@phdthesis{12366, abstract = {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. }, author = {Redchenko, Elena}, isbn = {978-3-99078-024-4}, issn = {2663-337X}, pages = {168}, publisher = {Institute of Science and Technology Austria}, title = {{Controllable states of superconducting Qubit ensembles}}, doi = {10.15479/at:ista:12132}, year = {2022}, } @phdthesis{11932, abstract = {The ability to form and retrieve memories is central to survival. In mammals, the hippocampus is a brain region essential to the acquisition and consolidation of new memories. It is also involved in keeping track of one’s position in space and aids navigation. Although this space-memory has been a source of contradiction, evidence supports the view that the role of the hippocampus in navigation is memory, thanks to the formation of cognitive maps. First introduced by Tolman in 1948, cognitive maps are generally used to organize experiences in memory; however, the detailed mechanisms by which these maps are formed and stored are not yet agreed upon. Some influential theories describe this process as involving three fundamental steps: initial encoding by the hippocampus, interactions between the hippocampus and other cortical areas, and long-term extra-hippocampal consolidation. In this thesis, I will show how the investigation of cognitive maps of space helped to shed light on each of these three memory processes. The first study included in this thesis deals with the initial encoding of spatial memories in the hippocampus. Much is known about encoding at the level of single cells, but less about their co-activity or joint contribution to the encoding of novel spatial information. I will describe the structure of an interaction network that allows for efficient encoding of noisy spatial information during the first exploration of a novel environment. The second study describes the interactions between the hippocampus and the prefrontal cortex (PFC), two areas directly and indirectly connected. It is known that the PFC, in concert with the hippocampus, is involved in various processes, including memory storage and spatial navigation. Nonetheless, the detailed mechanisms by which PFC receives information from the hippocampus are not clear. I will show how a transient improvement in theta phase locking of PFC cells enables interactions of cell pairs across the two regions. The third study describes the learning of behaviorally-relevant spatial locations in the hippocampus and the medial entorhinal cortex. I will show how the accumulation of firing around goal locations, a correlate of learning, can shed light on the transition from short- to long-term spatial memories and the speed of consolidation in different brain areas. The studies included in this thesis represent the main scientific contributions of my Ph.D. They involve statistical analyses and models of neural responses of cells in different brain areas of rats executing spatial tasks. I will conclude the thesis by discussing the impact of the findings on principles of memory formation and retention, including the mechanisms, the speed, and the duration of these processes.}, author = {Nardin, Michele}, issn = {2663-337X}, pages = {136}, publisher = {Institute of Science and Technology Austria}, title = {{On the encoding, transfer, and consolidation of spatial memories}}, doi = {10.15479/at:ista:11932}, year = {2022}, } @phdthesis{11193, abstract = {The infiltration of immune cells into tissues underlies the establishment of tissue-resident macrophages and responses to infections and tumors. However, the mechanisms immune cells utilize to collectively migrate through tissue barriers in vivo are not yet well understood. In this thesis, I describe two mechanisms that Drosophila immune cells (hemocytes) use to overcome the tissue barrier of the germband in the embryo. One strategy is the strengthening of the actin cortex through developmentally controlled transcriptional regulation induced by the Drosophila proto-oncogene family member Dfos, which I show in Chapter 2. Dfos induces expression of the tetraspanin TM4SF and the filamin Cher leading to higher levels of the activated formin Dia at the cortex and increased cortical F-actin. This enhanced cortical strength allows hemocytes to overcome the physical resistance of the surrounding tissue and translocate their nucleus to move forward. This mechanism affects the speed of migration when hemocytes face a confined environment in vivo. Another aspect of the invasion process is the initial step of the leading hemocytes entering the tissue, which potentially guides the follower cells. In Chapter 3, I describe a novel subpopulation of hemocytes activated by BMP signaling prior to tissue invasion that leads penetration into the germband. Hemocytes that are deficient in BMP signaling activation show impaired persistence at the tissue entry, while their migration speed remains unaffected. This suggests that there might be different mechanisms controlling immune cell migration within the confined environment in vivo, one of these being the general ability to overcome the resistance of the surrounding tissue and another affecting the order of hemocytes that collectively invade the tissue in a stream of individual cells. Together, my findings provide deeper insights into transcriptional changes in immune cells that enable efficient tissue invasion and pave the way for future studies investigating the early colonization of tissues by macrophages in higher organisms. Moreover, they extend the current view of Drosophila immune cell heterogeneity and point toward a potentially conserved role for canonical BMP signaling in specifying immune cells that lead the migration of tissue resident macrophages during embryogenesis.