The efficiency of different spectroscopic techniques are examined through four different approaches: detailed analysis of IR spectra from the APOGEE database and examination of persistence, observing extremely metal-poor stars using the Plaskett telescope at the DAO, three analyses of various applications of machine learning in astronomy, and efficient transmission of light through optical fibres. Through the first study, the technical effects of persistence in the APOGEE's IR spectra are examined, and a new technique for removing the persistence is introduced. Most of the globular cluster Pal 1's spectra in the APOGEE database are affected by persistence. Therefore, the Pal 1 spectra are corrected for the persistence and their stellar abundances are determined independently from the APOGEE's pipeline, ASPCAP. Our results for the known members of Pal 1 were in a close agreement with the results from Sakari et al. (2011). Comparison between the results from the corrected and the original spectra suggest that the persistence could have a critical effect on the results. The second study of this thesis focused on observations of extremely metal-poor (EMP) stars from the Pristine survey. Through the DAO-Pristine project, we narrowed down the initial list of the Pristine survey by observing over 50 targets during 25 observing nights. The Ca II triplet absorption lines of the observed targets were examined and used for estimating the metallicity of the objects. Twelve candidate EMP stars with weak Ca II triplet lines are chosen from the observed targets. These candidate EMP stars will be observed with larger telescopes for more accurate determination of their metallicity. This thesis also presents the result of a threefold analysis for using machine learning techniques in astronomy. The supervised machine learning methods are used for determination of the stellar parameters of stars using their raw spectra, and unsupervised machine learning methods are used for classification of supernovae Type Ia from their calibrated spectra. The supervised analysis of the IR and optical spectra suggested that the StarNet neural network (Fabbro et al. 2017) can predict the stellar parameters of the APOGEE database and synthetic spectra, efficiently and accurately. The effect of persistence in the StarNet's results are examined, and we showed that the persistence does not have a critical effect on the overall performance of the StarNet. In addition, multiple unsupervised machine learning techniques such as K-mean and Self Organizing Maps (SOMs) are used for classification of the supernovae Type Ia spectra. The preliminary results suggest that a minimum of three subclasses of supernovae Type Ia can be found from our data, which are consistent with the previous studies. Finally, this thesis presents our final results for an optical system we designed for the MSE project. At UVic, we have used the standard collimated beam method, or "ring test," to measure the Focal Ratio Degradation (FRD) of MSE-like fibres. The FRD of the system is determined from the ratio of the Full Width Half Maximum (FWHM) to the radius of the ring. Early ring test results from a sample of MSE-like fibres show an FRD of 3.7%, which meets the MSE science requirement (i.e. FRD < 5% at f/2). Also, we have automated the ring test for fast, repeatable, and efficient measurements of an individual fibre in multi-fibre bundles. Our future tests will include automated non-static fibres in preparation for the MSE build phases. / Graduate

In dieser Arbeit wird eine Analyse der TeV gamma-Strahlung in der Region um den galaktischen Sternhaufen Westerlund 2 präsentiert. Der dazu analysierte Datensatz beruht auf Observationen mit den Cherenkov Teleskopen des High Energy Stereoscopic System (H.E.S.S.) Experiments und umfasst ~80h Beobachtungszeit. Für die Datenanalyse wird die open-source Software gammapy benutzt, um morphologische und spektrale Modelle der gamma-Emission zu erstellen. Zur Modellauswahl wird das Akaike-Informationskriterium angewandt. Die Ergebisse der Analysen werden weiter mit Daten aus anderen Wellenlängenbereichen kombiniert, um Schlüsse auf den möglichen Ursprung der TeV-Signale zu ziehen. Neben Hinweisen auf eine diffuse gamma-Emission und mehrerer Hotspots um Westerlund 2 ist die Detektion von drei ausgedehnten gamma-Strahlungsquellen das Hauptergebnis der dargelegten Analysen. Zusätzlich zu den bekannten Quellen HESS J1023-575 und HESS J1026-582 wird die Detektion einer neuen, elliptischen Quelle südöstlich von HESS J1023-575 präsentiert. Diese neue Quelle, als ''TeV jet cloud'' bezeichnet, zeigt räumliche Übereinstimmung mit länglichen Gaswolken, die in CO und HI Radio Daten gefunden wurden. Der Ursprung dieser Gaswolken könnte der Jet eines Mikroquasars oder einer anisotropischen Supernova sein. Eine weitere räumliche Übereinstimmung zeigt HESS J1023-575 mit einer sphärischen Gaswolke, die ihren Ursprung in einer Supernova haben könnte. HESS J1023-575 und die Gaswolken sind dabei symmetrisch zur Hauptachse der neuen elliptischen gamma-Quelle ausgerichtet, was eine Verbindung der Komponenten in einem hadronischen Emissionszenario nahelegt. Aus den Wolkenmassen und der gamma-Emission ergibt sich eine Verstärkung der kosmischen Strahlung in der Region, was auf aktive Teilchenbeschleunigung hindeutet. Sollte ein Mikroquasar in der Region gefunden werden, könnte dieses die erste Detektion eines galaktischen hochenergetischen Jets mit Cherenkov Teleskopen sein. / This work presents a study of the TeV gamma-ray emission in the region of the stellar cluster Westerlund 2. The main dataset analysed in this work was obtained with the imaging atmospheric Cherenkov telescopes of the High Energy Stereoscopic System (H.E.S.S.), comprising a total of ~80h of observation time. The high-level analysis of the dataset is performed with the open-source software gammapy to produce extensive spectral and spatial models for the observed emission. The best-fitting models are determined by using the Akaike information criterion. The results are combined with findings from other wavelengths to probe different emission scenarios. Besides hints of a diffuse emission and the detection of multiple hotspots, the presented studies yield three extended gamma-ray sources around Westerlund 2. Besides the known sources HESS J1026-582 and HESS J1023-575, an elongated elliptical gamma-ray source referred to as ''TeV jet cloud'' is newly found to the south east of HESS J1023-575. It shows a spatial coincidence with elongated cloud structures seen in CO and HI radio data which may originate from a high energy jet of a mircroquasar or an anisotropic supernova. Another spatial agreement is seen between HESS J1023-575 and a spherical shell of hydrogen gas which may be the remains of an old supernova remnant. HESS J1023-575 and the gas cloud structures symmetrically align along the major axis of the TeV jet cloud. This suggests a connection of these components in a hadronic emission scenario. Combining the masses of the clouds with the measured gamma-ray flux yields a high cosmic ray enhancement factor, suggesting active particle acceleration in the region. If a microquasar would be found around the best-fit position of HESS J1023-575, this could be the first detection of a galactic high energy jet at TeV energies with Cherenkov telescopes.