TY - THES AB - Algorithms in computational 3-manifold topology typically take a triangulation as an input and return topological information about the underlying 3-manifold. However, extracting the desired information from a triangulation (e.g., evaluating an invariant) is often computationally very expensive. In recent years this complexity barrier has been successfully tackled in some cases by importing ideas from the theory of parameterized algorithms into the realm of 3-manifolds. Various computationally hard problems were shown to be efficiently solvable for input triangulations that are sufficiently “tree-like.” In this thesis we focus on the key combinatorial parameter in the above context: we consider the treewidth of a compact, orientable 3-manifold, i.e., the smallest treewidth of the dual graph of any triangulation thereof. By building on the work of Scharlemann–Thompson and Scharlemann–Schultens–Saito on generalized Heegaard splittings, and on the work of Jaco–Rubinstein on layered triangulations, we establish quantitative relations between the treewidth and classical topological invariants of a 3-manifold. In particular, among other results, we show that the treewidth of a closed, orientable, irreducible, non-Haken 3-manifold is always within a constant factor of its Heegaard genus. AU - Huszár, Kristóf ID - 8032 SN - 2663-337X TI - Combinatorial width parameters for 3-dimensional manifolds ER - TY - THES AB - During bacterial cell division, the tubulin-homolog FtsZ forms a ring-like structure at the center of the cell. This so-called Z-ring acts as a scaffold recruiting several division-related proteins to mid-cell and plays a key role in distributing proteins at the division site, a feature driven by the treadmilling motion of FtsZ filaments around the septum. What regulates the architecture, dynamics and stability of the Z-ring is still poorly understood, but FtsZ-associated proteins (Zaps) are known to play an important role. Advances in fluorescence microscopy and in vitro reconstitution experiments have helped to shed light into some of the dynamic properties of these complex systems, but methods that allow to collect and analyze large quantitative data sets of the underlying polymer dynamics are still missing. Here, using an in vitro reconstitution approach, we studied how different Zaps affect FtsZ filament dynamics and organization into large-scale patterns, giving special emphasis to the role of the well-conserved protein ZapA. For this purpose, we use high-resolution fluorescence microscopy combined with novel image analysis workfows to study pattern organization and polymerization dynamics of active filaments. We quantified the influence of Zaps on FtsZ on three diferent spatial scales: the large-scale organization of the membrane-bound filament network, the underlying polymerization dynamics and the behavior of single molecules. We found that ZapA cooperatively increases the spatial order of the filament network, binds only transiently to FtsZ filaments and has no effect on filament length and treadmilling velocity. Our data provides a model for how FtsZ-associated proteins can increase the precision and stability of the bacterial cell division machinery in a switch-like manner, without compromising filament dynamics. Furthermore, we believe that our automated quantitative methods can be used to analyze a large variety of dynamic cytoskeletal systems, using standard time-lapse movies of homogeneously labeled proteins obtained from experiments in vitro or even inside the living cell. AU - Dos Santos Caldas, Paulo R ID - 8358 SN - 2663-337X TI - Organization and dynamics of treadmilling filaments in cytoskeletal networks of FtsZ and its crosslinkers ER - TY - THES AB - Designing and verifying concurrent programs is a notoriously challenging, time consuming, and error prone task, even for experts. This is due to the sheer number of possible interleavings of a concurrent program, all of which have to be tracked and accounted for in a formal proof. Inventing an inductive invariant that captures all interleavings of a low-level implementation is theoretically possible, but practically intractable. We develop a refinement-based verification framework that provides mechanisms to simplify proof construction by decomposing the verification task into smaller subtasks. In a first line of work, we present a foundation for refinement reasoning over structured concurrent programs. We introduce layered concurrent programs as a compact notation to represent multi-layer refinement proofs. A layered concurrent program specifies a sequence of connected concurrent programs, from most concrete to most abstract, such that common parts of different programs are written exactly once. Each program in this sequence is expressed as structured concurrent program, i.e., a program over (potentially recursive) procedures, imperative control flow, gated atomic actions, structured parallelism, and asynchronous concurrency. This