https://docs.google.com/file/d/1806GOYJ9z7sHeOPI-6ZZ7Ih1Bl7A7XMu/edit?usp=docslist_api&filetype=mspresentation
The VELO Upgrade 2 (VELO U2) for the LHCb experiment relies on the TimeSPOT sensor for enhanced timing resolution and radiation hardness. Efficient simulation is crucial for optimizing the sensor design and predicting performance. Traditional Geant4/TCoDe simulations, while accurate, are computationally intensive, hindering large-scale design studies. This talk presents a novel approach using...
In this contribution we discuss the novel neural network architecture, based on the Kolmogorov-Arnold Representation Theorem, dubbed "Kolmogorov-Arnold Network" (KAN), its variants (like the Chebyshev-KAN, the Jacobi-KAN, the FastKAN), and its applications to numerical resolution of PDEs via the Physics-Informed Neural Network (PINN) framework.
We discuss our implementation of the API for...
Geant4 is a C++ toolkit library for the transport of particles through matter and it is commonly used for the simulation of high energy space missions, allowing for the evaluation of their performance and driving the instrument design. The increasing complexity of the new technology involved for the high-energy Universe observation requires the development of modern large-scale simulations and...
High-performance computing (HPC) has become indispensable for addressing the complex challenges of modern scientific research. From processing massive datasets to running simulations with millions of variables, HPC supports advancements across a range of disciplines. This presentation will provide an overview of the design and implementation of a new HPC data center, focusing on its ability to...
In recent years, blockchain has emerged as a promising technology for managing trusted information and facilitating the management of critical data by businesses and the public while maintaining high levels of security. Permissioned blockchains, unlike permissionless ones, restrict access to a select group of authorized entities, ensuring a controlled and secure environment. It is particularly...
The software toolbox used for "big data" analysis in the last few years is rapidly changing. The adoption of software design approaches able to exploit the new hardware architectures and improve code expressiveness plays a pivotal role in boosting data processing speed, resources optimisation, analysis portability and analysis preservation.
The scientific collaborations in the field of High...
In recent times, the combination of remote sensing and machine learning applications has led to great perspectives in the context of space economy. A flagship use case "AI algorithms for (satellite) imaging reconstruction" has been therefore established within the Working Group 6 (WP6) "Cross-Domain Initiatives and Space Economy" under Spoke 2, to focus on the analysis of satellite and aerial...
In this talk, I will present the progress made in deploying and customizing Rucio as a scalable, metadata-integrated prototype Data Lake as a solution for Data Management (DM) of the Interoperable Data Lake (IDL) project. Rucio is an open-source DM software designed for large-scale scientific experiments such as those in high-energy physics (HEP). Initially developed by CERN for the ATLAS...
The real-time track reconstruction task for LHC experiments shows a processing time which increases significantly as a function of the average number of proton-proton collisions per bunch crossing. The future upgrade to the High-Luminosity LHC (HL-LHC), with way higher levels of simultaneous collisions, could thus lead to a considerable growth in computational cost for the current trigger...
In mission-critical industries, continuous operation exposes equipment to wear that can escalate into costly failures and downtimes. Early anomaly detection is, therefore, essential to maintaining seamless operations. Graph Neural Networks (GNNs) are emerging as a powerful tool for predictive maintenance, offering unparalleled understanding of data from complex interconnected systems of...
Unmodeled methods are extensively employed to detect generic gravitational wave transients (GWTs), including signals that lack precise theoretical modeling. Interestingly, these methods also demonstrate competitive efficiency when applied to well-modeled gravitational wave signals, such as those from compact binary coalescences (CBCs), rivaling the widely used matched-filter approach. In this...
In this talk we will focus on hadronic jets initiated by heavy flavours. In particular, we will examine different observables to study the dead cone effect, i.e. the suppression of collinear QCD radiation around massive quarks, and to investigate the sensitivity of different observable definitions to the presence of quark masses.
Our results are based on all-order resummed predictions at...
The current High Rate Analysis platform offers a general purpose environment where analyzers can scale up their computations. The platform has proven to be able to support diverse use cases: recently, a CMS Coffea-based benchmark analysis has successfully been tested, adding up to the already tested ROOT's RDataFrame benchmark workflows, allowing for an initial comparison between the two...
