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We report a study on several static and dynamic properties of liquid Pd and Pt metals at thermodynamic conditions near their respective triple points. The calculations have been carried out by an ab initio molecular dynamics simulation technique. Results are reported for several static structural magnitudes which are compared with the available X-ray diffraction. As for the dynamic properties, results have been obtained for both single and collective dynamical magnitudes as well as for some transport coeffcients which are compared with the corresponding experimental data.

Liquid Ni has previously been studied by different approaches such as molecular dynamics simulations and experimental techniques including inelastic neutron and X-ray scattering. Although some puzzling results, such as the shape of the sound dispersion curve for q ≤ 1.0 Å−1, have already been sorted out, there still persist some discrepancies, among different studies, for greater q-values. We have performed ab initio simulation calculations which show how those differences can be reconciled. Moreover, we have found that the transverse current spectral functions have some features which, so far, had previously been shown by high pressure liquid metals.

We present preliminary results on the fabrication of patterned surfaces by Direct Laser Interference Patterning and the characterization and theoretical interpretation of their infrared emissivities. The upgraded experimental method is capable of studying the full directional emission of samples under a controlled atmosphere at high temperatures. The effects of surface patterning can be quantitatively studied and modeled using a numerical method based on rigorous coupled-wave analysis (RCWA), a technique usually employed for periodic surfaces. The results show that laser interference patterning is capable of modifying the infrared emission of metallic materials, and that these changes can be accurately measured and numerically reproduced.

In this work, we discuss the challenges associated with measuring and interpreting the vibrational properties of nanomaterials at mid- and far-infrared frequencies, where vibrational bands are often broad and overlapping. This issue is compounded by the complex interaction between infrared light and particulate samples, which depends on packing density and particle connectivity. Preliminary results concerning the far-infrared optical properties of Fe3O4 nanoparticles have been obtained using the two most reliable methods (specular reflectance and attenuated total reflectance). These results are compared to one another and to their Raman counterparts. Finally, the influences of particle size and composition on the vibrational spectra are qualitatively discussed.

The ATLAS Eventlndex is the global catalogue of all ATLAS real and simulated events. During the LHC long shutdown between Run 2 (20152018) and Run 3 (2022-2025) all its components were substantially revised and a new system was deployed for the start of Run 3 in Spring 2022. The new core storage system, based on HBase tables with a SQL interface provided by Phoenix, allows much faster data ingestion rates and scales much better than the old one to the data rates expected for the end of Run 3 and beyond. All user interfaces were also revised and a new command-line interface and web services were also deployed. The new system was initially populated with all existing data relative to Run 1 and Run 2 datasets, and then put online to receive Run 3 data in real time. After extensive testing, the old system, which ran in parallel to the new one for a few months, was finally switched off in October 2022. This paper describes the new system, the move of all existing data from the old to the new storage schemas and the operational experience gathered so far.

The ATLAS EventIndex is the global catalogue of all ATLAS real and simulated events. During the LHC long shutdown between Run 2 (20152018) and Run 3 (2022-2025) its components were substantially revised, and a new system was deployed for the start of Run 3 in Spring 2022. The new core storage system is based on HBase tables with a Phoenix interface. It allows faster data ingestion rates and scales better than the old system. This paper describes the data collection, the technical design of the core storage, and the properties that make it fast and efficient, namely the compact and optimized design of the events table, which already holds more than 400 billion entries, and all the auxiliary tables, and the EventIndex Supervisor, in charge of orchestrating the whole data collection, now simplified thanks to the Loaders, the Spark jobs that load the data into the new core system. The extractors, in charge of preparing the pieces of data that the loaders will put into the final back-end, have been updated too. The data migration from HDFS to HBase and Phoenix is also described.

ML/DL techniques have shown their power in the improvement of several studies and tasks in HEP, especially in physics analysis. Our approach has been to take a number of the ML/DL tools provided by several open-source platforms and apply them to several classification problems, for instance, to the tt¯ resonance extraction in the LHC experiments. Gradient-boosting Trees, Random Forest, Artificial Neural Networks (ANN), etc. have been used and optimized by means of adjusting several hyperparameters to control overfitting. On top of this, data simulation with traditional models is computationally very demanding, making the use of generative models an alternative for generating simulated Monte Carlo events with similar quality at a lower computational cost. This could help to produce more simulated data statistics available for better sensitivity and more accurate assessment of systematic errors in potential Physics Beyond Standard Model discoveries. In this work, we study the use of generative models based on Deep Learning as faster Monte Carlo event generators in the LHC context, reducing the time and energy cost of currently used methods. In particular, we focus on different configurations of Variational Autoencoders, taking as a starting point the well-known β-VAE and proposing the α-VAE as a new and simpler VAE architecture that improves the results in some experiments. Considerations will be made about the reliability of these simulated data when they are produced with very high statistics.

