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https://odr.chalmers.se/handle/20.500.12380/35

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Non-Supersymmetric AdS Solutions in Type IIB String Theory
(2023) Wikström, Johan; Chalmers tekniska högskola / Institutionen för fysik; Chalmers University of Technology / Department of Physics; E.W. Nilsson, Bengt
The task of finding a satisfactory theory of quantum gravity has turned out to be extremely challenging. In the context of string theory, which is a potential frame work of quantum gravity, this problem is represented by the vast number of possible string compactifications. The swampland program is an effort to sort through these possibilities and define what makes some theories of quantum gravity inconsistent. The result is a number of so-called swampland conjectures. This thesis studies an AdS vacuum in type IIB string theory that is relevant to one of these conjectures. It is explicitly shown that this vacuum, which is an S-fold of the form AdS4 × S 1 × S 5 , satisfies the type IIB equations of motion. The S-fold originates from uplifting a non-compact gauging of the 4-dimensional N = 8 supergravity. A more simple case illustrating non-compact gaugings, related to the gauge group SO(8), is treated here. Also discussed is the topology of the S-fold, which features a non-trivial SL(2, Z) monodromy when the S 1 is encircled, making the background non-geometric. The connection to the swampland program appears when a 2-parameter deformation of the AdS vacuum is used to break supersymmetry. Locally, these deformations only amount to a coordinate redefinition, which protects the vacuum solution from some non-perturbative decay channels. As the non-supersymmetric S-folds are also perturbatively stable, they have been suggested as a potential challenge to the Non SUSY AdS conjecture. However, more evidence of non-perturbative stability is likely needed to make a solid case for non-supersymmetric AdS vacua in quantum gravity.
Machine Learning Assisted Quantum Error Correction Using Scalable Neural Network Decoders
(2023) Havstöm, Pontus; Heuts, Olivia; Chalmers tekniska högskola / Institutionen för fysik; Chalmers University of Technology / Department of Physics; Granath, Mats
A necessary condition for fault-tolerant quantum computers is the implementation of quantum error correction, as the sensitive nature of quantum technology causes unavoidable errors on qubits. Topological stabilizer codes, such as the surface code and its variations, are promising candidates for near term implementations of quan tum error correcting codes. In surface codes, multiple physical qubits are encoded to represent a single logical qubit with a higher tolerance for errors than the indi vidual physical qubits. Errors on data qubits cannot be measured directly, and have to be corrected based on incomplete observations of the system from ancilla qubit measurement syndromes. Classical algorithms called decoders are used to determine correction operators based on the syndromes, which is a non-trivial and computa tionally expensive task. In practice, the error decoding must be fast, and as such it is of interest to develop decoders that rapidly determine correction operations while still remaining sufficiently accurate. Decoders based on neural networks have been shown to yield high decoding accuracy for small distance surface codes, while also having fast decoding time once trained. Many such decoders are however not necessarily scalable and have been designed for a specific code size. In this thesis, we develop two types of neural network based decoders using the deep learning architectures Graph Neural Networks (GNN) and Convolutional Neural Networks (CNN), both of which in principle allow for decoding arbitrarily large codes. We apply the decoders to the rotated surface code under depolarizing noise with perfect syndrome measurements, and evaluate their performance based on their accuracy, computational speed and scalability to large code distances. We show that the the decoders perform on par with the commonly used Minimum Weight Perfect Matching (MWPM) decoder at small codes and low physical error rates, with the CNN decoder outperforming the MWPM decoder for code distance d = 7. We also find that using a sparse graph representation of syndromes yields a favorable computational complexity for the GNN decoder on large-distance codes.
Entropies of weakly adsorbed molecules beyond the harmonic approximation
(2023) Cronquist, Olof; Chalmers tekniska högskola / Institutionen för fysik; Chalmers University of Technology / Department of Physics; Grönbeck, Henrik; Grönbeck, Henrik
Adsorption processes and reaction kinetics are described by the free energy. While the enthalpy contribution to the free energy can be evaluated with reasonable accuracy thanks to the developments of density functional theory (DFT), methods to accurately describe the entropy contributions are in many cases missing. One important example is adsorption in zeolites where some adsorbates are physisorbed, which is a state where the common harmonic approximation, as well as more sophisticated methods, can not accurately describe the entropy. Zeolites are crystalline microporous materials and have many applications, for example as catalysts. An important catalytic reaction over a zeolite material is selective catalytic reduction of NOx with ammonia as reducing agent (NH3-SCR). In this thesis, the entropy of species related to the NH3-SCR reaction is explored using two different methods, namely Complete Potential Energy Sampling (CPES) and Thermodynamic Integration (TI). Both methods rely on potential energy surfaces that are obtained with DFT calculations. In CPES, the full multidimensional potential energy surface is sampled by, for example, metadynamics. In TI, the starting point is the harmonic reference system to which calculates anharmonic corrections to the free energy are evaluated. Successful implementation of each method was demonstrated by reproducing results from previous works. When applicable, entropies were compared to experimental data, where only CPES showed to be in good agreement. However, free energy is the primary result of TI and our results are in good agreement with experimental data for the free energy and it is uncertain whether the entropy extraction, underlying method, or simulation setup is the culprit of TI. The results presented in the thesis increase the general understanding of entropies of weakly adsorbed molecules and, in particular, the understanding of entropy changes along the NH3-SCR reaction.
