Nouvelles observations radio de l'amas de galaxies MS 0735.6+7421 avec le Karl G. Jansky Very Large Array

Les amas des galaxies sont l’une des plus grandes structures liées gravitationnellement de l’univers. Leur dynamique est complexe et bien que plusieurs études multi-longueur d’onde ont été effectuées depuis la fin du 20ème siècle, il persiste plusieurs incertitudes sur les subtilités de leur dynamique. À ce jour, le consensus scientifique est que les trous noirs supermassifs actifs au centre des amas ont un impact important sur l’évolution de ces structures. Le trou noir central agit comme centre gravitationnel, mais lorsque ce trou noir est actif, son rôle ne se limite pas seulement à son impact gravitationnel. D’une part, les trous noirs actifs ont un rôle crucial dans l’émission thermique des amas. En effet, les jets radio influencent l’émission rayons-X des amas en poussant mécaniquement le milieu intra-amas qui émet en rayons-X via l’émission Bremsstrahlung. Ce phénomène engendre la formation de cavités rayons-X qui constituent une preuve de la rétroaction énergétique du trou noir sur l’ensemble de l’amas. Un tel phénomène est nécessaire afin d’expliquer les résultats observationnels qui témoignent d’un refroidissement moins important que prédit théoriquement au centre des amas à cœur froid. D’autre part, il existe de plus en plus d’études qui supportent l’hypothèse que les trous noirs actifs ont un rôle dans la (ré-)accélération de particules relativistes responsables de l’émission synchrotron au cœur des amas à cœur froid. Ces structures appelées mini-halos sont typiquement diffuses en radio et donc difficiles à détecter. Dans ce mémoire, nous étudierons en détail l’émission radio de l’amas de galaxies massif à cœur froid MS 0735.6+7421 (z = 0.216). Cet amas est unique puisqu’il possède les jets radio les plus énergétiques détectés au centre d’un amas à cœur froid. Il s’agit donc d’un exemple de trou noir actif parmi les plus extrêmes connus. Cet objet constitue ainsi une cible parfaite afin d’étudier le lien qui unit la rétroaction du trou noir actif central et l’émission synchrotron au centre des amas à cœur froid. Pour réaliser cette étude, nous avons effectué une analyse radio exhaustive de MS 0735.6+7421 à l’aide de données acquises sur le Karl G. Jansky Very Large Array. Cette analyse a permis de détecter une nouvelle structure radio diffuse jamais détectée auparavant. Cette nouvelle structure possède une puissance radio à 1.4 GHz qui concorde avec celles des mini-halos les plus lumineux. Le résultat principal de notre étude supporte donc l’hypothèse selon laquelle il existe un lien fondamental entre la rétroaction du trou noir actif central et la formation de mini-halos au centre des amas à cœur froid.Galaxy clusters are one of the largest gravitationally bound structures in the universe. They exhibit complex dynamics and even though several multi-wavelength studies have been conducted since the end of the 20th century, there are still a lot of uncertainties concerning their evolution. To this day, the scientific consensus is that the active supermassive black hole at the center of the cluster has a profound impact on the cluster’s evolution. Indeed, the central supermassive black hole has a substantial gravitational impact, but when the black hole actively accretes material, its role goes beyond its gravitational influence. Active supermassive black holes have a crucial role in terms of the thermal emission in clusters. Indeed, the radio jets influence the X-ray emission of clusters by mechanically pushing the intracluster medium which emits in X-ray via Bremsstrahlung emission. This leads to the formation of X-ray cavities which are proof of the energetic feedback of the central supermassive black hole on the cluster. Such a phenomenon is required to reconcile the observational results that report less cooling at the center of cool core clusters than what is theoretically predicted. Moreover, there are more and more studies that support the hypothesis that active supermassive black holes have a crucial role in the (re-)acceleration of seed particles responsible for synchrotron emission at the center of cool core clusters. These structures are named mini-halos and are usually difficult to detect because they are diffuse. In this Master’s thesis, we will study the radio emission of the massive cool core galaxy cluster MS 0735.6+7421 (z = 0.216). This cluster is unique because it exhibits the most powerful radio jets ever detected at the center of a cool core cluster. It thus contains one of the most powerful active supermassive black holes known. This object is a perfect target to study the link between active black hole feedback and synchrotron emission in cool core clusters. To conduct this study, we performed a radio analysis of MS 0735.6+7421 with new data obtained with the Karl G. Jansky Very Large Array. This analysis led to the discovery of an extended diffuse radio structure. This newly detected structure has a radio power at 1.4 GHz that matches the most luminous mini-halos known in the literature. The principal result of our study argues in favor of the hypothesis that there is a fundamental link between active black hole feedback and the formation of mini-halos at the center of cool core clusters

