Physical Sciences and Technology

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Identification of young star objects in the serpens south star-forming region of the aquila molecular cloud
(Al-Farabi Kazakh National University, 2026-06-19)
Н.Ш. Алимгазинова
;
A.B. Manapbayeva
;
Aruzhan Omar
;
Kunduz M. Turekhanova
;
Nurlan Abildayev
We present the results of a search and identification of young stellar objects (YSOs) in the Serpens South star-forming region, which is part of the Aquila Rift complex. Using AllWISE catalog data within a radius of 7′ from the center of the region, a multi-stage filtering procedure was applied to remove contaminating sources, including galaxies, active galactic nuclei, shock emission sources and PAH emission. Photometric criteria were then used to classify the sources according to their evolutionary stages. As a result, a sample of 145 YSO candidates was identified, including 1 protostar, 37 Class I objects, 48 Class II objects, 47 Class III objects and 12 transition disks. A quantitative analysis of the spatial distribution of the sources was performed using cumulative distribution functions, the Kolmogorov Smirnov test and bootstrap resampling. The results show that early-stage objects (Class I) exhibit pronounced clustering in the central region (R₅₀ = 0.26 pc) and are associated with dense filamentary structures, whereas Class II and III objects display a more extended distribution. A Jeans analysis combined with Monte Carlo simulations yielded a median gas density of n ≈ 1.6 × 105 cm-3, consistent with dense prestellar cores. Multiwavelength verification using infrared, X-ray, optical and radio catalogs showed that 78.6% of the objects possess independent infrared confirmation, while 70.3% have X-ray detections. In addition, 11 new YSO candidates not previously reported in published catalogs were identified. The obtained results demonstrate the high efficiency of WISE data for detecting heavily obscured sources and provide new insights into the early stages of star formation in dense filamentary environments. Keywords: Young stellar objects, Serpens South, Aquila Rift, WISE, star formation.
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Correlation analysis of the wind acceleration parameter in high-mass X-ray binaries
(Al-Farabi Kazakh National University, 2026-06-19)
Zhantay Muratkhan
;
Saken Toktarbay
;
Aray Muratkhan
;
Aliya Taukenova
;
Nadeem Azhar
This work presents a correlation analysis of the wind acceleration parameter β in high-mass X-ray binaries (HMXBs). The aim of the study is to determine how β depends on the geometric and dynamical characteristics of the system, primarily on the ratio of the orbital radius to the stellar radius, a⁄R_* and on the terminal wind velocity v_∞. For this purpose, published values of R_*, a and v_∞ together with measured wind velocities in the vicinity of the neutron star, were used. Based on these data, the parameters of the β-velocity law were determined numerically. The resulting β values were then approximated using a linear regression, β≈k a⁄R_* +c, yielding a simple empirical relation. The results show that the linear correlation between β and the orbital-to-stellar radius ratio is weak (with a Pearson correlation coefficient r ≈ 0.22) and is accompanied by substantial scatter, indicating the influence of additional physical factors. The linear regression yields a small positive slope (k ≈ 0.14), which suggests only a weak tendency for β to increase with the orbital ratio. Because of the small sample size, this trend should be regarded as tentative. The proposed linear model allows β to be estimated without detailed spectroscopic analysis and may be useful as a rough empirical indicator of wind-accretion properties in HMXBs. The originality of this study lies in providing a simple empirical first-order assessment of the β parameter in HMXBs based on observed orbital and wind properties in systems where detailed spectroscopic constraints are limited. Key words: high-mass X-ray binaries (HMXBs), β-law (β-velocity profile), wind velocity profile, terminal wind velocity, orbital ratio a⁄R_* , correlation analysis.

Physical Sciences and Technology

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