Detecting and Tracking Regions of Interest for Remote Measurement of Vital Parameters
(2022) Müller, Madeleine; Chalmers tekniska högskola / Institutionen för fysik; Chalmers University of Technology / Department of Physics; Forssen, Christian; Garcia Lozano, Marianela
The initial assessment of a mass casualty incident is essential to effectively conduct a rescue operation. The survival rate is affected by the complexity of the incident, and it is therefore imperative to enhance the operational capacities of emergency medical services and civil protection agencies in mass casualty incidents. This thesis investigates the possibilities for an unmanned aerial vehicle (UAV) to detect and track regions of interest for remote measurement of vital parameters in visual and thermal footage for first response triage purposes. The regions of interest are the nose, mouth, and chest, and the UAV characteristic taken under consideration in this thesis is image blur due to random camera motion. In this thesis, we take an object detection approach and implement the keypoint estimation framework KAPAO and the tracking algorithm SORT in several different experimental setups. Using KAPAO and SORT, we achieve a good result. For the detection in the thermal domain, the model created by transferring knowledge from the visual to the thermal domain achieves the highest performance. We also consider adversarial training on random motion blur, however the result shows a minimal impact on the model performance in the presence of characteristic low-altitude UAV motion blur. Regarding the tracking of the regions of interest, the result concludes that the SORT algorithm improves the performance compared to assigning tracking identification numbers based on frame-to-frame differences. The result shows that the distance to the subjects and the image quality impacts the performance. Compared with previous work on remote measurement of vital parameters, the algorithms of this thesis achieve a nearly perfect score on corresponding distances. If the distances are realizable in a UAV triage application is however unknown and has to be investigated further. Moreover, the work of this thesis problematizes the low-altitude UAV motion blur which poses a potential limitation in a potential UAV triage application. An alternative could hence be to use optical stabilization measurement for blur reduction.
High energy lithium-ion battery characterisation and overcharge abuse test
(2022) PATIL, AKHILESH SATISH; Chalmers tekniska högskola / Institutionen för fysik; Chalmers University of Technology / Department of Physics; Mellander, Bengt-Erik; Furlani, Maurizio
Batteries are finding extensive applications in different domains. Lithium-ion batteries are one of the most interesting kinds. They are used in most of the portable electronic equip ment, small and large appliances, electrical energy storage system and electric vehicles due to their high power and high energy densities. Nevertheless lithium-ion technology has its own dangers due to presence of highly volatile and flammable materials. These properties can lead to emissions of gas from the cell package, further leading to thermal runaway and toxic gas emissions. Many researches have reported that gas emissions in clude highly detrimental gases like hydrogen fluoride (HF), carbon monoxide (CO) as well as phosphoryl fluoride (POF3). The lithium-ion cell construction involves graphite based anode metal oxide cathode and a liquid electrolyte with high lithium ion mobility. Due to high electrochemical reactivity and mechanical degradation under different operative conditions, the battery will eventu ally lead to decreased performance. Cathodic materials limit the energy density and are the primary reason for the battery cost. Those materials being Nickel (Ni), Manganese (Mn) and Cobalt (Co) with lithium intercalating oxides. The different proportion of these metals can influence the performance levels in the batteries. In this thesis, a number of methods have been used to characterize prismatic lithium-ion battery cells. The investigation has included analysis of the disassembled cell components using: thermal analysis for the separator material, X-ray diffraction (XRD) for electrode materials and Fourier transform infrared spectroscopy (FTIR) for liquid electrolyte anal ysis, gas analysis, as well as electrical measurements such as impedance, charge and dis charge tests on the complete cell. Overcharge abuse tests have been performed to further investigate cell safety by analysing gas emissions using gas sensors, FTIR and physical parameters such as temperature across the thermal runaway in a cell fault scenario.

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