Test su un prototipo di rivelatore per la misura di sezione d’urto del neutrino elettronico

Il neutrino è una particella fondamentale del Modello Standard, è stata scoperta nel 1956 e col passare degli anni si venne a conoscenza del fatto che questi sono caratterizzati da una rispettiva antiparticella e da tre tipi di sapore. La fisica dei neutrini è tuttavia ancora ricca di incomprensioni: molte delle proprietà che descrivono queste particelle risultano ancora sconosciute. Il progetto ENUBET propone un’iniziativa con lo scopo di far luce su alcuni dei misteri che circondano le nostre conoscenze sui neutrini e sarà il protagonista di questo elaborato. Nel primo capitolo si farà un’introduzione sulla scoperta dei neutrini e sulle proprietà che li descrivono. Nel secondo capitolo, si introdurranno gli scopi del progetto ENUBET e verrà descritto il modo in cui questo progetto ha intenzione di approcciarsi alle problematiche legate alle incertezze sul flusso ed alla misura della sezione d’urto; inoltre si discuterà delle tecniche adottate dal progetto per raggiungere i propri obiettivi. Nel terzo capitolo verrà descritta l’attività di laboratorio da me svolta presso la sede dell’INFN di Bologna, nella quale ho assistito alla costruzione di un prototipo di calorimetro destinato ad essere sottoposto ad un test beam presso il CERN di Ginevra. Successivamente verrà discussa l’analisi dei dati prodotti dal suddetto test ed elaborati attraverso l’utilizzo del software ROOT

Cloud native approach for Machine Learning as a Service for High Energy Physics

Nowadays Machine Learning (ML) techniques are widely adopted in many areas of High Energy Physics (HEP) and certainly will play a significant role also in the upcoming High-Luminosity LHC (HL-LHC) upgrade foreseen at CERN. A huge amount of data will be produced by LHC and collected by the experiments, facing challenges at the exascale. Here, we present Machine Learning as a Service solution for HEP (MLaaS4HEP) to perform an entire ML pipeline (in terms of reading data, processing data, training ML models, serving predictions) in a completely model-agnostic fashion, directly using ROOT files of arbitrary size from local or distributed data sources. With the new version of MLaaS4HEP code based on uproot4, we provide new features to improve users’ experience with the framework and their workflows, e.g. users can provide some preprocessing operations to be applied to ROOT data before starting the ML pipeline. Then our approach is extended to use local and cloud resources via HTTP proxy which allows physicists to submit their workflows using the HTTP protocol. We discuss how this pipeline could be enabled in the INFN Cloud Provider and what could be the final architecture

Exceptional Microscale Plasticity in Amorphous Aluminum Oxide at Room Temperature

Oxide glasses are an elementary group of materials in modern society, but brittleness limits their wider usability at room temperature. As an exception to the rule, amorphous aluminum oxide (a-Al2O3) is a rare diatomic glassy material exhibiting significant nanoscale plasticity at room temperature. Here, it is shown experimentally that the room temperature plasticity of a-Al2O3 extends to the microscale and high strain rates using in situ micropillar compression. All tested a-Al2O3 micropillars deform without fracture at up to 50% strain via a combined mechanism of viscous creep and shear band slip propagation. Large-scale molecular dynamics simulations align with the main experimental observations and verify the plasticity mechanism at the atomic scale. The experimental strain rates reach magnitudes typical for impact loading scenarios, such as hammer forging, with strain rates up to the order of 1 000 s−1, and the total a-Al2O3 sample volume exhibiting significant low-temperature plasticity without fracture is expanded by 5 orders of magnitude from previous observations. The discovery is consistent with the theoretical prediction that the plasticity observed in a-Al2O3 can extend to macroscopic bulk scale and suggests that amorphous oxides show significant potential to be used as light, high-strength, and damage-tolerant engineering materials.Peer reviewe

PRISM (Polarized Radiation Imaging and Spectroscopy Mission): A White Paper on the Ultimate Polarimetric Spectro-Imaging of the Microwave and Far-Infrared Sky

PRISM (Polarized Radiation Imaging and Spectroscopy Mission) was proposed to ESA in response to the Call for White Papers for the definition of the L2 and L3 Missions in the ESA Science Programme. PRISM would have two instruments: (1) an imager with a 3.5m mirror (cooled to 4K for high performance in the far-infrared---that is, in the Wien part of the CMB blackbody spectrum), and (2) an Fourier Transform Spectrometer (FTS) somewhat like the COBE FIRAS instrument but over three orders of magnitude more sensitive. Highlights of the new science (beyond the obvious target of B-modes from gravity waves generated during inflation) made possible by these two instruments working in tandem include: (1) the ultimate galaxy cluster survey gathering 10e6 clusters extending to large redshift and measuring their peculiar velocities and temperatures (through the kSZ effect and relativistic corrections to the classic y-distortion spectrum, respectively) (2) a detailed investigation into the nature of the cosmic infrared background (CIB) consisting of at present unresolved dusty high-z galaxies, where most of the star formation in the universe took place, (3) searching for distortions from the perfect CMB blackbody spectrum, which will probe a large number of otherwise inaccessible effects (e.g., energy release through decaying dark matter, the primordial power spectrum on very small scales where measurements today are impossible due to erasure from Silk damping and contamination from non-linear cascading of power from larger length scales). These are but a few of the highlights of the new science that will be made possible with PRISM.Comment: 20 pages Late

