In order to discover new exoplanets, the Kepler mission has monitored a small portion of the sky in search of the tell-tale dimming signature of a planet passing in front of a star. Thus, a large database of stellar variability data was built up, and in 2016, Boyajian et al. (MNRAS 457, 3988) reported on an unusually deep and long-lasting dimming event, which was subsequently hypothesized to be due to alien megastructures (Wright et al. 2016, ApJ 816, 17). More natural explanations have since been put forward and explored, including the catastrophic breakup of one or more exoplanetary bodies. Such an event would lead to the production of a dust cloud large enough to explain the observed dimming. Since 2016, the sample of objects showing these deep and long-lasting dimming events has been expanded to about a dozen. In this Master's project, we will use the characteristics and statistics of those dimming events in comparison to the total number of stars monitored to find out how common catastrophic exocometary collisions are. This is important in understanding the stability of extrasolar planetary systems.

Massive stars are like rock stars: they live fast and die young. And they usually do so in an impressive way – supernova explosions that leave behind neutron stars and black holes. The explosions are also expected to “kick” the stellar remnants. The physics of these processes are not completely understood, and therefore many different core-collapse & supernova kick prescriptions are used in modelling of single & binary stars. This lack of knowledge makes it hard to understand other phenomena, such as X-ray binaries, gravitational-waves sources from merging remnants, gamma-ray bursts, etc. In this project we will use the POSYDON code to predict the outcomes of different prescriptions, and test them using observations.

The student will be trained in various aspects of research: (i) stellar evolution; (ii) scientific programming; (iii) scientific computing through simulations; (iv) statistical inference (Bayesian analysis, Machine Learning); (v) scientific writing in the format of a journal article; (vi) communication/organization via an international collaboration (https://posydon.org/) and presentation experience (basic English needed).

The most luminous persistent sources in the Universe are the ultraluminous X-ray sources (ULXs). We believe that their majority are accreting binaries: material from a normal stars is transferred to a neutron star or black hole, forming a hot accretion disk that emits in the X-rays. Many aspects of ULXs are not completely understood. Recent studies indicate that some of these ULXs are Be X-ray binaries: rapidly rotating B-type stars expels some of their material creating “decretion disks” around them, and while their companions (neutron star or black holes) are passing through that, they capture some of this material and shine in the X-rays! To understand this channel for forming ULXs, we need better modelling of BeXRBs. In this project we will use the POSYDON code to evolve Be-XRB systems, model their emission, and measure their contribution in the ULX populations.

The student will be trained in various aspects of research: (i) stellar evolution and accretion; (ii) scientific programming; (iii) scientific computing through simulations; (iv) statistical inference (Bayesian analysis, Machine Learning); (v) scientific writing in the format of a journal article; (vi) communication/organization via Interaction with members of an international collaboration (https://posydon.org/) and presentation experience (basic English needed).

In distant galaxies we cannot see individual stars. Thereby, to understand the physics of stellar evolution in the early Universe, we need to compare the spectra of galaxies against models. However, the X-ray part of the spectrum is extremely challenging. To constrain the theoretical models we need to model the spectra of individual sources. More importantly, predicting the X-ray spectrum is critical to probe the effect of stellar population in the early Universe (ionizing/heating the interstellar/integalactic medium). In this project we will use analytical models and empirical data to assign spectra in X-ray binaries produced by the POSYDON code, for different metallicities.

The student will be trained in various aspects of research: (i) stellar evolution and accretion; (ii) scientific programming; (iii) scientific computing via simulations; (iv) X-ray data analysis (v) scientific writing in the format of a journal article; (vi) communication/organization via interaction with members of an international collaboration (https://posydon.org/) and X-ray astronomy experts (Greece, USA) and presentation experience (basic English is needed).

The SPMN-CSIC network records about 20,000 meteors and fireballs every year, occurred over continental and insular Spain and neighboring countries. These luminous phenomena are produced by the arrival at hypervelocity of asteroidal and cometary rocks suffering ablation, and creating an ionized column called meteor. All these recordings are stored into the SPMN-CSIC meteor and fireball database that has been operational for 27 years. The goal of the proposed TFM is providing the candidate the basic skills to complete the astrometric measurements using a well-tested routine, and to learn the full reduction process of these data for obtaining valuable scientific publications. Then, using meteor recordings from several CCD and video stations all over Spain and Catalonia, we will be able to reconstruct the atmospheric trajectories, to obtain the radiant and incoming velocity, and finally to infer the heliocentric orbit in the Solar System of the meteoroids producing the recorded meteor events.