}, author = {Wachner, Stephanie}, issn = {2663-337X}, pages = {170}, publisher = {Institute of Science and Technology Austria}, title = {{Transcriptional regulation by Dfos and BMP-signaling support tissue invasion of Drosophila immune cells}}, doi = {10.15479/at:ista:11193}, year = {2022}, } @phdthesis{12378, abstract = {Environmental cues influence the highly dynamic morphology of microglia. Strategies to characterize these changes usually involve user-selected morphometric features, which preclude the identification of a spectrum of context-dependent morphological phenotypes. Here, we develop MorphOMICs, a topological data analysis approach, which enables semiautomatic mapping of microglial morphology into an atlas of cue-dependent phenotypes, overcomes feature-selection bias and minimizes biological variability. First, with MorphOMICs we derive the morphological spectrum of microglia across seven brain regions during postnatal development and in two distinct Alzheimer’s disease degeneration mouse models. We uncover region-specific and sexually dimorphic morphological trajectories, with females showing an earlier morphological shift than males in the degenerating brain. Overall, we demonstrate that both long primary- and short terminal processes provide distinct insights to morphological phenotypes. Moreover, using machine learning to map novel condition on the spectrum, we observe that microglia morphologies reflect a dose-dependent adaptation upon ketamine anesthesia and do not recover to control morphologies. Next, we took advantage of MorphOMICs to build a high-resolution and layer-specific map of microglial morphological spectrum in the retina, covering postnatal development and rd10 degeneration. Here, following photoreceptor death, microglia assume an early developmentlike morphology. Finally, we map microglial morphology following optic nerve crush on the retinal spectrum and observe a layer- and sex-dependent response. Overall, MorphOMICs opens a new perspective to analyze microglial morphology across multiple conditions, and provides a novel tool to characterize microglial morphology beyond the traditionally dichotomized view of microglia.}, author = {Colombo, Gloria}, issn = {2663-337X}, pages = {142}, publisher = {Institute of Science and Technology Austria}, title = {{MorphOMICs, a tool for mapping microglial morphology, reveals brain region- and sex-dependent phenotypes}}, doi = {10.15479/at:ista:12378}, year = {2022}, } @phdthesis{12401, abstract = {Detachment of the cancer cells from the bulk of the tumor is the first step of metastasis, which is the primary cause of cancer related deaths. It is unclear, which factors contribute to this step. Recent studies indicate a crucial role of the tumor microenvironment in malignant transformation and metastasis. Studying cancer cell invasion and detachments quantitatively in the context of its physiological microenvironment is technically challenging. Especially, precise control of microenvironmental properties in vivo is currently not possible. Here, I studied the role of microenvironment geometry in the invasion and detachment of cancer cells from the bulk with a simplistic and reductionist approach. In this approach, I engineered microfluidic devices to mimic a pseudo 3D extracellular matrix environment, where I was able to quantitatively tune the geometrical configuration of the microenvironment and follow tumor cells with fluorescence live imaging. To aid quantitative analysis I developed a widely applicable software application to automatically analyze and visualize particle tracking data. Quantitative analysis of tumor cell invasion in isotropic and anisotropic microenvironments showed that heterogeneity in the microenvironment promotes faster invasion and more frequent detachment of cells. These observations correlated with overall higher speed of cells at the edge of the bulk of the cells. In heterogeneous microenvironments cells preferentially passed through larger pores, thus invading areas of least resistance and generating finger-like invasive structures. The detachments occurred mostly at the tips of these structures. To investigate the potential mechanism, we established a two dimensional model to simulate active Brownian particles representing the cell nuclei dynamics. These simulations backed our in vitro observations without the need of precise fitting the simulation parameters. Our model suggests the importance of the pore heterogeneity in the direction perpendicular to the orientation of bias field (lateral heterogeneity), which causes the interface roughening.}, author = {Tasciyan, Saren}, issn = {2663-337X}, pages = {105}, publisher = {Institute of Science and Technology Austria}, title = {{Role of microenvironment heterogeneity in cancer cell invasion}}, doi = {10.15479/at:ista:12401}, year = {2022}, } @phdthesis{9022, abstract = {In the first part of the thesis we consider Hermitian random matrices. Firstly, we consider sample covariance matrices XX∗ with X having independent identically distributed (i.i.d.) centred entries. We prove a Central Limit Theorem for differences of linear statistics of XX∗ and its minor after removing the first column of X. Secondly, we consider Wigner-type matrices and prove that the eigenvalue statistics near cusp singularities of the limiting density of states are universal and that they form a Pearcey process. Since the limiting eigenvalue distribution admits only square root (edge) and cubic root (cusp) singularities, this concludes the third and last remaining case of the Wigner-Dyson-Mehta universality conjecture. The main technical ingredients are an optimal local law at the cusp, and the proof of the fast relaxation to equilibrium of the Dyson Brownian motion in the cusp regime. In the second part we consider non-Hermitian matrices X with centred i.i.d. entries. We normalise the entries of X to have variance N −1. It is well known that the empirical eigenvalue density converges to the uniform distribution on the unit disk (circular law). In the first project, we prove universality of the local eigenvalue statistics close to the edge of the spectrum. This is the non-Hermitian analogue of the TracyWidom universality at the Hermitian edge. Technically