When a nuclear explosion occurs certain radionuclides are emitted, notably xenon. Due to the fact that xenon is a noble gas, it is hard to contain and can therefore be detected far from the explosion site. There are four isotopes of xenon that are of interest in the detection of a nuclear explosion: 131mXe, 133mXe, 133Xe and 135Xe. By constantly measuring the amount of these isotopes in the air, changes in the concentration in an indication that a nuclear explosion has occurred. In this thesis a detector was modelled in GEANT4 and focuses on one kind of noble gas detector: SAUNA - the Swedish Automatic Unit for Noble gas Acquisition. SAUNA uses the coincidence technique in order to determine the concentration of xenon there is in the air. By using the coincidence technique, it is possible to reduce the impact of the background radiation and therefore increase the efficiency of the detector. 133Xe has a coincidence when it first undergoes beta decay, with an endpoint energy of 346 keV, and then emits a 80 keV gamma particle. 135Xe has also a dual coincidence, a beta decay with an endpoint energy of 910 keV together with a 250 keV gamma-ray. However both these isotopes have a triple coincidence decay that also can be exploited: for 133Xe, a beta particle with endpoint energy of 346 keV, a 30 keV X-ray and a 45 keV conversion electron, while for 135Xe there is instead of the gamma particle a 30 keV X-ray and a 214keV conversion electron that can be emitted together with the beta particle. The 30 keV X-ray together with the beta particle for 133Xe can also be used as a dual coincidence, in that case the conversion electron is ignored. For 133Xe, when a beta particle, a 45 keV conversion electron, and a 30 keV X-ray are emitted, the model was able to detect all three particles in 69.2% ± 0.1 of the cases. However, when only the particles with a detected energy within a 5 keV interval of their generated energies are considered to be in coincidence, then for 133Xe triple coincidence occurs in 22.9% ± 0.2 of the cases. For 135Xe the model was able to detect the triple coincidence (between a beta, 214 keV CE and 30 keV X-ray) in 63.5% ± 0.1 of the cases. This work shows that adding another particle in a coincidence reduces the chance to detect the coincidence. The positive effect of adding another particle in a coincidence is that the minimum detectable concentration of xenon should be smaller. The goal for future detectors should be to make it possible for the detector to take advantage of the triple coincidences but at the same time be also able to use the dual coincidences.

One of the major challenges hindering advancement of quantum computing is the sensitive nature of the physical systems used to build a quantum computer. One suggestion for improving reliability is a particular type of logic gates, based on Berry's geometric phase, showing improved robustness to external disturbance of the quantum system over the course of a calculation. Such logic gates have previously been shown for the smallest possible two-level qubits. Using the method of adiabatic shortcut we endevour to discover similarly realistic and robust logic gates for units of quantum information in higher dimensions. The example shown in this paper discusses three-level qutrits, but is expected to apply to theoretically unlimited higher dimensions since new geometric complications are expected to arise primarily when moving from a two-level to a multi-level problem.  We here present a set of primitive single-qutrit gates able to perform universal quantum computations if supplemented by a two-qutrit gate. We also present a set of condensed single-qutrit gates for commonly needed operations. By detailing the underlying mathematical framework, relying on the multi-dimensional generalisation of Berry's phase describing the time evolution of degenerate quantum states, we also suggest an easily scalable geometric interpretation of quantum gates in higher dimensions along with visual representation of logic gates using parameters of the physical system to sequentially unlock and manipulate subspaces of the quantum information unit.

The prime objectives of contrast agents in Magnetic Resonance Imaging(MRI) is to accelerate the relaxation rate of the solvent water protons in the surrounding tissue. Paramagnetic relaxation originates from dipole-dipole interactions between the nuclear spins and the fluctuating magnetic field induced by unpaired electrons. Currently Gadolinium(III) chelates are the most widely used contrast agents in MRI, and therefore it is incumbent to extend the fundamental theoretical understanding of parameters that drive the relaxation mechanism in these complexes. Traditionally the Solomon-Bloembergen-Morgan equations have been utilized to describe relaxation times in terms, primarily of the Zeeman interaction, which is the splitting of degenerate energy levels due to an applied magnetic field. However, in compounds such as Gadolinium(III) complexes with total electron spins higher than 1 (in this case S=7/2) other interactions such as the Zero-Field Splitting(ZFS) play a significant role. ZFS is the splitting of degenerate energy levels in the absence of an external magnetic field. For this purpose, the current research delves into an understanding of the relaxation process, focusing on ZFS in various complexes of interest, using quantum chemical methods as well as molecular dynamic simulations.

