@phdthesis{19456, abstract = {Making decisions requires flexibly adapting to changing environments, a process that depends on accurately interpreting current contingencies and integrating them with past experience. Two brain regions are particularly critical for this process, the medial prefrontal cortex (mPFC) and the hippocampus. Using contextual information from the hippocampus, the mPFC selects relevant cognitive frameworks and suppresses irrelevant ones to guide appropriate actions. Several studies have shown that some mPFC pyramidal neurons become spatially tuned when spatial information is required to guide goal-directed behavior. However, the role of prefrontal spatial representations in learning and decision making is not well understood. This work aims to characterize the role of mPFC spatial tuning in supporting a contextual association task. Rats were trained to learn two cue–location associations on a radial arm maze over multiple days, while we simultaneously recorded from dorsal CA1 of the hippocampus and the prelimbic area of the mPFC. We describe a subset of spatially tuned hippocampal and prefrontal pyramidal neurons that “flicker” between multiple spatial representations on different trials, suggesting dynamic, context-dependent coding. This flickering may provide a substrate for how the network reorganizes in response to task demands, likely by enabling the flexible evaluation of competing representations. }, author = {Cumpelik, Andrea D}, isbn = {978-3-99078-056-5}, issn = {2663-337X}, keywords = {neuroscience, decision making, learning, cognitive flexibility, medial prefrontal cortex, hippocampus, electrophysiology}, pages = {96}, publisher = {Institute of Science and Technology Austria}, title = {{The role of prefrontal spatial coding in supporting a contextual association task}}, doi = {10.15479/AT-ISTA-19456}, year = {2025}, } @phdthesis{19763, abstract = {Pattern formation in developing organs is controlled by morphogens. These signalling molecules form concentration gradients across tissues, thereby providing positional information that instructs the pattern of cell differentiation. Morphogen gradients are highly dynamic in space and time. Many factors such as morphogen production, spreading, degradation, cellular rearrangements and others could contribute to changes in the gradient shape, yet how the spatiotemporal signalling dynamics arise in many systems is still unclear. We studied the dynamics of morphogen signalling and tissue patterning in the developing vertebrate neural tube. In this system, neural crest, roof plate and distinct dorsal progenitor subtypes are specified in a spatially and temporally ordered manner in response to dorsal-toventral gradients of BMP and WNT signalling activity. How the BMP and WNT gradients are established and interpreted to ensure ordered cell specification is poorly understood. To address this question, we developed a 2D embryonic stem cell differentiation system that captures key features of dorsal neural tube development. In this system, differentiated colonies display remarkable self-organised pattern formation in response to uniformly applied BMP ligand. We established a method of differentiating the colonies using microfabricated stencils, which allowed us to control the initial size and shape of colonies without confining cell migration and colony growth. This led to highly reproducible pattern formation that facilitates quantification. Using this approach, we observed striking two-phase temporal dynamics of BMP signalling in our colonies: a BMP gradient rapidly forms from the periphery to the centre of colonies, subsequently disappears and is re-established again in the second phase. By combining our quantitative data with a data-driven theoretical model, we uncovered a temporal relay mechanism that underlies this biphasic BMP signalling dynamics. The first signalling phase is controlled by fast tissue-autonomous negative feedback that restricts the duration of the initial response to BMP. The early BMP activity gradient moreover controls the spatial organisation of the cell type pattern: the absence of a first phase results in disordered cell type pattern. The second phase is controlled by slow positive regulation of BMP signalling by the transcription factor LMX1A, a key regulator of roof plate identity. WNT promotes the second phase of BMP signalling via positive feedback on LMX1A. Altogether, the mechanism that we uncovered ensures the coupling of sequential developmental events, making pattern formation spatially and temporally organised. Furthermore, this mechanism allows the BMP signalling pathway to be reused in different contexts – first for the establishment of the neural plate border, and subsequently for dorsal neural progenitor patterning. Our study supports a general developmental principle in which multiple morphogens interact with transcriptional networks resulting in complex spatiotemporal signalling dynamics that ultimately drive organised pattern formation.}, author = {Rus, Stefanie}, issn = {2663-337X}, pages = {129}, publisher = {Institute of Science and Technology Austria}, title = {{Dynamics of morphogen signalling and cell fate decisions in the dorsal neural tube}}, doi = {10.15479/AT-ISTA-19763}, year = {2025}, } @phdthesis{19722, abstract = {As root epidermal cells progress from a phase of elongation to differentiation, their cortical microtubule (MT) arrays exhibit a transversal-to-longitudinal reorientation. The hormone cytokinin, a key regulator of root development, facilitates these cytoskeletal changes. However, the molecular mechanisms underlying hormone-mediated MT reorientation during root development are still unknown. Here, we find that MT reorientation in root cells differs from the existing model in hypocotyl cells, as it does not rely on MT plusend rescue. We show that cytokinin facilitates MT array reorganization during cell differentiation by promoting katanin’s (KTN1) severing activity, and by modulating KTN1’s association with microtubules. Cytokinin regulates SPIRAL2 (SPR2) in a phosphorylationdependent manner, directing its localization to, and stabilization of, the new MT minus-end created by katanin-mediated severing at crossovers. Notably, our findings suggest that dynamic and reversible phosphorylation at S579 of SPR2 is crucial for the proper functioning of the MT severing machinery. Finally, we identify MAP65-1 and CLASP as additional targets of cytokinin-dependent phosphoregulation. Cytokinin treatment decreases MT-MAP65-1 association in elongating cells, likely to expose MTs to KTN1-mediated severing, whereas it increases MT-CLASP association to stabilize the growing plus-end. In this way, cytokinin drives MT reorganization during cell development by simultaneously modulating several microtubule-associated proteins. These results reveal key molecular players in hormonemediated cytoskeletal regulation, and highlight protein phosphorylation as a powerful tool during this process.