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the Universities of Southampton, Sussex, Portsmouth, Queen Mary University of London, and Open University

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DISCnet Students Profiles

Lorenzo Zanisi - 2017 Entry
The University of Southampton

High redshift galaxies and their descendants

 

About Lorenzo

I am a focused, enthusiastic PhD researcher at the University of Southampton. I completed both my BSc in Physics with Astronomy  (hons) and MSc in Astronomy and Astrophysics (hons) at “La Sapienza” University of Rome. I am now working on theoretical and numerical models of galaxy formation and evolution. The goal of my project is to create accurate computer simulations that will shed light on how galaxies that were born just after the Big Bang have evolved until today. High performance computing tools are essential for this work; moreover the simulation output is so large it needs to be handled by means of Big Data analysis

techniques. Furthermore, the use of machine learning will be critical in recognizing the evolutionary paths of galaxies and their visual appearance.

What is your research?

Very massive, compact and already quiescent galaxies have been found lurking in the high redshift universe.  Only a few hundreds of million years after the Big Bang, these objects had time to form an amount of stars  almost comparable to that of the most massive galaxies that we see today in the near Universe, yet they are much smaller and their light profile is much more concentrated. What is the fate of these galaxies? Which are their descendants in the local Universe? Can we set up a theoretical picture so that their inferred evolutionary paths match data? These are some of the open questions in modern Astrophysics that I will try to address during my PhD.

What have you done in the first 6 months?

As the starting point of my project I am working both on data analysis and on a numerical model. More in detail, I am analyzing data from the Sloan Digital Sky Survey to discover new trends in galaxy populations. At the same time, I have built a simplified numerical model to understand how to reproduce such trends in the more detailed simulations I will create in the future. To achieve both tasks I am using several Python packages such as NumPy, SciPy, Pandas, Matplotlib, Seaborn, PySpark and Emcee.

Supervisory Team

Francesco Shankar (University of Southampton), Andrea Lapi (SISSA)

Why did you chose a DISCnet funded PhD?

All of the skills I will develop during my PhD are transferable to real-world problems and I will gain experience of this during the Data Science-driven placements offered by the industrial partners of DISCnet. With this expertise and work experience, I will be a competitive candidate for Data Science jobs, ready to make our world a better place.

 Keep up with Lorenzo's research on LinkedIn.