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.

In this thesis H-bonded systems (natural gas hydrates, water clusters, and crystal ice) are studied by density functional theory (DFT) computations. Natural gas hydrates (NGHs) play an important role in energy and environmental fields: NGHs are considered as a promising backup energy resource in the near-future due to their tremendous carbon content; improper exploration of NGHs could induce geological disasters and aggravate the greenhouse effect. In addition, many technologies based on gas hydrates are being applied and developed. The thermodynamic stabilities of various water cavities in different clathrate crystalline phases occupied by hydrocarbon gas molecules are studied by dispersion-corrected hybrid functionals. The Raman spectra of C-C and C-H stretching vibrations of hydrocarbon molecules in various water cavities in the solid state are derived. The trends of C-H stretching vibrational frequencies are found to follow the prediction by the “loose cage ─| tight cage” model. In addition, the trends and origins of 13C NMR chemical shifts of hydrocarbon molecules in various NGHs are presented. These theoretical results will enlarge the database of C-C and C-H stretching vibrational frequencies and 13C NMR parameters of hydrocarbon molecules in NGHs, and provide valuable information to help identify the types of clathrate phases and varieties of guest molecules included in NGHs samples taken from natural sites. The behavior of water clusters may help to understand the properties of its liquid and solid states. The thermodynamic stabilities and IR spectra of a small-, medium-, and large-sized water cluster are studied in this work. After full optimization of (H2O)20,54,100 using the hybrid functional B3LYP, the electronic energies, zero-point energies, internal energies, enthalpies, entropies, and Gibbs free energies of the water clusters are computed. The OH stretching vibrational IR spectra of (H2O)20,54,100 are also presented and split into sub-spectra for different H-bond types based on the specific contributions from each group. It is found that the OH stretching vibrational frequencies of water are sensitive to the conformations of the H-bonds and the vibrations of the H-bonds belonging to different types are located in separated regions in the IR spectra. Thus, the spectroscopic fingerprints will reflect the H-bond topology of the water molecules in a water cluster. Ice XI has been suggested to be involved in the process of planetary formation as a considerable electric field might be formed from the ferroelectric ice XI in space. IR and Raman spectroscopic technology can be directly used to identify the occurrence of ferroelectric ice XI in laboratory or extraterrestrial settings. Due to the difficulty for DFT to describe non-covalent systems, the performance of 16 different DFT methods applied on the ice Ih, VIII, IX, and XI crystal phases are assessed. Based on the computational accuracy and cost, the IR and Raman spectra of ice Ih and XI are derived and compared. The librational vibrations are found to be the identifier which can be used to distinguish ice Ih and ice XI in the universe. In addition, the existence only one kind of H-bond in ice Ih is demonstrated from the overlapping sub-spectra for different types of H-bonded pair configurations in 16 isomers of ice Ih. The region of water under negative pressure is an exotic land in lack of exploitation. Guest free clathrate hydrate (clathrate ice) of sII type has been recently confirmed experimentally at negative pressure. Does any other clathrate ice phase exist at negative pressure region? Since clathrate hydrate are isostructural with silica clathrate minerals and semiconductor clathrates, and crystal structure prediction by analogy with known structures and first-principles computations is an effective way to find new crystalline phases of solid materials, we are motived to look for new clathrate ice phases from silica or semiconductor clathrate materials based on first-principles computations. Borrowing the idea new clathrate frameworks of ZnO and SiC can be constructed by connecting their bubble clusters in different ways, new clathrate ice phases (sL, sL_I, sL_II, and sL_III) are generated by connecting the water bubble clusters according to different rules. Using the non-local dispersion-corrected vdW-DF2 functional, clathrate ice sL with ultralow density (0.6 g/cm3) is predicted by first-principles phase diagram computations to be stable under larger negative pressures than the sII phase. The phase diagram of water is thus extended into the lower negative pressure region.

