TP-IV: EPFL Astrophysics offers students access to cutting-edge research in modern astrophysics and cosmology via practical work assignments, aiming to decipher existing observations, test established theories, and push forward innovative tools and methods to increase our understanding of the Universe.
The wide variety of these mini research projects reflects the broad range of topics and expertise covered by the different astrophysics research groups and laboratories at EPFL.
Applications from other disciplines are welcome – if you wish to participate in a project, please contact directly the indicated faculty member.
Note that some of the Master thesis projects can potentially be adapted to be TP-IVb. Please check both pages!
Proposed projects
Available as 2025-2026 TP-IV a & b (or other 8 credits projects).
Radio astronomy provides a unique probe of astrophysical phenomena within and beyond our solar system. However, a new growing challenge of radio interferometers is Radio Frequency Interference (RFI). Some of the loudest sources of radio waves are not from astrophysical sources, but radio and TV broadcasts, high-speed wireless communications (e.g. cell phone networks and WiFi), and radar. Radio interferometers are often built in remote and radio-quiet locations to avoid these sources of RFI. However, transient radio sources in the sky such as satellites are much more difficult to avoid. As the number of active satellites has rapidly increased (from 1,000 in 2013 to over 5,000 in 2022), RFI has become a growing concern in the radio astronomy community[1].
Cosmology is entering a new era with the deployment of next-generation telescopes like eRosita, Euclid, CMB-S4, and SKA, which will conduct large multi-wavelength surveys. These instruments will collect an unprecedented amount of data, offering a unique opportunity to explore the natures of dark energy and dark matter (DM). However, fully leveraging this information requires direct comparisons with cosmological simulations—a task currently constrained by the limited volumes achievable with existing computational resources.
To address this challenge, machine learning-based emulators have emerged as a promising solution to accelerate the forward modeling of astrophysical observations. In this project, we will focus on generating maps of extragalactic gas properties (such as temperature and density) from underlying DM density fields, using conditional deep generative models, including pix2pix GANs (Isola et al., 2018), diffusion models (Ho et al., 2020), and stochastic interpolants (Albergo et al., 2023). Using the extensive CAMELS simulation suite (Villaescusa-Navarro et al., 2021), we aim to create realistic 2D projections of these fields and extend this work into 3D representations. Another critical aspect of this endeavor will be incorporating the effects of baryonic physics in the conditioning of the emulators.
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
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