Clusters counting in a drift chamber represents a highly promising
breakthrough in particle identification (PID) techniques for particle physics
experiments. In this paper, we trained neural network models, including a
Long Short-Term Memory (LSTM) model for the peak-finding algorithm and a
Convolutional Neural Network (CNN) model for the clusterization algorithm,
using various...
In many research and industrial settings, achieving fast, low-latency algorithmic responses is essential. To meet the demands of the upgraded LHC and future High Energy Physics (HEP) detectors, quick and powerful triggers are necessary. In recent years, machine learning algorithms have been widely applied to such tasks, and more recently, solutions based on Field Programmable Gate Arrays...
Lattice QCD is the leading framework for systematically studying the non-perturbative regime of Quantum Chromodynamics (QCD), the theory of strong interactions. Today, lattice methods are essential for high-precision calculations—both current and future—of fundamental quantities in the Standard Model of particle physics. These advancements are made possible by highly-parallelized HPC...
We present "LoopIn", a framework aimed at automating calculations of multi-loop scattering amplitudes for pQFT. It has been designed to have only few user input (process, number of loop, ps-points), from which it can provide numerical values for interference terms, helicity amplitudes or form factors.
"LoopIn" implements a modular structure, for which public codes can be interfaced as...
In this preliminary study I consider and explore the application of Machine Learning algorithms for reconstruction in Super-Kamiokande, the largest Water Cherenkov detector in the world. I simulated event samples to train a custom ResNet-18 based model whose perfomance is presented in this talk. The goal is the development of a Machine Learning based tool to be employed in proton decay...
The upgrade of the CMS apparatus for the HL-LHC will provide unprecedented timing measurement capabilities, in particular for charged particles through the Mip Timing Detector (MTD). One of the main goals of this upgrade is to compensate the deterioration of primary vertex reconstruction induced by the increased pileup of proton-proton collisions by separating clusters of tracks not only in...
Following the last lightning talk given at the 2023 Spoke2 Annual Meeting, about the flagship usecase UC2.2.2 “Quasi interactive analysis of big data with high throughput” of the Work Package 2 “Experimental High Energy Physics”, this contribution will report the status of the ongoing efforts.
Starting from the scientific production and going through the common cloud infrastructure deployment...
One of the most promising methods for evaluating trading strategies relies on the analysis of satellite data. The primary objective of SAIFIN (Satellite data and Artificial Intelligence for FINtech) is to develop an AI-based algorithmic trading system capable of identifying financial trading strategies by leveraging information retrieved from both web sources and satellite data.
The system...
Efficient satellite data management is essential to improve environmental monitoring and support various space economy applications. As part of Working Project 6 (WP6) ‘Cross-Domain Initiatives and Space Economy’ of Spoke 2, we developed a custom library designed to simplify the entire workflow from downloading to pre-processing and analysis of satellite data.
The library facilitates the...
WP6-Spoke2 of ICSC - Italian Research Center on HPC, Big Data and Quantum Computing has a use case dedicated to the integration of machine learning models to enhance Geant4. This is a well-known simulation framework in medical physics that can reproduce particle interactions down to the micrometer scale and below. However, the resources required scale linearly with the complexity of the system...
The search for continuous and persistent gravitational waves emitted by isolated and rotating neutron stars is a top priority for current and future ground-based detectors. However, those searches are typically bounded in sensitivity by their high computational costs. In this talk, I will introduce the flagship use case devoted to the Frequency-Hough algorithm, which performs a blind search...
In this contribution, we define (and test) a pipeline to perform virtual painting recolouring using raw data of X-Ray Fluorescence (XRF) analysis on pictorial artworks. To circumvent the small dataset size, we generate a synthetic dataset, starting from a database of XRF spectra; furthermore, to ensure a better generalisation capacity (and to tackle the issue of in-memory size and inference...
Vector boson scattering (VBS) processes serve as a powerful probe for detecting potential deviations from the Standard Model (SM) of particle physics. Recently, there has been increasing interest in studying VBS, with a particular focus on incorporating the polarization states of the gauge bosons. While the reconstruction of fully leptonic final states is clearer, hadronic final states require...