}, author = {Inumella, Syamala}, isbn = {978-3-99078-059-6}, issn = {2663-337X}, pages = {113}, publisher = {Institute of Science and Technology Austria}, title = {{Molecular mechanisms of microtubule reorganization in elongating root epidermal cells}}, doi = {10.15479/AT-ISTA-19722}, year = {2025}, } @phdthesis{20449, abstract = {Males and females of many species differ in morphology, physiology, and behavior. In taxa with genetic sex determination, sexual differentiation arises largely from sex-biased gene expression, which varies across tissues, developmental stages, and lineages. Increasing evidence highlights chromatin configuration, which can exist in open or closed states, and can be shaped by sex-determination path ways, as a key regulatory layer of this dimorphism. Degeneration of the Y or W chromosome further contributes to sex -specific differences by altering gene copy numbers relative to autosomes in heterogametic sex. To mitigate these imbalances, many eukaryotes have independently evolved dosage compensation mechanisms, often mediated through chromatin -level regulation. In this thesis, we investigate the evolutionary dynamics of sex chromosome differentiation in two species, Artemia franciscana and Cameraria ohridella , with a particular focus on the extent of dosage compensation following gene loss in the heterogametic sex and the potential chromatin-based mechanisms underlying this process. We further characterize sex -biased gene expression and its regulation through histone modifications. Our analyses also reveal that the A. franciscana genome is highly repetitive, with many genes containing intronic transposable elements. We find that enrichment of histonemo difications associated with constitutive heterochromatin, positively correlates with variation in gene expression levels. Collectively, these findings underscore role of chromatin regulation in shaping the evolution of sex chromosomes and sexual differentiation. }, author = {Bett, Vincent K}, issn = {2663-337X}, pages = {114}, publisher = {Institute of Science and Technology Austria}, title = {{Evolution and regulation of the Z chromosome}}, doi = {10.15479/AT-ISTA-20449}, year = {2025}, } @phdthesis{20694, abstract = {Understanding the mechanisms underlying speciation is a central aim of evolutionary biology. A persistent challenge in the field is to identify loci that contribute to reproductive isolation, while disentangling signals of selection from demography, linkage and intrinsic genomic features. Traditional population genomic approaches that rely on site-based statistics in arbitrary fixed windows face inherent limitations, as they conflate historical and contemporary processes of divergence and overlook haplotype structure. Recent advances in whole-genome sequencing and methods to infer ancestral recombination graphs (ARGs) now offer the opportunity to study genealogical relationships explicitly, revealing how lineages coalesce and recombine through time. By directly analysing haplotype clustering by species or phenotype and their patterns of coalescence, ARG-based methods show promise for diagnosing sweeps, identifying barrier loci maintained under divergent selection amid gene flow, and tracing their evolutionary history. In this thesis, I explore the utility of genealogical approaches for studying species divergence. In chapter 2, I propose a conceptual framework for defining haplotype blocks through the structure of the ARG, using simulations and empirical data to highlight how genealogical processes generate rich and often overlooked haplotypic patterns. In chapter 3, I examine the genomic basis of a key evolutionary innovation in marine snails Littorina. These snails offer a unique opportunity to study an innovation because they include a very recent transition from egg-laying to live bearing, yet snails with the different reproductive modes are not reciprocally monophyletic. I exploited this by using topology clustering in ARG-derived local genealogical trees to pinpoint narrow genomic regions or haplotype blocks that carry swept alleles, thus revealing that the transition from egg-laying to live-bearing involves multiple, live-bearer-specific sweeps. Chapter 4 establishes a population-scale, phased genomic resource for Antirrhinum majus, using cost-effective haplotagging, then optimizes imputation from low-coverage data against high-accuracy KASP sequencing to maximize sequence completeness with modest accuracy trade-offs against a traditional short-read sequence pipeline. A hybrid phasing strategy combines molecular phasing with statistical phasing to generate phased whole genome sequences of 1084 Antirrhinum individuals at a fraction of long-read sequencing costs. In chapter 5, I analyse hybridising populations from two replicate hybrid zones to find a parallel genetic basis of flower colour, amidst the noise in genomic differentiation landscape driven by variation in demographic history. While outlier genome scans of FST failed to dissect the causes of differentiation, ARG-based topology clustering revealed a reuse of colour associated haplotypes across hybrid zones. In addition to the biological insight, this chapter also presents a comparison of the latest ARG inference tools, showing that signals of Abstract viii topological clustering qualitatively agree between methods, despite differences in the tree sequences. Next, in chapter 6, by leveraging ~1000 individuals in one of the hybrid zones, I integrated genome-wide association studies of floral pigmentation with genealogical inference, to test for additional colour loci, and confirm the effect of previously described loci. This work demonstrates that flower colour variation is driven by a small number of large effect loci, while also hinting at the presence of a new candidate regulatory factor. Finally in chapter 7, in a preliminary analysis, I begin to dissect the genomic island of speciation around Rosea/Eluta to understand its evolutionary origins. My results show that it consists of 5 highly divergent loci, each of which is associated with flower colour. Using patterns of coalescence in genealogical trees, I find evidence of staggered selective sweeps and a persistent localized barrier to gene flow within an otherwise permeable genome. Together, these chapters add to the increasing pool of studies using genealogical approaches to complement and extend site-based statistics to use haplotype structures in speciation research. By tracking haplotypes directly and connecting genealogical clustering to population processes, ARG-based inference promises to provide new insights into how local selective pressures, demographic history, and long-term barriers interact to shape the genomic architecture of divergence. By underscoring the value of ARGs in revealing the finescale origins and maintenance of biodiversity, this thesis presents cautious optimism about the benefits of using genealogical inference to learn more than what site-based statistics could tell us.