrophysics and Cosmology (MOE)/Shanghai Key Laboratory for Particle Physics and Cosmology; Department of Astronomy, University of Illinois Urbana-Champaign（北京大学科维理天文与天体物理研究所; 北京大学物理学院天文学系; 上海交通大学物理与天文学院天文学系; 粒子天体物理与宇宙学教育部重点实验室/上海粒子物理与宇宙学重点实验室; 伊利诺伊大学厄巴纳-香槟分校天文学系）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究开发了结合椭圆拟合与傅里叶分解的自动化流程，通过模拟观测量化高红移星系棒探测偏差，提出自适应标准和校正因子，实现HST和JWST观测中超过60%的恢复率。
AI 中文摘要
星系棒的宇宙演化为了解盘状星系的动力学历史提供了关键见解。然而，对高红移星系棒的研究受到观测效应的严重阻碍，如分辨率降低和表面亮度变暗。为了量化这些偏差并为高红移星系建立稳健的棒探测与测量方法，我们开发了一个集成等照度椭圆拟合和傅里叶分解的自动化流程。我们使用一组全面的模拟观测来评估其性能，这些模拟观测是通过人为地将本地棒状星系的高质量图像红移以匹配哈勃太空望远镜（HST，$z \approx 0.5-3$）和詹姆斯·韦伯太空望远镜（JWST，$z \approx 1-6$）观测的背景和分辨率而生成的。我们发现，将源自本地星系的标准化棒探测标准应用于高红移数据会导致棒比例严重低估，在HST成像中$z>0.5$时遗漏超过50%的棒，在JWST成像中$z>2$时遗漏类似比例。使用通过模拟数据优化的自适应、红移依赖标准，在HST的$z \approx 3$和JWST的$z \approx 6$范围内实现了超过60%的恢复率。在测量可靠性方面，椭圆拟合方法显著优于傅里叶分解。虽然由于表面亮度变暗，椭圆拟合系统性地低估棒长度约4%至36%，但这种偏差是一致的且可校正（$\sigma \approx 0.88-2.22$）；相比之下，傅里叶方法在低信噪比情况下容易发生灾难性失败（$\sigma \approx 2.40-6.14$）。我们提出了一种标准化工作流程，优先采用模拟推导的自适应标准和椭圆拟合，提供定量校正因子和经验关系，使未来的研究能够从原始观测中恢复内在的棒统计特性。
英文摘要
The cosmic evolution of galactic bars offers key insights into the dynamical history of disk galaxies. However, studies of high-redshift bars are severely hampered by observational effects such as resolution degradation and surface brightness dimming. To quantify these biases and establish a robust methodology of bar detection and measurement for high-redshift galaxies, we develop an automated pipeline integrating isophotal ellipse fitting and Fourier decomposition. We benchmark its performance using a comprehensive set of mock observations generated by artificially redshifting high-quality images of local barred galaxies to match the background and resolution of HST ($z \approx 0.5-3$) and JWST ($z \approx 1-6$) observations. We find that applying standard bar detection criteria derived from local galaxies to high-redshift data results in a severe underestimation of the bar fraction, missing $>50%$ of bars at $z>0.5$ in HST imaging and a similar fraction at $z>2$ in JWST imaging. Using adaptive, redshift-dependent criteria optimized via mock data achieves recovery rates above $60%$ out to $z \approx 3$ for HST and $z \approx 6$ for JWST. The ellipse fitting method significantly outperforms Fourier decomposition in measurement reliability. While ellipse fitting systematically underestimates bar length by $\sim 4%$--$36%$ due to surface brightness dimming, this bias is consistent and correctable ($σ\approx 0.88$--$2.22$); in contrast, the Fourier method is prone to catastrophic failures ($σ\approx 2.40$--$6.14$) in the regime of low signal-to-noise ratio. We propose a standardized workflow that prioritizes mock-derived adaptive criteria and ellipse fitting, providing quantitative correction factors and empirical relations that enable future studies to recover intrinsic bar statistics from raw observations.
Comments32 pages, 20 figures, 10 tables. Submitted to The Astrophysical Journal
