TY - THES AB - The polaron model is a basic model of quantum field theory describing a single particle interacting with a bosonic field. It arises in many physical contexts. We are mostly concerned with models applicable in the context of an impurity atom in a Bose-Einstein condensate as well as the problem of electrons moving in polar crystals. The model has a simple structure in which the interaction of the particle with the field is given by a term linear in the field’s creation and annihilation operators. In this work, we investigate the properties of this model by providing rigorous estimates on various energies relevant to the problem. The estimates are obtained, for the most part, by suitable operator techniques which constitute the principal mathematical substance of the thesis. The first application of these techniques is to derive the polaron model rigorously from first principles, i.e., from a full microscopic quantum-mechanical many-body problem involving an impurity in an otherwise homogeneous system. We accomplish this for the N + 1 Bose gas in the mean-field regime by showing that a suitable polaron-type Hamiltonian arises at weak interactions as a low-energy effective theory for this problem. In the second part, we investigate rigorously the ground state of the model at fixed momentum and for large values of the coupling constant. Qualitatively, the system is expected to display a transition from the quasi-particle behavior at small momenta, where the dispersion relation is parabolic and the particle moves through the medium dragging along a cloud of phonons, to the radiative behavior at larger momenta where the polaron decelerates and emits free phonons. At the same time, in the strong coupling regime, the bosonic field is expected to behave purely classically. Accordingly, the effective mass of the polaron at strong coupling is conjectured to be asymptotically equal to the one obtained from the semiclassical counterpart of the problem, first studied by Landau and Pekar in the 1940s. For polaron models with regularized form factors and phonon dispersion relations of superfluid type, i.e., bounded below by a linear function of the wavenumbers for all phonon momenta as in the interacting Bose gas, we prove that for a large window of momenta below the radiation threshold, the energy-momentum relation at strong coupling is indeed essentially a parabola with semi-latus rectum equal to the Landau–Pekar effective mass, as expected. For the Fröhlich polaron describing electrons in polar crystals where the dispersion relation is of the optical type and the form factor is formally UV–singular due to the nature of the point charge-dipole interaction, we are able to give the corresponding upper bound. In contrast to the regular case, this requires the inclusion of the quantum fluctuations of the phonon field, which makes the problem considerably more difficult. The results are supplemented by studies on the absolute ground-state energy at strong coupling, a proof of the divergence of the effective mass with the coupling constant for a wide class of polaron models, as well as the discussion of the apparent UV singularity of the Fröhlich model and the application of the techniques used for its removal for the energy estimates. AU - Mysliwy, Krzysztof ID - 11473 SN - 2663-337X TI - Polarons in Bose gases and polar crystals: Some rigorous energy estimates ER - TY - THES AB - Because of the increasing popularity of machine learning methods, it is becoming important to understand the impact of learned components on automated decision-making systems and to guarantee that their consequences are beneficial to society. In other words, it is necessary to ensure that machine learning is sufficiently trustworthy to be used in real-world applications. This thesis studies two properties of machine learning models that are highly desirable for the sake of reliability: robustness and fairness. In the first part of the thesis we study the robustness of learning algorithms to training data corruption. Previous work has shown that machine learning models are vulnerable to a range of training set issues, varying from label noise through systematic biases to worst-case data manipulations. This is an especially relevant problem from a present perspective, since modern machine learning methods are particularly data hungry and therefore practitioners often have to rely on data collected from various external sources, e.g. from the Internet, from app users or via crowdsourcing. Naturally, such sources vary greatly in the quality and reliability of the data they provide. With these considerations in mind, we study the problem of designing machine learning algorithms that are robust to corruptions in data coming from multiple sources. We show that, in contrast