I envision a practical TFM, teaching the right methodology, defining several case studies and establishing a publishing goal to be achieved. All together to provide an appropriated student training, by gaining the required skills to continue a PhD thesis on this subject.

Requirements: A significant knowledge of English and Python are needed to be considered.

The stars form in the densest parts of the interstellar molecular clouds. The study of the star formation, which includes all stages from the initial conditions, before the gravitational collapse starts, to the formation of planets around the young stars. Several factors can regulate the process of the formation of the stars: turbulence, magnetic fields and the ionisation fraction of the clouds, the initial angular momentum of the clouds. The goal of this project is to study the properties of the magnetic fields in a selected small sample of star forming regions.  To do so, the student will work with recently acquired ALMA full polarisation data.  ALMA is the most powerful telescope in the (sub)millimetre domain. It is an aperture synthesis interferometer located in the Atacama plateau at an altitude of 5000 m. It consists of 64 state-of-the-art antennas, with receivers that can be tuned at different frequencies in the millimetre band.

Hydrogen-rich supernovae (SNe) showing long-lasting narrow emission lines in their spectra are known as SNe IIn. These objects arise from massive stars undergoing core collapse within a dense hydrogen-rich circumstellar medium (CSM). The source of the narrow emission lines is believed to be the result of interaction between the SN ejecta and this CSM, related to progenitor mass–loss episodes before the explosion. The physical mechanisms driving the mass loss are still not well understood.  However,  the environments where SNe explode can provide helpful information about these mechanisms and their progenitors. Therefore, this project aims to explore the environments of SNe IIn to constrain the progenitor properties of these interacting SNe and the role of metallicity in mass loss. The student will work with observations (data from the literature), astronomical tools, and Python codes.

Type II supernovae (SNe II) provide independent distance measurements to type Ia supernovae (SNe Ia), thus contributing to the elucidation of the origin of the Hubble tension [1]. There are different photometric and spectro-photometric methods for the standardisation of SNe II, such as the Expanding Photosphere Method (EPM), Standard Candle Method (SCM) and Photometric Colour Method (PCM) [2]. Although the spectro-photometric methods provide better precision (e.g. EPM, SCM), photometric methods are of special interest for the LSST era, where thousands of SNe will be discovered, but few will have spectroscopic follow-up. As with SNe Ia, the host galaxy in which they reside can imprint some systematic effects in their luminosities (e.g. [3]). This TFM aims at better understanding how the environment affects SNe II light curves and the possibility of applying host-galaxy properties as corrections to reduce the scatter in distance estimations. The student will fit SNe II with the PISCOLA light-curve fitter [4], measure host-galaxy photometry using HostPhot [5] and estimate galaxy properties via template fitting with different softwares.  Additionally, the student will compare galaxy parameters against SNe II properties, analyse the physical implications of these and quantify possible biases in SNe residing in, for instance, high- and low-mass galaxies.

[1] Hu & Wang 2023, Universe, 9, 2;  [2] de Jaeger & Galbany 2023 arXiv:2305.17243; [3] Sullivan et al. 2010, MNRAS, 406, 2; [4] Müller-Bravo et al. 2022, MNRAS, 512, 3; [5] Müller-Bravo & Galbany 2022, JOSS, 7, 76

Supernovae have been used as cosmological probes for a long time.  On the one hand, type Ia supernovae (SNe Ia) are excellent distance indicators and were used to discover the accelerated expansion of the Universe by measuring the Hubble constant (H0; e.g. [1]). On the other hand, type II supernovae (SNe II), although fainter and less precise than SNe Ia, provide an independent measurement of H0 [2]. The latter is of special interest for contributing to the elucidation of the origin of the so-called Hubble tension [3]. For SNe Ia, it is well known that near-infrared (NIR) wavelengths provide far superior precision when estimating distances, compared to the optical [4]. On the contrary, SNe II remain relatively unexplored at these wavelengths. The aim of this TFM is to study the NIR light curves of the Carnegie Supernova Project sample of SNe and explore the possibility of using these wavelengths for cosmology. The student will fit SNe II with the PISCOLA light-curve fitter [5] and use statistical tools, including machine-learning such as Principal Component Analysis, to find correlations between light-curve parameters and measure distances. If the results are promising, this might open a new path for supernova cosmology.