Materials at extreme conditions exhibit properties that differ substantially from ambient conditions. High pressure and high temperature expose anharmonic, non-linear behavior, and can provoke phase transitions among other effects. Experimental setups to study that sort of effects are typically costly and experiments themselves are laborious. It is common to apply theoretical techniques in order to provide a road-map for experimental research. In this thesis I cover computational algorithms based on first-principles calculations for high-temperature and high-pressure conditions. The two thoroughly described algorithms are: 1) the free energy studies using temperature-dependent effective potential method (TDEP), and 2) a higher-order elastic constants calculation procedure. The algorithms are described in an easy to follow manner with motivation for every step covered. The Free energy calculation algorithm is demonstrated with applications to hexagonal close-packed Iron at the conditions close to the inner Earth Core’s. The algorithm of elastic constants calculation is demonstrated with application to Molybdenum, Tantalum, and Niobium. Other projects included in the thesis are the study of effects of van der Waals corrections on the graphite and diamond equations of state. / Material vid extrema förhållanden uppvisar egenskaper som skiljer sig avsevärt från omgivningsförhållanden. Högt tryck och hög temperatur exponera anharmonicity, icke-linjärt beteende, och kan framkalla fasövergångar bland andra effekter. Experimentella uppställningar för att studera denna typ av effekter är vanligtvis dyra och experiment själva är mödosam. Det är vanligt att tillämpa teoretiska metoder för att ge en färdplan för experimentell forskning. I denna avhandling täcker jag beräkningsalgoritmer baserat på första principer beräkningar för hög temperatur och högt tryck. De två grundligt beskrivna algoritmer är: 1) den fria energin studier med temperaturberoende effektiv potentiell metod (TDEP), och 2) en högre ordning elastiska konstantberäkningsproceduren. Algoritmerna beskrivs i en lätt att följa sätt med motivation för varje steg som omfattas. Den fria energiberäkningsalgoritm visas med program till hexagonal tätpackad järn på villkoren nära jordens inre kärna. Algoritmen av elastiska konstanter beräkning demonstreras med tillämpning till molybden, tantal, och niob. Andra projekt som ingår i avhandlingen är effekterna av van der Waals-korrigeringar på tillståndsekvation och elastiska konstanter i grafit och diamant.

Bacteria can quickly spread throughout the human body, making certain diseases hard or impossible to cure. In order to understand how the bacteria can initiate and develop into an infection, microfluidic chambers in a lab environment are used as a template of how bacteria reacts to different types of flows. However, accurately tracking the movement of bacteria is a difficult task, where small objects has to be captured with a high resolution and digitally analysed with computationally heavy methods. Popular imaging methods utilise digital holographic microscopy, where three-dimensional movement is captured in two-dimensional images by numerical reconstruction of the diffraction of light. Since numerical reconstructions become computationally heavy when a good accuracy is required, this master's thesis work focus on evaluating the possibility of using convolutional neural networks to quickly and accurately determine the spatial properties of bacteria. By thorough testing and analysis of state of the art and old networks a new network design is presented, designed to eliminate as many imaging issues as possible. We found that there are certain network design choices that help with reducing the overall error of the system, and with a well chosen training set with sensible augmentations, some networks were able to reach a 60% classification accuracy when determining the vertical rotation of the bacteria. Unfortunately, due to the lack of experimental data where the ground-truth is known, not much experimental testing could be performed. However, a few tests showed that images of high quality could be classified within the expected range of vertical rotation. / Bakterier kan snabbt sprida sig genom människokroppen, vilket försvårar starkt möjligheterna att kurera vissa sjukdomar. För att få en inblick i hur bakterier kan initiera och utvecklas till en infektion används som mall laborativa uppställningar med vätskekanaler i mikroskala när man söker förstå hur bakterier reagerar på olika typer av flöden. Att spåra dessa rörelser med god säkerhet är dock en utmaning, då man experimentellt söker fånga små skalor med hög upplösning, som sedan ska analyseras med datorintensiva metoder. Populära avbildningsmetoder använder sig utav digital holografisk mikroskopi, där tredimensionella rörelser kan fångas med hjälp av tvådimensionella bilder genom att numeriskt återskapa ljusets brytningsmönster mot objekten. Eftersom dessa metoder blir beräkningstunga när god säkerhet krävs så utforskar detta examensarbete möjligheterna att utnyttja faltningsnätverk för att snabbt och säkert bestämma vertikalrotationen hos bakterier avbildade med holografi. Genom nogranna tester av moderna samt äldre nätverk så presenteras en ny nätverksdesign, utvecklad i mål med att eliminera så många avbildningsproblem som möjligt. Vi fann att vissa designval vid nätverksutvecklingen kan hjälpa med att reducera klassificeringsfelen givet vårt system, och med en väl utvald träningsmängd med lämpliga justeringar så lyckades vi nå en klassificeringssäkerhet på över 60% med vissa nätverk. På grund av bristande experimentellt data där de riktiga värdena är kända så har ingen utförlig experimentell analys utförts, men några tester på experimentella bilder i god kvalité har visats ge resultat som tyder på en korrekt analys inom den förväntade vertikalrotationen.