we analyse the evolution of the spectral distribution of X along the Ornstein-Uhlenbeck flow for very long time (up to t = +∞). In the second project, we consider linear statistics of eigenvalues for macroscopic test functions f in the Sobolev space H2+ϵ and prove their convergence to the projection of the Gaussian Free Field on the unit disk. We prove this result for non-Hermitian matrices with real or complex entries. The main technical ingredients are: (i) local law for products of two resolvents at different spectral parameters, (ii) analysis of correlated Dyson Brownian motions. In the third and final part we discuss the mathematically rigorous application of supersymmetric techniques (SUSY ) to give a lower tail estimate of the lowest singular value of X − z, with z ∈ C. More precisely, we use superbosonisation formula to give an integral representation of the resolvent of (X − z)(X − z)∗ which reduces to two and three contour integrals in the complex and real case, respectively. The rigorous analysis of these integrals is quite challenging since simple saddle point analysis cannot be applied (the main contribution comes from a non-trivial manifold). Our result improves classical smoothing inequalities in the regime |z| ≈ 1; this result is essential to prove edge universality for i.i.d. non-Hermitian matrices.}, author = {Cipolloni, Giorgio}, issn = {2663-337X}, pages = {380}, publisher = {Institute of Science and Technology Austria}, title = {{Fluctuations in the spectrum of random matrices}}, doi = {10.15479/AT:ISTA:9022}, year = {2021}, } @phdthesis{10030, abstract = {This PhD thesis is primarily focused on the study of discrete transport problems, introduced for the first time in the seminal works of Maas [Maa11] and Mielke [Mie11] on finite state Markov chains and reaction-diffusion equations, respectively. More in detail, my research focuses on the study of transport costs on graphs, in particular the convergence and the stability of such problems in the discrete-to-continuum limit. This thesis also includes some results concerning non-commutative optimal transport. The first chapter of this thesis consists of a general introduction to the optimal transport problems, both in the discrete, the continuous, and the non-commutative setting. Chapters 2 and 3 present the content of two works, obtained in collaboration with Peter Gladbach, Eva Kopfer, and Jan Maas, where we have been able to show the convergence of discrete transport costs on periodic graphs to suitable continuous ones, which can be described by means of a homogenisation result. We first focus on the particular case of quadratic costs on the real line and then extending the result to more general costs in arbitrary dimension. Our results are the first complete characterisation of limits of transport costs on periodic graphs in arbitrary dimension which do not rely on any additional symmetry. In Chapter 4 we turn our attention to one of the intriguing connection between evolution equations and optimal transport, represented by the theory of gradient flows. We show that discrete gradient flow structures associated to a finite volume approximation of a certain class of diffusive equations (Fokker–Planck) is stable in the limit of vanishing meshes, reproving the convergence of the scheme via the method of evolutionary Γ-convergence and exploiting a more variational point of view on the problem. This is based on a collaboration with Dominik Forkert and Jan Maas. Chapter 5 represents a change of perspective, moving away from the discrete world and reaching the non-commutative one. As in the discrete case, we discuss how classical tools coming from the commutative optimal transport can be translated into the setting of density matrices. In particular, in this final chapter we present a non-commutative version of the Schrödinger problem (or entropic regularised optimal transport problem) and discuss existence and characterisation of minimisers, a duality result, and present a non-commutative version of the well-known Sinkhorn algorithm to compute the above mentioned optimisers. This is based on a joint work with Dario Feliciangeli and Augusto Gerolin. Finally, Appendix A and B contain some additional material and discussions, with particular attention to Harnack inequalities and the regularity of flows on discrete spaces.}, author = {Portinale, Lorenzo}, issn = {2663-337X}, publisher = {Institute of Science and Technology Austria}, title = {{Discrete-to-continuum limits of transport problems and gradient flows in the space of measures}}, doi = {10.15479/at:ista:10030}, year = {2021}, } @phdthesis{9733, abstract = {This thesis is the result of the research carried out by the author during his PhD at IST Austria between 2017 and 2021. It mainly focuses on the Fröhlich polaron model, specifically to its regime of strong coupling. This model, which is rigorously introduced and discussed in the introduction, has been of great interest in condensed matter physics and field theory for more than eighty years. It is used to describe an electron interacting with the atoms of a solid material (the strength of this interaction is modeled by the presence of a coupling constant α in the Hamiltonian of the system). The particular regime examined here, which is mathematically described by considering the limit α →∞, displays many interesting features related to the emergence of classical behavior, which allows for a simplified effective description of the system under analysis. The properties, the range of validity and a quantitative analysis of the precision of such classical approximations are the main object of the present work. We specify our investigation to the study of the ground state energy of the system, its dynamics and its effective mass. For each of these problems, we provide in the introduction an overview of the previously known results and a detailed account of the original contributions by the author.