In recent decades, thousands of exoplanets have been discovered. The next step is to characterize theobserved planets in terms of their radii, masses, density, physical conditions and composition of theiratmospheres. Several space-based observatories such as TESS and CHEOPS have started determiningthe first three observables but characterization of exoplanetary atmospheres is waiting for observationcampaigns with instruments like CRIRES+ at the VLT and NIRSpec on the JWST. To ensure the efficiencyof data acquisition, careful planning of observations is necessary. In this project we developeda software tool to select and rank candidates based on the feasibility of observations of atmosphericfeatures during transits with CRIRES+. We also review different techniques to retrieve transmissionspectra from transit observations and modeling of exoplanet atmospheres in order to clarify the requirementsfor the data. Our CRIRES-planning-tool is built on astronomical observation planningmethods from astropy and astroplan and the exposure time calculator designed for CRIRES+ byESO and UU. We conclude that observations for atmospheric characterization with CRIRES+ are feasible.However, we observed that for a robust candidate selection, careful iterative tuning of proposedconstraints is required.

No description available.

A small report that investigates neutrino emission from supernovae, in order to estimate at what distance you will have to be from a supernova for the neutrino radiation to kill you.

No description available.

This thesis considers emission from gamma-ray bursts (GRBs), the most powerful explosions known in the Universe. Most GRBs are likely associated with the final stages of stellar evolution, where the core of a massive star collapses, and gives birth to a highly compact object such as a neutron star or black hole. The wide energy range of the Fermi Gamma-ray Space Telescope allows for unprecedented studies of GRBs. Fermi data is used to study the emission released at the photosphere of the relativistic outow ejected from the central compact object. The thesis present studies of two of the strongest GRBs ever detected; GRB 090902B (Papers I, II) and GRB 110721A (Paper III). Photospheric emission is identied and its properties are studied for both GRBs. For the first time, observational evidence is found for spectral broadening of photospheric emission. Motivated by these results, possible mechanisms to make the emission from the photosphere appear broader than the Planck spectrum are examined. Two separate theoretical explanations are presented. Apart from the possibility of energy dissipation below the photosphere (Paper II), geometrical effects in outflows with angle dependent properties is shown to significantly broaden the photospheric spectrum (Paper IV). Most importantly, the observed spectrum below the peak energy may become significantly softer inthe latter case. This thesis thus concludes that photospheric emission in GRBs may be more common than previously thought. This is because the emission spectrum from the jet photosphere does not necessarily need to be a Planck function. On the contrary it is shown that broader and/or multicomponent spectra naturally arise, consistent with what is generally observed. In particular, the thesis presents a new mechanism for spectral broadening due to geometrical effects, which must be taken into consideration in the study of GRB emission. / <p>QC 20120907</p>

When high-energy neutrinos interact with matter, radio waves will be emitted. Radio detectionallows us to measure UHE(&gt; 1016eV) neutrinos by instrumenting a huge volume with a sparsearray of radio antenna stations at a low cost. The radio signal measured by the antennas can then beanalyzed to estimate the physics quantity of the corresponding interaction. Traditional reconstructionmethods are time-consuming to develop and often do not account for all information in the signal. Onthe other hand, deep learning-based reconstruction is a powerful technique for radio detector data.Promising results predicting the neutrino energy and direction have been already achieved. However,so far, only the nominal value was predicted, but for the interpretation of data, the event-by-eventuncertainty is crucial and almost as important as the reconstruction of the nominal value. In thisthesis, I added an event-by-event uncertainty prediction of neutrino energy to the deep learningreconstruction using two methods: 1) Likelihood Inference or 2) Normalising Flows. NormalizingFlows allows predicting arbitrary PDFs event-by-event, whereas the first method only predicts astandard deviation per event. The predicted PDFs using Normalising Flows are close to a Gaussian.Hence, both methods can be used interchangeably

HD 140283, also known as the Methuselah star, is an old, metal-poor star on the subgiant branch.It has been the subject of many studies due to its relatively large apparent brightness, and due to itbeing one of the oldest stars known. Accurate age measurements can therefore put limits on the ageof the Universe, and help constrain cosmological models. We present a new investigation of the ageof HD 140283, based on the precise parallax measured by Gaia, PARSEC and BaSTI stellar isochronemodels, and a careful consideration of systematics. We find τ = 13.8 ± 0.5 Gyr, where the error isdominated by the effective temperature uncertainty. This does not imply an obvious tension with thestandard ΛCDM cosmological model (τuniverse = 13.80 ± 0.02 Gyr).

As they are evaporating, black holes are emitting radiations called Hawking radiations. Our goal is to determine at which distance it is possible to measure those radiations with current telescopes. Being capable of measuring those radiations would mean that we can use them as standard candles i.e. we could use it as distance indicator. To do so, we are  first going to compute the different characteristics of a black hole such as its energy peak, temperature,  flux and lifetime. Knowing that, we will be able to describe how, theoretically, we could use black holes as standard candles. Finally, we will take the Fermi-LAT telescope as an example of what we can observe in practice and at which distance.

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Today an abundance of objects are circulating in earth captured orbit. Monitoring these objects is of national security interest. One way to map any object in orbit is with their Keplerian elements. A method for estimating the Keplerian elements of a satellite orbit simulating a ground based radar station has been investigated. A frequency modulated continuous wave radar (FMCW) with a central transmitter antenna and a grid of receivers was modeled in MATLAB. The maximum likelihood estimator (MLE) was obtained to estimate the parameters from the received signal. The method takes advantage of the relations between the Cartesian position and velocity and the Keplerian elements to confine the search space. For a signal to noise ratio (SNR) of 10dB, the satellite was followed during a time period of 0.1s where the positions were found within average error of range: ±1.4m, azimuth: ±2.0·10−6 rad and elevation: ±8.4·10−7 rad. Using a linear approximation of the velocity the Keplerian elements were found within average error of i: ±0.0050 rad, Ω:±0.0050 rad, ω: ±0.0058 rad, a: ±2.60·105m, e:±0.0021 and ν: ±0.24 rad. A method to obtain more accurate estimates is proposed.