The treatment plan for radiation therapy with protons is based on images from a computed tomography (CT) scanner. This is problematic since the photons in the x-ray beam from the CT scanner and the protons are affected differently by the tissue in the patient, which introduce an uncertainty in the track length of the protons. The hypothesis of this study is that a new generation of CT scanners (DECT), with the capacity to simultaneously scan the patient with two photon spectra of different mean energy, will improve the tissue characterisation and which in turn reduce the uncertainty in the track length of the protons. In this study, the accuracy and precision of a DECT-based method from the literature is compared to the conventional calibration method used today at the University clinics in Sweden to relate the attenuation of the photon beam to the slowing down of the protons. The methods are tested on CT images of a phantom, a plastic body containing tissue equivalent plastic inserts of known elemental composition. The results turned out to be inconclusive as there were large uncertainties in the measurements. The method has potential, as has been shown in the literature, but there are many questions that need to be answered before the method is ready to be implemented at the clinic. / En proton som färdas genom människokroppen deponerar endast en liten del av sin energi längs vägen innan den plötsligt deponerar allt i slutet på dess bana. Hur lång dess bana är beror på protonens ursprungliga energi och den atomära sammansättningen hos vävnaden den passerar igenom. Om sammansättningen är känd går det genom att justera den initiala energin bestämma banlängden. Denna egenskap gör protonen väldigt attraktiv för strålterpi, då det innbär möjligheten att behandla med hög precision samt bespara frisk vävnad onödig dos. Strålterapi med protoner planeras idag med bilder från en skiktröntgen (CT) som underlag. Ett problem med det är att röntgenstrålarna från CT-skannern påverkas annorlunda än protonerna av vävnaden, vilket introducerar en osäkerhet i protonernas banlängd. Hypotesen i denna studie är att en ny generation av CT-scanner (DECT), med möjlighet att simultant skanna patienten med två fotonspektran av olika medelenergi, på ett bättre sätt ska kunna bestämma den atomära sammansättningen för vävnaden och därmed reducera osäkerheten i protonernas banlängd. Noggrannhet och precision för en DECT-baserad metod från litteraturen jämförs med den SECT-baserade kalibreringsmetoden, som idag används på Universitetssjukhusen i Sverige för att relatera fotonstrålens dämpning i vävnaden till protonernas inbromsning. Metoderna testas på CT bilder av ett fantom, en plastkropp innehållandes olika cylindrar av vävnadsekvivalent plast med känd atomär sammansättning. Resultatet av den här studien är inte starkt nog för att bevisa hypotesen för studien. Det insamlade bildmaterialet innehåller höga brusnivåer jämfört med de som rapporteras i literaturen. Brusnivåer är så höga att det mesta av resultatet inte kan anses som statistiskt signifikant. Det är dessutom svårt att göra en direkt jämförelse av prestanda med befintlig teori för vävnadskaraktärisering, då bildmaterialet från de CT skanners som jämfördes är av olika typer. De resultat som publicerats i litteraturen visar att den DECT-baserade metoden har potential, men den här studien gör tydligt att det fortfarande finns frågor som måste besvaras innan metoden är redo att implementeras kliniskt.