E-Dissertationen

Characterising the broadband polarisation properties of extragalactic radio sources at 3 GHz

2026-06-10T00:00:00Z

Characterising the broadband polarisation properties of extragalactic radio sources at 3 GHz Ranchod, Shilpa Magnetic fields are ubiquitous in the Universe and are fundamentally linked to galaxy evolution, influencing star-formation, cosmic-ray propagation and feedback mechanisms. The radio frequency regime, at centimetre wavelengths, is a powerful probe of cosmic magnetic fields through the detection of galaxies emitting linearly polarised synchrotron emission. The Faraday rotation measure (RM) of this emission can be used to study the properties of both the emitting source and the intervening magneto-ionic media (e.g. the Galactic interstellar medium). Large, dense samples of polarised extragalactic sources form RM grids that can be used to map the foreground magnetic field of the Milky Way. Over the past few years, the increasing sensitivity of modern interferometers has given new accessibility to the μJy radio sky, increasing the RM sky density. It is therefore key to establish a clear understanding of the faint polarised source population and the foreground effects that shape RM measurements. Broadband spectro-polarimetry provides an enhanced perspective on this, revealing Faraday complexities in the Stokes Q and U spectral behaviour, which trace turbulence or differential Faraday rotation along the line-of-sight. Through the projects presented in this thesis, I aim to address two important factors in improving our interpretation of RM grid experiments, (i) understanding both the observational biases and physical nature of Faraday complexity at low Galactic latitudes, (ii) characterising the extragalactic polarised source population.
Firstly, in analysing the SPASS/ATCA RM catalogue (Schnitzeler et. al., 2019), the most extensive broadband polarisation catalogue in the southern sky, we report a Galactic latitude dependence of Faraday complexity for polarised sources at |b| < 10°, with the degree of complexity increasing towards the Galactic plane. Through higher angular resolution (θ = 15′′) follow-up observations of 95 sources, we find that this trend is primarily driven by contamination from large-scale Galactic polarised emission in the SPASS/ATCA spectra, which we effectively filter out. We find 42% of the observed sources in our sample are Faraday complex, with an increased fraction of Faraday complex sources surrounding the spiral arm tangents and towards the Galactic centre. We constrain the scale of this complexity to < 2.4 pc, consistent with turbulent injection scales in the spiral arms. These results emphasise the importance of broadband spectro-polarimetric observations to fully characterise small-scale and/or turbulent structures in the Galactic magnetic field, and that it is essential to correctly filter contaminating polarised emission when interpreting foreground turbulence.
Secondly, we reprocess the VLA-COSMOS 3 GHz Large Project (Smolčić et. al., 2017), one of the deepest S-band continuum surveys (2.3 μJy beam⁻¹), for polarisation calibration and imaging. Here, we present the deepest polarised source count at 3 GHz to date, and the second deepest overall, returning an RM density of 42 deg⁻². We find that these source counts are consistent with those at the more typically-studied 1.4 GHz band, a combined effect of spectral index and depolarisation, which we attribute to differential Faraday rotation in the lobes of radio galaxies. Through the available multi-wavelength catalogues, we identify all polarised sources as radio galaxies (i.e. active galactic nuclei), and confirm that no star-forming galaxies are detected in polarisation. We place an upper limit on the density of polarised star-forming galaxies to be < 0.58 deg⁻², implying that surveys much deeper than 2.6 μJy beam⁻¹ will be required to readily probe this population, even at higher frequencies where Faraday depolarisation effects are less pronounced.
Finally, I present a demonstrator project with the recently installed MeerKAT S-band receivers, with a focus on extragalactic wide-field imaging. We present MeerKAT S-band observations of the DEEP2 field, the emptiest radio field in the southern sky. The total intensity source counts are consistent with those from the literature, and also show that only a fraction of integration time is required with MeerKAT for comparable results with legacy S-band surveys. Here, I also present the science goals and survey design for the MeerKAT+ S-band Legacy survey, a 3000 hour, full-Stokes survey of the southern sky at Dec ≤ −40°. This survey will be extremely versatile across Galactic, galaxy evolution, magnetism and transient science, and with an expected 10⁵ polarised source detections, will provide a higher frequency perspective on the RM grid of the southern sky.

Development of an automated RNA capture-SELEX for enriching modular RNA light-up sensors

2026-06-09T00:00:00Z

Development of an automated RNA capture-SELEX for enriching modular RNA light-up sensors Legen, Tjasa This thesis examines recent advances in selecting and functionalizing RNA aptamers for molecular sensing applications. Two related studies have been carried out: developing a robotic platform for automated RNA aptamer selection targeting small molecules and creating a modular approach to design fluorogenic RNA sensors. Together, these studies offer a framework that combines standardized aptamer discovery with adaptable sensor design.
The systematic evolution of ligands by exponential enrichment (SELEX) was adapted to a robotic platform, minimizing manual intervention and enhancing reproducibility. Traditional SELEX often involves immobilizing small-molecule targets, which can alter ligand properties. To address this, capture-SELEX was used, in which RNA libraries are immobilized via hybridization to captureoligodeoxynucleotides (ODNs), and unmodified ligands in solution facilitate the recovery of bound sequences. By optimizing the robotic system, a preferential immobilization strategy for the library was systematically investigated, resulting in more substantial enrichment of binding sequences. The platform completes up to twelve selection cycles in 72 hours and has successfully enriched aptamers for several small molecules, including neomycin B, theophylline, and riboflavin. Interaction analysis using fluorescence polarization and isothermal titration calorimetry confirmed specific binding properties of enriched aptamers, with affinities in the micromolar range. Although the current capture-SELEX protocol used on the robotic system has limitations in the affinity of the enriched aptamers compared to immobilization-based selections, it offers a standardized, high-throughput method for the rapid assessment of the utility of aptamers for small molecules.
In the second part of this work, the capture-SELEX strategy was extended to enable the selection of modular allosteric RNA sensors. RNA libraries were designed to couple ligand-binding aptamers to fluorogenic RNA scaffolds, enabling molecular recognition to be directly translated into fluorescence output. Using this library in capture-SELEX, aptamers that bind thiamine pyrophosphate (TPP) were identified. These aptamers were then fused to Broccoli and its red-shifted variant, Red Broccoli, to develop ligand-responsive sensors. By optimizing the linker and spacer regions, the signal-to-background ratio was improved. The selected sensors demonstrated specificity for TPP and thiamine monophosphate, with minimal response to thiamine or unrelated nucleotides. The modular design facilitated the easy swapping of fluorogenic domains and the adjustment of sensor properties, demonstrating its effectiveness for rapid and efficient development of RNA-based sensors.
Overall, this thesis establishes a scalable framework for RNA aptamer discovery and deployment. By integrating automated selection with modular sensor engineering, the presented approach provides a generalizable strategy for developing RNA-based sensing systems applicable to biosensing, synthetic biology, and molecular diagnostics.