}, author = {Feliciangeli, Dario}, issn = {2663-337X}, pages = {180}, publisher = {Institute of Science and Technology Austria}, title = {{The polaron at strong coupling}}, doi = {10.15479/at:ista:9733}, year = {2021}, } @phdthesis{10199, abstract = {The design and verification of concurrent systems remains an open challenge due to the non-determinism that arises from the inter-process communication. In particular, concurrent programs are notoriously difficult both to be written correctly and to be analyzed formally, as complex thread interaction has to be accounted for. The difficulties are further exacerbated when concurrent programs get executed on modern-day hardware, which contains various buffering and caching mechanisms for efficiency reasons. This causes further subtle non-determinism, which can often produce very unintuitive behavior of the concurrent programs. Model checking is at the forefront of tackling the verification problem, where the task is to decide, given as input a concurrent system and a desired property, whether the system satisfies the property. The inherent state-space explosion problem in model checking of concurrent systems causes naïve explicit methods not to scale, thus more inventive methods are required. One such method is stateless model checking (SMC), which explores in memory-efficient manner the program executions rather than the states of the program. State-of-the-art SMC is typically coupled with partial order reduction (POR) techniques, which argue that certain executions provably produce identical system behavior, thus limiting the amount of executions one needs to explore in order to cover all possible behaviors. Another method to tackle the state-space explosion is symbolic model checking, where the considered techniques operate on a succinct implicit representation of the input system rather than explicitly accessing the system. In this thesis we present new techniques for verification of concurrent systems. We present several novel POR methods for SMC of concurrent programs under various models of semantics, some of which account for write-buffering mechanisms. Additionally, we present novel algorithms for symbolic model checking of finite-state concurrent systems, where the desired property of the systems is to ensure a formally defined notion of fairness.}, author = {Toman, Viktor}, issn = {2663-337X}, keywords = {concurrency, verification, model checking}, pages = {166}, publisher = {Institute of Science and Technology Austria}, title = {{Improved verification techniques for concurrent systems}}, doi = {10.15479/at:ista:10199}, year = {2021}, } @phdthesis{10007, abstract = {The present thesis is concerned with the derivation of weak-strong uniqueness principles for curvature driven interface evolution problems not satisfying a comparison principle. The specific examples being treated are two-phase Navier-Stokes flow with surface tension, modeling the evolution of two incompressible, viscous and immiscible fluids separated by a sharp interface, and multiphase mean curvature flow, which serves as an idealized model for the motion of grain boundaries in an annealing polycrystalline material. Our main results - obtained in joint works with Julian Fischer, Tim Laux and Theresa M. Simon - state that prior to the formation of geometric singularities due to topology changes, the weak solution concept of Abels (Interfaces Free Bound. 9, 2007) to two-phase Navier-Stokes flow with surface tension and the weak solution concept of Laux and Otto (Calc. Var. Partial Differential Equations 55, 2016) to multiphase mean curvature flow (for networks in R^2 or double bubbles in R^3) represents the unique solution to these interface evolution problems within the class of classical solutions, respectively. To the best of the author's knowledge, for interface evolution problems not admitting a geometric comparison principle the derivation of a weak-strong uniqueness principle represented an open problem, so that the works contained in the present thesis constitute the first positive results in this direction. The key ingredient of our approach consists of the introduction of a novel concept of relative entropies for a class of curvature driven interface evolution problems, for which the associated energy contains an interfacial contribution being proportional to the surface area of the evolving (network of) interface(s). The interfacial part of the relative entropy gives sufficient control on the interface error between a weak and a classical solution, and its time evolution can be computed, at least in principle, for any energy dissipating weak solution concept. A resulting stability estimate for the relative entropy essentially entails the above mentioned weak-strong uniqueness principles. The present thesis contains a detailed introduction to our relative entropy approach, which in particular highlights potential applications to other problems in curvature driven interface evolution not treated in this thesis.}, author = {Hensel, Sebastian}, issn = {2663-337X}, pages = {300}, publisher = {Institute of Science and Technology Austria}, title = {{Curvature driven interface evolution: Uniqueness properties of weak solution concepts}}, doi = {10.15479/at:ista:10007}, year = {2021}, } @phdthesis{10429, abstract = {The scalability of concurrent data structures and distributed algorithms strongly depends on reducing the contention for shared resources and the costs of synchronization and communication. We show how such cost reductions can be attained by relaxing the strict consistency conditions required by sequential implementations. In the first part of the thesis, we consider relaxation in the context of concurrent data structures. Specifically, in data structures such as priority queues, imposing strong semantics renders scalability impossible, since a correct implementation of the remove operation should return only the element with highest priority. Intuitively, attempting to invoke remove operations concurrently creates a race condition. This bottleneck