A note on the birefringence angle estimation in CMB data analysis

Parity violating physics beyond the standard model of particle physics induces a rotation of the linear polarization of photons. This effect, also known as cosmological birefringence (CB), can be tested with the observations of the cosmic microwave background (CMB) anisotropies which are linearly polarized at the level of $5-10\%$. In particular CB produces non-null CMB cross correlations between temperature and B mode-polarization, and between E- and B-mode polarization. Here we study the properties of the so called D-estimators, often used to constrain such an effect. After deriving the framework of both frequentist and Bayesian analysis, we discuss the interplay between birefringence and weak-lensing, which, albeit parity conserving, modifies pre-existing TB and EB cross correlation.Comment: 12 pages. Accepted for publication in JCA

High Performance Astronomical Data Analysis towards Exascale

To date, most data-intensive HPC jobs in the government, academic and industrial sectors have involved the modelling and simulation of complex physical systems. In more recent times, the scientific data explosion is fuelling the growth of a new trend in HPC: high performance data analysis (HPDA). Some scientific disciplines (e.g. bioscience, weather and climate, security) are exploring the possibilities of HPDA to promote new insight, identifying some problems related to the nature of current HPC systems. In the design and development of the Exascale supercomputing facilities, HPDA is playing a crucial role. In this paper we will present the work done in the ExaNeSt and EuroExa EU-funded projects to build a prototype of a low power Exascale facility able to facilitate the astrophysical community in using HPC resources for data analysis and simulations

The Euclid Science Ground Segment Distributed Infrastructure: System Integration and Challenges

The Science Ground Segment (SGS) of the Euclid mission provides distributed and redundant data storage and processing, federating nine Science Data Centres (SDCs) and a Science Operations Centre. The SGS reference architecture is based on loosely coupled systems and services, broadly organized into a common infrastructure of transverse software components and the scientific data Processing Functions. The SGS common infrastructure includes: 1) the Euclid Archive System (EAS), a central metadata repository which inventories, indexes and localizes the huge amount of distributed data; 2) a Distributed Storage System of EAS, providing a unified view of the SDCs storage systems and supporting several transfer protocols; 3) an Infrastructure Abstraction Layer, isolating the scientific data processing software from the underlying IT infrastructure and providing a common, lightweight workflow management system; 4) a Common Orchestration System, performing a balanced distribution of data and processing among the SDCs. Virtualization is another key element of the SGS infrastructure. We present the status of the Euclid SGS software infrastructure, the prototypes developed and the continuous system integration and testing performed through the Euclid “SGS Challenges”

The Euclid Science Ground Segment Distributed Infrastructure: System Integration and Challenges

The Science Ground Segment (SGS) of the Euclid mission provides distributed and redundant data storage and processing, federating nine Science Data Centres (SDCs) and a Science Operations Centre. The SGS reference architecture is based on loosely coupled systems and services, broadly organized into a common infrastructure of transverse software components and the scientific data Processing Functions. The SGS common infrastructure includes: 1) the Euclid Archive System (EAS), a central metadata repository which inventories, indexes and localizes the huge amount of distributed data; 2) a Distributed Storage System of EAS, providing a unified view of the SDCs storage systems and supporting several transfer protocols; 3) an Infrastructure Abstraction Layer, isolating the scientific data processing software from the underlying IT infrastructure and providing a common, lightweight workflow management system; 4) a Common Orchestration System, performing a balanced distribution of data and processing among the SDCs. Virtualization is another key element of the SGS infrastructure. We present the status of the Euclid SGS software infrastructure, the prototypes developed and the continuous system integration and testing performed through the Euclid “SGS Challenges”

The Euclid Science Ground Segment Distributed Infrastructure: System Integration and Challenges

