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arXiv 2601.00522astro-ph.GAastro-ph.IM
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银河系旋转曲线的新经验拟合

A New Empirical Fit to Galaxy Rotation Curves

David C. Flynn, Jim Cannaliato

AI总结:

本文提出了一种新的经验模型,通过引入速度修正项ω来拟合银河系旋转曲线,该方法在RMSE和R平方指标上优于MOND和CDM模型,且无需参数调优。

摘要:

我们提出了一种新的经验模型用于银河系旋转曲线,该模型引入了一个速度修正项ω,来源于观测到的恒星运动,并基于开普勒基线进行锚定。与参数化暗物质模型或修正引力理论不同,这种方法不改变牛顿动力学或引入暗物质分布。相反,它识别出一种可重复的运动偏移,这种偏移在广泛范围的银河系中与观测到的旋转剖面一致。使用SPARC数据[1],我们证明该模型能够一致地实现高质量的拟合,经常在RMSE和R平方指标上优于MOND和CDM暗物质模型,而无需参数调优。该方法可重复,对质量建模依赖性极低,并提供了一种简化的方法用于表征银河系动力学。虽然速度修正项ω缺乏明确的物理解释,但其经验成功促使进一步探索。我们将该模型定位为一个局部运动工具,而非宇宙学框架,并欢迎就其对银河系结构和引力理论的影响进行讨论。附录B展示了RMSE和R2比较,表明该方法在代表性银河系样本中一致优于MOND和CDM暗物质模型。

英文摘要:

We present a new empirical model for galaxy rotation curves that introduces a velocity correction term ω, derived from observed stellar motion and anchored to Keplerian baselines. Unlike parametric halo models or modified gravity theories, this approach does not alter Newtonian dynamics or invoke dark matter distributions. Instead, it identifies a repeatable kinematic offset that aligns with observed rotation profiles across a wide range of galaxies. Using SPARC data [1], we demonstrate that this model consistently achieves high fidelity fits, often outperforming MOND and CDM halo models in RMSE and R-squared metrics without parametric tuning. The method is reproducible, minimally dependent on mass modeling, and offers a streamlined alternative for characterizing galactic dynamics. While the velocity correction ω lacks a definitive physical interpretation, its empirical success invites further exploration. We position this model as a local kinematic tool rather than a cosmological framework, and we welcome dialogue on its implications for galactic structure and gravitational theory. Appendix B presents RMSE and R2 comparisons showing that this method consistently outperforms MOND and CDM halo models across a representative galaxy sample.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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