Surfing the high energy output branch of nonlinear energy harvesters

Hysteresis and multistability are fundamental phenomena of driven nonlinear oscillators, which, however, restrict many applications such as mechanical energy harvesting. We introduce an electrical control mechanism to switch from the low to the high energy output branch of a nonlinear energy harvester by exploiting the strong interplay between its electrical and mechanical degrees of freedom. This method improves the energy conversion efficiency over a wide bandwidth in a frequency-amplitude-varying environment using only a small energy budget. The underlying effect is independent of the device scale and the transduction method and is explained using a modified Duffing oscillator model.

Effects of spin on high-energy radiation from accreting black holes

Observations of jets in X-ray binaries show a correlation between radio power and black hole spin. This correlation, if confirmed, points toward the idea that relativistic jets may be powered by the rotational energy of black holes. In order to examine this further, we perform general relativistic radiative transport calculations on magnetically arrested accretion flows, which are known to produce powerful jets via the Blandfordâ Znajek (BZ) mechanism. We find that the X-ray and γ-ray emission strongly depend on spin and inclination angle. Surprisingly, the high-energy power does not show the same dependence on spin as the BZ jet power, but instead can be understood as a redshift effect. In particular, photons observed perpendicular to the spin axis suffer little net redshift until originating from close to the horizon. Such observers see deeper into the hot, dense, highly magnetized inner disk region. This effect is largest for rapidly rotating black holes due to a combination of frame dragging and decreasing horizon radius. While the X-ray emission is dominated by the near horizon region, the near-infrared (NIR) radiation originates at larger radii. Therefore, the ratio of X-ray to NIR power is an observational signature of black hole spin.

Machine learning as a service for high energy physics (MLaaS4HEP): a service for ML-based data analyses

With the CERN LHC program underway, there has been an acceleration of data growth in the High Energy Physics (HEP) field and the usage of Machine Learning (ML) in HEP will be critical during the HL-LHC program when the data that will be produced will reach the exascale. ML techniques have been successfully used in many areas of HEP nevertheless, the development of a ML project and its implementation for production use is a highly time-consuming task and requires specific skills. Complicating this scenario is the fact that HEP data is stored in ROOT data format, which is mostly unknown outside of the HEP community. The work presented in this thesis is focused on the development of a ML as a Service (MLaaS) solution for HEP, aiming to provide a cloud service that allows HEP users to run ML pipelines via HTTP calls. These pipelines are executed by using the MLaaS4HEP framework, which allows reading data, processing data, and training ML models directly using ROOT files of arbitrary size from local or distributed data sources. Such a solution provides HEP users non-expert in ML with a tool that allows them to apply ML techniques in their analyses in a streamlined manner. Over the years the MLaaS4HEP framework has been developed, validated, and tested and new features have been added. A first MLaaS solution has been developed by automatizing the deployment of a platform equipped with the MLaaS4HEP framework. Then, a service with APIs has been developed, so that a user after being authenticated and authorized can submit MLaaS4HEP workflows producing trained ML models ready for the inference phase. A working prototype of this service is currently running on a virtual machine of INFN-Cloud and is compliant to be added to the INFN Cloud portfolio of services.

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.

Uno studio sulla massima deflessione degli ultra-high-energy cosmic rays da parte dei campi magnetici primordiali

Gli Ultra-High-Energy Cosmic Rays sono dei raggi cosmici-dotati di energia estremamente elevata-che raggiungono la Terra con un bassissimo rateo e dei quali abbiamo pochi dati a riguardo; le incertezze riguardano la loro composizione, la loro sorgente, i metodi di accelerazione e le caratteristiche dei campi magnetici che li deviano durante il loro cammino. L’obiettivo di questo studio è determinare quali modelli di campo magnetico possano descrivere correttamente la propagazione degli UHECRs, andando a fare un confronto con i dati sperimentali a disposizione; infatti, quello che osserviamo è una distribuzione isotropa nel cielo e, di conseguenza, i modelli teorici di propagazione, per poter essere accettati, devono rispecchiare tale comportamento. Sono stati testati nove modelli di campo magnetico tratti da simulazioni cosmologiche, andando a considerare due diverse composizione per i CRs (simil-ferro e simil-protone) e il risultato ha dato delle risposte positive solo per tre di essi. Tali modelli, per cui troviamo accordo, sono caratterizzati da una scala di inomegeneità più ampia rispetto a quella dei modelli scartati, infatti, analizzando il loro spettro di potenza, il maggior contributo è dato da fluttuazioni di campo magnetico su scale di 10 Mpc. Ciò naturalmente, viste anche le poche informazioni riguardo ai campi magnetici intergalattici, ci porta a pensare che campi di questo tipo siano favoriti. Inoltre, per tali modelli, gli esiti sono risultati particolarmente in accordo con i dati sperimentali, considerando CRs con composizione simile al ferro: ciò fa pensare che tale composizione possa essere quella effettiva.

