In this thesis we present an experimental realisation of a double loop type Magnetic Paul Trap. We show that a microgram heavy NdFeB permanent magnet can stably be levitated for hours at room...Show moreIn this thesis we present an experimental realisation of a double loop type Magnetic Paul Trap. We show that a microgram heavy NdFeB permanent magnet can stably be levitated for hours at room temperature in this trap. Magnetic levitation of a magnetized particle is theoretically possible with this trap by generating opposed alternating magnetic fields. We show the fabrication of a printed circuit structure capable of producing these fields, as well as the engineering behind the realisation of the trap. Both by optical and magnetic readout we characterize the motion of the trapped magnet and show that its center of mass motion frequencies $\omega_z = 2\omega_{x,y} \approx 20Hz$. We characterize the damping on these modes and find that at low pressure the quality factor is strongly limited (to $Q \approx 90$) by coupling to the environment through generation of Eddy currents.Show less
In the pursuit of designing complex materials with desired properties, un- derstanding their design parameter space is crucial. However, this space’s convolution often hinders comprehension of...Show moreIn the pursuit of designing complex materials with desired properties, un- derstanding their design parameter space is crucial. However, this space’s convolution often hinders comprehension of complex materials’ responses as a function of their design parameters. Machine Learning has recently emerged as a promising tool for capturing patterns in complex design spaces, although this performance often comes at the cost of interpretabil- ity. This thesis aims to explore the design parameter space of interact- ing hysterons using interpretable Machine Learning, specifically Decision Tree inspired methods. Despite the complexity of the design parameter space of even small systems of interacting hysterons, interpretable Ma- chine Learning can classify coarse-grained properties of the system effec- tively. Introducing the Support Vector Classifier (SVC) inspired Decision Tree, we achieve almost perfect isolation of these properties. This model preserves interpretability while effectively probing the statistical structure of design parameter space of systems of interacting hysterons.Show less
This project employs reinforcement learning techniques to explore novel decoding strategies for quantum error correction, particularly focusing on the toric code, to address the challenge of...Show moreThis project employs reinforcement learning techniques to explore novel decoding strategies for quantum error correction, particularly focusing on the toric code, to address the challenge of maintaining stable quantum states for fault-tolerant quantum computing. Two game frameworks are established, including a novel dynamic game framework applicable to the training and measuring of RL agents and potential application in multiagent scenarios. The RL agents use Stable Baselines 3’s Proximal Policy Optimization and show to achieve Minimum Weight Perfect Matching performance on 3 × 3 toric code lattices in both the static and dynamic game frameworks.Show less
The intergalactic medium (IGM) contains most of the baryonic matter of the Universe and serves as a suitable environment for probing the thermal history of the Universe. The crucial moment in IGM...Show moreThe intergalactic medium (IGM) contains most of the baryonic matter of the Universe and serves as a suitable environment for probing the thermal history of the Universe. The crucial moment in IGM evolution is the Epoch of Reionization, corresponding to the transition from neutral to ionized IGM. However, due to the observational limitations, this period is still not well understood. In this thesis, we focus on constraining IGM thermal history by using Lyman-alpha forests data. This method is applicable in a wide range of temperatures, densities, and ionization fractions of cosmic gas at z about 2 − 5. Observations show that the longitudinal flux power spectrum of the Lyman-α forest exhibits a cut-off at small scales. This phenomenon is caused by thermal Doppler broadening, peculiar velocities along the line of sight (LOS), Hydrogen pressure smoothing, and warm dark matter. The first two effects act only along LOS, while the last two affect all spatial directions. To separate the one-dimensional and three-dimensional effects, we used the method of close quasar pairs, which is based on studying the correlations between Lyman-alpha forests of close quasar pairs. We used the Kolmogorov-Smirnov test to analyze the differences between distributions of phase difference, which characterizes correlations between Lyman-alpha forests. The calculations were performed for various thermal histories, parameters characterizing IGM, LOS separations, and wavenumbers, and accounting for different effects (Doppler broadening and peculiar velocities). Our results indicate that this method can distinguish various thermal histories regardless of the IGM thermal state and one-dimensional effects. Moreover, at separations of the order of pressure broadening, there is a prominent feature caused by different influences of pressure smoothing at large and small scales. In addition, this simple and powerful approach has the potential to distinguish scenarios with warm dark matter.Show less
