M. Zanetti
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View article: Learning to Validate Generative Models: a Goodness-of-Fit Approach
Learning to Validate Generative Models: a Goodness-of-Fit Approach Open
Generative models are increasingly central to scientific workflows, yet their systematic use and interpretation require a proper understanding of their limitations through rigorous validation. Classic approaches struggle with scalability, …
View article: Low-energy single-electron detector with sub-micron resolution
Low-energy single-electron detector with sub-micron resolution Open
Single-electron detectors are a key component of electron microscopes and advanced electron optics experiments. We present a YAG:Ce scintillator-based single-electron detector with a spatial resolution of 1 micrometer at an electron energy…
View article: An Experimental Setup to Study Electron Transport and Thermalization in Cryogenic Para-Hydrogen Crystal Matrices
An Experimental Setup to Study Electron Transport and Thermalization in Cryogenic Para-Hydrogen Crystal Matrices Open
We present an experimental apparatus to investigate electron transport and thermalization in cryogenic para-hydrogen crystal matrices. This paper describes the techniques used to grow and characterize the cryogenic para-hydrogen crystals, …
View article: FEROCE: Front-End RDMA Over Converged Ethernet, a lightweight RoCE endpoint
FEROCE: Front-End RDMA Over Converged Ethernet, a lightweight RoCE endpoint Open
In a DAQ system a large fraction of CPU resources is engaged in networking rather than in data processing. The common network stacks that take care of network traffic usually manipulate data through several copies performing expensive oper…
View article: Measuring the electric dipole moment of the electron using polar molecules in a parahydrogen matrix
Measuring the electric dipole moment of the electron using polar molecules in a parahydrogen matrix Open
This paper outlines the groundwork we have done in preparation for our proposed experiment to measure the electric dipole moment of the electron in barium monofluoride molecules within a cryogenic parahydrogen matrix. We describe the exper…
View article: Front-end RDMA over Converged Ethernet, real-time firmware simulation
Front-end RDMA over Converged Ethernet, real-time firmware simulation Open
Several physics experiments are moving towards new acquisition models. In this work some ideas to implement Remote Direct Memory Access (RDMA) directly on the front-end electronics have been explored, part of the computing farm's CPU resou…
View article: 40 MHz triggerless readout of the CMS Drift Tube muon detector
40 MHz triggerless readout of the CMS Drift Tube muon detector Open
The Level-1 trigger scouting system of the CMS experiment aims at intercepting the intermediate data produced by the L1 trigger processors before the final trigger decision. This system can be complemented by adding the raw stream of data …
View article: Corduliid Emeralds and Other Odonata of the Last Seminatural Venetian Alluvial Plains
Corduliid Emeralds and Other Odonata of the Last Seminatural Venetian Alluvial Plains Open
View article: Triggerless data acquisition pipeline for Machine Learning based statistical anomaly detection
Triggerless data acquisition pipeline for Machine Learning based statistical anomaly detection Open
This work describes an online processing pipeline designed to identify anomalies in a continuous stream of data collected without external triggers from a particle detector. The processing pipeline begins with a local reconstruction algori…
View article: Triggerless data acquisition pipeline for Machine Learning based statistical anomaly detection
Triggerless data acquisition pipeline for Machine Learning based statistical anomaly detection Open
This work describes an online processing pipeline designed to identify anomalies in a continuous stream of data collected without external triggers from a particle detector. The processing pipeline begins with a local reconstruction algori…
View article: Fast kernel methods for data quality monitoring as a goodness-of-fit test
Fast kernel methods for data quality monitoring as a goodness-of-fit test Open
We propose an accurate and efficient machine learning approach for monitoring particle detectors in real-time. The goal is to assess the compatibility of incoming experimental data with a reference dataset, characterising the data behaviou…
View article: Fast kernel methods for Data Quality Monitoring as a goodness-of-fit test
Fast kernel methods for Data Quality Monitoring as a goodness-of-fit test Open
We here propose a machine learning approach for monitoring particle detectors in real-time. The goal is to assess the compatibility of incoming experimental data with a reference dataset, characterising the data behaviour under normal circ…
View article: A fast and flexible machine learning approach to data quality monitoring
A fast and flexible machine learning approach to data quality monitoring Open
We present a machine learning based approach for real-time monitoring of particle detectors. The proposed strategy evaluates the compatibility between incoming batches of experimental data and a reference sample representing the data behav…
View article: Trigger-less readout and unbiased data quality monitoring of the CMS drift tubes muon detector
Trigger-less readout and unbiased data quality monitoring of the CMS drift tubes muon detector Open
The CMS experiment 40 MHz data scouting project is aimed at intercepting the data produced at the level of the detectors’ front-end without the filters induced by hardware-based triggers. A first implementation is realized by the trigger-l…
View article: Muon trigger with fast Neural Networks on FPGA, a demonstrator
Muon trigger with fast Neural Networks on FPGA, a demonstrator Open
The online reconstruction of muon tracks in High Energy Physics experiments is a highly demanding task, typically performed on reconfigurable digital circuits, such as FPGAs. Complex analytical algorithms are executed in a quasi-real-time …
View article: Learning new physics efficiently with nonparametric methods
Learning new physics efficiently with nonparametric methods Open
We present a machine learning approach for model-independent new physics searches. The corresponding algorithm is powered by recent large-scale implementations of kernel methods, nonparametric learning algorithms that can approximate any c…
View article: DQM for Drift Tube Chambers
DQM for Drift Tube Chambers Open
Dataset for DQM for Drift Tube Chambers. The dataset include a reference sample and smaller data samples characterized by anomalous effects. Plots for data visualization are provided.