}, author = {Pal, Arka}, issn = {2663-337X}, pages = {268}, publisher = {Institute of Science and Technology Austria}, title = {{Using genealogies to study the genomic basis of species divergence}}, doi = {10.15479/AT-ISTA-20694}, year = {2025}, } @phdthesis{19993, abstract = {Ants are frequently challenged by different pathogens, which they counter with individual and collective responses. Usually, the pathogens like fungi or viruses are solitary and passive pathogens transmitted from host to host. Here, we use a nematobacterial pathogen complex to study worm-borne disease in black garden ants. These entomopathogenic nematodes are active parasites with an own behavior and chasing pray. In the first chapter, we investigated the basic biology of the host-pathogen relationship. We tested different ant life stages and found that adult ants display defense behaviors and are generally resistant to nematode infection, whereas brood is highly susceptible. In the case of worker pupae, we found a slight protective effect of the cocoon. When larvae are accompanied by adults, meaning a queen or a group of workers, survival is significantly enhanced. Moreover, we found that nematodes can transmit from infected cadavers to healthy worker larvae, confirming a transmissible disease in ants. Again, worker presence significantly reduces transmission risk. In the end, we were also able to disentangle the pathogen system and investigate the pathogenic effect of the bacterial and nematode components. In the second chapter, we studied the effect of multiple infections in adult queens and queen larvae. By multiple exposures in the mode of coinfection and superinfections, we wanted to assess the detrimental effect of combined fungal and nematode exposure to better understand how the pathogens interact with each other in an ant host. We found instances where combined exposure lead to higher mortality in a given time frame in both, adult queens and queen larvae. Overall entomopathogenic nematodes are a promising model to study worm infections in ants which extend our knowledge on collective disease defense.}, author = {Strahodinsky, Florian}, issn = {2663-337X}, pages = {138}, publisher = {Institute of Science and Technology Austria}, title = {{Social immunity in a tri-partite host-pathogen relationship}}, doi = {10.15479/AT-ISTA-19993}, year = {2025}, } @phdthesis{20470, abstract = {Systems design has classically relied on composable systems, in which individual subsystems have defined inputs, outputs, and interactions with each other; however, attempts at designing complex systems in synthetic biology has often run in to issues of crosstalk and interference, given that these systems must function within the context of the host. In nature, mobile genetic elements are systems that have evolved to travel between hosts, and thus appear to be a good candidate with which to evaluate composability. Selecting temperate phages as a model system, I used mathematical modelling to identify sources of information that temperate phages should respond to. I found that essential proteins of temperate phages can interfere with potential hosts, indicating limitations to composability. I also designed a lysogeny reporter construct and characterize its behavior across various laboratory and environmental strains, finding differences in phage lambda lysogens, and potential interference from prophages that already exist within the environmental strains. Although the information gathered is not conclusive, it suggests that composability is not a key property of temperate phages, implying that biological systems may not be composable, and that other system design principles should be considered when designing synthetic systems.}, author = {Wu, Bryan}, issn = {2663-337X}, pages = {102}, publisher = {Institute of Science and Technology Austria}, title = {{An examination on phages as a naturally composable system}}, doi = {10.15479/AT-ISTA-20470}, year = {2025}, } @phdthesis{20777, abstract = {A major challenge in neuroscience is deciphering how the brain orchestrates behavior in response to changes in environmental conditions. This process is characterized by several processing stages, from perception to the storage of important information. Information storage is performed by a memory system implemented through complex networks of highly interconnected neurons. The collective operational principles of neuronal networks that support formation and storage are the main topics of this thesis. To investigate the collective dynamics of the hippocampus from the perspective of the brain criticality hypothesis, I started by analyzing cascades of neural activity ¯ neuronal avalanches ¯ that have been characterized by the absence of a typical spatial or temporal scale. Measures derived from neuronal avalanches suggested that during wakefulness the hippocampus operated further away from criticality than during sleep/rest. In addition, neural activity propagated differently in these two brain states, as indicated by different collapses of the avalanche shapes. Next, the Phenomenological Renormalization Group approach also indicated conceptually similar differences, through the scaling exponent of activity variance α, which was higher during sleep/rest than during awake. These results confirmed that the activity of the hippocampus exhibits signatures of criticality and that these signatures change with the state of the brain. Next, I found that memory retention was predicted by the scaling exponent of activity variance α. The exponent α measured during the sleep/rest session that followed learning correlated with memory retention during the subsequent unrewarded testing session. Moreover, α predicted performance even when controlled for reactivation that occurs in parallel. Second, α measured in the sleep/rest phase that preceded learning was correlated with the learning speed. I analyzed distributions of the cells’ characteristic timescale and burstiness. The day-to-day variability of these distributions, during sleep/rest that followed learning, correlated with the scaling exponent of activity variance α, as well as with memory retention. These findings confirmed that variance scaling and functional heterogeneity provide behaviorally meaningful perspectives on hippocampal activity, as they are directly related to memory consolidation. I further investigated the process of memory acquisition and consolidation between the hippocampus CA1 and the mEC. During learning, CA1 cells shifted their firing field towards the goals, while mEC cells remained mostly stable, shifting their firing fields towards the goals during sleep/rest that followed learning. This shift during sleep/rest was supported by the reactivation process, which occurred in two ways, synchronously with CA1 (during SWRs) and independently of the hippocampal SWRs. Both types of reactivation predicted subsequent memory retention, as well as the amount of goal-related remapping. Again, the day-to-day variability of the distribution of the cell timescales correlated with the goal-related remapping, in CA1 during the learning session and in mEC during sleep/rest. These results suggest that in spatial navigation tasks, the functional responsibilities of CA1 and mEC change between learning and sleep/rest and that their function benefits from increased functional heterogeneity among cells. }, author = {Zivadinovic, Predrag}, issn = {2663-337X}, pages = {104}, publisher = {Institute of Science and Technology Austria}, title = {{Scale-free activity as a basis for spatial learning and memory in the brain}}, doi = {10.15479/AT-ISTA-20777}, year = {2025}, } @phdthesis{19836, abstract = {Over the past century, researchers have been fascinated by the