The application of different analytical techniques is fundamental in forensic drug analysis. In the wake of the occurrence of large numbers of new psychoactive substances possessing similar chemical structures as already known ones, focus has been placed on applied criteria for their univocal identification. These criteria vary, obviously, depending on the applied technique and analytical approach. However, when two or more substances are proven to have similar analytical properties, these criteria no longer apply, which imply that complementary techniques have to be used in their differentiation. This work describes the synthesis of some structural analogues to synthetic cannabinoids and cathinones based on the evolving patterns in the illicit drug market. Six synthetic cannabinoids and six synthetic cathinones were synthesized, that, at the time for this study, were not as yet found in drug seizures. Further, a selection of their spectroscopic data is compared to those of already existing analogues; mainly isomers and homologues. The applied techniques were mass spectrometry (MS), Fourier transformed infrared (FTIR, gas phase) spectroscopy and nuclear magnetic resonance (NMR) spectroscopy. In total, 59 different compounds were analyzed with the  selected techniques. The results from comparison of spectroscopic data showed that isomeric substances may in some cases be difficult to unambiguously identify based only on their GC-MS EI spectra. On the other hand, GC-FTIR demonstrated more distinguishable spectra. The spectra for the homologous compounds showed however, that the GC-FTIR technique was less successful compared to GC-MS. Also a pronounced fragmentation pattern for some of the cathinones was found. In conclusion, this thesis highlights the importance of using complementary techniques for the univocal identification of synthetic cannabinoids and cathinones. By increasing the number of analogues investigated, the more may be learnt about the capabilities of different techniques for structural differentiations, and thereby providing important identification criteria leading to trustworthy forensic evidence.

A fully functioning Comprehensive nuclear-Test-Ban Treaty (CTBT) is essential for a world free of nuclear weapons. To measure radionuclides in the atmosphere in accordance with the CTBT, facilities such as SAUNA uses double coincidence techniques to discriminate between interesting Xenon isotopes. In this paper, a Monte-Carlo code (open source) based on first principles simulating a radionuclide detector has been built to investigate the viability of triple coincidence methods for measurements of $^{131m}$Xe, $^{133m}$Xe, $^{133}$Xe and $^{135}$Xe and found that by measuring $\beta - $ Ce $-$ X-ray coincides in $^{133}$Xe and $^{135}$Xe one could seperate the 30 keV photon energy region of interest by as much as $42.9 \pm 26.8$ keV and $214 \pm 50.8$ keV away from the original electron $-$ photon energy axes measured in SAUNA, using concentrations of Xenon isotopes typical for a nuclear weapons test one day after testing. The conclusion is that triple  coincidence  is  a  viable  method  for  nuclear weapons detection in light of double coincidence methods,  if only considering this  theoretical  approach.   No  conclusions  on  the  practicality  of  triple  coincidence methods in a CTBT could be drawn from these results.

The ejecta following the collision and merging of two neutron stars (kilonova) are currently considered promising sites for nucleosynthesis of r-process elements. Since the observed kilonova in 2017, GW2017817, astrophysicists have been working to analyze the collected electromagnetic spectra, trying to identify r-process elements. However, a lack of fundamental atomic data has been holding the efforts back. Motivated by spectral modelling of kilonovae out of equilibrium, this project aims to create a tool that uses line lists of spectroscopic accuracy from the Vienna Atomic Line Database (VALD) to generate energy level lists automatically for any ion. VALD in particular is used because it has wavelengths accurate enough for line identification purposes. The resulting level lists are compared to equivalent level lists from the database managed by the National Institute for Standards and Technology (NIST), in order to both ensure that the tool worked, and identify discrepancies between the databases. A number of problems with the VALD data were identified, mostly resulting in duplicate and missing energy levels. Finally, we also test the data in computations of kilonova expansion opacities in a complete solar r-process abundance mixture. Further work is needed to evaluate how damaging these problems are when modelling kilonovae, and when necessary remedy said problems. / Ejektat från en kollision och sammanslagning av två neutronstjärnor (kilonova) betraktas som lovande platser för nukleosyntes av r-processämnena. Sedan den observerade kilonovan år 2017, GW2017817, har astrofysiker försökt analysera de insamlade elektromagnetiska spektrumen för att försöka identifiera r-processämnen. Denna analys har dock hindrats på grund av en brist på fundamental atomisk data. Motiverat av spektralmodellering av kilonovor utanför ekvilibrium, syftar detta projekt på att utveckla ett verktyg för att utifrån spektroskopiskt noggranna linjelistor från Vienna Atomic Line Database (VALD) gererera listor över energinivåer automatiskt för godtycklig jon. VALD används på grund av att den har våglänger som är noggranna nog för linjeidentifiering. De resulterande nivålistorna jämförs med motsvarande nivålistor från databasen som sköts av National Institute for Standards and Technology (NIST), detta för att dels säkerställa att verktyget fungerade, dels identifiera skillnader mellan databaserna. Ett antal problem med VALD identifierades, vilka oftast resulterade i dubbletter eller avsaknad av energinivåer. Slutligen testades datan i beräkningar av kilonova-expansionsopaciteter i en komplett solär r-process-ämnesblandning. Vidare arbete krävs för att evaluera hur skadliga dessa problem är för modellering av kilonovor, och vid behov åtgärda problemen.

