High Mass X-Ray Binaries: Stars that Sculpt the Universe

High-mass X-ray binaries (HMXBs), composed of a massive star and a compact object such as a neutron star, are essential for studying stellar wind dynamics and their influence on the formation of galaxies. In these systems, the massive star\u27s stellar wind interacts with the compact object, leading to the production of X-rays. These stellar winds are often clumpy, which introduces variability in X-ray emissions, offering a unique opportunity to analyze the properties of the wind. This study focuses on the HMXB 4U 1700-371, utilizing NuSTAR data to explore the variability in X-ray emission and to quantify the characteristics of the clumps within the stellar wind. The primary objectives are to measure soft X-ray absorption and analyze the hardness ratio to estimate clump size and density. We also examine the iron line emissions to understand the ionization state of the wind clumps. Preliminary results show significant absorption patterns in the NuSTAR hardness ratio, indicating that the stellar wind clumps are ingesting X­ rays from the neutron star. By analyzing the X-ray spectra, we can constrain the size of these clumps and estimate their density, providing valuable insights into the inhomogeneous nature of the stellar wind. These findings are crucial for refining models of stellar wind behavior, as they help improve our understanding of how irregular wind structures affect X-ray emission in HMXBs. Additionally, this research contributes to a broader understanding of stellar evolution, the impact of clumpy stellar winds on high-energy astrophysical systems, and the mechanisms driving X-ray emissions in extreme gravitational fields

Trust in Human-AI Symbiosis

As Artificial Intelligence increasingly supports critical decision-making in different real-world contexts, understanding trust between humans and Al becomes crucial. The goal of this study is to explore how various levels of Al transparency, control, and error influence human trust in Al-based decision support in safety-critical systems. By evaluating participant responses to Al recommendations across different operational modes, this research aims to identify optimal conditions that foster trust and enhance collaboration between humans and Al in high-risk environments. The findings will inform the development of more effective and reliable Al systems