### List of proposed projects

**Proposed by**: David Harvey (Faculty), Yves Revaz (Faculty)

Simulating the formation of galaxies is vital to our understanding how the Universe formed and the underlying physics behind it. By simulating galaxies we can test theories, and probe the nature of the elusive dark matter. However, simulating galaxies can take a long time, in particular, owing to the treatement of the cooling due to molecules and metals. Indeed, an accurate treatement requires to solve many non-linear inter-dependent equations. If we can speed up the estimation of metal-cooling in galaxies we will be able to dramatically speed up our simulations. In a complete new and unique way, this masters project will aim to use deep learning to quickly and precisely estimate the abundances and cooling of a set of atomic species at play during the formation of galaxies. By constructing a model that can bypass the need to carry out complicated equations we can hopefully speed up the simulations and hence open up the possibility to probe new models of dark matter. The student will get then hands on simulations, machine learning, deep learning and gain experience in using python packages such as tensor flow and the GRACKLE libraries.

**Type of project:**Master project/Semester project

**References**:

**Type of project:**Master project/Semester project

**References**:

**References**:

**References**:

The VELOCE (VELOcities of CEpheids) project provides unprecedented time-series radial velocity data of 256 classical Cepheids, including 75 spectroscopic binaries. Modeling these data is challenging because several signals are present at once: large amplitude pulsations (speeds of 10-70 km/s over weeks), orbital motion (up to 25 km/s over years), and other modulations, such as multi-periodicity, fluctuating periods, time-variable amplitudes, etc.

The goal of this project will be to extend an existing Markov Chain Monte Carlo code that models orbital motion to include the signals due to pulsational variability. The project can be easily extended to treat fluctuating periods or amplitudes as well. The challenge will be to find efficient implementations that allow to infer a maximum of information from the VELOCE radial velocity curves without overfitting.

In this project, you will learn to

- work with optical spectra and high-precision radial velocity time series of pulsating stars
- develop MCMC analysis tools and sharpen your statistics skills
- contribute to a large Python code base (> 10000 lines) and an ongoing research program

… and more!

This project can be done as a TP-IVb, other 8 ECTS, or Master project.

Contact: Giordano Viviani, Richard Anderson

The VELOCE (VELOcities of CEpheids) project provides unprecedented time-series radial velocity data of 256 classical Cepheids, including 75 spectroscopic binaries. Modeling these data is challenging because several signals are present at once: large amplitude pulsations (speeds of 10-70 km/s over weeks), orbital motion (up to 25 km/s over years), and other modulations, such as multi-periodicity, fluctuating periods, time-variable amplitudes, etc.

The goal of this project will be to develop RV curve fitting methods using Regularization techniques to minimize the number of fit parameters used for representing pulsational variability. Regularization will improve the representation of Cepheid RV curves and allow to obtain more accurate orbital parameters, while also allowing the definition of RV template curves applicable to large spectroscopic surveys.

In this project, you will learn to

- work with high-precision radial velocity time series of pulsating stars
- develop regularization techniques for variability analyses and sharpen your statistics skills
- contribute to a large Python code base (> 10000 lines) and an ongoing research program

… and more!

This project can be done as a TP-IVb, other 8 ECTS, or Master project.

Contact: Giordano Viviani, Richard Anderson

Cepheids are pulsating stars whose radius and brightness vary within a stable period. This feature is particularly important in astrometry since it allows us to measure their distance accurately. And consequently, use them as standard candles to calibrate the cosmic distance ladder. However, many other effects other than their pulsation can modify the incoming signals from these stars, such as the presence of an orbiting star. In these cases, the spectra, and therefore the measured radial velocity, of the Cepheid will contain information from both phenomena that can be complicated to distinguish.

The aim of this project is to explore a newly developed methodology that could allow us to determine the pulsation and orbit periods of binary Cepheids without using any prior knowledge. This method constructs periodograms calculated using the concept of partial distance correlation, which allows us to effectively distinguish the Doppler shifts due to orbital motion and the spectral line variability induced by the stellar activity.

In this project, the student will work with part of the python package SPARTA and apply it to real study cases. The student will study the limitations and strong points of this method. Understand the precision and accuracy of the results. Propose modifications or improvements to the technique and experiment with them.

**Links:**

Method: https://ui.adsabs.harvard.edu/abs/2022A%26A…659A.189B/abstract

SPARTA: https://github.com/SPARTA-dev/SPARTA

This project can be done as a TP-IVb, other 8 ECTS, or Master project.

Contact: Giordano Viviani, Richard Anderson

Pulsating stars are extremely useful tools for astrophysics, since their light variations allow to measure distances and probe their interior structure. The current era of large time-domain surveys is revolutionizing our knowledge of pulsations and increases enormously their applicability for distance measurements. This allows us to unravel the structure of the Milky Way, the nearby Universe, and calibrate measurements of the expansion of the Universe.

In this project, we will use the all-sky survey TESS combined with the ESA space mission Gaia to obtain an unprecedented view of low-amplitude multi-periodic long-period variable stars in the Milky Way. The goal of the project will be to identify the variable stars through their variability, determine the variability properties, and calibrate the period-luminosity relations that allow to use them for distance measurements.

In this project, you will learn to

- access large astronomical data sets through online archives, such as the Gaia archive and MAST
- process large amounts of photometric time series using python
- use astrometric (positions, parallax, proper motion) and photometric data to maximum advantage
- distinguish different variability classes
- calibrate period-luminosity relations

… and more!

This project can be done as a TP-IVb, other 8 ECTS, or Master project.

Contact: Bastian Lengen, Richard Anderson