[1] Riess et al. 1998, AJ, 116, 3; [2] de Jaeger. 2022, MNRAS, 514, 3; [3] Hu & Wang 2023, Universe, 9, 2; [4] Freedman et al. 2009, ApJ, 704, 2; [5] Müller-Bravo et al. 2022, MNRAS, 512, 3

The outer Galaxy is the portion of the Milky Way located at Galactocentric distances beyond the Solar Circle. It shows chemical properties significantly different from those in the Inner Galaxy, with a decrease in abundances of elements such as oxygen, carbon and nitrogen compared to the Solar neighbourhood. The lower abundances of these heavy elements in the Outer Galaxy have suggested in the past that this region of the Galaxy is not suitable to form planetary systems in which Earth-like planets capable of sustaining life could be born, and therefore it is not considered to be part of the Galactic Habitable Zone. In more detail, a lack of elements such as carbon, oxygen and nitrogen is expected to result in a lack of complex organic molecules (COMs), which are thought to be precursors of more complex biogenic molecules.

Interestingly, recent discoveries suggest that COMs may be present in the Outer Galaxy, thus redefining our understanding of the Galactic Habitable Zone. Together with an international team, we have initiated the CHEMOUT project ("CHEMical complexity in star-forming regions of the OUTer Galaxy") aimed at studying the presence of complex molecules and their connection to the building blocks of life in this inhospite region of the Galaxy. The student will analyse observations of the whole CHEMOUT sample recently taken with the Yebes 40m radio telescope, located in Guadalajara. The project will focus on the characterization of the spectra and the identification of molecular species that could help to understand the chemical and physical properties of these regions. The student will have the opportunity to work and interact with all the members from the CHEMOUT collaboration.

Most stars do not form in isolation, but in rich clusters containing hundreds of stars that are initially deeply embedded inside large molecular clouds. Therefore, understanding the formation of stars, and eventually planets, requires characterising the fragmentation process of the molecular cloud into dense cores out of which stars will eventually form. The number of newly-formed stars with a given mass, the so-called IMF (initial mass function), is a key parameter in the study of the formation and evolution of clusters that transcends all astrophysical fields. During the last decades, some theories have claimed that the IMF is related to the masses of the dense cores that fragment out of the molecular cloud, the so-called CMF (core mass function). The first observational results supported this possible connection, however biases and limitations on the spatial resolution and the accuracy of core mass determination may have affected the results obtained so far.

We seek to overcome these known observational biases and perform a detailed study of the CMF in four embedded clusters at different evolutionary stages, emerging from the same molecular cloud. For this, we have acquired ALMA band 6 (220 GHz) observations, reaching a spatial resolution of 200 au and a mass sensitivity of 0.1 Msun, which will allow us to resolve all the members in the cluster and probe the CMF from low to high core masses. The student will work with new high-quality ALMA data to produce images of the dust continuum emission of the dense cores in these four clusters. Following the generation of the astrophysical images, the student will use automatic procedures to identify and extract all the detected cores. This will allow us to determine properties such as their masses, sizes and location within the cluster. With the masses, the CMF of these clusters will be constructed and compared to the IMF.

The expansion rate of the universe parameterized by the Hubble-Lemaitre parameter H(z), has been a major endeavor in cosmology since the discovery of the expanding Universe. H(z) is not constant, but rather varies over cosmic time following the deceleration and acceleration of the Universe. In the last years, significant effort has been put forth to measure with high precision the local value of the Hubble-Lemaitre parameter known as the Hubble constant (H0), and today H0 is estimated from the distance ladder with an uncertainty of ~1%. Perplexingly, these findings have revealed a dramatic discrepancy dubbed the Hubble tension: the estimation of H0 from the local distance ladder is in strong disagreement (at 5 sigma or 99.99% level) with the value inferred at high-redshift from the angular scale of fluctuations in the cosmic microwave background (CMB), possibly hinting towards new physics beyond the standard model. This discrepancy represents the most urgent puzzle of modern cosmology, and it is nowadays one of its hottest topics.

