arXiv subjects

Xiangming Cheng

Publications and source records attributed to Xiangming Cheng.

6 recordsLinked to original sources

arXiv2026

An adaptive parameter optimization method for astronomical image alignment using Bayesian optimization. I. A hierarchical search strategy for FWHM and SNR

The alignment and stacking of astronomical images are fundamental steps for detecting faint objects and performing high?precision astrometry. In traditional alignment workflows, the extraction of source lists is critically dependent on key parameters such as the Full Width at Half Maximum (FWHM) and the Signal-to-Noise Ratio (SNR) threshold. These parameters are often selected manually through an inefficient trial-error process that lacks objectivity and does not guarantee optimal results. We present an adaptive method for optimizing astronomical image alignment parameters based on Bayesian Optimization (BO). We frame the parameter search as an optimization problem, with an objective function designed to maximize the number of successfully matched source pairs. By employing a hierarchical search strategy, we perform an efficient global search for FWHM and SNR to automatically determine the optimal combination for a given observational dataset. Experimental results demonstrate that our method effectively handles image data with varying seeing conditions and back?ground noise levels. It rapidly converges to a robust set of alignment parameters, achieving sub-pixel accuracy and significantly improving the automation level and success rate of the alignment process. This work may provide a useful basis for developing large-scale, automated astronomical data processing pipelines

astro-ph.IM↗

arXiv2026

CosmicWeb-21cm array: A New Radio Observation Array Design for 21cm Cosmology

This paper presents the CosmicWeb-21cm array, a novel radio interferometer designed to overcome the key challenges in 21 cm cosmology. Its core innovations include: (1) a multi-scale nested geometry combining a hexagonal core with logarithmic spiral arms for excellent UV coverage and calibration robustness; (2) an intelligent non-uniform frequency sampling strategy that adapts resolution to foreground and signal characteristics, reducing data volume while preserving information; and (3) a machine-learning-enhanced, physics-informed processing pipeline that achieves 99.7\% foreground removal efficiency; (4) a dual-polarization crossed dipole integrated with a dielectric lens and cryogenically cooled LNA, achieving stable beam patterns and low noise temperature ($<35$ K) across 50-250 MHz. These co-designed advances enable high sensitivity mapping of the Epoch of Reionization, dark energy constraints and cosmic-web structure.

astro-ph.IM↗

arXiv2023

Predicting Astrometric Microlensing Events from Gaia DR3

Currently astrometric microlensing is the only tool that can directly measure the mass of a single star, it can also help us to detect compact objects like isolated neutron stars and black holes. The number of microlensing events that are being predicted and reported is increasing. In the paper, the potential lens stars are selected from three types of stars, high-proper-motion stars, nearby stars and high-mass stars. For each potential lens star, we select a larger search scope to find possible matching sources to avoid missing events as much as possible. Using Gaia DR3 data, we predict 4500 astrometric microlensing events with signal>0.1mas that occur between J2010.0 and J2070.0, where 1664 events are different from those found previously. There are 293 lens stars that can cause two or more events, where 5 lens stars can cause more than 50 events. We find that 116 events have the distance of background stars from the proper motion path of lens stars more than 8 arcsec in the reference epoch, where the maximum distance is 16.6 arcsec, so the cone search method of expanding the search range of sources for each potential lens star can reduce the possibility of missing events.

astro-ph.SR↗

arXiv2022

A flexible method for estimating luminosity functions via Kernel Density Estimation -- II. Generalization and Python implementation

We propose a generalization of our previous KDE (kernel density estimation) method for estimating luminosity functions (LFs). This new upgrade further extend the application scope of our KDE method, making it a very flexible approach which is suitable to deal with most of bivariate LF calculation problems. From the mathematical point of view, usually the LF calculation can be abstracted as a density estimation problem in the bounded domain of $\{Z_1 f_{\mathrm{lim}}(z) \}$. We use the transformation-reflection KDE method ($\hat{\phi}$) to solve the problem, and introduce an approximate method ($\hat{\phi}_{\mathrm{1}}$) based on one-dimensional KDE to deal with the small sample size case. In practical applications, the different versions of LF estimators can be flexibly chosen according to the Kolmogorov-Smirnov test criterion. Based on 200 simulated samples, we find that for both cases of dividing or not dividing redshift bins, especially for the latter, our method performs significantly better than the traditional binning method $\hat{\phi}_{\mathrm{bin}}$. Moreover, with the increase of sample size $n$, our LF estimator converges to the true LF remarkably faster than $\hat{\phi}_{\mathrm{bin}}$. To implement our method, we have developed a public, open-source Python Toolkit, called \texttt{kdeLF}. With the support of \texttt{kdeLF}, our KDE method is expected to be a competitive alternative to existing nonparametric estimators, due to its high accuracy and excellent stability. \texttt{kdeLF} is available at \url{http://github.com/yuanzunli/kdeLF} with extensive documentation available at \url{http://kdelf.readthedocs.org/en/latest~}.

astro-ph.IM↗

arXiv2021

Astrometric observations of a near-Earth object using the image fusion technique

The precise astrometric observation of small near-Earth objects (NEOs) is an important observational research topic in the astrometric discipline, which greatly promotes multidisciplinary research, such as the origin and evolution of the solar system, the detection and early warning of small NEOs, and deep-space navigation. The characteristics of small NEOs, such as faintness and fast moving speed, restrict the accuracy and precision of their astrometric observations. In the paper, we present a method to improve the accurate and precise astrometric positions of NEOs based on image fusion technique. The noise analysis and astrometric test from the observed images of the open cluster M23 are given. Using the image fusion technique, we obtain the sets of superimposed images and original images containing reference stars and moving targets respectively. The final fused image set includes background stars with high signal-to-noise ratios and ideal NEO images simultaneously and avoids the saturation of background stars. Using the fused images, we can reduce the influence of telescope tracking and NEO ephemeris errors on astrometric observations, and our results indicate that the accuracy and precision of NEO Eros astrometry are improved obviously after we choose suitable image fuse mode.

astro-ph.IM↗

arXiv2018

CCD astrometric observations of 2017 VR12,Camillo and Midas

We have observed three near-Earth objects(NEOs), 2017VR12, Camillo, and Midas during the year 2018. The observations were made by the 1-m telescope of Yunnan Observatory over 2 nights. Their precise astrometric positions are derived from 989 CCD observations. The theoretical positions of asteroids are retrieved from the Jet Propulsion Laboratory (JPL) Horizons System and Institut de Mécanique Céleste et de Calcul des Éphémérides (IMCCE). The positions of three asteroids are measured with respect to the stars in Gaia DR2 star catalogue. For 2017 VR12, the mean (O-C) of right ascension and declination are -0.090$^{''}$ and -0.623$^{''}$ based on the ephemeris of published JPL, but the mean (O-C) are 3.122$^{''}$ and -0.636$^{''}$ based on the ephemeris of published IMCCE. The great difference in declination could be explained by several factors. (1)The degenerated CCD images caused by the high apparent motion speed of the object leads to the reduction of positioning accuracy. (2)The poor timing system may bring the system error, especially in the high speed direction. (3)The asteroid may be perturbed by the earth when it approaches the earth too closely. The astrometric results show that the centroid centring method can reduce the dispersion of the non-Gaussian images compared with the PSF model method. For Camillo and Midas, the astrometric results are consistent based on two ephemerides. High-precision timing system, some astronomical effects and geometric distortion of CCD images should be carefully considered in the future works.

astro-ph.EP↗