to the case of a single dataset with outliers, successful learning within this model is possible both theoretically and practically, even under worst-case data corruptions. The second part of this thesis deals with fairness-aware machine learning. There are multiple areas where machine learning models have shown promising results, but where careful considerations are required, in order to avoid discrimanative decisions taken by such learned components. Ensuring fairness can be particularly challenging, because real-world training datasets are expected to contain various forms of historical bias that may affect the learning process. In this thesis we show that data corruption can indeed render the problem of achieving fairness impossible, by tightly characterizing the theoretical limits of fair learning under worst-case data manipulations. However, assuming access to clean data, we also show how fairness-aware learning can be made practical in contexts beyond binary classification, in particular in the challenging learning to rank setting. AU - Konstantinov, Nikola H ID - 10799 KW - robustness KW - fairness KW - machine learning KW - PAC learning KW - adversarial learning SN - 2663-337X TI - Robustness and fairness in machine learning ER - TY - THES AB - Plant growth and development is well known to be both, flexible and dynamic. The high capacity for post-embryonic organ formation and tissue regeneration requires tightly regulated intercellular communication and coordinated tissue polarization. One of the most important drivers for patterning and polarity in plant development is the phytohormone auxin. Auxin has the unique characteristic to establish polarized channels for its own active directional cell to cell transport. This fascinating phenomenon is called auxin canalization. Those auxin transport channels are characterized by the expression and polar, subcellular localization of PIN auxin efflux carriers. PIN proteins have the ability to dynamically change their localization and auxin itself can affect this by interfering with trafficking. Most of the underlying molecular mechanisms of canalization still remain enigmatic. What is known so far is that canonical auxin signaling is indispensable but also other non-canonical signaling components are thought to play a role. In order to shed light into the mysteries auf auxin canalization this study revisits the branches of auxin signaling in detail. Further a new auxin analogue, PISA, is developed which triggers auxin-like responses but does not directly activate canonical transcriptional auxin signaling. We revisit the direct auxin effect on PIN trafficking where we found that, contradictory to previous observations, auxin is very specifically promoting endocytosis of PIN2 but has no overall effect on endocytosis. Further, we evaluate which cellular processes related to PIN subcellular dynamics are involved in the establishment of auxin conducting channels and the formation of vascular tissue. We are re-evaluating the function of AUXIN BINDING PROTEIN 1 (ABP1) and provide a comprehensive picture about its developmental phneotypes and involvement in auxin signaling and canalization. Lastly, we are focusing on the crosstalk between the hormone strigolactone (SL) and auxin and found that SL is interfering with essentially all processes involved in auxin canalization in a non-transcriptional manner. Lastly we identify a new way of SL perception and signaling which is emanating from mitochondria, is independent of canonical SL signaling and is modulating primary root growth. AU - Gallei, Michelle C ID - 11626 SN - 2663-337X TI - Auxin and strigolactone non-canonical signaling regulating development in Arabidopsis thaliana ER - TY - THES AB - The complex yarn structure of knitted and woven fabrics gives rise to both a mechanical and visual complexity. The small-scale interactions of yarns colliding with and pulling on each other result in drastically different large-scale stretching and bending behavior, introducing anisotropy, curling, and more. While simulating cloth as individual yarns can reproduce this complexity and match the quality of real fabric, it may be too computationally expensive for large fabrics. On the other hand, continuum-based approaches do not need to discretize the cloth at a stitch-level, but it is non-trivial to find a material model that would replicate the large-scale behavior of yarn fabrics, and they discard the intricate visual detail. In this thesis, we discuss three methods to try and bridge the gap between small-scale and large-scale yarn mechanics using numerical homogenization: fitting a continuum model to periodic yarn simulations, adding mechanics-aware yarn detail onto thin-shell simulations, and quantitatively fitting yarn parameters to physical measurements