One of the ways to alleviate the Hubble tension is to reduce the systematic uncertainties of the methods used to determine H0. For the distance ladder method, one of the main contributors to the systematics is the standardization of Cepheids and type Ia supernovae (SNe Ia). In particular, Cepheids calibration takes into account the known Period-Luminosity relation with a correction based on metallicity. However, the SHOES team assigned to each Cepheid a metallicity based on the radial distance and a metallicity gradient measured from HII regions. To address this possible leading systematic, the student will use integral field spectroscopy (IFS) from 29 of the 37 SH0ES Cepheid and SN Ia galaxies, to measure local metallicities at positions where Cepheid stars are found, and compare them with those used in the SH0ES work. With this exquisite dataset, the student will also map their local environmental properties (star formation rate, stellar age and dust extinction) to explore the environment effects in Cepheid distance estimation and in the determination of the current expansion of the universe H0.

Starting date: Anytime between Sep 2023 and January 2024

X-ray binaries (XRBs) are X-ray bright systems composed of a compact object (a black hole or a neutron star) and a companion star, typically referred to as the primary and the secondary star, respectively. Under the effect of the extreme gravity field around the compact object, matter is transferred from the secondary to the primary and finally accreted onto it. As this happens, the gravitational energy of matter is converted into radiation mainly in the X-ray band. Observing these systems with multi-wavelength telescopes provides scientists with the opportunity to study the behavior of matter in some of the most extreme environments in the Universe, such as neutron-star cores, and perform tests of General Relativity. In particular, the physical properties of the accretion flow around the compact object, e.g. its geometry, its temperature, and its chemical composition, can be probed with the analysis of X-ray spectra. Investigating the X-ray variability over short time-scales, i.e. from seconds to fractions of a millisecond, enables the discovery of periodic and quasi-periodic signals such as coherent pulsations (in the case of neutron stars) and quasi-periodic oscillations, whose nature is still debated. 

In this internship, we will use data from different X-ray telescopes, such as XMM-Newton, Chandra, and Swift to perform spectral and timing studies of an X-ray binary. The project will provide the student with the opportunity to learn how to reduce and analyze X-ray data, along with a theoretical background on accretion physics and compact objects.

The student will work as part of the MAGNESIA group at the ICE institute, a group focused on studying neutron-star physics through both an observational and theoretical perspective. They will also be welcome to join our activities, such as weekly group meetings and scientific projects, and benefit from the range of expertises of our team members.

Supermassive black holes of 10⁹ solar masses are found at the center of most massive galaxies. These galaxies and their black holes are thought to grow synchronously at the same time. Under this scenario, the supermassive black holes would have evolved from seed black holes of smaller mass formed in the early Universe. Detecting such seeds when the Universe was very young is extremely challenging but with the advent of cutting-edge observations we can now reach distant galaxies hosting black holes that are actively acretting matter: active galactic nuclei (AGN). Recently, a few AGN have been observed in dwarf galaxies when the Universe was much younger than it is today, 6,000 million years after the Big Bang. The black holes powering this distant AGN are found to be more massive than expected from a synchronized growth with their host galaxies (i.e., they are over-massive black holes), a result that challenges models of black hole-galaxy co-evolution (Mezcua, Siudek et al. 2023).

This TFM aims at identifying AGN in dwarf distant galaxies and estimating their black hole mass. The results can confirm if distant AGN dwarf galaxies host over-massive black holes or whether instead, they host black holes of smaller mass. The latter could represent the relics of the early Universe seed black holes from which supermassive black holes form. This project will have important implications for our understanding of the seed black hole formation. A basic knowledge of python is advisable.

Active galactic nuclei (AGN) are powered by massive black holes and play a key role in galaxy formation and evolution. From an observational point of view, the black hole mass correlates with the properties of the host galaxies, but the origin of this relationship is still largely unexplored and our understanding of the feedback process between black holes and galaxies is still incomplete.  Large-scale spectroscopic surveys provide a unique opportunity to study the co-evolution of black hole and host properties. However, the selection of AGN is still a challenging task. The standard selection methods based on emission line ratios result in incomplete and contaminated AGN samples. The goal of this TFM is to identify AGN based on an unsupervised machine learning method. The high-dimensional nature of galaxy spectra makes it challenging for humans to detect features associated with AGN, but not for advanced machine-learning algorithms. In this project, we aim at developing a new approach to identify AGN using the full information from the galaxy spectra and machine-learning techniques. Such an approach promises unbiased AGN selection and will be of interest for planning future AGN observing strategies. A good knowledge of python and basic knowledge of machine-learning methods is advisable.