quantum nature of the physical world, initially striving to understand its fundamental principles and consequences, and eventually progressing toward engineering systems that can control and manipulate quantum properties. Today, we stand at the dawn of the quantum technology era. While some quantum technologies follow well-defined roadmaps, others are still in the exciting and uncertain early stages of development. In the fields of quantum computing and quantum simulation, research is being conducted across a wide variety of platforms. Each of these demonstrates control over quantum properties but also faces challenges in scaling up to the level of a mature technology. This thesis explores some of the fundamental properties of hole spin qubits in planar germanium. Semiconductor spin qubits are considered strong candidates for the realization of quantum processors, owing to their long relaxation and coherence times, as well as their compatibility with existing semiconductor industry infrastructure. Among these, hole spin qubits in planar germanium are particularly promising. Their advantages include a large effective mass, which eases fabrication constraints; inherent protection from hyperfine noise; and strong spin-orbit interaction, which enables fast and purely electrical control. However, spin-orbit coupling also introduces site-dependent variability across qubits, particularly in the g-tensors and spin-flip tunneling, which might cause that the quantization axes are not aligned. In this thesis, we investigate the tilt between the quantization axes of two hole spins hosted in a double quantum dot as a function of both the magnetic field direction and various electrostatic configurations, demonstrating that both parameters influence this tilt. We conclude by introducing a machine-learning-assisted routine to automatically tune baseband spin qubits. This approach may prove to be a powerful tool for characterizing spin-orbit effects and gaining deeper insight into the physics governing spin qubit behavior. }, author = {Saez Mollejo, Jaime}, issn = {2663-337X}, pages = {175}, publisher = {Institute of Science and Technology Austria}, title = {{Singlet-triplet qubits in planar Germanium: From exchange anisotropies to autonomous tuning }}, doi = {10.15479/AT-ISTA-19836}, year = {2025}, } @phdthesis{20563, abstract = {The theory of optimal transport provides an elegant and powerful description of many evolution equations as gradient flows. The primary objective of this thesis is to adapt and extend the theory to deal with important equations that are not covered by the classical framework, specifically boundary value problems and kinetic equations. Additionally, we establish new results in periodic homogenization for discrete dynamical optimal transport and in quantization of measures. Section 1.1 serves as an invitation to the classical theory of optimal transport, including the main definitions and a selection of well-established theorems. Sections 1.2-1.5 introduce the main results of this thesis, outline the motivations, and review the current state of the art. In Chapter 2, we consider the Fokker–Planck equation on a bounded set with positive Dirichlet boundary conditions. We construct a time-discrete scheme involving a modification of the Wasserstein distance and, under weak assumptions, prove its convergence to a solution of this boundary value problem. In dimension 1, we show that this solution is a gradient flow in a suitable space of measures. Chapter 3 presents joint work with Giovanni Brigati and Jan Maas. We introduce a new theory of optimal transport to describe and study particle systems at the mesoscopic scale. We prove adapted versions of some fundamental theorems, including the Benamou–Brenier formula and the identification of absolutely continuous curves of measures. Chapter 4 presents joint work with Lorenzo Portinale. We prove convergence of dynamical transportation functionals on periodic graphs in the large-scale limit when the cost functional is asymptotically linear. Additionally, we show that discrete 1-Wasserstein distances converge to 1-Wasserstein distances constructed from crystalline norms on R d . Chapter 5 concerns optimal empirical quantization: the problem of approximating a measure by the sum of n equally weighted Dirac deltas, so as to minimize the error in the p-Wasserstein distance. Our main result is an analog of Zador’s theorem, providing asymptotic bounds for the minimal error as n tends to infinity. }, author = {Quattrocchi, Filippo}, issn = {2663-337X}, keywords = {optimal transport, kinetic equations, boundary value problems, quantization, gradient flows, homogenization}, pages = {240}, publisher = {Institute of Science and Technology Austria}, title = {{Optimal transport methods for kinetic equations, boundary value problems, and discretization of measures}}, doi = {10.15479/AT-ISTA-20563}, year = {2025}, } @phdthesis{19906, abstract = {Flows of ordinary fluids such as water or air transition from laminar to turbulent motion as the velocity increases. This simple dependence of the flow state solely on inertia, does not apply to more complex substances such as polymericand biofluids which commonly have elastic as well as viscous properties. Here various different instabilities and turbulent states can arise at low and even vanishing inertia, while high inertia turbulence counterintuitively is suppressed and its drag strongly reduced. We here show in experiments of a viscoelastic model fluid that the phenomena observed at low and high inertia have a common origin and that the same dynamical state, elasto-inertial turbulence, persists across four orders of magnitude in Reynolds number, ranging from very low inertia, all the way to high inertia Maximum drag reduction (MDR) asymptote. We also explore the transitions from Newtonian turbulence to MDR, and specific cases of flow at high polymer concentrations, exploring the relationship between flow at these wide range of control parameters. }, author = {Suresh, Sarath S}, issn = {2663-337X}, pages = {82}, publisher = {Institute of Science and Technology Austria}, title = {{Turbulence in polymeric flows: A characterisation of elasto-inertial turbulence and the maximum drag reduction asymptote}}, doi = {10.15479/AT-ISTA-19906}, year = {2025}, } @phdthesis{19533, abstract = {This thesis explores advancements in quantum remote sensing and non-equilibrium phase transitions in the microwave regime, with a focus on dissipative phase transitions and quantumenhanced sensing. In the first project, I experimentally studied photon blockade breakdown as a dissipative phase transition in a zero-dimensional cavity-qubit system. By defining an appropriate thermodynamic limit, we demonstrated that the observed bistability is a genuine signature of a first-order phase transition in this system. This work provides insight into non-equilibrium quantum dynamics and phase transitions in driven-dissipative open quantum systems. The second project focuses on the experimental realization of a phase-conjugate receiver for quantum illumination (QI), a quantum sensing protocol that enhances target detection in noisy environments using entangled light. While an ideal spontaneous parametric