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New challenges for distributed computing at the CMS experiment

JOURNAL OF INSTRUMENTATION 2020年第7期15卷

作者： Krammer, N. Austrian Acad Sci Inst High Energy Phys Vienna Austria

The Large Hadron Collider (LHC) experiments soon step into the next period of run-3 data taking with an increased data rate and high pileup requiring an excellent working computing infrastructure. In the future High-Luminosity LHC (HL-LHC) data-taking period, the compute, storage and network facilities have to be further extended by large factors and flexible and sophisticated computing models are essential. New techniques of modern state-of-the-art methods in physics analysis and data science, Deep Learning and Big data tools, are crucial to handle high-dimensional and more complex problems. Beside flexible cloud computing technologies the usage of High Performance Computing (HPC) at the LHC experiments are explored. In this presentation, I will discuss the LHC run-3 and future HL-LHC runs computing technologies and the utilization of modern physics analysis and data science methods for the increasing and complex demands of large-scale scientific computing.

关键词： Computing (architecture, farms, GRID for recording, storage, archiving, and distribution of data) Analysis and statistical methods data processing methods

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Integrated software for the analysis of high-resolution scattering signals during mm-wave beam injection

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JOURNAL OF INSTRUMENTATION 2020年第1期15卷

作者： Baiocchi, B. Bin, W. Bruschi, A. Figini, L. Tartari, U. Alessi, E. D'Arcangelo, O. CNR Inst Plasma Sci & Technol Via R Cozzi 53 I-20125 Milan Italy ENEA CR Frascati Fus & Nucl Safety Dept Via E Fermi 45 I-00044 Rome Italy

Recently, during Collective Thomson Scattering (CTS) measurements at mm-waves aimed at studying the ion dynamics in fusion plasmas, strong signals of scattering of the injected beam with non-CTS origin have been detected. A possible explanation of these signals in terms of parametric decay instabilities (PDIs) of the injected wave with power threshold much lower than previously envisaged by theory was proposed [1, 2]. The experimental activity with CTS diagnostic at FTU is aimed at two purposes: the characterization of the thermal ion distribution function and the investigation of the possible low power PDIs processes foreseen by the recent models. In order to ease the data analysis, a set of data processing tools has been integrated on purpose, with an activity started in 2014. Here we present the last implementation of an integrated data analysis tool, aimed at the investigation of the signals detected with the CTS diagnostic. The last version of the software integrates information included in the raw spectra of scattered radiation with the modeled ECE emission, with the aim of providing calibrated spectra improved with respect to the ones provided up to now. The correct calibration of the signals on the real line of sight of the beams is helpful to better distinguish anomalous emissions from less powerful CTS radiation. In addition, the analysis tool compares the calibrated spectra with the ones predicted considering real scattering parameters evaluated by means of realistic beam-trajectories, changing during the pulse, allowing also to extract information on ion dynamics and plasma composition. The last version of the software, which takes into account also multi-reflection beam-tracing simulations in both polarization modes in support to the scattering experiments, is presented.

关键词： Analysis and statistical methods data processing methods Simulation methods and programs

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Reconstruction in an imaging calorimeter for HL-LHC

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JOURNAL OF INSTRUMENTATION 2020年第6期15卷

作者： Di Pilato, A. Chen, Z. Pantaleo, F. Rovere, M. Univ Bari Piazza Umberto I I-70121 Bari Italy Natl Inst Nucl Phys INFN Sez Bari Via Amendola 173 I-70126 Bari Italy Northwestern Univ 633 Clark St Evanston IL 60208 USA European Org Nucl Res CERN Esplanade Particules 1 CH-1211 Meyrin Switzerland

The CMS endcap calorimeter upgrade for the High Luminosity LHC in 2027 uses silicon sensors to achieve radiation tolerance, with the further benefit of a very high readout granularity. Small scintillator tiles with individual SiPM readout are used in regions permitted by the radiation levels. A reconstruction framework is being developed to fully exploit the granularity and other significant features of the detector like precision timing, especially in the high pileup environment of HL-LHC. An iterative clustering framework (TICL) has been put in place, and is being actively developed. The framework takes as input the clusters of energy deposited in individual calorimeter layers delivered by the CLUE algorithm, which has recently been revised and tuned. Mindful of the projected extreme pressure on computing capacity in the HL-LHC era, the algorithms are being designed with modern parallel architectures in mind. Important speedup has recently been obtained for the clustering algorithm by running it on GPUs. Machine learning techniques are being developed and integrated into the reconstruction framework. This paper will describe the approaches being considered and show first results.