of real fabric. To start, we present a method for animating yarn-level cloth effects using a thin-shell solver. We first use a large number of periodic yarn-level simulations to build a model of the potential energy density of the cloth, and then use it to compute forces in a thin-shell simulator. The resulting simulations faithfully reproduce expected effects like the stiffening of woven fabrics and the highly deformable nature and anisotropy of knitted fabrics at a fraction of the cost of full yarn-level simulation. While our thin-shell simulations are able to capture large-scale yarn mechanics, they lack the rich visual detail of yarn-level simulations. Therefore, we propose a method to animate yarn-level cloth geometry on top of an underlying deforming mesh in a mechanics-aware fashion in real time. Using triangle strains to interpolate precomputed yarn geometry, we are able to reproduce effects such as knit loops tightening under stretching at negligible cost. Finally, we introduce a methodology for inverse-modeling of yarn-level mechanics of cloth, based on the mechanical response of fabrics in the real world. We compile a database from physical tests of several knitted fabrics used in the textile industry spanning diverse physical properties like stiffness, nonlinearity, and anisotropy. We then develop a system for approximating these mechanical responses with yarn-level cloth simulation, using homogenized shell models to speed up computation and adding some small-but-necessary extensions to yarn-level models used in computer graphics. AU - Sperl, Georg ID - 12358 SN - 2663-337X TI - Homogenizing yarn simulations: Large-scale mechanics, small-scale detail, and quantitative fitting ER - TY - THES AB - In this Thesis, I study composite quantum impurities with variational techniques, both inspired by machine learning as well as fully analytic. I supplement this with exploration of other applications of machine learning, in particular artificial neural networks, in many-body physics. In Chapters 3 and 4, I study quasiparticle systems with variational approach. I derive a Hamiltonian describing the angulon quasiparticle in the presence of a magnetic field. I apply analytic variational treatment to this Hamiltonian. Then, I introduce a variational approach for non-additive systems, based on artificial neural networks. I exemplify this approach on the example of the polaron quasiparticle (Fröhlich Hamiltonian). In Chapter 5, I continue using artificial neural networks, albeit in a different setting. I apply artificial neural networks to detect phases from snapshots of two types physical systems. Namely, I study Monte Carlo snapshots of multilayer classical spin models as well as molecular dynamics maps of colloidal systems. The main type of networks that I use here are convolutional neural networks, known for their applicability to image data. AU - Rzadkowski, Wojciech ID - 10759 SN - 2663-337X TI - Analytic and machine learning approaches to composite quantum impurities ER - TY - THES AB - One of the fundamental questions in Neuroscience is how the structure of synapses and their physiological properties are related. While synaptic transmission remains a dynamic process, electron microscopy provides images with comparably low temporal resolution (Studer et al., 2014). The current work overcomes this challenge and describes an improved “Flash and Freeze” technique (Watanabe et al., 2013a; Watanabe et al., 2013b) to study synaptic transmission at the hippocampal mossy fiber-CA3 pyramidal neuron synapses, using mouse acute brain slices and organotypic slices culture. The improved method allowed for selective stimulation of presynaptic mossy fiber boutons and the observation of synaptic vesicle pool dynamics at the active zones. Our results uncovered several intriguing morphological features of mossy fiber boutons. First, the docked vesicle pool was largely depleted (more than 70%) after stimulation, implying that the docked synaptic vesicles pool and readily releasable pool are vastly overlapping in mossy fiber boutons. Second, the synaptic vesicles are skewed towards larger diameters, displaying a wide range of sizes. An increase in the mean diameter of synaptic vesicles, after single and repetitive stimulation, suggests that smaller vesicles have a higher release probability. Third, we observed putative endocytotic structures after moderate light stimulation, matching the timing of previously described ultrafast endocytosis (Watanabe et al., 2013a; Delvendahl et al., 2016). In addition, synaptic transmission depends on a sophisticated system of protein machinery and calcium channels (Südhof, 2013b), which amplifies the challenge in studying synaptic communication as these interactions can be potentially modified during synaptic