down-conversion (SPDC) source and receiver could, in theory, provide up to a 6 dB advantage over classical illumination, no such ideal receiver exists. Instead, we explore an experimental realization of a phase-conjugate receiver for QI in the microwave regime at millikelvin temperatures using a Josephson parametric converter (JPC) as a source of continuous-variable Gaussian entangled signal-idler pairs, where a maximum 3 dB advantage is theoretically achievable. We investigate key experimental limitations that constrain practical QI performance, contributing to the development of quantum-enhanced sensing. Additionally, this thesis presents efficient digital signal processing (DSP) techniques implemented in C++ and Python in collaboration with Przemysław Zieliński and Luka Drmić. These methods, optimized using the Intel Integrated Performance Primitives (IPP) library, have been essential in data acquisition, noise filtering, and correlation analysis across multiple research projects. Although not real-time, these DSP techniques significantly enhance the accuracy of quantum measurements. Overall, this thesis advances quantum-enhanced sensing by establishing the thermodynamic limit in a single transmon-cavity system and experimentally exploring a phase-conjugate receiver for QI. These findings contribute to quantum metrology, particularly for weak signal detection and remote sensing in noisy environments. }, author = {Sett, Riya}, issn = {2663-337X}, keywords = {phase transition, open quantum system, phase diagram, cavity quantum electrodynamics, superconducting qubits, semiclassical physics, quantum optics, josephson junction, parametric converter, phase conjugation, quantum radar, quantum entanglement, correlation, quantum sensing}, pages = {109}, publisher = {Institute of Science and Technology Austria}, title = {{Quantum remote sensing and non-equilibrium phase transitions in the microwave regime}}, doi = {10.15479/AT-ISTA-19533}, year = {2025}, } @phdthesis{14711, abstract = {In nature, different species find their niche in a range of environments, each with its unique characteristics. While some thrive in uniform (homogeneous) landscapes where environmental conditions stay relatively consistent across space, others traverse the complexities of spatially heterogeneous terrains. Comprehending how species are distributed and how they interact within these landscapes holds the key to gaining insights into their evolutionary dynamics while also informing conservation and management strategies. For species inhabiting heterogeneous landscapes, when the rate of dispersal is low compared to spatial fluctuations in selection pressure, localized adaptations may emerge. Such adaptation in response to varying selection strengths plays an important role in the persistence of populations in our rapidly changing world. Hence, species in nature are continuously in a struggle to adapt to local environmental conditions, to ensure their continued survival. Natural populations can often adapt in time scales short enough for evolutionary changes to influence ecological dynamics and vice versa, thereby creating a feedback between evolution and demography. The analysis of this feedback and the relative contributions of gene flow, demography, drift, and natural selection to genetic variation and differentiation has remained a recurring theme in evolutionary biology. Nevertheless, the effective role of these forces in maintaining variation and shaping patterns of diversity is not fully understood. Even in homogeneous environments devoid of local adaptations, such understanding remains elusive. Understanding this feedback is crucial, for example in determining the conditions under which extinction risk can be mitigated in peripheral populations subject to deleterious mutation accumulation at the edges of species’ ranges as well as in highly fragmented populations. In this thesis we explore both uniform and spatially heterogeneous metapopulations, investigating and providing theoretical insights into the dynamics of local adaptation in the latter and examining the dynamics of load and extinction as well as the impact of joint ecological and evolutionary (eco-evolutionary) dynamics in the former. The thesis is divided into 5 chapters. Chapter 1 provides a general introduction into the subject matter, clarifying concepts and ideas used throughout the thesis. In chapter 2, we explore how fast a species distributed across a heterogeneous landscape adapts to changing conditions marked by alterations in carrying capacity, selection pressure, and migration rate. In chapter 3, we investigate how migration selection and drift influences adaptation and the maintenance of variation in a metapopulation with three habitats, an extension of previous models of adaptation in two habitats. We further develop analytical approximations for the critical threshold required for polymorphism to persist. The focus of chapter 4 of the thesis is on understanding the interplay between ecology and evolution as coupled processes. We investigate how eco-evolutionary feedback between migration, selection, drift, and demography influences eco-evolutionary outcomes in marginal populations subject to deleterious mutation accumulation. Using simulations as well as theoretical approximations of the coupled dynamics of population size and allele frequency, we analyze how gene flow from a large mainland source influences genetic load and population size on an island (i.e., in a marginal population) under genetically realistic assumptions. Analyses of this sort are important because small isolated populations, are repeatedly affected by complex interactions between ecological and evolutionary processes, which can lead to their death. Understanding these interactions can therefore provide an insight into the conditions under which extinction risk can be mitigated in peripheral populations thus, contributing to conservation and restoration efforts. Chapter 5 extends the analysis in chapter 4 to consider the dynamics of load (due to deleterious mutation accumulation) and extinction risk in a metapopulation. We explore the role of gene flow, selection, and dominance on load and extinction risk and further pinpoint critical thresholds required for metapopulation persistence. Overall this research contributes to our understanding of ecological and evolutionary mechanisms that shape species’ persistence in fragmented landscapes, a crucial foundation for successful conservation efforts and biodiversity management.