One of the greatest remaining puzzles in physics is what particle dark matter consists of. For this project, the theory of dark pions is considered, a Hidden Valley model that extends the Standard...Show moreOne of the greatest remaining puzzles in physics is what particle dark matter consists of. For this project, the theory of dark pions is considered, a Hidden Valley model that extends the Standard Model with new, dark particles and a new force, dark QCD. A sensitivity study is performed to determine how many dark pions are expected to be in acceptance of the LHCb detector for Run 2 conditions; the LHCb is well-suited to search for particles in the considered O(1) GeV mass and O(1) - O(100) ps lifetime range. Additionally, a framework has been developed to study the dependence of the sensitivity on a number of theoretical parameters of the dark QCD model, namely the probability to form a dark vector meson instead of a dark pion, the number of colours in dark QCD, the dark QCD scale, and the Higgs mass. It is found that O(100) dark pions are in LHCb acceptance for different track categories, and that the considered the- oretical parameters do not drastically change the number of expected particles (with some small caveats), staying within a difference of about 20%. This is acceptable given the expected experimental uncertainty, showing theory inde- pendent searches for dark pions are possible.Show less
Cancer metastasis remains a critical area of study within the field of cancer research. The tumor microenvironment (TME), comprising various cell types and the extracellular matrix (ECM), plays a...Show moreCancer metastasis remains a critical area of study within the field of cancer research. The tumor microenvironment (TME), comprising various cell types and the extracellular matrix (ECM), plays a pivotal role in controlling tumor initiation and progression. Here we show an investigation into the mechanical phenotype of Hs 578T breast cancer cells within the TME, focusing particularly on the role of cell-ECM interactions in modulating cellular traction forces. Hs 578T cells with an integrin- α2 (ITGA2) stable knockout were utilized, and the resulting pressures were compared between the control and knockout at different collagen concentrations. Attention is hence given to the ITGA2 and its role in mediating cell-ECM interactions. Through the utilization of elastic hydrogel microparticles as localized stress sensors and advanced microscopy techniques, we show that increasing the collagen concentration results in increased traction forces exerted by control breast cancer cells. Conversely, the traction forces by ITGA2 Hs 578T knockout cells remain unaffected by changes in collagen concentration. Also, a linear relationship between the traction and its standard deviation, regardless of the Hs 578T cell type and collagen concentration, is observed. The findings contribute to a deeper understanding of cancer biomechanics, offering insights into potential therapeutic targets for inhibiting metastatic spread in breast cancer.Show less
One of the best constraints on the warmness of the dark matter comes from the Lyman-$\alpha$ forest observations. Warm dark matter (WDM) free streaming smooths out the smallest structures; in the...Show moreOne of the best constraints on the warmness of the dark matter comes from the Lyman-$\alpha$ forest observations. Warm dark matter (WDM) free streaming smooths out the smallest structures; in the Lyman-$\alpha$ flux power spectrum, this creates a lack of power at such scales. However, different astrophysical effects can create a similar picture. For example, thermodynamic pressure does not allow baryons to collapse into small dark matter structures, making them look larger. Recent high-resolution measurements shifted the source of uncertainty from data statistics to modeling systematics, emphasizing the degeneracy between WDM free streaming and astrophysical effects. In this work, we present a semi-analytical approach to model the pressure effect and WDM free streaming on the Lyman-$\alpha$ flux power spectrum to better study the degeneracy between them. We use the theory developed for the 3D matter power spectrum and show how to apply it to the flux power spectrum. We get an excellent agreement between our modeling and SPH simulations for a wide range of thermal histories, dark matter masses, and redshifts. Finally, using our semi-analytical approach, we show how to constrain the warmness of dark matter, taking into account degeneracy with the pressure effect. We get the following constraint, directly confirmed by running a simulation $m_\mathrm{WDM}\geq\qty{3}{keV}.$Show less
In this thesis the relative spectral energy density of stochastic primordial gravitational waves is investigated. Decoupling of Standard Model particles and neutrino free-streaming affect the...Show moreIn this thesis the relative spectral energy density of stochastic primordial gravitational waves is investigated. Decoupling of Standard Model particles and neutrino free-streaming affect the expansion history of the universe and thus leave characteristic signatures on the amplitude of the gravitational wave spectrum. Adding extra light or heavy particles damps the spectrum at frequencies before the particle decouples. Including an extra neutrino species amplifies the spectrum at larger wave numbers, but damps it at shorter wave numbers. Measuring these primordial gravitational waves reveals the thermal history of the universe. One possible non-standard thermal history is early matter domination due to the inflaton. It is shown that, in this cosmology, the end of early matter domination and beginning of the radiation era depend linearly on the reheating temperature.Show less
In this research, a quantum and classical version of a value-based reinforcement learning method are compared to each other. This is done by training each of them to try and learn how to play a...Show moreIn this research, a quantum and classical version of a value-based reinforcement learning method are compared to each other. This is done by training each of them to try and learn how to play a simple game called Fox in a hole. The two models are compared to each other based on performance, training stability, convergence speed, and amount of trainable parameters. After hyperparameter tuning and further experimentation of the models, no clear difference is found between their performances and training stabilities. Nonetheless, the quantum model does seem to converge slower as the dimensionality of the game grows, and it also seems to require longer computation times than the classical model to keep up with its performance. Thus, the results suggest that for the task at hand, a classical value-based RL method is preferred over a quantum version of it.Show less