关键词： Computing (architecture, farms, GRID for recording, storage, archiving, and distribution of data) data processing methods Pattern recognition, cluster finding, calibration and fitting methods Software architectures (event data models, frameworks and databases)

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Efficient and versatile toolbox for analysis of time-tagged measurements

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JOURNAL OF INSTRUMENTATION 2021年第8期16卷

作者： Lin, Z. Schweickert, L. Gyger, S. Jons, K. D. Zwiller, V. Royal Inst Technol Dept Appl Phys Roslagstullsbacken 21 S-11421 Stockholm Sweden Tianjin Univ Sch Precis Instrument & Optoelect Engn Weijin Rd 92 Tianjin Peoples R China Paderborn Univ Dept Phys D-33098 Paderborn Germany

Acquisition and analysis of time-tagged events is a ubiquitous tool in scientific and industrial applications. With increasing time resolution, number of input channels, and acquired events, the amount of data can be overwhelming for standard processing techniques. We developed the Extensible Time-tag Analyzer (ETA), a powerful and versatile, yet easy to use software to efficiently analyze and display time-tagged data. Our tool allows for flexible extraction of correlation from time-tagged data beyond start-stop measurements that were traditionally used. A combination of state diagrams and simple code snippets allows for analysis of arbitrary complexity while keeping computational efficiency high.

关键词： data processing methods Detector control systems (detector and experiment monitor- ing and slow-control systems architecture hardware algorithms databases) Simulation methods and programs Analysis and statistical methods

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Photon radiation effects in kinematic reconstruction of top quarks

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JOURNAL OF INSTRUMENTATION 2021年第12期16卷

作者： Dobur, D. Knolle, J. Mestdach, G. Skovpen, K. Univ Ghent Sint Pietersnieuwstr 33 B-9000 Ghent Belgium

Kinematic reconstruction of top quarks allows to define a set of kinematic observables relevant to various physics processes that involve top quarks and provides an additional handle for the suppression of background events. Radiation of photons in association with the top quarks alters the kinematics and the topology of the event, leading to visible systematic effects in measurable observables. The present study introduces an improved reconstruction of the top quark kinematics in the presence of photon radiation. The results are presented for processes with top quark pair production, as well as for singly-produced top quarks.

关键词： Analysis and statistical methods data processing methods

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The use of FPGA in drift chambers for data transfer rate reduction

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JOURNAL OF INSTRUMENTATION 2020年第9期15卷

作者： Chiarello, G. Cocciolo, G. Corvaglia, A. Cuna, F. Grancagnolo, F. Panareo, M. Tassielli, G. F. Univ Sapienza Roma Dipartimento Fis Piazzale A Moro 2 I-00185 Rome Italy Ist Nazl Fis Nucl Sez Roma Piazzale A Moro I-00185 Rome Italy Univ Salento Dipartimento Matemat & Fis Via Arnesano I-73100 Lecce Italy Ist Nazl Fis Nucl Sez Lecce Via Arnesano Lecce Italy

The widespread use in drift chambers of light helium-based gas mixtures is aimed to minimize the multiple scattering contribution to the momentum measurement for low momentum particles. However, because of the limited number of ionization clusters produced, these gas mixtures introduce a substantial bias in the impact parameter estimate, particularly for short impact parameters and small drift cells. Recently, an alternative impact parameter reconstruction technique (Cluster Timing) has been proposed, which consists in using, with statistical considerations, the distribution of the drift times of all individual ionization clusters, to reduce the bias and, consequently, to improve the spatial resolution. A hardware test of such application is illustrated with the details of the applied algorithm.

关键词： Gaseous detectors data processing methods data reduction methods data acquisition concepts

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Pulse shape discrimination in CUPID-Mo using principal component analysis

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JOURNAL OF INSTRUMENTATION 2021年第3期16卷