}, author = {Olusanya, Oluwafunmilola O}, issn = {2663-337X}, pages = {183}, publisher = {Institute of Science and Technology Austria}, title = {{Local adaptation, genetic load and extinction in metapopulations}}, doi = {10.15479/at:ista:14711}, year = {2024}, } @phdthesis{15020, abstract = {This thesis consists of four distinct pieces of work within theoretical biology, with two themes in common: the concept of optimization in biological systems, and the use of information-theoretic tools to quantify biological stochasticity and statistical uncertainty. Chapter 2 develops a statistical framework for studying biological systems which we believe to be optimized for a particular utility function, such as retinal neurons conveying information about visual stimuli. We formalize such beliefs as maximum-entropy Bayesian priors, constrained by the expected utility. We explore how such priors aid inference of system parameters with limited data and enable optimality hypothesis testing: is the utility higher than by chance? Chapter 3 examines the ultimate biological optimization process: evolution by natural selection. As some individuals survive and reproduce more successfully than others, populations evolve towards fitter genotypes and phenotypes. We formalize this as accumulation of genetic information, and use population genetics theory to study how much such information can be accumulated per generation and maintained in the face of random mutation and genetic drift. We identify the population size and fitness variance as the key quantities that control information accumulation and maintenance. Chapter 4 reuses the concept of genetic information from Chapter 3, but from a different perspective: we ask how much genetic information organisms actually need, in particular in the context of gene regulation. For example, how much information is needed to bind transcription factors at correct locations within the genome? Population genetics provides us with a refined answer: with an increasing population size, populations achieve higher fitness by maintaining more genetic information. Moreover, regulatory parameters experience selection pressure to optimize the fitness-information trade-off, i.e. minimize the information needed for a given fitness. This provides an evolutionary derivation of the optimization priors introduced in Chapter 2. Chapter 5 proves an upper bound on mutual information between a signal and a communication channel output (such as neural activity). Mutual information is an important utility measure for biological systems, but its practical use can be difficult due to the large dimensionality of many biological channels. Sometimes, a lower bound on mutual information is computed by replacing the high-dimensional channel outputs with decodes (signal estimates). Our result provides a corresponding upper bound, provided that the decodes are the maximum posterior estimates of the signal.}, author = {Hledik, Michal}, issn = {2663-337X}, keywords = {Theoretical biology, Optimality, Evolution, Information}, pages = {158}, publisher = {Institute of Science and Technology Austria}, title = {{Genetic information and biological optimization}}, doi = {10.15479/at:ista:15020}, year = {2024}, } @phdthesis{17133, abstract = {An ideal quantum computer relies on qubits capable of performing fast gate operations and maintaining strong interconnections while preserving their quantum coherence. Since the inception of experimental eforts toward building a quantum computer, the community has faced challenges in engineering such a system. Among the various methods of implementing a quantum computer, superconducting qubits have shown fast gates close to tens of nanoseconds, with the state-of-the-art reaching a coherence of a few milliseconds. However, achieving simultaneously long lifetimes with fast qubit operations poses an inherent paradox. Qubits with high coherence require isolation from the environment, while fast operation necessitates strong coupling of the qubit. This thesis approaches this issue by proposing the idea of engineering superconducting qubits capable of transitioning between operating in a protected regime, where the qubit is completely isolated from the environment, and coupling to the communication channels as needed. In this direction, we use the geometric superinductor to scan the parameter space of rf-SQUID devices, searching for a regime where we can take the qubit protection to its extreme. This leads us to the inductively shunted transmon (IST) regime, characterized by EJ /EC ≫ 1 and EJ /EL ≫ 1, where the circuit potential exhibits a double well with a large barrier separating the local ground states of each quantum well. In this regime, although it is anticipated that the two quantum wells would be isolated from each other, we observe single fuxon tunneling between them. The interplay of the cavity photons and the fuxon transition forms a rich physical system, containing resonance conditions that allow the preparation of the fuxon ground or excited states. This enables us to study the relaxation rate of such transition and show that it can be as large as 3.6 hours. Dynamically controlling the barrier height between the two quantum wells allows for controllable coupling, which scales exponentially, for a qubit encoded in two fuxon states. The 0-π qubit is one of the very few known superconducting circuit types that ofers exponential protection from both relaxation and dephasing simultaneously. However, this qubit is not exempt from the fact that such protection comes at the expense of complex readout and control. In this thesis, we propose a way to controllably break the circuit symmetry, the key reason for the protection, to momentarily restore the ability to control and manipulate the qubit. An asymmetry in capacitances and inductances in the 0-π circuit is detrimental since they lead to coupling of the protected state to the thermally occupied parasitic mode of the circuit. However, here we try to exploit a controlled asymmetry in Josephson energies and show that this can be used as a tunable coupler between the protected states. In the future, this should allow to perform gate operations by dynamically controlling the asymmetry instead of driving the protected transition with microwave pulses. Therefore, we believe that the proposed method can make the use of protected qubits more practical in experimental realizations of quantum computing.}, author = {Hassani, Farid}, isbn = {978-3-99078-040-4}, issn = {2663-337X}, keywords = {Quantum information, Qubits, Superconducting devices}, pages = {161}, publisher = {Institute of Science and Technology Austria}, title = {{Superconducting qubits capable of dynamic switching between protected and high-speed control regimes}}, doi = {10.15479/at:ista:17133}, year = {2024}, } @phdthesis{17156, abstract = {This dissertation is the summary of the author’s work, concerning the relations between cohomology rings of algebraic varieties and rings of functions on zero schemes and fixed point schemes. For most of the thesis, the focus is on smooth complex varieties with an action of a principally paired group, e.g. a parabolic subgroup of a reductive group. The fundamental theorem 5.2.11 from co-authored article [66] says that if the principal nilpotent has a unique zero, then the zero scheme over the Kostant section is isomorphic to the spectrum of the equivariant cohomology ring, remembering the grading in terms of a C^* action. A similar statement is proved also for the G-invariant functions on the total zero scheme over the whole Lie algebra. Additionally, we are able to prove an analogous result for the GKM spaces, which poses the question on a joint generalisation. We also tackle the situation of a singular variety. As long as it is embedded in a smooth variety with regular action, we are able to study its cohomology as well by means of the zero scheme. In case of e.g. Schubert varieties this determines the cohomology ring completely. In largest generality, this allows us to see a significant part of the cohomology ring. We also show (Theorem 6.2.1) that the cohomology ring of spherical varieties appears as the ring of functions on the zero scheme. The computational aspect is not easy, but one can hope that this can bring some concrete information about such cohomology rings. Lastly, the K-theory conjecture 6.3.1 is studied, with some results attained for GKM spaces. The thesis includes also an introduction to group actions on algebraic varieties. In particular, the vector fields associated to the actions are extensively studied. We also provide a version of the Kostant section for arbitrary principally paired group, which parametrises the regular orbits in the Lie algebra of an algebraic group. Before proving the main theorem, we also include a historical overview of the field. In particular we bring together the results of Akyildiz, Carrell and Lieberman on non-equivariant cohomology rings.