Hydrogen-rich supernovae (SNe II) are produced by the final explosion of massive stars (>8 Msun). They retain a significant fraction of hydrogen at the moment of the explosion, and hence their spectra show prominent Balmer lines. Recently, SNe II have been proposed as metallicity indicators, making them relevant in the cosmic context. More precisely, theoretical models predict that the strength of metal lines around 50 days post-explosion is related to the metallicity of the SN progenitor [1]. Thus, SN II metal-line pseudo-equivalent-widths (pEWs) generally become stronger when metallicity increases. This project aims to explore this correlation and test the parameter space obtained from the models. The student will work with observations and models, astronomical tools and python codes. The sample used for the project comprises spectra from the literature and new observations, plus theoretical models developed by Dr Luc Dessart.

Characterization of exoplanets requires high instrumental precision as well as combining measurements from very different sources in a common framework. In addition to this, numerous instrumental and astrophysical degeneracies exist so interpreting this high quality data requires holistic and unbiased techniques to combine all the data consistently. Although we can simulate most of the complexity of the observations, these degeneracies are often difficult to predict a priori, creating all sorts of false negative and false positive detections of exoplanet features.

To account for this, and to accommodate the increasing complexity of astronomical datasets, we will implement data and model driven machine learning techniques. Instead of predicting all the cross dependencies a priori, we will use deep neural networks to identify exoplanetary features in time-series (true Doppler signals, true transit signals) and on spectroscopic observations such as the ones that are being obtained from ground based and space based observatories. This project will work with both synthetic and real observations from ground and space based observatories. Detailed knowledge of machine learning is not required, but good coding skills (especially in Python, which is the main coding language for machine learning techniques) are strongly recommended.

The Radio Occultations and Heavy Precipitation aboard PAZ satellite (ROHP-PAZ) is an experiment that had the objective to test, for the first time, the capability of the Global Navigation Satellite System (GNSS) Polarimetric Radio Occultation (PRO) technique to sense precipitation. Led by the Institut de Ciències de l’Espai (ICE-CSIC,IEEC) and on orbit since February 2018, the results of the analyses of first years of data have demonstrated that PRO are not only able to sense rain, but also to provide information of the vertical cloud structures.

With the objective to continue with the validation of the PRO technique and exploit its applications, the aim of this project is to analyze the numerous coincident measurements between the ROHP-PAZ observations and radars and radiometers. The NASA’s Global Precipitation Measurement (GPM) core satellite (CO) flies a precipitation radar that provides detailed information about rain and, partially, of its associated cloud structure. A significant number of coincidences have been identified between our ROHP-PAZ observations and GPM-CO, which are complemented by the numerous microwave radiometers also aboard GPM-CO and from other satellite platforms.

This project will consist on analyzing the coincidences and infer relationships between the different observations, with the objective to characterize the vertical structure of the ROHP-PAZ observations.

The Institute of Space Sciences is developing a radio-interferometer in the 10.7 GHz – 12.7 GHz range. The current development of the instrument requires the characterization of the current hardware in terms of phase delay measurements and its noise characteristics in a controlled environment.

The interferometer will be set up in our laboratory. A known signal will be injected into the different antenna ports and will be used as a calibration signal. Using post-processing techniques, the complex cross-correlation (visibility functions) obtained with the interferometer will be computed, and its stability and noise characterized. These measurements will yield the ultimate precision of the achievable phase delays. Phase closures shall be applied to the measured visibilities to determine the stability of the instrument itself. This is an experimental project.