can be circumvented by relaxing semantics of the affected data structure, thus allowing removal of the elements which are no longer required to have the highest priority. We prove that the randomized implementations of relaxed data structures provide provable guarantees on the priority of the removed elements even under concurrency. Additionally, we show that in some cases the relaxed data structures can be used to scale the classical algorithms which are usually implemented with the exact ones. In the second part, we study parallel variants of the stochastic gradient descent (SGD) algorithm, which distribute computation among the multiple processors, thus reducing the running time. Unfortunately, in order for standard parallel SGD to succeed, each processor has to maintain a local copy of the necessary model parameter, which is identical to the local copies of other processors; the overheads from this perfect consistency in terms of communication and synchronization can negate the speedup gained by distributing the computation. We show that the consistency conditions required by SGD can be relaxed, allowing the algorithm to be more flexible in terms of tolerating quantized communication, asynchrony, or even crash faults, while its convergence remains asymptotically the same.}, author = {Nadiradze, Giorgi}, issn = {2663-337X}, pages = {132}, publisher = {Institute of Science and Technology Austria}, title = {{On achieving scalability through relaxation}}, doi = {10.15479/at:ista:10429}, year = {2021}, } @phdthesis{9418, abstract = {Deep learning is best known for its empirical success across a wide range of applications spanning computer vision, natural language processing and speech. Of equal significance, though perhaps less known, are its ramifications for learning theory: deep networks have been observed to perform surprisingly well in the high-capacity regime, aka the overfitting or underspecified regime. Classically, this regime on the far right of the bias-variance curve is associated with poor generalisation; however, recent experiments with deep networks challenge this view. This thesis is devoted to investigating various aspects of underspecification in deep learning. First, we argue that deep learning models are underspecified on two levels: a) any given training dataset can be fit by many different functions, and b) any given function can be expressed by many different parameter configurations. We refer to the second kind of underspecification as parameterisation redundancy and we precisely characterise its extent. Second, we characterise the implicit criteria (the inductive bias) that guide learning in the underspecified regime. Specifically, we consider a nonlinear but tractable classification setting, and show that given the choice, neural networks learn classifiers with a large margin. Third, we consider learning scenarios where the inductive bias is not by itself sufficient to deal with underspecification. We then study different ways of ‘tightening the specification’: i) In the setting of representation learning with variational autoencoders, we propose a hand- crafted regulariser based on mutual information. ii) In the setting of binary classification, we consider soft-label (real-valued) supervision. We derive a generalisation bound for linear networks supervised in this way and verify that soft labels facilitate fast learning. Finally, we explore an application of soft-label supervision to the training of multi-exit models.}, author = {Bui Thi Mai, Phuong}, issn = {2663-337X}, pages = {125}, publisher = {Institute of Science and Technology Austria}, title = {{Underspecification in deep learning}}, doi = {10.15479/AT:ISTA:9418}, year = {2021}, } @phdthesis{9056, abstract = {In this thesis we study persistence of multi-covers of Euclidean balls and the geometric structures underlying their computation, in particular Delaunay mosaics and Voronoi tessellations. The k-fold cover for some discrete input point set consists of the space where at least k balls of radius r around the input points overlap. Persistence is a notion that captures, in some sense, the topology of the shape underlying the input. While persistence is usually computed for the union of balls, the k-fold cover is of interest as it captures local density, and thus might approximate the shape of the input better if the input data is noisy. To compute persistence of these k-fold covers, we need a discretization that is provided by higher-order Delaunay mosaics. We present and implement a simple and efficient algorithm for the computation of higher-order Delaunay mosaics, and use it to give experimental results for their combinatorial properties. The algorithm makes use of a new geometric structure, the rhomboid tiling. It contains the higher-order Delaunay mosaics as slices, and by introducing a filtration function on the tiling, we also obtain higher-order α-shapes as slices. These allow us to compute persistence of the multi-covers for varying radius r; the computation for varying k is less straight-foward and involves the rhomboid tiling directly. We apply our algorithms to experimental sphere packings to shed light on their structural properties. Finally, inspired by periodic structures in packings and materials, we propose and implement an algorithm for periodic Delaunay triangulations to be integrated into the Computational Geometry Algorithms Library (CGAL), and discuss the implications on persistence for periodic data sets.