2. Exploring the devouring nature of Neutron Stars through Stellar Wind studies.

 

ESAC supervisor: Camille Diez
Collaborator(s): Peter Kretschmar (ESAC), Felix Fürst (ESAC), Victoria Grinberg (ESTEC)

Site: ESAC

Neutron stars are the end products of massive stars and are among the most fascinating and extreme objects in the Universe. In the case of a high-mass X-ray binary (HMXB), the neutron star accretes material from a massive star, usually of more than 10 solar masses. The massive star loses large amounts of its mass via “stellar wind”. As the material falls onto the neutron star's surface, it releases immense amounts of energy, making HMXBs some of the brightest X-ray sources in the sky.

Studying the stellar wind tells us about the life cycle of some of the most massive stars in the galaxy, about how they shape and influence their surroundings, and about the interactions of matter and energy under the most extreme conditions. Those areas of research can be assessed through time-resolved high-resolution spectroscopy currently possible with e.g. XMM-Newton to lay the foundations for future revolutionary X-ray observatories such as the upcoming XRISM and ESA’s flagship mission Athena.

To achieve this goal, the project will be structured as followed:

  • Introduction to the field’s background and methods with some of the world-leading experts and most important papers.
  • Extraction of X-ray data of an HMXB taken with ESA’s XMM-Newton observatory.
  • Analysis of lightcurves and spectra of the source to infer properties of the wind and constrain spectral models. We will use the Interactive Spectral Interpretation System (ISIS), designed to facilitate the interpretation and analysis of high resolution X-ray spectra, and develop scripts to analyse data (S-Lang preferred, Python is also possible).

From this study, the trainee will gain knowledge about X-ray missions, data analysis software, programming skills and will benefit from local and international collaborations with X-ray experts. The results may lead to a future scientific publication, after the traineeship.

Project duration: 3 months (project focusing on the analysis part) up to 6 months (full project).

Desirable expertise or programming language:

  • Enthusiasm and curiosity for exploring scientific data.
  • The trainee should be comfortable with the project being conducted in English.
  • Basic astrophysics background, e.g. an introductory lecture is a plus.
  • The project explicitly offers the chance to develop and improve your coding skills. If the trainee chooses to code in Python (or any other language than S-Lang), experience in this programming language, e.g. from a university course, is highly desirable but not required.

 

To apply for this project please fill in an online application form through the following link.