Study level

  • Vacation research experience scheme

Faculty/School

Faculty of Science

School of Chemistry and Physics

Topic status

We're looking for students to study this topic.

Research centre

Supervisors

Dr Michael Cowley
Position
Senior Lecturer
Division / Faculty
Faculty of Science

Overview

This project aims to explore the identification and properties of accreting supermassive black holes, commonly known as active galactic nuclei (AGN), by cross-matching the FourStar Galaxy Evolution Survey (ZFOURGE) with the Wide-field Infrared Survey Explorer (WISE) data. Using WISE infrared colors to pinpoint AGNs and comparing these findings with results from the spectral energy distribution (SED) decomposition on ZFOURGE data, you will enhance AGN identification techniques and deepen our understanding of their physical characteristics. This comparative approach will improve our knowledge of AGN traits across various wavelengths, contributing significantly to the broader field of galaxy evolution studies.

Research activities

Participants in this research project will:
  • conduct a literature review to understand current methodologies for AGN identification using infrared colours and SED decomposition, focusing on the strengths and limitations of each method
  • retrieve and crossmatch the ZFOURGE and WISE datasets using celestial coordinates, ensuring a high degree of accuracy in the matching process
  • apply WISE color selection criteria to identify AGN candidates and use specialised software to decompose the SEDs of galaxies from the ZFOURGE data to independently identify AGNs
  • compare the AGN populations identified by WISE colors and SED decomposition to assess the effectiveness and reliability of each method
  • analyse the physical properties of identified AGNs, such as their luminosity, redshift distribution, and host galaxy characteristics, to provide insights into the role of AGNs in galaxy evolution
  • prepare a comprehensive report and presentation to communicate research findings to the academic community, highlighting methodological innovations and insights into AGN properties.

Outcomes

Through this project, participants will:
  • develop critical skills in data analysis and astronomical research methodologies
  • gain a detailed understanding of AGN identification techniques and their application in real world datasets
  • contribute to the refinement of AGN identification methods and the broader understanding of galaxy evolution processes
  • potentially produce findings suitable for publication in peer-reviewed astronomical journals.

Skills and experience

The analysis and interpretation of the data will involve custom-designed data processing. Therefore, familiarity with a programming language, such as Python or IDL, is desirable.

Keywords

Contact

Contact the supervisor for more information.