Search for bottom-type, vectorlike quark pair production in a fully hadronic final state in proton-proton collisions at s=13 TeV

A search is described for the production of a pair of bottom-type vectorlike quarks (VLQs), each decaying into a b or ¯ b quark and either a Higgs or a Z boson, with a mass greater than 1000 GeV. The analysis is based on data from proton-proton collisions at a 13 TeV center-of-mass energy recorded at the CERN LHC, corresponding to a total integrated luminosity of 137     fb − 1 . As the predominant decay modes of the Higgs and Z bosons are to a pair of quarks, the analysis focuses on final states consisting of jets resulting from the six quarks produced in the events. Since the two jets produced in the decay of a highly Lorentz-boosted Higgs or Z boson can merge to form a single jet, nine independent analyses are performed, categorized by the number of observed jets and the reconstructed event mode. No signal in excess of the expected background is observed. Lower limits are set on the VLQ mass at 95% confidence level equal to 1570 GeV in the case where the VLQ decays exclusively to a b quark and a Higgs boson, 1390 GeV for when it decays exclusively to a b quark and a Z boson, and 1450 GeV for when it decays equally in these two modes. These limits represent significant improvements over the previously published VLQ limits

Machine learning "as a service" for high energy physics (MLaaS4HEP): evolution of a framework for ML-based physics analyses

The scientific success of the LHC experiments at CERN highly depends on the availability of computing resources which efficiently store, process, and analyse the amount of data collected every year. This is ensured by the Worldwide LHC Computing Grid infrastructure that connect computing centres distributed all over the world with high performance network. LHC has an ambitious experimental program for the coming years, which includes large investments and improvements both for the hardware of the detectors and for the software and computing systems, in order to deal with the huge increase in the event rate expected from the High Luminosity LHC (HL-LHC) phase and consequently with the huge amount of data that will be produced. Since few years the role of Artificial Intelligence has become relevant in the High Energy Physics (HEP) world. Machine Learning (ML) and Deep Learning algorithms have been successfully used in many areas of HEP, like online and offline reconstruction programs, detector simulation, object reconstruction, identification, Monte Carlo generation, and surely they will be crucial in the HL-LHC phase. This thesis aims at contributing to a CMS R&D project, regarding a ML "as a Service" solution for HEP needs (MLaaS4HEP). It consists in a data-service able to perform an entire ML pipeline (in terms of reading data, processing data, training ML models, serving predictions) in a completely model-agnostic fashion, directly using ROOT files of arbitrary size from local or distributed data sources. This framework has been updated adding new features in the data preprocessing phase, allowing more flexibility to the user. Since the MLaaS4HEP framework is experiment agnostic, the ATLAS Higgs Boson ML challenge has been chosen as physics use case, with the aim to test MLaaS4HEP and the contribution done with this work

The Challenging Differentiation of Psoriatic Arthritis from Other Arthropathies and Nonspecific Arthralgias in Patients with Psoriasis: Results of a Cross-Sectional Rheumatologic Assessment of a Large Dermatologic Cohort

Aiming to identify the potential challenges in the classification of musculoskeletal manifestations in patients with psoriasis (PsO), this study analyzed the outcomes of a cross-sectional rheumatologic assessment of 1057 PsO patients. In total, 209 had a previous diagnosis of psoriatic arthritis (PsA). Out of the remaining 848 subjects, 293 (35%) were classified as suspected PsA cases according to the rheumatologist’s judgment and/or Early PsA Screening Questionnaire score (EARP) ≥ 3. However, only 14% received a PsA diagnosis, 49% had a PsA-alternative diagnosis, and the remaining 37% had nonspecific arthralgias. Most of the newly diagnosed PsA patients had a symptoms duration ≥1 year (72%) and moderate disease activity (55%) with active oligoarthritis (85%), dactylitis, or enthesitis (35%) as the most frequent clinical pattern. The most frequent PsA-alternative diagnoses were osteoarthritis and fibromyalgia (44% and 41%). The only factors with significant (p < 0.05) utility in discriminating PsA from other diseases and nonspecific arthralgias were young age and EARP score with a history of morning stiffness, swollen joints, or dactylitis. These results demonstrated a high prevalence of suspected musculoskeletal symptoms in PsO patients, with, however, only a small proportion due to PsA. Close collaboration between the dermatologist and rheumatologist plays a crucial role in the differential diagnosis of PsA, as well as in monitoring nonspecific arthralgias for the potential transition to overt PsA

PRISM (Polarized Radiation Imaging and Spectroscopy Mission): an extended white paper

Contains fulltext : 126057.pdf (preprint version ) (Open Access