}, author = {Osang, Georg F}, issn = {2663-337X}, pages = {134}, publisher = {Institute of Science and Technology Austria}, title = {{Multi-cover persistence and Delaunay mosaics}}, doi = {10.15479/AT:ISTA:9056}, year = {2021}, } @phdthesis{9920, abstract = {This work is concerned with two fascinating circuit quantum electrodynamics components, the Josephson junction and the geometric superinductor, and the interesting experiments that can be done by combining the two. The Josephson junction has revolutionized the field of superconducting circuits as a non-linear dissipation-less circuit element and is used in almost all superconducting qubit implementations since the 90s. On the other hand, the superinductor is a relatively new circuit element introduced as a key component of the fluxonium qubit in 2009. This is an inductor with characteristic impedance larger than the resistance quantum and self-resonance frequency in the GHz regime. The combination of these two elements can occur in two fundamental ways: in parallel and in series. When connected in parallel the two create the fluxonium qubit, a loop with large inductance and a rich energy spectrum reliant on quantum tunneling. On the other hand placing the two elements in series aids with the measurement of the IV curve of a single Josephson junction in a high impedance environment. In this limit theory predicts that the junction will behave as its dual element: the phase-slip junction. While the Josephson junction acts as a non-linear inductor the phase-slip junction has the behavior of a non-linear capacitance and can be used to measure new Josephson junction phenomena, namely Coulomb blockade of Cooper pairs and phase-locked Bloch oscillations. The latter experiment allows for a direct link between frequency and current which is an elusive connection in quantum metrology. This work introduces the geometric superinductor, a superconducting circuit element where the high inductance is due to the geometry rather than the material properties of the superconductor, realized from a highly miniaturized superconducting planar coil. These structures will be described and characterized as resonators and qubit inductors and progress towards the measurement of phase-locked Bloch oscillations will be presented.}, author = {Peruzzo, Matilda}, isbn = {978-3-99078-013-8}, issn = {2663-337X}, keywords = {quantum computing, superinductor, quantum metrology}, pages = {149}, publisher = {Institute of Science and Technology Austria}, title = {{Geometric superinductors and their applications in circuit quantum electrodynamics}}, doi = {10.15479/at:ista:9920}, year = {2021}, } @phdthesis{10035, abstract = {Many security definitions come in two flavors: a stronger “adaptive” flavor, where the adversary can arbitrarily make various choices during the course of the attack, and a weaker “selective” flavor where the adversary must commit to some or all of their choices a-priori. For example, in the context of identity-based encryption, selective security requires the adversary to decide on the identity of the attacked party at the very beginning of the game whereas adaptive security allows the attacker to first see the master public key and some secret keys before making this choice. Often, it appears to be much easier to achieve selective security than it is to achieve adaptive security. A series of several recent works shows how to cleverly achieve adaptive security in several such scenarios including generalized selective decryption [Pan07][FJP15], constrained PRFs [FKPR14], and Yao’s garbled circuits [JW16]. Although the above works expressed vague intuition that they share a common technique, the connection was never made precise. In this work we present a new framework (published at Crypto ’17 [JKK+17a]) that connects all of these works and allows us to present them in a unified and simplified fashion. Having the framework in place, we show how to achieve adaptive security for proxy re-encryption schemes (published at PKC ’19 [FKKP19]) and provide the first adaptive security proofs for continuous group key agreement protocols (published at S&P ’21 [KPW+21]). Questioning optimality of our framework, we then show that currently used proof techniques cannot lead to significantly better security guarantees for "graph-building" games (published at TCC ’21 [KKPW21a]). These games cover generalized selective decryption, as well as the security of prominent constructions for constrained PRFs, continuous group key agreement, and proxy re-encryption. Finally, we revisit the adaptive security of Yao’s garbled circuits and extend the analysis of Jafargholi and Wichs in two directions: While they prove adaptive security only for a modified construction with increased online complexity, we provide the first positive results for the original construction by Yao (published at TCC ’21 [KKP21a]). On the negative side, we prove that the results of Jafargholi and Wichs are essentially optimal by showing that no black-box reduction can provide a significantly better security bound (published at Crypto ’21 [KKPW21c]).}, author = {Klein, Karen}, issn = {2663-337X}, pages = {276}, publisher = {Institute of Science and Technology Austria}, title = {{On the adaptive security of graph-based games}}, doi = {10.15479/at:ista:10035}, year = {2021}, } @phdthesis{10293, abstract = {Indirect reciprocity in evolutionary game theory is a prominent mechanism for explaining the evolution of cooperation among unrelated individuals. In contrast to direct reciprocity, which is based on individuals meeting repeatedly, and conditionally cooperating by using their own experiences, indirect reciprocity is based on individuals’ reputations. If a player helps another, this increases the helper’s public standing, benefitting them in the future. This lets cooperation in the population emerge without individuals having to meet more than once. While the two modes of reciprocity are intertwined, they are difficult to compare. Thus, they are usually studied in isolation. Direct reciprocity can maintain cooperation with simple strategies, and is robust against noise even when players do not remember more than their partner’s last action. Meanwhile, indirect reciprocity requires its successful strategies, or social norms, to be more complex. Exhaustive search previously identified eight such norms, called the “leading eight”, which excel at maintaining cooperation. However, as the first result of this thesis, we show that the leading eight break down once