}, author = {Rychlewicz, Kamil P}, issn = {2663-337X}, keywords = {equivariant cohomology, zero schemes, algebraic groups, Lie algebras}, pages = {117}, publisher = {Institute of Science and Technology Austria}, title = {{Equivariant cohomology and rings of functions}}, doi = {10.15479/at:ista:17156}, year = {2024}, } @phdthesis{17164, abstract = {This thesis is structured into two parts. In the first part, we consider the random variable X := Tr(f1(W)A1 . . . fk(W)Ak) where W is an N × N Hermitian Wigner matrix, k ∈ N, and we choose (possibly N-dependent) regular functions f1, . . . , fk as well as bounded deterministic matrices A1, . . . , Ak. In this context, we prove a functional central limit theorem on macroscopic and mesoscopic scales, showing that the fluctuations of X around its expectation are Gaussian and that the limiting covariance structure is given by a deterministic recursion. We further give explicit error bounds in terms of the scaling of f1, . . . , fk and the number of traceless matrices among A1, . . . , Ak, thus extending the results of Cipolloni, Erdős and Schröder [40] to products of arbitrary length k ≥ 2. Analyzing the underlying combinatorics leads to a non-recursive formula for the variance of X as well as the covariance of X and Y := Tr(fk+1(W)Ak+1 . . . fk+ℓ(W)Ak+ℓ) of similar build. When restricted to polynomials, these formulas reproduce recent results of Male, Mingo, Peché, and Speicher [107], showing that the underlying combinatorics of noncrossing partitions and annular non-crossing permutations continue to stay valid beyond the setting of second-order free probability theory. As an application, we consider the fluctuation of Tr(eitW A1e −itW A2)/N around its thermal value Tr(A1) Tr(A2)/N2 when t is large and give an explicit formula for the variance. The second part of the thesis collects three smaller projects focusing on different random matrix models. In the first project, we show that a class of weakly perturbed Hamiltonians of the form Hλ = H0 + λW, where W is a Wigner matrix, exhibits prethermalization. That is, the time evolution generated by Hλ relaxes to its ultimate thermal state via an intermediate prethermal state with a lifetime of order λ −2 . As the main result, we obtain a general relaxation formula, expressing the perturbed dynamics via the unperturbed dynamics and the ultimate thermal state. The proof relies on a two-resolvent global law for the deformed Wigner matrix Hλ. The second project focuses on correlated random matrices, more precisely on a correlated N × N Hermitian random matrix with a polynomially decaying metric correlation structure. A trivial a priori bound shows that the operator norm of this model is stochastically dominated by √ N. However, by calculating the trace of the moments of the matrix and using the summable decay of the cumulants, the norm estimate can be improved to a bound of order one. In the third project, we consider a multiplicative perturbation of the form UA(t) where U is a unitary random matrix and A = diag(t, 1, ..., 1). This so-called UA model was first introduced by Fyodorov [73] for its applications in scattering theory. We give a general description of the eigenvalue trajectories obtained by varying the parameter t and introduce a flow of deterministic domains that separates the outlier resulting from the rank-one perturbation from the typical eigenvalues for all sub-critical timescales. The results are obtained under generic assumptions on U that hold for various unitary random matrices, including the circular unitary ensemble (CUE) in the original formulation of the model.}, author = {Reker, Jana}, issn = {2663-337X}, keywords = {Random Matrices, Spectrum, Central Limit Theorem, Resolvent, Free Probability}, pages = {206}, publisher = {Institute of Science and Technology Austria}, title = {{Central limit theorems for random matrices: From resolvents to free probability}}, doi = {10.15479/at:ista:17164}, year = {2024}, } @phdthesis{18515, abstract = {Understanding the role of evolutionary processes in shaping genetic variation has been a primary goal in evolutionary genetics. In this regard, a key question is how genetically distinct populations evolve in the face of gene flow, thereby generating genetic and phenotypic divergence and reproductive isolation (RI). This requires quantifying the role and relative contributions of prezygotic and postzygotic isolating mechanisms on the reduction of gene exchange between populations, and identifying regions in the genome that mediate RI, which is often polygenic. Further, this needs distinguishing neutral and selected regions in the genome, and discerning how selection influences patterns of neutral divergence. Population structure, defined as any deviation from panmixia, such as geographic distribution, movement and mating patterns of individuals, influences how genetic variation is structured in space and shapes the neutral null model. Availability of large scale spatial genomic datasets now enables us to detect signatures of population structure in genetic data and infer population genetic parameters. Such inferences are crucial and have wide applications in biodiversity, conservation genetics, population management and medical genetics. However, inferences are based on assumptions that do not always match the complex reality, thus leading to erroneous conclusions. Moreover, the role and interaction of heterogeneous population density and dispersal, which are ubiquitous in nature, has been challenging to study owing to their mathematical complexity. In such scenarios, feedback between theory, data and simulations can prove to be useful. In this thesis, I examine the effect of population structure on neutral genetic variation and barriers to gene exchange in hybridising populations, thereby bridging together the fields of spatial population genetics and speciation. Despite being a key concept in speciation, reproductive isolation (RI) lacks a quantitative definition and has been used and measured differently across different fields. Chapter 2 gives a quantitative definition of RI, in terms of the effect of genetic differences on gene flow. We give analytical predictions for RI in a range of scenarios, in terms of effective