作者： Huang, R. Armengaud, E. Augier, C. Barabash, A. S. Bellini, F. Benato, G. Benoit, A. Beretta, M. Berge, L. Billard, J. Borovlev, Yu A. Bourgeois, Ch Brudanin, V. B. Camus, P. Cardani, L. Casali, N. Cazes, A. Chapellier, M. Charlieux, F. de Combarieu, M. Dafinei, I Danevich, F. A. De Jesus, M. Dixon, T. Dumoulin, L. Eitel, K. Ferri, F. Fujikawa, B. K. Gascon, J. Gironi, L. Giuliani, A. Grigorieva, V. D. Gros, M. Guerard, E. Helis, D. L. Huang, H. Z. Johnston, J. Juillard, A. Khalife, H. Kleifges, M. Kobychev, V. V. Kolomensky, Yu G. Konovalov, S., I Loaiza, P. Ma, L. Makarov, E. P. de Marcillac, P. Mariam, R. Marini, L. Marnieros, S. Misiak, D. Navick, X-F Nones, C. Norman, E. B. Olivieri, E. Ouellet, J. L. Pagnanini, L. Pari, P. Pattavina, L. Paul, B. Pavan, M. Peng, H. Pessina, G. Pirro, S. Poda, D., V Polischuk, O. G. Previtali, E. Redon, Th Rozov, S. Rusconi, C. Sanglard, V Scarpaci, J. A. Schaffner, K. Schmidt, B. Shen, Y. Shlegel, V. N. Siebenborn, B. Singh, V Tomei, C. Tretyak, V., I Umatov, V., I Vagneron, L. Velazquez, M. Weber, M. Welliver, B. Winslow, L. Xue, M. Yakushev, E. Zarytskyy, M. M. Zolotarova, A. S. Univ Calif Berkeley Berkeley CA 94720 USA Univ Paris Saclay CEA IRFU F-91191 Gif Sur Yvette France Univ Lyon Univ Lyon 1 CNRS IN2P3 IP2I Lyon F-69622 Villeurbanne France Natl Res Ctr Kurchatov Inst Inst Theoret & Expt Phys Moscow 117218 Russia Sapienza Univ Roma Dipartimento Fis Ple Aldo Moro 2 I-00185 Rome Italy Ist Nazl Fis Nucl Lab Nazl Gran Sasso I-67100 Assergi AQ Italy CNRS Neel F-38042 Grenoble 9 France Univ Milano Bicocca Dipartimento Fis I-20126 Milan Italy Ist Nazl Fis Nucl Sez Milano Bicocca I-20126 Milan Italy Univ Paris Saclay CNRS IN2P3 IJCLab F-91405 Orsay France Nikolaev Inst Inorgan Chem Novosibirsk 630090 Russia JINR Lab Nucl Problems Dubna 141980 Moscow Region Russia Ist Nazl Fis Nucl Sez Roma Ple Aldo Moro 2 I-00185 Rome Italy Univ Paris Saclay CEA IRAMIS F-91191 Gif Sur Yvette France Inst Nucl Res UA-03028 Kiev Ukraine Karlsruhe Inst Technol Inst Astroparticle Phys D-76021 Karlsruhe Germany Lawrence Berkeley Natl Lab Berkeley CA 94720 USA Fudan Univ Key Lab Nucl Phys & Ion Beam Applicat MOE Shanghai 200433 Peoples R China MIT Cambridge MA 02139 USA Karlsruhe Inst Technol Inst Prozessdatenverarbeitung & Elekt D-76021 Karlsruhe Germany Gran Sasso Sci Inst I-67100 Laquila Italy Tech Univ Munich Phys Dept D-85748 Garching Germany Univ Sci & Technol China Dept Modern Phys Hefei 230027 Peoples R China Univ South Carolina Dept Phys & Astron Columbia SC 29208 USA Univ Grenoble Alpes SIMAP Grenoble INP CNRS F-38402 Saint Martin Dheres France Northwestern Univ Evanston IL 60208 USA

CUPID-Mo is a cryogenic detector array designed to search for neutrinoless double-beta decay (0 nu beta beta) of Mo-100. It uses 20 scintillating Mo-100-enriched Li2MoO4 bolometers instrumented with Ge light detectors to perform active suppression of alpha backgrounds, drastically reducing the expected background in the 0 nu beta beta signal region. As a result, pileup events and small detector instabilities that mimic normal signals become non-negligible potential backgrounds. These types of events can in principle be eliminated based on their signal shapes, which are different from those of regular bolometric pulses. We show that a purely data-driven principal component analysis based approach is able to filter out these anomalous events, without the aid of detector response simulations.