The ATLAS Spanish Tier-1 and Tier-2s have more than 18 years of experience in the deployment and development of LHC computing components and their successful operation. The sites are actively participating in, and in some cases coordinating, R&D computing activities in the LHC Run 3 and developing the computing models needed in the HL-LHC period. In this contribution, we present details on the integration of some components, such as HPC computing resources to execute ATLAS simulation workflows; the development of new techniques to improve efficiency in a cost-effective way; and improvements in Data Organization, Management and Access through storage consolidations, the use of data caches, and improving experiment data catalogues, through contributions such as Event Index. The design and deployment of novel analysis facilities using GPUs together with CPUs and techniques like Machine Learning are also presented. ATLAS Tier-1 and Tier-2 sites in Spain, are, and will be, contributing to significant R&D in computing and evaluating different models for improving performance of computing and data storage capacity in the LHC High Luminosity era.

The resources of the HPC centers are a potential aid to meet the future challenges of HL-LHC [1] in terms of computational requirements. Spanish HPC centers have recently been used to implement all necessary edge services to integrate resources into the LHC experiment workflow management system. In this article, we describe the integration of ATLAS with the extension plan to other LHC experiments. We chose to configure a dedicated ARC-CE [2] and interact with the HPC login and transfer nodes using ssh commands. The repository that includes a partial copy of the ATLAS experiment software on CVMFS is packaged in a singularity image to overcome network isolation for HPC nodes and reduce software requirements. ATLAS provided the initial container, and the authors adapted it to the specific HPC environment. This article shows the Spanish contribution to the simulation of experiments after the Spanish Ministry of Science agreement and the Barcelona Supercomputing Center (BSC), the center that operates MareNostrum 4. Finally, we discuss some challenges to take advantage of the next generation of HPC machines with heterogeneous architecture combining CPU and GPU.

Pseudo Schell-model sources were introduced and studied in the scalar domain as those partially coherent sources that present a degree of coherence depending on the difference between the radial coordinates of the two considered points. In this work we study the propagation features of a class of beams radiated from sources of this kind, but endowed with a vectorial nature. The polarization pattern and the degree of polarization are not uniform across the beam section but remain invariant upon free paraxial propagation. On the other hand, their coherence and irradiance features are also non-uniform but in this case they change at each z-plane. The field characteristics can be varied on acting on the free parameters of the cross-spectral density matrix of the source.

Recently, the use of full Poincaré beams for extracting the Mueller matrix of a sample has been proposed. These beams present all possible polarization states across their transverse section. By placing a CCD camera behind a simple polarization analyzer formed by a quarter wave phase plate and a linear polarizer, a polarization map of the beam cross section can be obtained. This polarization map is modified when a sample is inserted before the polarization state analyzer. Comparison of these two polarization maps allows to obtain the Mueller matrix of the sample. An overdetermined system of linear equations (thousands of equations) can be written from this comparison. Standard mathematical methods are used to find optimum solution of this overdetermined system of equations. Some experimental results will be presented to check the performance of the proposed polarimetric method.

The ATLAS Spanish Tier-1 and Tier-2s have more than 15 years of experience in the deployment and development of LHC computing components and their successful operations. The sites are already actively participating in, and even coordinating, emerging R&D computing activities and developing new computing models needed for the Run3 and HighLuminosity LHC periods. In this contribution, we present details on the integration of new components, such as High Performance Computing resources to execute ATLAS simulation workflows. The development of new techniques to improve efficiency in a cost-effective way, such as storage and CPU federations is shown in this document. Improvements in data organization, management and access through storage consolidations (“data-lakes”), the use of data caches, and improving experiment data catalogs, like Event Index, are explained in this proceeding. The design and deployment of new analysis facilities using GPUs together with CPUs and techniques like Machine Learning will also be presented. Tier-1 and Tier-2 sites, are, and will be, contributing to significant R&D in computing, evaluating different models for improving performance of computing and data storage capacity in the High-Luminosity LHC era.

The Event Index service of the ATLAS experiment at the LHC keeps references to all real and simulated events. Hadoop Map files and HBase tables are used to store the Event Index data, a subset of data is also stored in the Oracle database. Several user interfaces are currently used to access and search the data, from a simple command line interface, through a programmable API, to sophisticated graphical web services. It provides a dynamic graph-like overview of all available data (and data collections). Data are shown together with their relations, like paternity or overlaps. Each data entity then gives users a set of actions available for the referenced data. Some actions are provided directly by the Event Index system, others are just interfaces to different ATLAS services. In many cases, specialized views are offered for detailed data inspection, such as histograms, Venn diagrams, etc. This paper documents the current status of the service, its features and performance. The future system evolution to the new Event Index architecture based on the Apache Phoenix is also described as well as possible extension to a more general framework for giving a new, more intuitive access to experiment data.