plasticity. And although recent study elucidated the potential correlation between physiological and morphological properties of synapses during synaptic plasticity (Vandael et al., 2020), the molecular underpinning of it remains unknown. Thus, the presented work tries to overcome this challenge and aims to pinpoint changes in the molecular architecture at hippocampal mossy fiber bouton synapses during short- and long-term potentiation (STP and LTP), we combined chemical potentiation, with the application of a cyclic adenosine monophosphate agonist (i.e. forskolin) and freeze-fracture replica immunolabelling. This method allowed the localization of membrane-bound proteins with nanometer precision within the active zone, in particular, P/Q-type calcium channels and synaptic vesicle priming proteins Munc13-1/2. First, we found that the number of clusters of Munc13-1 in the mossy fiber bouton active zone increased significantly during STP, but decreased to lower than the control value during LTP. Secondly, although the distance between the calcium channels and Munc13-1s did not change after induction of STP, it shortened during the LTP phase. Additionally, forskolin did not affect Munc13-2 distribution during STP and LTP. These results indicate the existence of two distinct mechanisms that govern STP and LTP at mossy fiber bouton synapses: an increase in the readily realizable pool in the case of STP and a potential increase in release probability during LTP. “Flash and freeze” and functional electron microscopy, are versatile methods that can be successfully applied to intact brain circuits to study synaptic transmission even at the molecular level. AU - Kim, Olena ID - 11196 SN - 2663-337X TI - Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses ER - TY - THES AB - Social insects are a common model to study disease dynamics in social animals. Even though pathogens should thrive in social insect colonies as the hosts engage in frequent social interactions, are closely related and live in a pathogen-rich environment, disease outbreaks are rare. This is because social insects have evolved mechanisms to keep pathogens at bay – and fight disease as a collective. Social insect colonies are often viewed as “superorganisms” with division of labor between reproductive “germ-like” queens and males and “somatic” workers, which together form an interdependent reproductive unit that parallels a multicellular body. Superorganisms possess a “social immune system” that comprises of collective disease defenses performed by the workers - summarized as “social immunity”. In social groups immunization (reduced susceptibility to a parasite upon secondary exposure to the same parasite) can e.g. be triggered by social interactions (“social immunization”). Social immunization can be caused by (i) asymptomatic low-level infections that are acquired during caregiving to a contagious individual that can give an immune boost, which can induce protection upon later encounter with the same pathogen (active immunization) or (ii) by transfer of immune effectors between individuals (passive immunization). In the second chapter, I built up on a study that I co-authored that found that low-level infections can not only be protective, but also be costly and make the host more susceptible to detrimental superinfections after contact to a very dissimilar pathogen. I here now tested different degrees of phylogenetically-distant fungal strains of M. brunneum and M. robertsii in L. neglectus and can describe the occurrence of cross-protection of social immunization if the first and second pathogen are from the same level. Interestingly, low-level infections only provided protection when the first strain was less virulent than the second strain and elicited higher immune gene expression. In the third and fourth chapters, I expanded on the role of social immunity in sexual selection, a so far unstudied field. I used the fungus Metarhizium robertsii and the ant Cardiocondyla obscurior as a model, as in this species mating occurs in the presence of workers and can be studied under laboratory conditions. Before males mate with virgin queens in the nest they engage in fierce combat over the access to their mating partners. First, I focused on male-male competition in the third chapter and found that fighting with a contagious male is costly as it can lead to contamination of the rival, but that workers can decrease the risk of disease contraction by performing sanitary care. In the fourth chapter, I studied the effect of fungal infection on survival and mating success of sexuals (freshly emerged queens and males) and found that worker-performed sanitary care can buffer the negative effect that a pathogenic contagion would have on sexuals by spore removal from the exposed individuals. When