The formation of relatively close (about 10 astronomical units, au) stellar binaries may inhibit or reduce significantly planet forma1on, because the circumstellar disk are expected to have a small radius ( about 1 au), and the circumbinary disk may not be stable and dense enough for planet forma1on. We have obtained with ALMA very high angular resolu1on and high fidelity images of the molecular gas around a well know very young binary system. ALMA (Atacama Large Millimeter Arrays) is the most powerful radio facility at millimeter wavelengths. The project will consist in analyzing the images to better understand how the accretion proceeds from the observed spiral filaments toward the 1ny circumstellar disk around the two young stars. Ultimately, we want to see whether the accre1on prices is high enough to allow planet formation at au scales.

Stellar activity poses a major limitation to the extraction of planetary signals from radial velocities and transits. An evolving and rotating inhomogeneous star surface hampers the detection of small planets in temperate orbits and also atmospheric characterization of exoplanets using transit spectroscopy. Our ability to account for these effects is closely related to improving our understanding of stellar activity as a function of time and wavelength. This project will develop methodology to retrieve planetary signals from data affected by activity. One of the main tools will be the StarSim code, which is capable of accurately simulating stellar variability effects. Among other sources, proprietary data from the CARMENES radial velocity spectrometer will be analyzed.

The Cosmology and Extragalactic Astronomy groups at ICE-IFAE-PIC have a long expertise on generating mock galaxy catalogs for several large extra-galactic surveys ongoing or being in which we actively collaborate such as PAU, DES or Euclid. In order to fully exploit and interpret the observed data from galaxy surveys it is essential to produce mock galaxy catalogues since they can help in a variety of ways. They are useful to design and calibrate galaxy surveys. They can help to study selection effects, to calibrate errors and explore systematic effects, to test new techniques to measure cosmological parameters or to calibrate cluster finders and photometric redshift estimators.

Accurately reproducing observed distributions in simulations is mandatory to achieve successful scientific analysis. In this Master thesis project we propose to apply in a novel way a method to estimate a continuous transformation that maps one N-dimensional probability density function distribution to another. This method will allow not only to reproduce the observed distributions but also to maintain the correlations between the observables. We will apply and validate this methodology using MICE and/or Euclid simulations.

The detection of gravitational waves (GWs) gave great impulse to the possibility of observing strong and quantum gravity effects in Black Hole (BH) systems. At the moment we can only affirm that the Schwarzschild solution is not wrong if compared to the data, but a number of future experiments is promising to reach much higher levels of sensitivity and probe different frequency ranges and larger redshifts. For the first time over the last century, possible anomalies pointing at new physics and giving insights on the nature of the gravitational interaction and BHs may be detected. Various alternative descriptions of BHs have been developed with the aim of solving some of the most puzzling issues of gravitation, central singularity and information loss paradox and the related no-hair theorem among the others.

As usual in physics, a lot of information can be extracted through scattering experiments. Within this framework the quasi-normal modes (QNMs) and greybody factors play a fundamental role. The first are the dissipation modes of a perturbed BH and they seem to be deeply related to the nature of the BH itself. This is why they are considered as the characteristic oscillation modes of the BH. Furthermore, they are seen to dominate the ringdown gravitational waveforms at late time so that they are among the preferred candidates to host possible deviations from the general relativistic description. On the other side, the greybody factors encode the deviation of Hawking radiation from the pure black-body one, or in other words, the percentage of Hawking radiation which could reach us after scattering through the potential barrier surrounding the BH. Again, these quantities are intimately connected to the parameters describing the BH.

Therefore, a deep investigation of QNMs and greybody factors in different physical situations (such as possible exotic compact objects) and with different tools (both purely theoretical and numerical) offers a rich playground to test the quantum nature of gravity, no-hair theorems and alternative theories of gravity among other things.

Compact stars, and more particularly neutron stars, are a unique laboratory for testing matter under extreme conditions. Over the past years a particular effort has been invested in studying different scenarios for the dense phases of matter in the core of neutron stars, from quarks to hadrons at high densities. The final aim is to understand neutron star observables, such as the mass, radius, magnetic fields or rotation, in terms of a plausible scenario for its interior.

For this purpose, theoretical approaches based on effective field theories for hadronic and quark matter have been developed in our group. The master thesis proposed aims at following the study of the interior of neutron stars by applying the previously developed theoretical frameworks to obtain the equation of state and transport properties of dense matter in the core of neutron stars. With these ingredients, we will be able to address the mass and radius of neutron stars as well as the dynamical properties of neutron stars, going from rotation to the effect of magnetic fields onto neutron stars.