Intuitive Explainable Artificial Intelligence for Molecular Design

2026-06-09T00:00:00Z

Intuitive Explainable Artificial Intelligence for Molecular Design Lamens, Alec With the onset of artificial intelligence (AI), machine learning (ML) approaches have become increasingly embedded into the drug discovery pipeline with the aim of accelerating research and reducing cost. Exemplary applications include quantitative structure-property relationship modeling and de novo design of candidate molecules. However, the practical impact of these ML models has been limited by the opaque nature of their predictions, termed the black-box problem. The proliferation of large-scale public chemical datasets combined with advances in high-performance computing has driven a shift from traditional ML approaches toward more complex deep learning (DL) methods. While powerful, these models further exacerbate the inability to rationalize model outcomes. Therefore, the field of explainable AI (XAI) has attracted substantial interest to improve the transparency of model decisions. Given the wide range of available XAI approaches and lack of established practices, these methods are often applied without careful consideration for their suitability to the task at hand. This represents a problem in drug discovery where interpretable explanations are critical to guide experimental follow-up. To address this issue, this dissertation proposes the adaptation of established XAI approaches to operate on the level of chemical structure and facilitate interpretable ML for molecular design. The first study demonstrates the use of Shapley additive explanations (SHAP) to analyze feature sets driving the correct prediction of compound promiscuity. This is followed by a benchmarking study comparing several methods for the calculation of feature importance values, revealing inconsistencies across approaches that complicate the interpretation of feature-importance explanations. To support chemically meaningful interpretability, SHAP values are then combined with counterfactual reasoning, yielding the SHAP-CF methodology. Thereafter, a novel counterfactual method is introduced that generates candidate counterfactuals through the iterative recombination of molecular cores and substituents. This method is evaluated on a challenging multi-class kinase inhibitor prediction task, demonstrating its capacity to generate large numbers of counterfactuals, enabling in-depth analysis. Next, a closely related XAI concept, contrastive explanations, is adapted for molecular design by introducing rational chemical modifications to test compounds through the exchange of scaffolds or substituents with structural analogues, termed MolCE. This approach is shown to provide chemically relevant contrastive explanations that enable direct causal insights into the structural factors that drive model predictions. Finally, MolAnchor is introduced, a domain-adapted variant of the rule-based Anchors method. By conforming the principles underlying the Anchors framework to operate on retrosynthetically meaningful molecular fragments, MolAnchor produces interpretable fragment-level decision rules. A follow-up study showcases how the if-then formulation of the fragment rules is particularly complementary to causal reasoning. Taken together, the studies presented hereindemonstrate the utility of XAI methods that have been augmented with domain-specific information to provide chemically intuitive explanations for predictive models applied to molecular design.

A geometric compactification of the moduli space of grafted surfaces

2026-06-05T00:00:00Z

A geometric compactification of the moduli space of grafted surfaces Monti, Andrea Egidio In this thesis, we study the degenerations of complex projective structures on an orientable surface S of genus at least two, aiming to describe a compactification of their moduli space and provide a geometric interpretation of the boundary points. The moduli space PT(S) of complex projective structures admits a parametrisation due to Thurston via grafting: each structure corresponds to a metric on S that is obtained from a hyperbolic one by grafting, namely inserting, flat parts along a measured lamination. This construction yields a homeomorphism PT(S) ≅ T(S) × ML(S), where T(S) is Teichmüller space and ML(S) the space of measured laminations. We refer to the metric surfaces resulting from grafting as grafted surfaces.
We prove that degenerating sequences of grafted surfaces, suitably rescaled, can converge geometrically to half-translation surfaces, that is, Euclidean surfaces with cone singularities. We use the orthogeodesic foliation introduced by Calderon and Farre to analyse this phenomenon, and we construct a bordification of PT(S) whose boundary at infinity is given by the moduli space ℙ_ℂQT(S) of half-translation surfaces up to rotation and rescale. The topology on this bordification is the one induced by a marked version of Gromov-Hausdorff convergence introduced in this work.
We also show that PT(S) embeds into the space of projective geodesic currents and this embedding extends continuously to our bordification too. We describe the whole closure of its image, when embedding PT(S) into projective currents using a novel l¹-variant of the grafted metric. The boundary in this case is described by mixed structures, which have appeared in different forms in the bordification of other moduli spaces of geometric structures on surfaces. As an application, we describe the limits of so-called generalised stretch rays in Teichmüller space.