we remove the fundamental assumption that information is synchronized and public, such that everyone agrees on reputations. Once we consider a more realistic scenario of imperfect information, where reputations are private, and individuals occasionally misinterpret or miss observations, the leading eight do not promote cooperation anymore. Instead, minor initial disagreements can proliferate, fragmenting populations into subgroups. In a next step, we consider ways to mitigate this issue. We first explore whether introducing “generosity” can stabilize cooperation when players use the leading eight strategies in noisy environments. This approach of modifying strategies to include probabilistic elements for coping with errors is known to work well in direct reciprocity. However, as we show here, it fails for the more complex norms of indirect reciprocity. Imperfect information still prevents cooperation from evolving. On the other hand, we succeeded to show in this thesis that modifying the leading eight to use “quantitative assessment”, i.e. tracking reputation scores on a scale beyond good and bad, and making overall judgments of others based on a threshold, is highly successful, even when noise increases in the environment. Cooperation can flourish when reputations are more nuanced, and players have a broader understanding what it means to be “good.” Finally, we present a single theoretical framework that unites the two modes of reciprocity despite their differences. Within this framework, we identify a novel simple and successful strategy for indirect reciprocity, which can cope with noisy environments and has an analogue in direct reciprocity. We can also analyze decision making when different sources of information are available. Our results help highlight that for sustaining cooperation, already the most simple rules of reciprocity can be sufficient.}, author = {Schmid, Laura}, issn = {2663-337X}, pages = {171}, publisher = {Institute of Science and Technology Austria}, title = {{Evolution of cooperation via (in)direct reciprocity under imperfect information}}, doi = {10.15479/at:ista:10293}, year = {2021}, } @phdthesis{9992, abstract = {Blood – this is what animals use to heal wounds fast and efficient. Plants do not have blood circulation and their cells cannot move. However, plants have evolved remarkable capacities to regenerate tissues and organs preventing further damage. In my PhD research, I studied the wound healing in the Arabidopsis root. I used a UV laser to ablate single cells in the root tip and observed the consequent wound healing. Interestingly, the inner adjacent cells induced a division plane switch and subsequently adopted the cell type of the killed cell to replace it. We termed this form of wound healing “restorative divisions”. This initial observation triggered the questions of my PhD studies: How and why do cells orient their division planes, how do they feel the wound and why does this happen only in inner adjacent cells. For answering these questions, I used a quite simple experimental setup: 5 day - old seedlings were stained with propidium iodide to visualize cell walls and dead cells; ablation was carried out using a special laser cutter and a confocal microscope. Adaptation of the novel vertical microscope system made it possible to observe wounds in real time. This revealed that restorative divisions occur at increased frequency compared to normal divisions. Additionally, the major plant hormone auxin accumulates in wound adjacent cells and drives the expression of the wound-stress responsive transcription factor ERF115. Using this as a marker gene for wound responses, we found that an important part of wound signalling is the sensing of the collapse of the ablated cell. The collapse causes a radical pressure drop, which results in strong tissue deformations. These deformations manifest in an invasion of the now free spot specifically by the inner adjacent cells within seconds, probably because of higher pressure of the inner tissues. Long-term imaging revealed that those deformed cells continuously expand towards the wound hole and that this is crucial for the restorative division. These wound-expanding cells exhibit an abnormal, biphasic polarity of microtubule arrays before the division. Experiments inhibiting cell expansion suggest that it is the biphasic stretching that induces those MT arrays. Adapting the micromanipulator aspiration system from animal scientists at our institute confirmed the hypothesis that stretching influences microtubule stability. In conclusion, this shows that microtubules react to tissue deformation and this facilitates the observed division plane switch. This puts mechanical cues and tensions at the most prominent position for explaining the growth and wound healing properties of plants. Hence, it shines light onto the importance of understanding mechanical signal transduction. }, author = {Hörmayer, Lukas}, issn = {2663-337X}, pages = {168}, publisher = {Institute of Science and Technology Austria}, title = {{Wound healing in the Arabidopsis root meristem}}, doi = {10.15479/at:ista:9992}, year = {2021}, } @phdthesis{10135, abstract = {Plants maintain the capacity to develop new organs e.g. lateral roots post-embryonically throughout their whole life and thereby flexibly adapt to ever-changing environmental conditions. Plant hormones auxin and cytokinin are the main regulators of the lateral root organogenesis. Additionally to their solo activities, the interaction between auxin and cytokinin plays crucial role in fine-tuning of lateral root development and growth. In particular, cytokinin modulates auxin distribution within the developing lateral root by affecting the endomembrane trafficking of auxin transporter PIN1 and promoting its vacuolar degradation (Marhavý et al., 2011, 2014). This effect is independent of transcription and translation. Therefore, it suggests novel, non-canonical cytokinin activity occuring possibly on the posttranslational level. Impact of cytokinin and other plant hormones on auxin transporters (including PIN1) on the posttranslational level is described in detail in the introduction part of this thesis in a form of a review (Semeradova et al., 2020). To gain insights into the molecular machinery underlying cytokinin effect on the endomembrane trafficking in the plant cell, in particular on the PIN1 degradation, we conducted two large proteomic screens: 1) Identification of cytokinin binding proteins using chemical proteomics. 