migration rates for discrete populations and barrier strength for continuous populations. In addition to this, we discuss current measures of RI and their limitations, and propose the need for new measures that combine organismal and genetic perspectives of RI. In chapter 3, I examine the combined effect of assortative mating, sexual selection and viability selection on RI. For this, we consider a polygenic ‘magic’ trait under a mainland-island model. We obtain novel theoretical predictions for molecular divergence in terms of effective migration rates, which bears a simple relationship to measurable fitness components of migrants and various early generation hybrids. We explore the conditions under which local adaptation can be maintained despite maladaptive gene flow and quantify the relative contributions of viability and sexual selection to genome-wide barriers to gene flow. The next two chapters of the thesis focus on a hybrid zone of Antirrhinum majus that consist of two subspecies- the magenta flowered A. m. pseudomajus and the yellow flowered A.m. striatum. Previous studies have suggested that flower colour is target of pollinator mediated selection and is influenced only by few genes. While these regions show high genetic differentiation between the subspecies, the rest of the genome is seen to be well mixed. Chapter 4 examines the effects of heterogeneous population density and leptokurtic dispersal on isolation by distance and the distribution of heterozygosity by focusing on non-flower colour markers. Chapter 5 analyses cline shapes and associations among 6 focal flower colour markers to understand how selection and dispersal maintain this hybrid zone. We see sharp coincident stepped clines at all loci and positive associations throughout the hybrid zone, contrary to the expected patterns from diffusive gene flow. With a novel scheme of inferring dispersal combined with multilocus simulations, we show that stepped clines do not reflect genetic barriers to gene flow, but are rather a result of long-distance migration. This framework allows us to get realistic estimates gene flow and selection and shows how traditional cline analysis may lead to inaccurate conclusions when assumptions of the theory are not met. Overall, this thesis investigates how different features of population structure leave detectable signatures in genetic variation, namely in patterns of isolation by distance, linkage disequilibrium and genetic divergence. It also highlights how effective migration rates provide useful way of analysing polygenic architectures and shed new light into hybrid zones. In doing so, I identify scenarios when simple models become insufficient and suggest possibe directions by combining genetic data with simulations.}, author = {Surendranadh, Parvathy}, issn = {2663-337X}, pages = {219}, publisher = {Institute of Science and Technology Austria}, title = {{Effect of population structure on neutral genetic variation and barriers to gene exchange}}, doi = {10.15479/at:ista:18515}, year = {2024}, } @phdthesis{18568, abstract = {Locomotion is ubiquitous in the animal kingdom because an animal's survival depends on its ability to navigate its environment to find food, avoid predators and locate potential mates. These behaviours require control mechanisms that can extract information from the environment, particularly visual cues. Selective evolutionary pressures have thus refined such visuomotor transformations in a species-specific manner to meet the specific ecological and ethological challenges of each organism. However, a common challenge across organisms as visual information processing becomes increasingly detailed is the mechanisms required to synthesise disparate pieces of information into a coherent percept or unified picture of the world. In this thesis, I investigate how disparate visual information is combined in the brain of Drosophila melanogaster to effectively guide locomotion. For this, I first designed and built a behavioural setup to record locomotion and present visual stimuli to freely-walking fruit flies in a closed-loop manner. This setup allowed the investigation of innate visually-guided behaviours, including the optomotor reflex and courtship. Second, taking advantage of my system I investigated the optomotor response, a reflexive visual stabilisation behaviour in which flies turn in the direction of global motion to minimise retinal slip. This behaviour is thought to be mediated by Lobula plate tangential cells (LPTCs); a complex network of optic-flow-sensitive neurons essential for self-motion estimation. Using a novel genetic mutant, I demonstrate that electrical coupling between two LPTC subtypes, contralateral HS and H2 neurons, regulates the balance between smooth optomotor turning and saccadic anti-optomotor responses. These findings underscore the critical role of binocular motion cue integration in guiding course control. Finally, I developed a novel behavioural paradigm in which a sexually aroused male fruit fly is presented with an optomotor distractor. This setup creates competition between two visual behaviours, courtship tracking and the optomotor response, enabling me to explore how the visual system resolves this conflict. In this setting, males engaged in courtship selectively suppress their optomotor response based on the female's location. Furthermore, when this experiment is replicated with an “artificial female”, optogenetically aroused males alternate between tracking and optomotor responses. The probability and dynamics of this switching are determined by the relative strengths of the two competing stimuli. In summary, the results presented in this thesis explore two mechanisms – integration and competition - through which visual information is combined in the brain of the fruit fly to drive locomotion.}, author = {Satapathy, Roshan K}, isbn = {978-3-99078-047-3}, issn = {2663-337X}, pages = {114}, publisher = {Institute of Science and Technology Austria}, title = {{Mechanisms of visual integration and competition in innate behaviours in Drosophila melanogaster}}, doi = {10.15479/at:ista:18568}, year = {2024}, } @phdthesis{18674, abstract = {Mapping the complex and dense arrangement of cells and their connectivity in brain tissue requires volumetric imaging at nanoscale spatial resolution. While light microscopy excels at visualizing specific molecules and individual cells, achieving dense, synapse-level circuit reconstruction has not been possible with any light microscopy technique. Thus, the goal of my work was to develop image and data analysis pipelines for brain tissue visualization and reconstruction with light microscopy. To achieve dense circuit reconstruction with single-synapse resolution, I developed both conventional and deep-learning-based synapse detection algorithms, as well as connectivity analysis pipelines that integrate synapse detection with volumetric segmentation of brain tissue.}, author = {Lyudchik, Julia}, isbn = { 978-3-99078-051-0}, issn = {2663-337X}, pages = {217}, publisher = {Institute of Science and Technology Austria}, title = {{Image analysis for brain tissue reconstruction with super-resolution light microscopy}}, doi = {10.15479/at:ista:18674}, year = {2024}, }