View article: DQM for Drift Tube Chambers
DQM for Drift Tube Chambers Open
Dataset for DQM for Drift Tube Chambers. The dataset include a reference sample and smaller data samples characterized by anomalous effects. Plots for data visualization are provided.
View article: A horizontally scalable online processing system for trigger-less data acquisition
A horizontally scalable online processing system for trigger-less data acquisition Open
View article: How difficult it was to acquire COVID digital certificate in summer 2021: Response of EU national contact points for cross-border health care
How difficult it was to acquire COVID digital certificate in summer 2021: Response of EU national contact points for cross-border health care Open
View article: Learning new physics efficiently with nonparametric methods
Learning new physics efficiently with nonparametric methods Open
We present a machine learning approach for model-independent new physics searches. The corresponding algorithm is powered by recent large-scale implementations of kernel methods, nonparametric learning algorithms that can approximate any c…
View article: Enhance pluvial flood risk assessment using spatio-temporal machine learning models
Enhance pluvial flood risk assessment using spatio-temporal machine learning models Open
<p>Extreme weather events (e.g., heavy rainfall) are natural hazards that pose increasing threats to many sectors and across sub-regions worldwide (IPCC, 2014), exposing people and assets to damaging effects. In order to predict pluv…
View article: Learning new physics from an imperfect machine
Learning new physics from an imperfect machine Open
We show how to deal with uncertainties on the Standard Model predictions in an agnostic new physics search strategy that exploits artificial neural networks. Our approach builds directly on the specific Maximum Likelihood ratio treatment o…
View article: Muon detection in electron-positron annihilation for muon collider studies
Muon detection in electron-positron annihilation for muon collider studies Open
View article: Learning New Physics from an Imperfect Machine
Learning New Physics from an Imperfect Machine Open
We show how to deal with uncertainties on the Standard Model predictions in an agnostic new physics search strategy that exploits artificial neural networks. Our approach builds directly on the specific Maximum Likelihood ratio treatment o…
View article: A horizontally scalable online processing system for trigger-less data acquisition
A horizontally scalable online processing system for trigger-less data acquisition Open
The majority of high energy physics experiments rely on data acquisition and hardware-based trigger systems performing a number of stringent selections before storing data for offline analysis. The online reconstruction and selection perfo…
View article: Conceptual design report for the LUXE experiment
Conceptual design report for the LUXE experiment Open
This Conceptual Design Report describes LUXE (Laser Und XFEL Experiment), an experimental campaign that aims to combine the high-quality and high-energy electron beam of the European XFEL with a powerful laser to explore the uncharted terr…
View article: Muon trigger with fast Neural Networks on FPGA, a demonstrator
Muon trigger with fast Neural Networks on FPGA, a demonstrator Open
The online reconstruction of muon tracks in High Energy Physics experiments is a highly demanding task, typically performed with programmable logic boards, such as FPGAs. Complex analytical algorithms are executed in a quasi-real-time envi…
View article: NPLM: Learning Multivariate New Physics
NPLM: Learning Multivariate New Physics Open
Archive of synthetic data used for the studies presented in arXiv:1912.12155
View article: NPLM: Learning Multivariate New Physics
NPLM: Learning Multivariate New Physics Open
Archive of synthetic data used for the studies presented in arXiv:1912.12155