In this research the seasonal variation of the atmospheric muon rate at the KM3NeT/ARCA detector was studied in order to determine the temperature correlation coefficient αT. KM3NeT is a cubic...Show moreIn this research the seasonal variation of the atmospheric muon rate at the KM3NeT/ARCA detector was studied in order to determine the temperature correlation coefficient αT. KM3NeT is a cubic kilometer neutrino telescope consisting of two large volume water-Cherenkov detectors, ARCA and ORCA, located in the Mediterranean sea. The Cherenkov radiation emitted from high energy muons traveling through the seawater gets detected by an assembly of 31 Photo-multiplier tubes situated inside a sphere shaped Digital Optical Module (DOM). 18 of such DOMs are connected to form a Detection Unit (DU). For the ARCA detector, these DUs are located at the seafloor at around 3.5 km depth, extending vertically to about 2.7 km below sea level. Taking advantage of correlations between hits registered at different PMTs within a DOM, a measurement of the atmospheric muon rate at each DOM can be determined. Furthermore, the difference in height of the DOMs in each DU enables the utilization of the depth dependence of atmospheric muons to precisely determine the muon rate at the ARCA detector. This makes it possible to detect rate variations of a few percent. Additionally, the effective temperature is determined through a weighted integral of the available temperature data above the geographic location of the ARCA detector. Comparing the atmospheric muon rate and the effective temperature during the data taking period of 26.09.2021 until 1.06.2022 a temperature correlation of αT = 1.166 ± 0.128 was established. This is slightly above the theoretically predicted value of 0.86. To verify the robustness of the proposed method of determining the rate and temperature correlation, cross checks were done with Monte Carlo files, background signals and the examination of the depth relationship with time. All returned the expected results. However, when the same method was employed on a smaller data set covering the data taking period between 12.05.2021 and 2.09.2021, no significant correlation between the atmospheric muon rate and the effective temperature could be established. Furthermore, the performed cross checks on this data set did not confirm expectations. This is most likely due to the small data set which is not able to accurately capture the long term seasonal effect. However these results should not be neglected. Therefore, while the employed method did return promising results for a larger set of data, more investigation into the efficiency determination and the errors on the fitted slope are needed to confidently verify the reliability of the final result. It is further suggested to revisit this study once a consistent data set of minimally one year is available.Show less
Dissipation will be introduced in to the Extended Dicke Model (EDM) using the Lindblad equation. Equations of motion and their associated fixed points will be derived using a semi-classical...Show moreDissipation will be introduced in to the Extended Dicke Model (EDM) using the Lindblad equation. Equations of motion and their associated fixed points will be derived using a semi-classical approximation. Total spin of the system will be shown to be a non-conserved quantity. It will be shown that in the Bound Luminosity State the dissipative system can be described by an EOM solely dependent on the y-component of the spin.Show less
Metamaterials feature specific properties that are not commonly found in nature. An example of such a property is input sequence sensitivity, or non-Abelian behavior. Here, we study the driving...Show moreMetamaterials feature specific properties that are not commonly found in nature. An example of such a property is input sequence sensitivity, or non-Abelian behavior. Here, we study the driving sequence dependent response of a non-Abelian metamaterial with four inputs. In previous research, these inputs were actuated with equal strength. However, in this thesis we take a novel approach by first pre-stressing the metamaterial by actuating one beam with a certain strength, and then sequentially actuating and deactuating another pair of beams using a different actuation strength. This allows us to "program" the non-Abelian response by using pre-stress. We explore this two-dimensional actuation space experimentally, and collect the ensuing behavior in a "phase diagram". We find that pre-stressing allows more complex sequential responses than without pre-stressing. In particular, pre-stressing can change the response to sequential actuation from non-Abelian to Abelian and vice-versa. Our work thus uncovers a viable strategy for externally tunable, or programmable, non-Abelian behavior.Show less
Learning curves are important for decision making in supervised machine learning. They show how the performance of a machine learning model develops over a given resource. In this work, we consider...Show moreLearning curves are important for decision making in supervised machine learning. They show how the performance of a machine learning model develops over a given resource. In this work, we consider learning curves that model the performance of a machine learning model as a function of the number of data points used for training. For decision making, it is of- ten useful to extrapolate learning curves, which can be done, for example, by fitting a parametric model based on the observed values, or by using an extrapolation model trained on learning curves from similar datasets. We perform an analysis comparing these two techniques with different ob- servations and prediction objectives. When only a small number of initial segments of the learning curve have been observed we find that it is better to rely on learning curves from similar datasets. Once more observations have been made, a parametric model, or just the last observation, should be used. Moreover, we find that using a parametric model is mostly use- ful when the exact value of the learning curve itself is of interest. Lastly, we use this knowledge to improve machine learning on a particle physics dataset.Show less