2) Monitoring of proteomic and phosphoproteomic changes upon cytokinin treatment. In the first screen, we identified DYNAMIN RELATED PROTEIN 2A (DRP2A). We found that DRP2A plays a role in cytokinin regulated processes during the plant growth and that cytokinin treatment promotes destabilization of DRP2A protein. However, the role of DRP2A in the PIN1 degradation remains to be elucidated. In the second screen, we found VACUOLAR PROTEIN SORTING 9A (VPS9A). VPS9a plays crucial role in plant’s response to cytokin and in cytokinin mediated PIN1 degradation. Altogether, we identified proteins, which bind to cytokinin and proteins that in response to cytokinin exhibit significantly changed abundance or phosphorylation pattern. By combining information from these two screens, we can pave our way towards understanding of noncanonical cytokinin effects.}, author = {Semerádová, Hana}, isbn = {978-3-99078-014-5}, issn = {2663-337X}, publisher = {Institute of Science and Technology Austria}, title = {{Molecular mechanisms of the cytokinin-regulated endomembrane trafficking to coordinate plant organogenesis}}, doi = {10.15479/at:ista:10135}, year = {2021}, } @phdthesis{10058, abstract = {Quantum information and computation has become a vast field paved with opportunities for researchers and investors. As large multinational companies and international funds are heavily investing in quantum technologies it is still a question which platform is best suited for the task of realizing a scalable quantum processor. In this work we investigate hole spins in Ge quantum wells. These hold great promise as they possess several favorable properties: a small effective mass, a strong spin-orbit coupling, long relaxation time and an inherent immunity to hyperfine noise. All these characteristics helped Ge hole spin qubits to evolve from a single qubit to a fully entangled four qubit processor in only 3 years. Here, we investigated a qubit approach leveraging the large out-of-plane g-factors of heavy hole states in Ge quantum dots. We found this qubit to be reproducibly operable at extremely low magnetic field and at large speeds while maintaining coherence. This was possible because large differences of g-factors in adjacent dots can be achieved in the out-of-plane direction. In the in-plane direction the small g-factors, on the other hand, can be altered very effectively by the confinement potentials. Here, we found that this can even lead to a sign change of the g-factors. The resulting g-factor difference alters the dynamics of the system drastically and produces effects typically attributed to a spin-orbit induced spin-flip term. The investigations carried out in this thesis give further insights into the possibilities of holes in Ge and reveal new physical properties that need to be considered when designing future spin qubit experiments.}, author = {Jirovec, Daniel}, issn = {2663-337X}, keywords = {qubits, quantum computing, holes}, pages = {151}, publisher = {Institute of Science and Technology Austria}, title = {{Singlet-Triplet qubits and spin-orbit interaction in 2-dimensional Ge hole gases}}, doi = {10.15479/at:ista:10058}, year = {2021}, } @phdthesis{9562, abstract = {Left-right asymmetries can be considered a fundamental organizational principle of the vertebrate central nervous system. The hippocampal CA3-CA1 pyramidal cell synaptic connection shows an input-side dependent asymmetry where the hemispheric location of the presynaptic CA3 neuron determines the synaptic properties. Left-input synapses terminating on apical dendrites in stratum radiatum have a higher density of NMDA receptor subunit GluN2B, a lower density of AMPA receptor subunit GluA1 and smaller areas with less often perforated PSDs. On the other hand, left-input synapses terminating on basal dendrites in stratum oriens have lower GluN2B densities than right-input ones. Apical and basal synapses further employ different signaling pathways involved in LTP. SDS-digested freeze-fracture replica labeling can visualize synaptic membrane proteins with high sensitivity and resolution, and has been used to reveal the asymmetry at the electron microscopic level. However, it requires time-consuming manual demarcation of the synaptic surface for quantitative measurements. To facilitate the analysis of replica labeling, I first developed a software named Darea, which utilizes deep-learning to automatize this demarcation. With Darea I characterized the synaptic distribution of NMDA and AMPA receptors as well as the voltage-gated Ca2+ channels in CA1 stratum radiatum and oriens. Second, I explored the role of GluN2B and its carboxy-terminus in the establishment of input-side dependent hippocampal asymmetry. In conditional knock-out mice lacking GluN2B expression in CA1 and GluN2B-2A swap mice, where GluN2B carboxy-terminus was exchanged to that of GluN2A, no significant asymmetries of GluN2B, GluA1 and PSD area were detected. We further discovered a previously unknown functional asymmetry of GluN2A, which was also lost in the swap mouse. These results demonstrate that GluN2B carboxy-terminus plays a critical role in normal formation of input-side dependent asymmetry.}, author = {Kleindienst, David}, issn = {2663-337X}, pages = {124}, publisher = {Institute of Science and Technology Austria}, title = {{2B or not 2B: Hippocampal asymmetries mediated by NMDA receptor subunit GluN2B C-terminus and high-throughput image analysis by Deep-Learning}}, doi = {10.15479/at:ista:9562}, year = {2021}, }