Coherent detection employing multilevel modulation format has become one of the most promising technologies for next generation high speed transmission system due to the high power and spectral efficiencies. With the powerful digital signal processing (DSP), coherent optical receivers allow the significant equalization of chromatic dispersion (CD), polarization mode dispersion (PMD), phase noise (PN) and nonlinear effects in the electrical domain. Recently, the realizations of these DSP algorithms for mitigating the channel distortions in the transmission system are the most attractive investigations.  The CD equalization can be performed by the digital filters developed in the time and the frequency domain, which can suppress the fiber dispersion effectively. The PMD compensation is usually performed in the time domain with the adaptive least mean square (LMS) and constant modulus algorithms (CMA) equalization. Feed-forward and feed-back carrier phase estimation algorithms are employed to mitigate the phase noise from the transmitter and local oscillator lasers. The fiber nonlinearities are compensated by using the digital backward propagation methods based on solving the nolinear Schrodinger (NLS) equation and the Manakov equation.  In this dissertation, we present a comparative analysis of three digital filters for chromatic dispersion compensation, an analytical evaluation of carrier phase estimation with digital equalization enhanced phase noise and a brief discussion for PMD adaptive equalization. To implement these investigations, a 112-Gbit/s non-return-to-zero polarization division multiplexed quadrature phase shift keying (NRZ-PDM-QPSK) coherent transmission system is realized in the VPI simulation platform. With the coherent transmission system, these CD equalizers have been compared by evaluating their applicability for different fiber lengths, their usability for dispersion perturbations and their computational complexity. Meanwhile, the bit-error-rate (BER) floor in carrier phase estimation using a one-tap normalized LMS filter is evaluated analytically, and the numerical results are compared to a differential QPSK detection system. / QC 20110629

Renewed enthusiasm for space exploration brings more ambitious missions to light butthe constraints of chemical rockets put imposing limits on what is feasible. Nuclearthermal rockets provide an attractive and efficient alternative to shorten travel timesand increase payload. In this thesis, a dynamic model of a Nuclear thermal rocketengine is derived in order to simulate the resulting performance of the engine. Thework is inspired by a similar model on the Space Shuttle Main Engine (SSME).

Utilizing density functional theory (DFT) the Vienna Ab initio Simulation Package (VASP) was used to calculate the Raman spectra for five single-walled carbon nanotubes (SWCNTs) with chiralities (4,4), (6,6), (8,0), (12,0) and (7,1). The radial breathing mode (RBM), when compared with experimental frequencies, shows good correlation. When compared to RBM:s calculated with tight binding the frequencies calculated with DFT displayed higher accuracy. The precision of G-band frequencies were inconclusive due to lack of experimental data. The frequencies did not agree well with the results from tight-binding theory. The correctness of the Raman activity estimations using results from DFT calculations was found to be questionable. An unknown mode, which was found to be highly Raman active in the calculated spectra of (4,4), (6,6), and possibly (8,0), and (12,0), is also discussed. It was concluded that further calculations on larger tubes, especially armchair tubes are relevant for future studies. Further verification of the determination of Raman activity is also needed. / F7042T - Project in Engineering Physics

Nanophotonic and plasmonic research have seen many breakthroughs lately which has created a demand for automated design algorithms to optimize optical elements at the nanometer scale. This work focuses on plasmonic nanostructures that are small metal particles interacting with electromagnetic radiation on length scales typically less than the wavelength. Plasmonic effects from nanostructures are used for enhancing and manipulating electromagnetic fields at the nanometer scale which have seen many applications in sensing requiring an ultra-high sensitivity and a small resolution. This work is about how deep learning methods can be used for designing plasmonic gold nanostructures. In particular, we investigate how convolutional neural networks can be used to predict the optical properties of nanostructures and how conditional generative adversarial networks (cGAN) can be used for designing structures with desired optical properties. The data in this work consist of images with differently shaped nanostructures and the corresponding spectral data for the scattering cross section, the absorption cross section, the polarization rotation and the polarization ellipticity. Utilizing the convolutional EfficientNet architectures, we train a forward model to predict the spectral data of anisotropically shaped nanostructures with images of the structure shape as input. We achieve a mean squared error of 2.5 × 10−4, 2.5 ×10−4, 6.0 ×10−4, and 4.9 ×10−4 respectively for each variable which agrees with the literature for similar problems. For the inverse design models, we show that label projection can be used to improve the results of two common GAN architectures in combination with a novel label embedding network. We use the Wasserstein GAN method with gradient penalty for training the models to generate images of nanostructure shapes conditioned on spectral data. The best model achieves a pixelwise mean absolute error of 4.9×10−3 and an estimated spectral mean absolute error of 8.4×10−3 between original and generated images when trained on a dataset containing cylindrical dimer structures. Furthermore, we have shown that the pixelwise mean absolute error is reduced when more conditional input variables are added to the model and that the model can learn different nanostructure shapes when trained on a large dataset containing different anisotropic gold nanostructure shapes. The best pixelwise mean absolute error found is 1.1×10−2 and the estimated spectral mean absolute error is 1.7 × 10−2 on the full dataset using all available input data.