social immunity was prevented and queens could contract spores from their mating partner, very low dosages led to negative consequences: their lifespan was reduced and they produced fewer offspring with poor immunocompetence compared to healthy queens. Interestingly, cohabitation with a late-stage infected male where no spore transfer was possible had a positive effect on offspring immunity – male offspring of mothers that apparently perceived an infected partner in their vicinity reacted more sensitively to fungal challenge than male offspring without paternal pathogen history. AU - Metzler, Sina ID - 10727 SN - 2663-337X TI - Pathogen-mediated sexual selection and immunization in ant colonies ER - TY - THES AB - As the overall global mean surface temperature is increasing due to climate change, plant adaptation to those stressful conditions is of utmost importance for their survival. Plants are sessile organisms, thus to compensate for their lack of mobility, they evolved a variety of mechanisms enabling them to flexibly adjust their physiological, growth and developmental processes to fluctuating temperatures and to survive in harsh environments. While these unique adaptation abilities provide an important evolutionary advantage, overall modulation of plant growth and developmental program due to non-optimal temperature negatively affects biomass production, crop productivity or sensitivity to pathogens. Thus, understanding molecular processes underlying plant adaptation to increased temperature can provide important resources for breeding strategies to ensure sufficient agricultural food production. An increase in ambient temperature by a few degrees leads to profound changes in organ growth including enhanced hypocotyl elongation, expansion of petioles, hyponastic growth of leaves and cotyledons, collectively named thermomorphogenesis (Casal & Balasubramanian, 2019). Auxin, one of the best-studied growth hormones, plays an essential role in this process by direct activation of transcriptional and non-transcriptional processes resulting in elongation growth (Majda & Robert, 2018).To modulate hypocotyl growth in response to high ambient temperature (hAT), auxin needs to be redistributed accordingly. PINs, auxin efflux transporters, are key components of the polar auxin transport (PAT) machinery, which controls the amount and direction of auxin translocated in the plant tissues and organs(Adamowski & Friml, 2015). Hence, PIN-mediated transport is tightly linked with thermo-morphogenesis, and interference with PAT through either chemical or genetic means dramatically affecting the adaptive responses to hAT. Intriguingly, despite the key role of PIN mediated transport in growth response to hAT, whether and how PINs at the level of expression adapt to fluctuation in temperature is scarcely understood. With genetic, molecular and advanced bio-imaging approaches, we demonstrate the role of PIN auxin transporters in the regulation of hypocotyl growth in response to hAT. We show that via adjustment of PIN3, PIN4 and PIN7 expression in cotyledons and hypocotyls, auxin distribution is modulated thereby determining elongation pattern of epidermal cells at hAT. Furthermore, we identified three Zinc-Finger (ZF) transcription factors as novel molecular components of the thermo-regulatory network, which through negative regulation of PIN transcription adjust the transport of auxin at hAT. Our results suggest that the ZF-PIN module might be a part of the negative feedback loop attenuating the activity of the thermo-sensing pathway to restrain exaggerated growth and developmental responses to hAT. AU - Artner, Christina ID - 11879 KW - high ambient temperature KW - auxin KW - PINs KW - Zinc-Finger proteins KW - thermomorphogenesis KW - stress SN - 2663-337X TI - Modulation of auxin transport via ZF proteins adjust plant response to high ambient temperature ER - TY - THES AB - AMPA receptors (AMPARs) mediate fast excitatory neurotransmission and their role is implicated in complex processes such as learning and memory and various neurological diseases. These receptors are composed of different subunits and the subunit composition can affect channel properties, receptor trafficking and interaction with other associated proteins. Using the high sensitivity SDS-digested freeze-fracture replica labeling (SDS-FRL) for electron microscopy I investigated the number, density, and localization of AMPAR subunits, GluA1, GluA2, GluA3, and GluA1-3 (panAMPA) in pyramidal cells in the CA1 area of mouse hippocampus. I have found that the immunogold labeling for all of these subunits in the postsynaptic sites was highest in stratum radiatum and lowest in stratum lacunosummoleculare. The labeling density for the all subunits in the extrasynaptic sites showed a