Data consistency and classification model transferability across biomedical Raman spectroscopy systems

Surgical guidance applications using Raman spectroscopy are being developed at a rapid pace in oncology to ensure safe and complete tumor resection during surgery. Clinical translation of these approaches relies on the acquisition of large spectral and histopathological data sets to train classification models. Data calibration must ensure compatibility across Raman systems and predictive model transferability to allow multi-centric studies to be conducted. This paper addresses issues relating to Raman measurement standardization by first comparing Raman spectral measurements made on an optical phantom and acquired with nine distinct point probe systems and one wide-field imaging instrument. Data standardization method led to normalized root-mean-square deviations between instruments of 2%. A classification model discriminating between white and gray matter was trained with one point probe system. When used to classify independent data sets acquired with the other systems, model predictions led to >95% accuracy, preliminarily demonstrating model transferability across different biomedical Raman spectroscopy instruments

Probing the role of thermal vibrational disorder in the SPT of VO 2_2 2 by Raman spectroscopy

Abstract Phase competition in transition metal oxides has attracted remarkable interest for fundamental aspects and technological applications. Here, we report a concurrent study of the phase transitions in undoped and Cr-doped VO $$_2$$ 2 thin films. The structural, morphological and electrical properties of our films are examined and the microstructural effect on the metal–insulator transition (MIT) are highlighted. We further present a distinctive approach for analyzing the Raman data of undoped and Cr-doped VO $$_2$$ 2 thin films as a function of temperature, which are quantitatively correlated to the electrical measurements of VO $$_2$$ 2 films to give an insight into the coupling between the structural phase transition (SPT) and the MIT. These data are also combined with reported EXAFS measurements and a connection between the Raman intensities and the mean Debye–Waller factors $$\sigma ^2$$ σ 2 is established. We found that the temperature dependence of the $$\sigma _{R}^{2}(V-V)$$ σ R 2 ( V - V ) as calculated from the Raman intensity retraces the temperature profile of the $$\sigma _{EXAFS}^{2}(V-V)$$ σ EXAFS 2 ( V - V ) as obtained from the EXAFS data analysis. Our findings provide an evidence on the critical role of the thermal vibrational disorder in the VO $$_2$$ 2 phase transitions. Our study demonstrates that correlating Raman data with EXAFS analysis, the lattice and electronic structural dynamics can be probed

A Machine Learning Approach to Integral Field Unit Spectroscopy Observations: III. Disentangling Multiple Components in H ii regions

International audienceIn the first two papers of this series (Rhea et al. 2020b; Rhea et al. 2021), we demonstrated the dynamism of machine learning applied to optical spectral analysis by using neural networks to extract kinematic parameters and emission-line ratios directly from the spectra observed by the SITELLE instrument located at the Canada-France-Hawai'i Telescope. In this third installment, we develop a framework using a convolutional neural network trained on synthetic spectra to determine the number of line-of-sight components present in the SN3 filter (656-683nm) spectral range of SITELLE. We compare this methodology to standard practice using Bayesian Inference. Our results demonstrate that a neural network approach returns more accurate results and uses less computational resources over a range of spectral resolutions. Furthermore, we apply the network to SITELLE observations of the merging galaxy system NGC2207/IC2163. We find that the closest interacting sector and the central regions of the galaxies are best characterized by two line-of-sight components while the outskirts and spiral arms are well-constrained by a single component. Determining the number of resolvable components is crucial in disentangling different galactic components in merging systems and properly extracting their respective kinematics