关键词： Analysis and statistical methods Calorimeters data processing methods Double-beta decay detectors

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An automated system to define the optimal operating settings of cryogenic calorimeters

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NUCLEAR INSTRUMENTS & methods IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2021年 1008卷 165451-165451页

作者： Alfonso, K. Bucci, C. Canonica, L. Carniti, P. Di Domizio, S. Giachero, A. Gotti, C. Marini, L. Nutini, I Pessina, G. Univ Milano Bicocca Dipartimento Fis I-20126 Milan Italy Ist Nazl Fis Nucl Sez Milano Bicocca I-20126 Milan Italy Univ Calif Los Angeles Dept Phys & Astron Los Angeles CA 90095 USA Ist Nazl Fis Nucl Lab Nazl Gran Sasso I-67100 Laquila Italy MIT 77 Massachusetts Ave Cambridge MA 02139 USA Univ Genoa Dipartimento Fis I-16146 Genoa Italy Ist Nazl Fis Nucl Sez Genova I-16146 Genoa Italy Univ Calif Berkeley Dept Phys Berkeley CA 94720 USA Lawrence Berkeley Natl Lab Nucl Sci Div Berkeley CA 94720 USA Max Planck Inst Phys & Astrophys D-80805 Munich Germany

Cryogenic macro-calorimeters instrumented with NTD thermistors have been developed for several decades. The choice of the optimal bias current is crucial for a proper operation of these detectors, both in terms of energy resolution and stability. In this paper we present a set of automatic measurements and analysis procedures for the characterization and optimization of the working configuration of the NTD thermistors. The presented procedures were developed for CUORE, an array of 988 cryogenic macro-calorimeters instrumented with NTD thermistors that has been taking data since 2017. These procedures made it possible to characterize a large number of detectors in a reliable way. They are suitable enough to be used also in other large arrays of cryogenic detectors, such as CUPID.

关键词： Cryogenic detectors Cryogenics and thermal models data processing methods Double-beta decay detectors

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First application of machine learning algorithms to the position reconstruction in Resistive Silicon Detectors

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JOURNAL OF INSTRUMENTATION 2021年第3期16卷

作者： Siviero, F. Arcidiacono, R. Cartiglia, N. Costa, M. Ferrero, M. Legger, F. Mandurrino, M. Sola, V Staiano, A. Tornago, M. Univ Torino Turin Italy Ist Nazl Fis Nucl Sez Torino Turin Italy Univ Piemonte Orientale Vercelli Italy

RSDs (Resistive AC-Coupled Silicon Detectors) are n-in-p silicon sensors based on the LGAD (Low-Gain Avalanche Diode) technology, featuring a continuous gain layer over the whole sensor area. The truly innovative feature of these sensors is that the signal induced by an ionising particle is seen on several pixels, allowing the use of reconstruction techniques that combine the information from many read-out channels. In this contribution, the first application of a machine learning technique to RSD devices is presented. The spatial resolution of this technique is compared to that obtained with the standard RSD reconstruction methods that use analytical descriptions of the signal sharing mechanism. A Multi-Output regressor algorithm, trained with a combination of simulated and real data, leads to a spatial resolution of less than 2 mu m for a sensor with a 100 mu m pixel. The prospects of future improvements are also discussed.

关键词： Particle tracking detectors (Solid-state detectors) data processing methods Timing detectors

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Anomalous jet identification via sequence modeling

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JOURNAL OF INSTRUMENTATION 2021年第8期16卷

作者： Kahn, A. Gonski, J. Ochoa, I Williams, D. Brooijmans, G. Columbia Univ Nevis Labs Irvington NY 10533 USA Lab Instrumentat & Expt Particle Phys Lisbon Portugal

This paper presents a novel method of searching for boosted hadronically decaying objects by treating them as anomalous elements of a contaminated dataset. A Variational Recurrent Neural Network (VRNN) is used to model jets as sequences of constituent four-vectors. After applying a pre-processing method which boosts each jet to the same reference mass, energy, and orientation, the VRNN provides each jet an Anomaly Score that distinguishes between the structure of signal and background jets. The model is trained in an entirely unsupervised setting and without high level variables, making the score more robust against mass and p(T) correlations when compared to methods based primarily on jet substructure. Performance is evaluated on the jet level, as well as in an analysis context by searching for a heavy resonance with a final state of two boosted jets. The Anomaly Score shows consistent performance along a wide range of signal contamination amounts, for both two and three-pronged jet substructure hypotheses. Analysis results demonstrate that the use of Anomaly Score as a classifier enhances signal sensitivity while retaining a smoothly falling background jet mass distribution. The model's discriminatory performance resulting from an unsupervised training scenario opens up the possibility to train directly on data without a pre-defined signal hypothesis.

关键词： Analysis and statistical methods data processing methods Pattern recognition cluster finding calibration and fitting methods

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