16 citations · 43 across the 13 of their papers we have counts for
13 papers
Parameter Estimation Horizon of Core-Collapse Supernovae with Current and Next-Generation Gravitational-Wave Detectors
Almat Akhmetali, Y. Sultan Abylkairov, Daniil Orel +7
Core-collapse supernovae (CCSNe) are powerful sources of gravitational waves (GWs). These signals propagate essentially unobstructed, providing a unique probe of the supernova cent…
Toward More Realistic Machine-Learning Inference of the Dense-Matter Equation of State from Supernova Gravitational Waves
Almat Akhmetali, Y. Sultan Abylkairov, Marat Zaidyn +6
Gravitational waves from core-collapse supernovae offer a unique probe of the equation of state (EOS) of dense nuclear matter. For rapidly rotating stars, previous machine-learning…
Evolution of fractality in centrally concentrated young clusters
Almat Akhmetali, Adilkhan Assilkhan, Mordecai-Mark Mac Low +6
We investigate the structural evolution of young star clusters forming within centrally concentrated molecular clouds. Our simulations use the Torch framework, which integrates the…
Probing Supernovae through gravitational wave entropy
Aknur Sakan, Nurzhan Ussipov, Ernazar Abdikamalov +6
We study an entropy-based framework to analyze gravitational-wave signals from core-collapse supernovae. We use waveforms generated by numerical simulations and analyze them in bot…
Machine learning-based classification of variable stars using phase-folded light curves
Almat Akhmetali, Alisher Zhunuskanov, Timur Namazbayev +4
Classifying variable stars is crucial for advancing our understanding of stellar evolution and dynamics. As large-scale surveys generate increasing volumes of light curve data, the…
Gamma-ray burst light curve reconstruction with predictive models
Zhunuskanov A., Sakan A., Akhmetali A. +2
Gamma-ray bursts represent some of the most energetic and complex phenomena in the universe, characterized by highly variable light curves that often contain observational gaps. Re…
The Role of Fractal Dimension in Wireless Mesh Network Performance
Marat Zaidyn, Sayat Akhtanov, Dana Turlykozhayeva +4
Wireless mesh networks (WMNs) depend on the spatial distribution of nodes, which directly influences connectivity, routing efficiency, and overall network performance. Conventional…
Luminis Stellarum et Machina: Applications of Machine Learning in Light Curve Analysis
Almat Akhmetali, Alisher Zhunuskanov, Aknur Sakan +4
The rapid advancement of observational capabilities in astronomy has led to an exponential growth in the volume of light curve (LC) data, creating both opportunities and challenges…
MEGA: Maximum-Entropy Genetic Algorithm for Router Nodes Placement in Wireless Mesh Networks
N. Ussipov, S. Akhtanov, D. Turlykozhayeva +7
Over the past decade, Wireless Mesh Networks (WMNs) have seen significant advancements due to their simple deployment, cost-effectiveness, ease of implementation and reliable servi…
Single Gateway Placement in Wireless Mesh Networks
D. A. Turlykozhayeva, W. Waldemar, A. B. Akhmetali +3
Wireless Mesh Networks (WMNs) are crucial for various sectors due to their adaptability and scalability, providing robust connectivity where traditional wired networks are impracti…
Automatic modulation classification for MIMO system based on the mutual information feature extraction
N. Ussipov, S. Akhtanov, Z. Zhanabaev +6
Automatic Modulation Classification (AMC) is an essential technology that is widely applied into various communications scenarios. In recent years, many Machine Learning and Deep-L…
Routing Algorithm for Software Defined Network Based on Boxcovering Algorithm
Dana Turlykozhayeva, Sayat Akhtanov, Nurzhan Ussipov +3
A routing algorithm is the most fundamental problem in complex network communication. In complex networks, the amount of computation increases as the number of nodes increases whic…
Fractal dimension of star clusters
N. Ussipov, A. Akhmetali, M. Zaidyn +4
Quantitative analysis of the structure of star clusters is crucial for understanding their formation and evolution. In this article, we explore the application of fractal dimension…