Development of a heterogeneous clustering algorithm for particle shower reconstruction in high energy physics using the SYCL abstraction layer

Nei prossimi anni è atteso un aggiornamento sostanziale di LHC, che prevede di aumentare la luminosità integrata di un fattore 10 rispetto a quella attuale. Tale parametro è proporzionale al numero di collisioni per unità di tempo. Per questo, le risorse computazionali necessarie a tutti i livelli della ricostruzione cresceranno notevolmente. Dunque, la collaborazione CMS ha cominciato già da alcuni anni ad esplorare le possibilità offerte dal calcolo eterogeneo, ovvero la pratica di distribuire la computazione tra CPU e altri acceleratori dedicati, come ad esempio schede grafiche (GPU). Una delle difficoltà di questo approccio è la necessità di scrivere, validare e mantenere codice diverso per ogni dispositivo su cui dovrà essere eseguito. Questa tesi presenta la possibilità di usare SYCL per tradurre codice per la ricostruzione di eventi in modo che sia eseguibile ed efficiente su diversi dispositivi senza modifiche sostanziali. SYCL è un livello di astrazione per il calcolo eterogeneo, che rispetta lo standard ISO C++. Questo studio si concentra sul porting di un algoritmo di clustering dei depositi di energia calorimetrici, CLUE, usando oneAPI, l'implementazione SYCL supportata da Intel. Inizialmente, è stato tradotto l'algoritmo nella sua versione standalone, principalmente per prendere familiarità con SYCL e per la comodità di confronto delle performance con le versioni già esistenti. In questo caso, le prestazioni sono molto simili a quelle di codice CUDA nativo, a parità di hardware. Per validare la fisica, l'algoritmo è stato integrato all'interno di una versione ridotta del framework usato da CMS per la ricostruzione. I risultati fisici sono identici alle altre implementazioni mentre, dal punto di vista delle prestazioni computazionali, in alcuni casi, SYCL produce codice più veloce di altri livelli di astrazione adottati da CMS, presentandosi dunque come una possibilità interessante per il futuro del calcolo eterogeneo nella fisica delle alte energie.

Ultradünne molekulare Filme auf Isolatoreinkristalloberflächen : strukturelle und infrarotoptische Eigenschaften

Surfaces, insulators, thin films, low-energy electron diffraction, infrared-spectroscopy, helium atom scattering, quantum chemistry

Developing a non-public research software for public use

EasyLEED is a program designed for the extraction of intensity-energy spectra from low-energy electron diffraction patterns. It can be used to get information about the position of individual atoms on a surface of some substance. The goal of this thesis is to make easyLEED useful in LEED-research. It is achieved by adding new features, i.e. plotting intensity-energy spectra, setting tracking parameters and allowing exporting and importing of settings and spot location data, to the program. The detailed description of these added features and how they’re done and how they impact on the usefulness of the program in research are presented in this thesis. Improving the calculational part of the program is not discussed.

Adsorption, orientation and thermal decomposition of copper(II) hexafluoroacetylacetonate on rutile TiO2(110)

We have investigated the adsorption and thermal decomposition of copper hexafluoroacetylacetonate (Cu-11(hfaC)(2)) on single crystal rutile TiO2(110). Low energy electron diffraction shows that room temperature saturation coverage of the Cu-II(hfac)(2) adsorbate forms an ordered (2 x 1) over-layer. X-ray and ultra-violet photoemission spectroscopy of the saturated surface were recorded as the sample was annealed in a sequential manner to reveal decomposition pathways. The results show that the molecule dissociatively adsorbs by detachment of one of the two ligands to form hfac and Cu-1(hfac) which chemisorb to the substrate at 298 K. These ligands only begin to decompose once the surface temperature exceeds 473 K where Cu core level shifts indicate metallisation. This reduction from Cu(I) to Cu(0) takes place in the absence of an external reducing agent and without disproportionation and is accompanied by the onset of decomposition of the hfac ligands. Finally, C K-edge near edge X-ray absorption fine structure experiments indicate that both the ligands adsorb aligned in the < 001 > direction and we propose a model in which the hfac ligands adsorb on the 5-fold coordinated Ti atoms and the Cu-1(hfac) moiety attaches to the bridging O atoms in a square planar geometry. The calculated tilt angle for these combined geometries is approximately 10 degrees to the surface normal.