The Science Ground Segment (SGS) of the Euclid mission provides distributed and redundant data storage and processing, federating nine Science Data Centres (SDCs) and a Science Operations Centre. The SGS reference architecture is based on loosely coupled systems and services, broadly organized into a common infrastructure of transverse software components and the scientific data Processing Functions. The SGS common infrastructure includes: 1) the Euclid Archive System (EAS), a central metadata repository which inventories, indexes and localizes the huge amount of distributed data; 2) a Distributed Storage System of EAS, providing a unified view of the SDCs storage systems and supporting several transfer protocols; 3) an Infrastructure Abstraction Layer, isolating the scientific data processing software from the underlying IT infrastructure and providing a common, lightweight workflow management system; 4) a Common Orchestration System, performing a balanced distribution of data and processing among the SDCs. Virtualization is another key element of the SGS infrastructure. We present the status of the Euclid SGS software infrastructure, the prototypes developed and the continuous system integration and testing performed through the Euclid “SGS Challenges”

The Euclid science ground segment distributed infrastructure: System integration and challenges

The Science Ground Segment (SGS) of the Euclid mission provides distributed and redundant data storage and processing, federating nine Science Data Centres (SDCs) and a Science Operations Centre. The SGS reference architecture is based on loosely coupled systems and services, broadly organized into a common infrastructure of transverse software components and the scientific data Processing Functions. The SGS common infrastructure includes: 1) the Euclid Archive System (EAS), a central metadata repository which inventories, indexes and localizes the huge amount of distributed data; 2) a Distributed Storage System of EAS, providing a unified view of the SDCs storage systems and supporting several transfer protocols; 3) an Infrastructure Abstraction Layer, isolating the scientific data processing software from the underlying IT infrastructure and providing a common, lightweight workflow management system; 4) a Common Orchestration System, performing a balanced distribution of data and processing among the SDCs. Virtualization is another key element of the SGS infrastructure. We present the status of the Euclid SGS software infrastructure, the prototypes developed and the continuous system integration and testing performed through the Euclid “SGS Challenges”

The Indigo System in acute lower-limb malperfusion (INDIAN) registry. Protocol

Background: Acute lower limb ischemia (ALLI) poses a major threat to limb survival. For many years, surgical thromboembolectomy was the mainstay of treatment. Recent years have brought an endovascular revolution to the management of ALLI. It seems that the newly designed endovascular thrombectomy devices may shift treatment recommendations toward endovascular options. This protocol study aims to collect evidence supporting the latest hypothesis. Objective: The devices under investigation are the Penumbra/Indigo Systems (Penumbra Inc). The objective of this clinical investigation is to evaluate, in a controlled setting, the early safety and effectiveness of the devices and to define the optimal technique for the use of these systems in patients with confirmed peripheral acute occlusions. Methods: This study will be an interventional prospective trial of patients with a diagnosis of ALLI treated with Penumbra/Indigo devices. This project is intended to be a national platform where every physician invited to participate could register his or her own data procedure. The primary outcome is the technical success of thromboaspiration with the Indigo System. Assessment of vessel patency will be recorded using the Thrombolysis in Myocardial Infarction (TIMI) score classifications before and after use of the device. Clinical success at follow-up is defined as an improvement of Rutherford classification at 1-month follow-up of one class or more as compared to the preprocedure Rutherford classification. Secondary endpoints include the following: (1) safety rate at discharge, defined as the absence of any serious adverse events; (2) primary patency at 1 month, defined as a target lesion without a hemodynamically significant stenosis or reocclusion on duplex ultrasound (>50%) and without target lesion reintervention within 1 month; and (3) limb salvage at 1 month. Results: The study is currently in the recruitment phase and the final patient is expected to be treated by the end of March 2019. A total of 150 patients will be recruited. Analyses will focus on primary and secondary endpoints. Conclusions: These new endovascular thrombectomy devices that are specifically designed for peripheral intervention in this difficult set of patients, as those under investigation in the proposed registry, may offer improved clinical outcomes with lower rates of major systemic and local complications. Following completion of this study, it is expected that the value of the Indigo Thrombectomy System in the treatment of ALLI will be better defined. As a result, a shift of treatment recommendations toward endovascular options may be observed in the near future