gradual increase from the pyramidal cell soma towards the distal part of stratum radiatum. The densities of extrasynaptic GluA1, GluA2 and panAMPA labeling reached 10-15% of synaptic densities, while the ratio of extrasynaptic labeling for GluA3 was significantly lower compared than those for other subunits. The labeling patterns for GluA1, GluA2 and GluA1-3 are similar and their densities were higher in the periphery than center of synapses. In contrast, the GluA3- containing receptors were more centrally localized compared to the GluA1- and GluA2- containing receptors. The hippocampus plays a central role in learning and memory. Contextual learning has been shown to require the delivery of AMPA receptors to CA1 synapses in the dorsal hippocampus. However, proximodistal heterogeneity of this plasticity and particular contribution of different AMPA receptor subunits are not fully understood. By combining inhibitory avoidance task, a hippocampus-dependent contextual fear-learning paradigm, with SDS-FRL, I have revealed an increase in synaptic density specific to GluA1-containing AMPA receptors in the CA1 area. The intrasynaptic distribution of GluA1 also changed from the periphery to center-preferred pattern. Furthermore, this synaptic plasticity was evident selectively in stratum radiatum but not stratum oriens, and in the CA1 subregion proximal but not distal to CA2. These findings further contribute to our understanding of how specific hippocampal subregions and AMPA receptor subunits are involved in physiological learning. Although the immunolabeling results above shed light on subunit-specific plasticity in AMPAR distribution, no tools to visualize and study the subunit composition at the single channel level in situ have been available. Electron microscopy with conventional immunogold labeling approaches has limitations in the single channel analysis because of the large size of antibodies and steric hindrance hampering multiple subunit labeling of single channels. I managed to develop a new chemical labeling system using a short peptide tag and small synthetic probes, which form specific covalent bond with a cysteine residue in the tag fused to proteins of interest (reactive tag system). I additionally made substantial progress into adapting this system for AMPA receptor subunits. AU - Jevtic, Marijo ID - 11393 SN - 2663-337X TI - Contextual fear learning induced changes in AMPA receptor subtypes along the proximodistal axis in dorsal hippocampus ER - TY - THES AB - Recent substantial advances in the feld of superconducting circuits have shown its potential as a leading platform for future quantum computing. In contrast to classical computers based on bits that are represented by a single binary value, 0 or 1, quantum bits (or qubits) can be in a superposition of both. Thus, quantum computers can store and handle more information at the same time and a quantum advantage has already been demonstrated for two types of computational tasks. Rapid progress in academic and industry labs accelerates the development of superconducting processors which may soon fnd applications in complex computations, chemical simulations, cryptography, and optimization. Now that these machines are scaled up to tackle such problems the questions of qubit interconnects and networks becomes very relevant. How to route signals on-chip between diferent processor components? What is the most efcient way to entangle qubits? And how to then send and process entangled signals between distant cryostats hosting superconducting processors? In this thesis, we are looking for solutions to these problems by studying the collective behavior of superconducting qubit ensembles. We frst demonstrate on-demand tunable directional scattering of microwave photons from a pair of qubits in a waveguide. Such a device can route microwave photons on-chip with a high diode efciency. Then we focus on studying ultra-strong coupling regimes between light (microwave photons) and matter (superconducting qubits), a regime that could be promising for extremely fast multi-qubit entanglement generation. Finally, we show coherent pulse storage and periodic revivals in a fve qubit ensemble strongly coupled to a resonator. Such a reconfgurable storage device could be used as part of a quantum repeater that is needed for longer-distance quantum communication. The achieved high degree of control over multi-qubit ensembles highlights not only the beautiful physics of circuit quantum electrodynamics, it also represents the frst step toward new quantum simulation and communication methods, and certain techniques may also fnd applications in future superconducting quantum computing hardware. AU - Redchenko, Elena ID - 12366 SN - 2663-337X TI - Controllable states of superconducting Qubit ensembles ER -