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Thesis Opportunities
Testing the models of Quasi-Periodic Oscillations with physically-motivated frequency searches
Quasi-periodic oscillations are signal oscillations with non-constant frequency observed around neutron stars and black holes, the origin of which is still a mystery. It is likely that there is no single explanation, as there are various types of oscillations that appear at different times and systems, at different frequencies and with different behaviors. Possible explanations include from frame dragging to resonances at specific distances from the compact object. By running targeted, physically motivated searches for new QPOs, we aim at testing the predictive power of the models. For Theses on this topic, you will perform spectro-polarimetric-temporal analysis of X-ray data from various black holes or neutron stars using data from various satellites including IXPE, NuSTAR, NICER, XMM-Newton, HXMT, RXTE
Machine learning and advanced statistical methods for multi-probe inference on the physical properties of dark matter and dark energy
This research focuses on the application of machine learning and advanced statistical methods to reconstruct the physical properties of dark matter and dark energy. By integrating data from diverse cosmic probes -- such as the Cosmic Microwave Background, Large-Scale Structure, and weak lensing -- the project aims to overcome the computational bottlenecks of traditional Bayesian inference. Non-parametric and emulator-based techniques are employed to explore high-dimensional parameter spaces, allowing for precise tests of dark matter particle models and dynamical dark energy equations of state. The study evaluates how these automated frameworks can break existing cosmological tensions and optimize the scientific return of next-generation surveys.
Multimessenger Synergies: Probing Physics Beyond the Standard Model with Gravitational Waves and Neutrinos
This thesis investigates the synergy between gravitational waves and neutrinos to probe physics beyond the Standard Model. The research evaluates how new physical scenarios, such as sterile neutrinos or non-standard interactions, modify signals from high-energy cosmic events. By applying common statistical frameworks to future observations from the Einstein Telescope and next-generation neutrino detectors, the project quantifies the sensitivity of joint measurements in constraining new particle physics parameters in the multimessenger era.
Search for Non-Standard Black Hole Signatures in Gravitational Wave Transients
This project explores the detection of gravitational wave signals originating from non-standard black hole candidates, such as regular black holes or exotic mimickers. The research focuses on identifying specific signatures in the late-merger and ringdown phases, including potential echoes or deviations in quasinormal modes that differ from General Relativity predictions. By utilizing unmodeled transient search techniques and signal reconstruction methods, the project aims to evaluate the sensitivity of current and future detectors, such as the Einstein Telescope, to these objects. The work provides a framework for distinguishing standard Kerr black holes from theoretical alternatives, contributing to the search for new physics in the strong-field regime.
Cross-Correlation of Multi-Tracer Surveys: Probing the Large-Scale Structure of the Universe
This project investigates the synergistic use of different cosmic tracers, such as gravitational waves, fast radio bursts, and neutral hydrogen, to map the large-scale structure of the universe. The research focuses on cross-correlation techniques that combine discrete events and intensity maps to mitigate foreground noise and individual tracer biases. By applying these methods to future data from facilities like the Einstein Telescope and the SKA Observatory, the project aims to improve constraints on the growth of structure and the nature of dark matter and dark energy.
Population Studies of Binary Black Holes in Dense Stellar Environments
This project investigates the formation and evolution of binary black holes within dense environments, such as globular clusters.The research focuses on identifying specific observational signatures, including high eccentricities and mass-ratio distributions, that distinguish dynamical assembly from isolated binary evolution. By analyzing population models against current and future gravitational wave data, the project aims to quantify the contribution to the observed merger rate due to different assumptions on the astrophysical environment and the underlying cosmology. The work provides insights into the life cycles of massive stars and the complex gravitational interactions that drive the growth of black hole populations across cosmic time.
Hierarchical Bayesian Inference for Cosmology and Black Hole Populations
This project exploits gravitational wave sources as cosmic probes to perform simultaneous inference on the expansion history of the universe and the intrinsic properties of black hole populations. The research implements a hierarchical Bayesian framework to jointly model cosmological parameters and the astrophysical distributions of compact binaries, effectively breaking the degeneracies between source masses and cosmological redshift. By analyzing the synergies with large-scale structure and the evolution of features in the mass spectrum, the study evaluates the potential of gravitational wave events to provide independent measurements of the late-time expansion rate of the universe. The project aims to quantify the precision of these joint constraints for next-generation detectors like the Einstein Telescope, ensuring that astrophysical uncertainties do not bias fundamental cosmological results.