Galaxy Evolution in Cosmic Structures A - Numerical Simulations of Galaxy Formation

Detailed Program:

The course is structured into four modules, designed to equip students with the essential skills needed to undertake a research project using numerical astrophysics techniques. While the focus will primarily be on cosmological simulations of galaxy formation, discussions on applying these techniques to other astrophysical problems will be encouraged.

1. Module 1: Introduction to numerical simulations, with emphasis on cosmological simulations of galaxy formation. Topics include:
   • Basics of numerical simulations and initial conditions
   • Numerical techniques for integrating equations of motion and fluid dynamics
   • Role of subgrid models in star formation processes
   • Overview of current state-of-the-art numerical simulations
   • Upcoming simulations of galaxy formation and key challenges in the field

   This module includes hands-on exercises focused on analysing cutting-edge numerical simulations, simulating real-world research in numerical cosmology.

2. Module 2: Cosmological initial conditions and existing codes for generating them. Key topics:
   • Methods for generating cosmological initial conditions: Gaussian random field and power spectrum (using the MUSIC code)
   • Determining feasible simulation sizes based on computational resources
   • Running a simulation using the massively parallel GADGET-4 code

   This module includes hands-on exercises in basic analysis of student-generated simulations, providing tools to assess validity and detect numerical errors. Necessary codes and a Docker environment will be provided to streamline workflow.

3. Module 3: Advanced data structures to improve efficiency in large dataset analysis. Topics include:
   • Linked Lists: Reducing complexity of spatial data searches within the simulation volume
   • Hash Tables: Efficient cross-matching of data across temporal outputs in simulations

   Students will engage in hands-on exercises to implement and apply these data structures, measuring speed improvements over standard algorithms.

4. Module 4: Visualisation techniques for cosmological hydrodynamical simulations. Key concepts:
   • Particles in cells: Managing shot noise and the importance of data normalization
   • Smooth maps: Generating smooth visual representations
   • Clustering techniques for particles: Applying SPH techniques with the py-sphviewer code
   • Simulation movies: Aspects such as movie length, frame rate, and interpolation

   Hands-on exercises will use the py-sphviewer code on existing simulations, allowing students to explore various visualisation methods essential for measuring astrophysical properties.

Prerequisites:

• Basic understanding of cosmology and physics at the MSc level
• A laptop for participation in hands-on exercises

Teaching Form:

The course will consist of electronic presentations covering the key concepts of each module, followed by hands-on exercises. The course will run over four weeks, with two 2-hour lectures per week, completing each module within one week and allowing in-class time for exercises.

Textbook and Teaching Resources:

• Required materials (electronic presentations and shared files) will be provided during lessons.
• Simulation data and required software will be provided during lectures.

Semester:

The course will be offered during the first semester of the 2024/2025 academic year, likely beginning in November.

Assessment Method:

Final assessment will consist of a written report summarising the findings of a proposed exercise, where students apply techniques studied throughout the course.

Office Hours:

By appointment