The ATLAS EventIndex was designed in 2012-2013 to provide a global event catalogue and limited event-level metadata for ATLAS analysis groups and users during the LHC Run 2 (2015-2018). It provides a good and reliable service for the initial use cases (mainly event picking) and several additional ones, such as production consistency checks, duplicate event detection and measurements of the overlaps of trigger chains and derivation datasets. The LHC Run 3, starting in 2021, will see increased data-taking and simulation production rates, with which the current infrastructure would still cope but may be stretched to its limits by the end of Run 3. This proceeding describes the implementation of a new core storage service that will be able to provide at least the same functionality as the current one for increased data ingestion and search rates, and with increasing volumes of stored data. It is based on a set of HBase tables, with schemas derived from the current Oracle implementation, coupled to Apache Phoenix for data access; in this way we will add to the advantages of a BigData based storage system the possibility of SQL as well as NoSQL data access, allowing to re-use most of the existing code for metadata integration.

The ATLAS EventIndex currently runs in production in order to build a complete catalogue of events for experiments with large amounts of data. The current approach is to index all final produced data files at CERN Tier0, and at hundreds of grid sites, with a distributed data collection architecture using Object Stores to temporarily maintain the conveyed information, with references to them sent with a Messaging System. The final backend of all the indexed data is a central Hadoop infrastructure at CERN; an Oracle relational database is used for faster access to a subset of this information. In the future of ATLAS, instead of files, the event should be the atomic information unit for metadata, in order to accommodate future data processing and storage technologies. Files will no longer be static quantities, possibly dynamically aggregating data, and also allowing event-level granularity processing in heavily parallel computing environments. It also simplifies the handling of loss and or extension of data. In this sense the EventIndex may evolve towards a generalized whiteboard, with the ability to build collections and virtual datasets for end users. This proceedings describes the current Distributed Data Collection Architecture of the ATLAS EventIndex project, with details of the Producer, Consumer and Supervisor entities, and the protocol and information temporarily stored in the ObjectStore. It also shows the data flow rates and performance achieved since the new Object Store as temporary store approach was put in production in July 2017. We review the challenges imposed by the expected increasing rates that will reach 35 billion new real events per year in Run 3, and 100 billion new real events per year in Run 4. For simulated events the numbers are even higher, with 100 billion events/year in run 3, and 300 billion events/year in run 4. We also outline the challenges we face in order to accommodate future use cases in the EventIndex.

The ATLAS EventIndex has been in operation since the beginning of LHC Run 2 in 2015. Like all software projects, its components have been constantly evolving and improving in performance. The main data store in Hadoop, based on MapFiles and HBase, can work for the rest of Run 2 but new solutions are explored for the future. Kudu offers an interesting environment, with a mixture of BigData and relational database features, which look promising at the design level. This environment is used to build a prototype to measure the scaling capabilities as functions of data input rates, total data volumes and data query and retrieval rates. In this proceedings we report on the selected data schemas and on the current performance measurements with the Kudu prototype.

Gaseous Electron Multipliers (GEM) are well known for stable operation at high particle fluxes. We present a study of the intrinsic limits of GEMdetectors when exposed to very high particle fluxes of the order of MHz/mm2. We give an interpretation to the variations of the effective gain, which, as a function of the particle flux, first increases and then decreases. We also discuss the reduction of the ion back-flow with increasing flux. We present measurements and simulations of a triple GEM detector, describing its behaviour in terms of accumulation of positive ions that results in changes of the transfer fields and the amplification fields. The behaviour is expected to be common to all multi-stage amplification devices where the efficiency of transferring the electrons from one stage to the next one is not 100%.

Several static and dynamic properties of liquid transition metals Cr, Mn and Co are studied for the first time using the orbital free ab-initio molecular dynamics simulation (OF-AIMD). This method is based on the density functional theory (DFT) which accounts for the electronic energy of the system whereas the interionic forces are derived from the electronic energy via the Hellman-Feynman theorem. The external energy functional is treated with a local pseudopotential. Results are reported for static structure factors, isothermal compressibility, diffusion coeffcients, sound velocity and viscosity and comparison is performed with the available experimental data and other theoretical calculations.

A large number of environmental samples are routinely measured world-wide using gamma-ray spectrometry some of its assets being easy sample preparation and comprehensive data for many radionu-clides in one analysis. Although other techniques can be considered more suitable for analysing 238U in environmental samples, it is also routinely done by gamma-ray spectrometry. One mainly uses γ-ray emissions following the decay of the first daughter, 234Th, for determining the 238U activity. However, the low-energy gamma-rays at 63 keV and 92.5 keV are very difficult to quantify in a robust way due to high attenuation and interferences. This paper quantifies parameters affecting the possibility of making robust quantification of 238U via 234Th using gamma-ray spectrometry. It addresses the use of correct decay data, suitable detectors, optimised sample size, enhanced spectral amplification, correction for peak interferences and control of background.

The static and dynamic properties of liquid Sn at two different thermodynamic states have been studied from the Orbital Free Ab-Initio Molecular Dynamics (OFAIMD) simulation method. This method is based on the density functional theory (DFT) of Hohenberg and Kohn. The exchange and correlation interaction is described here with the local density approximation (LDA). We, in this study, have developed a pseudopotential model to describe the external non-Coulombic interaction acting on an electron; this is an essential ingredient of the theory. We have studied several static and dynamic properties of the system. The calculated results are found to be good in agreement with the available experimental data. They are also found to be of similar accuracy as those of other ab-initio studies.