is in contrast to existing refinement-based verifiers, which represent concurrent systems as flat transition relations. We present a powerful refinement proof rule that decomposes refinement checking over structured programs into modular verification conditions. Refinement checking is supported by a new form of modular, parameterized invariants, called yield invariants, and a linear permission system to enhance local reasoning. In a second line of work, we present two new reduction-based program transformations that target asynchronous programs. These transformations reduce the number of interleavings that need to be considered, thus reducing the complexity of invariants. Synchronization simplifies the verification of asynchronous programs by introducing the fiction, for proof purposes, that asynchronous operations complete synchronously. Synchronization summarizes an asynchronous computation as immediate atomic effect. Inductive sequentialization establishes sequential reductions that captures every behavior of the original program up to reordering of coarse-grained commutative actions. A sequential reduction of a concurrent program is easy to reason about since it corresponds to a simple execution of the program in an idealized synchronous environment, where processes act in a fixed order and at the same speed. Our approach is implemented the CIVL verifier, which has been successfully used for the verification of several complex concurrent programs. In our methodology, the overall correctness of a program is established piecemeal by focusing on the invariant required for each refinement step separately. While the programmer does the creative work of specifying the chain of programs and the inductive invariant justifying each link in the chain, the tool automatically constructs the verification conditions underlying each refinement step. AU - Kragl, Bernhard ID - 8332 SN - 2663-337X TI - Verifying concurrent programs: Refinement, synchronization, sequentialization ER - TY - THES AB - The oft-quoted dictum by Arthur Schawlow: ``A diatomic molecule has one atom too many'' has been disavowed. Inspired by the possibility to experimentally manipulate and enhance chemical reactivity in helium nanodroplets, we investigate the rotation of coupled cold molecules in the presence of a many-body environment. In this thesis, we introduce new variational approaches to quantum impurities and apply them to the Fröhlich polaron - a quasiparticle formed out of an electron (or other point-like impurity) in a polar medium, and to the angulon - a quasiparticle formed out of a rotating molecule in a bosonic bath. With this theoretical toolbox, we reveal the self-localization transition for the angulon quasiparticle. We show that, unlike for polarons, self-localization of angulons occurs at finite impurity-bath coupling already at the mean-field level. The transition is accompanied by the spherical-symmetry breaking of the angulon ground state and a discontinuity in the first derivative of the ground-state energy. Moreover, the type of symmetry breaking is dictated by the symmetry of the microscopic impurity-bath interaction, which leads to a number of distinct self-localized states. For the system containing multiple impurities, by analogy with the bipolaron, we introduce the biangulon quasiparticle describing two rotating molecules that align with respect to each other due to the effective attractive interaction mediated by the excitations of the bath. We study this system from the strong-coupling regime to the weak molecule-bath interaction regime. We show that the molecules tend to have a strong alignment in the ground state, the biangulon shows shifted angulon instabilities and an additional spectral instability, where resonant angular momentum transfer between the molecules and the bath takes place. Finally, we introduce a diagonalization scheme that allows us to describe the transition from two separated angulons to a biangulon as a function of the distance between the two molecules. AU - Li, Xiang ID - 8958 SN - 2663-337X TI - Rotation of coupled cold molecules in the presence of a many-body environment ER - TY - THES AB - Form versus function is a long-standing debate in various design-related fields, such as architecture as well as graphic and industrial design. A good design that balances form and function often requires considerable human effort and collaboration among experts from different professional fields. Computational design tools provide a new paradigm for designing functional objects. In computational design, form and function are represented as mathematical quantities, with the help of numerical and combinatorial algorithms, they can assist even novice users in designing versatile models that exhibit their desired functionality. This thesis presents three disparate research studies on the computational design of functional objects: The appearance of 3d print—we optimize the volumetric material distribution