Resolving particle acceleration and transport in the jets of the microquasar SS 433 with H.E.S.S. and HAWC

The microquasar SS 433 offers a unique laboratory to study the physics of mildly relativistic jets and the associated non-thermal processes. It hosts a compact binary system, from which a pair of counter-propagating jets is observed to emanate. The jets are resolved by observations out to distances of approximately 0.1 pc from the central source, but further out, they remain dark until they abruptly reappear at around 25 pc as bright X-ray sources. These outer jets were recently reported to be sources of TeV gamma-rays by the High Altitude Water Cherenkov (HAWC) observatory. This thesis presents a complete picture of the TeV emission from the jets of SS 433 including new data from the High Energy Stereoscopic System (H.E.S.S.) and the HAWC observatory. To fully exploit the capabilities of the H.E.S.S. observations, a new approach to background rejection is presented. It is based on the detection of Cherenkov light from muons by large Imaging Atmospheric Cherenkov Telescopes (IACTs), such as the telescope located at the center of the H.E.S.S. array. The application of this technique leads to a factor four reduction in background above several tens of TeV in the H.E.S.S. stereoscopic analysis. This thesis presents the detection of the SS 433 outer jets for the first time with an IACT array using H.E.S.S.. The superior angular and energy resolution of H.E.S.S. compared to HAWC allow for a detailed study of the emission from the jets, including a measurement of the physical extension of the emission and of the spectra out to tens of TeV. These observations also reveal the presence of striking energy- dependent morphology, ruling out a hadronic origin for the bulk of the gamma-ray emission. Photons above 10 TeV are observed only close to the base of the outer jets, implying efficient particle acceleration to very-high energies at that location. Evidence suggests that the acceleration is due to a shock, thus providing a clue to the long-standing question of the reappearance of the jets. The observed energy-dependent morphology is modeled as a consequence of the particle cooling times and the advection flow of the jet, which constrains the jet dynamics and, in particular, results in an estimate of the velocity of the outer jets at their base. This solves several issues concerning the non-thermal processes occurring in the jets and their dynamics, but also opens up new questions that highlight our incomplete understanding of the SS 433 system. A joint analysis of the H.E.S.S. and HAWC data would provide insights on the system across the entire range of TeV energies. To make this possible, a tool capable of reading and analyzing the data from both instruments is required. This thesis presents the extension and validation of an existing data format and analysis tool shared among IACTs to the data from particle detector arrays such as the HAWC observatory. This framework is then used to revisit the HAWC observations of the SS 433 region with the inclusion of additional data taken since the first detection was reported. The existence of this framework enables for the first time the joint analysis of the H.E.S.S. and HAWC data, the preliminary results of which are presente

Gammapy: A Python package for gamma-ray astronomy

In this article, we present Gammapy, an open-source Python package for the analysis of astronomical $\gamma$-ray data, and illustrate the functionalities of its first long-term-support release, version 1.0. Built on the modern Python scientific ecosystem, Gammapy provides a uniform platform for reducing and modeling data from different $\gamma$-ray instruments for many analysis scenarios. Gammapy complies with several well-established data conventions in high-energy astrophysics, providing serialized data products that are interoperable with other software packages. Starting from event lists and instrument response functions, Gammapy provides functionalities to reduce these data by binning them in energy and sky coordinates. Several techniques for background estimation are implemented in the package to handle the residual hadronic background affecting $\gamma$-ray instruments. After the data are binned, the flux and morphology of one or more $\gamma$-ray sources can be estimated using Poisson maximum likelihood fitting and assuming a variety of spectral, temporal, and spatial models. Estimation of flux points, likelihood profiles, and light curves is also supported. After describing the structure of the package, we show, using publicly available $\gamma$-ray data, the capabilities of Gammapy in multiple traditional and novel $\gamma$-ray analysis scenarios, such as spectral and spectro-morphological modeling and estimations of a spectral energy distribution and a light curve. Its flexibility and power are displayed in a final multi-instrument example, where datasets from different instruments, at different stages of data reduction, are simultaneously fitted with an astrophysical flux model.Comment: 26 pages, 16 figure

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Gammapy V1.0

Gammapy is an open-source Python package for gamma-ray astronomy built on Numpy, Scipy and Astropy. It is used as core library for the Science Analysis tools of the Cherenkov Telescope Array (CTA), recommended by the H.E.S.S. collaboration to be used for Science publications, and is already widely used in the analysis of existing gamma-ray instruments, such as MAGIC, VERITAS and HAWC

Gammapy V1.0

Gammapy is an open-source Python package for gamma-ray astronomy built on Numpy, Scipy and Astropy. It is used as core library for the Science Analysis tools of the Cherenkov Telescope Array (CTA), recommended by the H.E.S.S. collaboration to be used for Science publications, and is already widely used in the analysis of existing gamma-ray instruments, such as MAGIC, VERITAS and HAWC

Gammapy V1.0

Gammapy is an open-source Python package for gamma-ray astronomy built on Numpy, Scipy and Astropy. It is used as core library for the Science Analysis tools of the Cherenkov Telescope Array (CTA), recommended by the H.E.S.S. collaboration to be used for Science publications, and is already widely used in the analysis of existing gamma-ray instruments, such as MAGIC, VERITAS and HAWC

Gammapy V1.0

Gammapy is an open-source Python package for gamma-ray astronomy built on Numpy, Scipy and Astropy. It is used as core library for the Science Analysis tools of the Cherenkov Telescope Array (CTA), recommended by the H.E.S.S. collaboration to be used for Science publications, and is already widely used in the analysis of existing gamma-ray instruments, such as MAGIC, VERITAS and HAWC

Gammapy V1.0

Gammapy is an open-source Python package for gamma-ray astronomy built on Numpy, Scipy and Astropy. It is used as core library for the Science Analysis tools of the Cherenkov Telescope Array (CTA), recommended by the H.E.S.S. collaboration to be used for Science publications, and is already widely used in the analysis of existing gamma-ray instruments, such as MAGIC, VERITAS and HAWC

Gammapy V1.0

Gammapy is an open-source Python package for gamma-ray astronomy built on Numpy, Scipy and Astropy. It is used as core library for the Science Analysis tools of the Cherenkov Telescope Array (CTA), recommended by the H.E.S.S. collaboration to be used for Science publications, and is already widely used in the analysis of existing gamma-ray instruments, such as MAGIC, VERITAS and HAWC