Surface geometry of Cu{531}

We present a combined quantitative low-energy electron diffraction (LEED) and density-functional theory (DFT) study of the chiral Cu{531} surface. The surface shows large inward relaxations with respect to the bulk interlayer distance of the first two layers and a large expansion of the distance between the fourth and fifth layers. (The latter is the first layer having the same coordination as the Cu atoms in the bulk.) Additional calculations have been performed to study the likelihood of faceting by comparing surface energies of possible facet terminations. No overall significant reduction in energy with respect to planar {531} could be found for any of the tested combinations of facets, which is in agreement with the experimental findings.

The adsorption geometry of sulphur on Ir{100}: a quantitative LEED study

A quantitative low energy electron diffraction (LEED) analysis has been performed for the p(2 x 2)-S and c(2 x 2)-S surface structures formed by exposing the (1 x 1) phase of Ir{100} to H2S at 750 K. S is found to adsorb on the fourfold hollow sites in both structures leading to Pendry R-factor values of 0.17 for the p(2 x 2)-S and 0.16 for the c(2 x 2)-S structures. The distances between S and the nearest and next-nearest Ir atoms were found to be similar in both structures: 2.36 +/- 0.01 angstrom and 3.33 +/- 0.01 angstrom, respectively. The buckling in the second substrate layer is consistent with other structural studies for S adsorption on fcc{100} transition metal surfaces: 0.09 angstrom for p(2 x 2)-S and 0.02 angstrom for c(2 x 2)-S structures. The (1 x 5) reconstruction, which is the most stable phase for clean Ir{100}, is completely lifted and a c(2 x 2)-S overlayer is formed after exposure to H,S at 300 K followed by annealing to 520 K. CO temperature-programmed desorption (TPD) experiments indicate that the major factor in the poisoning of Ir by S is site blocking. (c) 2005 Elsevier B.V. All rights reserved.

Phase mixing and phase separation accompanying the catalytic oxidation of CO on Ir{100}

The co-adsorption of CO and O on the unreconstructed (1 x 1) phase of Ir {100} was examined by low energy electron diffraction (LEED) and temperature programmed desorption (TPD). When CO is adsorbed at 188 K onto the Ir{100} surface precovered with 0.5 ML O, a mixed c(4 x 2)-(2O + CO) overlayer is formed. All CO is oxidised upon heating and desorbs as CO2 in three distinct stages at 230 K, 330 K and 430 K in a 2:1:2 ratio. The excess oxygen left on the surface after all CO has reacted forms an overlayer with a LEED pattern with p(2 x 10) periodicity. This overlayer consists of stripes with a local p(2 x 1)-O arrangement of oxygen atoms separated by stripes of uncovered It. When CO is adsorbed at 300 K onto the surface precovered with 0.5 ML O an apparent (2 x 2) LEED pattern is observed. LEED IV analysis reveals that this pattern is a superposition of diffraction patterns from islands of c(2 x 2)-CO and p(2 x 1)-O structures on the surface. Heating this co-adsorbed overlayer leads to the desorption of CO, in two stages at 330 K and 430 K; the excess CO (0.1 ML) desorbs at 590 K. LEED IV structural analysis of the mixed c(4 x 2) O and CO overlayer shows that both the CO molecules and the O atoms occupy bridge sites. The O atoms show significant lateral displacements of 0.14 angstrom away from the CO molecules; the C-O bond is slightly expanded with respect to the gas phase (1.19 angstrom); the modifications of the Ir substrate with respect to the bulk-terminated surface are very small. (c) 2006 Elsevier B.V. All rights reserved.

Experimental structure determination of the chemisorbed overlayers of chlorine and iodine on Au{111}

We have performed an experimental structure determination of the ordered p(sqrt[3] x sqrt[3])R30 degrees structures of chlorine and iodine on Au{111} using low-energy electron diffraction (LEED). Despite great similarities in the structure of the underlying substrate, which shows only minor deviations from the bulk positions in both cases, chlorine and iodine are found to adsorb in different adsorption sites, fcc and hcp hollow sites, respectively. The experimental Au-Cl and Au-I bond lengths of 2.56 and 2.84 A are close to the sums of the covalent radii, supporting the view that the bond is essentially covalent in nature; however, they are significantly shorter than predicted theoretically.