for faithfully replicating colored surface texture in 3d printing; the dynamic motion of mechanical structures— our design system helps the novice user to retarget various mechanical templates with different functionality to complex 3d shapes; and a more abstract functionality, multistability—our algorithm automatically generates models that exhibit multiple stable target poses. For each of these cases, our computational design tools not only ensure the functionality of the results but also permit the user aesthetic freedom over the form. Moreover, fabrication constraints were taken into account, which allow for the immediate creation of physical realization via 3D printing or laser cutting. AU - Zhang, Ran ID - 8386 SN - 2663-337X TI - Structure-aware computational design and its application to 3D printable volume scattering, mechanism, and multistability ER - TY - THES AB - Quantum computation enables the execution of algorithms that have exponential complexity. This might open the path towards the synthesis of new materials or medical drugs, optimization of transport or financial strategies etc., intractable on even the fastest classical computers. A quantum computer consists of interconnected two level quantum systems, called qubits, that satisfy DiVincezo’s criteria. Worldwide, there are ongoing efforts to find the qubit architecture which will unite quantum error correction compatible single and two qubit fidelities, long distance qubit to qubit coupling and calability. Superconducting qubits have gone the furthest in this race, demonstrating an algorithm running on 53 coupled qubits, but still the fidelities are not even close to those required for realizing a single logical qubit. emiconductor qubits offer extremely good characteristics, but they are currently investigated across different platforms. Uniting those good characteristics into a single platform might be a big step towards the quantum computer realization. Here we describe the implementation of a hole spin qubit hosted in a Ge hut wire double quantum dot. The high and tunable spin-orbit coupling together with a heavy hole state character is expected to allow fast spin manipulation and long coherence times. Furthermore large lever arms, for hut wire devices, should allow good coupling to superconducting resonators enabling efficient long distance spin to spin coupling and a sensitive gate reflectometry spin readout. The developed cryogenic setup (printed circuit board sample holders, filtering, high-frequency wiring) enabled us to perform low temperature spin dynamics experiments. Indeed, we measured the fastest single spin qubit Rabi frequencies reported so far, reaching 140 MHz, while the dephasing times of 130 ns oppose the long decoherence predictions. In order to further investigate this, a double quantum dot gate was connected directly to a lumped element resonator which enabled gate reflectometry readout. The vanishing inter-dot transition signal, for increasing external magnetic field, revealed the spin nature of the measured quantity. AU - Kukucka, Josip ID - 7996 SN - 2663-337X TI - Implementation of a hole spin qubit in Ge hut wires and dispersive spin sensing ER - TY - THES AB - Deep neural networks have established a new standard for data-dependent feature extraction pipelines in the Computer Vision literature. Despite their remarkable performance in the standard supervised learning scenario, i.e. when models are trained with labeled data and tested on samples that follow a similar distribution, neural networks have been shown to struggle with more advanced generalization abilities, such as transferring knowledge across visually different domains, or generalizing to new unseen combinations of known concepts. In this thesis we argue that, in contrast to the usual black-box behavior of neural networks, leveraging more structured internal representations is a promising direction for tackling such problems. In particular, we focus on two forms of structure. First, we tackle modularity: We show that (i) compositional architectures are a natural tool for modeling reasoning tasks, in that they efficiently capture their combinatorial nature, which is key for generalizing beyond the compositions seen during training. We investigate how to to learn such models, both formally and experimentally, for the task of abstract visual reasoning. Then, we show that (ii) in some settings, modularity allows us to efficiently break down complex tasks into smaller, easier, modules, thereby improving computational efficiency; We study this behavior in the context of generative models for colorization, as well as for small objects detection. Secondly, we investigate the inherently layered structure of representations learned by neural networks, and analyze its role in the context of transfer learning and domain adaptation across visually dissimilar domains. AU - Royer, Amélie ID - 8390 SN - 2663-337X TI - Leveraging structure in Computer Vision tasks for