Superchirality is a property of light with not yet fully discovered future possibilities in industry and research. In this research, an attempt to obtain a bright superchiral lattice is made by...Show moreSuperchirality is a property of light with not yet fully discovered future possibilities in industry and research. In this research, an attempt to obtain a bright superchiral lattice is made by superposing four laser beams in a particular configuration. Additionally, this superposition should theoretically lead to homogeneous electric fields without modulation, which is potentially useful in microscopy. Recording the field with a simple CMOS camera and observing its fast Fourier transform gives rise to aliasing effects due to undersampling caused by the fact that interference occurs at a subpixel level. This phenomenon is investigated by numeric and analytic simulations. By rotation of the camera, pixel superresolution was achieved, which effectively enables the possibility to investigate the interference patterns at a subpixel level and hence measure the angle between pair of beams with good accuracy. With newly developed beam alignment methods we have achieved and confirmed a beam alignment that is sufficient for production of bright superchirality lattices.Show less
Understanding the early formation of attitudes towards emerging technologies, such as quantum science & technology (QS&T), is essential for aligning the effect of science communication in...Show moreUnderstanding the early formation of attitudes towards emerging technologies, such as quantum science & technology (QS&T), is essential for aligning the effect of science communication in practice with its intentions. This study explores the application of natural language processing (NLP) techniques to investigate the influence of news articles on social media comments regarding QS&T. We curated a dataset of 217 articles and 14, 391 top-level comments from Reddit. Employing GPT-4, a semi-automated annotation method was developed to label comments for sentiment and engagement towards QS&T, achieving a Cohen’s kappa of 0.82 when pooling over multiple labelling repetitions and comparing with human annotations. We then used support-vector regression to determine if news article embeddings could be used to predict comment sentiment and engagement. After experimenting with various embedding strategies, including Sentence-BERT and RoBERTa models, no significant correlations were found between article content and comment sentiment or engagement towards QS&T. Further interdisciplinary work in empirical communication research and NLP is suggested to explore alternative representations for news articles and their ability to predict perceptions in news comments.Show less
The past decades have shown a rise in skin cancer. This creates the need for prevention and efficient treatment. The most common skin cancer (melanoma) can only be treated when detected early. In...Show moreThe past decades have shown a rise in skin cancer. This creates the need for prevention and efficient treatment. The most common skin cancer (melanoma) can only be treated when detected early. In this thesis we propose a method of increasing awareness for people with a high risk of skin cancer as well as allowing for early detection. Skin cancer is hard to detect, even for experiences healthcare professionals. One of the signals of potential harm full lesions is change over time. We propose to develop an application with which changes in skin lesions can be identified early. By allowing patients to film their body with a mobile phone camera we aim to track the development of lesions. If a patient films their body regularly changes can be detected and the application can urge the patient to consult a dermatologist. In this thesis we explore the possibility of combining the frames of these films into an overview displaying the patients complete back or arm. Combining frames is called stitching. Different stitching techniques found in literature are explored and tested for effectiveness. The optimizations performed are reported and the final result is presented. The location of the different lesions on an overview of the body is needed to show the patient and the healthcare professional where potential harmful lesions are located on the body. This allows for further inspection at the dermatology department.Show less
Supernovae are powerful cosmic explosions that usually occur within their host galaxies. However, recent observations have discovered a small but growing number of supernovae located outside of...Show moreSupernovae are powerful cosmic explosions that usually occur within their host galaxies. However, recent observations have discovered a small but growing number of supernovae located outside of their host galaxies, known as orphan supernovae. This thesis project aims to investigate these peculiar events and their host environments to gain insights into the mechanisms that drive them. The objectives include analyzing a large sample of supernovae and determining if we actually observe a population of orphan supernovae. The methodology involves data analysis and theoretical modeling, utilizing public catalogs, archival data, and wide-field surveys.Show less