flexible Deep Learning models ER - TY - THES AB - In this thesis we study certain mathematical aspects of evolution. The two primary forces that drive an evolutionary process are mutation and selection. Mutation generates new variants in a population. Selection chooses among the variants depending on the reproductive rates of individuals. Evolutionary processes are intrinsically random – a new mutation that is initially present in the population at low frequency can go extinct, even if it confers a reproductive advantage. The overall rate of evolution is largely determined by two quantities: the probability that an invading advantageous mutation spreads through the population (called fixation probability) and the time until it does so (called fixation time). Both those quantities crucially depend not only on the strength of the invading mutation but also on the population structure. In this thesis, we aim to understand how the underlying population structure affects the overall rate of evolution. Specifically, we study population structures that increase the fixation probability of advantageous mutants (called amplifiers of selection). Broadly speaking, our results are of three different types: We present various strong amplifiers, we identify regimes under which only limited amplification is feasible, and we propose population structures that provide different tradeoffs between high fixation probability and short fixation time. AU - Tkadlec, Josef ID - 7196 TI - A role of graphs in evolutionary processes ER - TY - THES AB - We present solutions to several problems originating from geometry and discrete mathematics: existence of equipartitions, maps without Tverberg multiple points, and inscribing quadrilaterals. Equivariant obstruction theory is the natural topological approach to these type of questions. However, for the specific problems we consider it had yielded only partial or no results. We get our results by complementing equivariant obstruction theory with other techniques from topology and geometry. AU - Avvakumov, Sergey ID - 8156 SN - 2663-337X TI - Topological methods in geometry and discrete mathematics ER - TY - THES AB - Fabrication of curved shells plays an important role in modern design, industry, and science. Among their remarkable properties are, for example, aesthetics of organic shapes, ability to evenly distribute loads, or efficient flow separation. They find applications across vast length scales ranging from sky-scraper architecture to microscopic devices. But, at the same time, the design of curved shells and their manufacturing process pose a variety of challenges. In this thesis, they are addressed from several perspectives. In particular, this thesis presents approaches based on the transformation of initially flat sheets into the target curved surfaces. This involves problems of interactive design of shells with nontrivial mechanical constraints, inverse design of complex structural materials, and data-driven modeling of delicate and time-dependent physical properties. At the same time, two newly-developed self-morphing mechanisms targeting flat-to-curved transformation are presented. In architecture, doubly curved surfaces can be realized as cold bent glass panelizations. Originally flat glass panels are bent into frames and remain stressed. This is a cost-efficient fabrication approach compared to hot bending, when glass panels are shaped plastically. However such constructions are prone to breaking during bending, and it is highly nontrivial to navigate the design space, keeping the panels fabricable and aesthetically pleasing at the same time. We introduce an interactive design system for cold bent glass façades, while previously even offline optimization for such scenarios has not been sufficiently developed. Our method is based on a deep learning approach providing quick and high precision estimation of glass panel shape and stress while handling the shape multimodality. Fabrication of smaller objects of scales below 1 m, can also greatly benefit from shaping originally flat sheets. In this respect, we designed new self-morphing shell mechanisms transforming from an initial flat state to a doubly curved state with high precision and detail. Our so-called CurveUps demonstrate the encodement of the geometric information into the shell. Furthermore, we explored the frontiers of programmable materials and showed how temporal information can additionally be encoded into a flat shell. This allows prescribing deformation sequences for doubly curved surfaces and, thus, facilitates self-collision avoidance enabling complex shapes and functionalities otherwise impossible. Both of these methods include inverse design tools keeping the user in the design loop. AU - Guseinov, Ruslan ID - 8366 KW - computer-aided design KW - shape modeling KW - self-morphing KW - mechanical engineering SN - 2663-337X TI - Computational design of curved thin shells: From glass façades to programmable matter ER -