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Topical Workshop on Electronics for Particle Physics

作者： Wang, T. Yang, J. Sun, Z. Zhang, L. Song, K. Univ Sci & Technol China State Key Lab Particle Detect & Elect 96 JinZhai Rd Hefei Peoples R China

The data acquisition system is a vital component in the high-energy physics experi-ment. To reduce redundant developments and allow for a fast setup under changing conditions, D-Matrix has been developed as an integrative solution in digital signal domain, including the hardware infrastructure and the data handling logical system. Its philosophy is to abstract different tasks in the data processing and encapsulate them as reusable modules with standard inter-module connectors. Furthermore, D-Matrix builds a unified model to integrate software and hardware design so that the system can be built from a global view. D-Matrix will be used in ion cooler-storage-ring external-target experiments. It aims at the research of phase structure of cold and high baryon density nuclear matter and the equation of states of cold asymmetric nuclear matter at supra-saturation densities. This DAQ can also be used in other high-energy physics experiments with little modifications. This paper presents the architecture and some details of the D-Matrix.

关键词： data acquisition concepts data acquisition circuits data processing methods

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A novel technique for an alignment-insensitive density calibration of Thomson scattering diagnostics developed at W7-X

A novel technique for an alignment-insensitive density calib...

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4th European Conference on Plasma Diagnostics (ECPD)

作者： Fuchert, G. Nelde, P. Pasch, E. Beurskens, M. N. A. Bozhenkov, S. A. Brunner, K. J. Meineke, J. Scott, E. R. Wolf, R. C. Max Planck Inst Plasma Phys Greifswald Germany Univ Wisconsin Madison WI USA Tech Univ Berlin Berlin Germany

In most laboratory setups in plasma physics, including magnetic-confinement experiments for fusion research, laser-based Thomson scattering allows for absolutely calibrated density measurements without input from other diagnostics and with high spatial resolution. A common issue is the alignment stability of either the laser beam or the observation optics. Frequent recalibrations are typically required. This is a challenge in particular for larger fusion experiments;while beam paths tend to get longer, the access for alignment and calibration gets more restricted. Therefore, simple, fast and robust calibration methods are required. A novel calibration technique has been developed at W7-X to account for alignment variations in the calibration procedure. This will decrease the pulse-to-pulse variations significantly and allow for a longer time duration before a recalibration becomes necessary. By monitoring the beam position accurately, it could be shown that misalignment leads to deterministic and reproducible changes in the measured density. The introduced density errors can be corrected for by monitoring the laser beam for every individual laser pulse. In the last experimental campaign, this has been done retrospectively by introducing parallel shifts to the laser beam path in order to show the feasibility of this method. It could be demonstrated that the impact of introduced shifts on the electron density can be successfully corrected for. For future campaigns, the beam alignment will intentionally be varied during the absolute calibration in order to cover the full range of expected beam positions. During the actual experiments, the beam positions will be monitored likewise and each density profile will be evaluated with the most suitable calibration factor. While probably not needed for W7-X, vibrations of the observation optics could be included in the same way.

关键词： data processing methods Detector alignment and calibration methods (lasers sources particle-beams) Plasma diagnostics interferometry spectroscopy and imaging

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Quasi-continuous re-binning of measured spectra and associated uncertainties

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JOURNAL OF INSTRUMENTATION 2024年第7期19卷 T07001页

作者： Dombrowski, H. Phys Tech Bundesanstalt PTB Bundesallee 100 D-38116 Braunschweig Germany

As part of an evaluation of gamma -ray spectra or other spectra, the need to adapt the binning quasi -continuously may arise. Often, the re -distribution of measured events to a new energy scale may be required. The necessity to change the energy scale can have several reasons. Frequently, a drift of the detector or the amplifier leads to different energy scales of measured spectra in time. In order to calculate difference spectra or sum spectra, the energy axis and binning of all spectra has to be adapted. Moreover, before a spectrum is unfolded, its energy axis also has to be adapted to the energy scale of the response matrix. Widespread commercial software packages, which are commonly used for the analysis of spectra, do not include an algorithm which solves this task. Three algorithms are presented in this work after shedding light on the mathematical background. An analysis of the statistical uncertainty of the counts of re -binned or remapped spectra completes this paper.

关键词： data processing methods Gamma detectors (scintillators CZT HPGe HgI etc)

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Flavor identification of atmospheric neutrinos in JUNO with machine learning

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JOURNAL OF INSTRUMENTATION 2024年第3期19卷 C03008页

作者： Zeng, F. Duyang, H. Li, T. Liu, J. Liu, Z. Luo, W. Ma, W. Y. Shandong Univ Inst Frontier & Interdisciplinary Sci 72 Binhai Rd Qingdao 266237 Peoples R China Chinese Acad Sci Inst High Energy Phys 19B Yuquan Rd Beijing 100049 Peoples R China

The Jiangmen Underground Neutrino Observatory (JUNO) is designed to determine neutrino mass ordering (NMO) using a large liquid scintillator detector located in southern China. While JUNO's NMO sensitivity mostly comes from reactor neutrinos, atmospheric neutrino oscillations in JUNO can provide complimentary sensitivity via matter effects, and enhance its overall sensitivity in a joint analysis. Neutrino flavor identification is crucial to atmospheric neutrino oscillation measurements, but is traditionally a very difficult task in liquid scintillator detectors such as JUNO. In this paper, we present a novel method for the flavor identification of atmospheric neutrinos in JUNO with machine learning techniques. This method takes features from photomultiplier tube waveforms as inputs, and shows promising results with JUNO simulation. This method could also be applied to other liquid scintillator detectors, potentially benefiting other future atmospheric neutrino oscillation experiments.

关键词： data processing methods Neutrino detectors

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Refine neutrino events reconstruction with BEiT-3

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JOURNAL OF INSTRUMENTATION 2024年第6期19卷 T06003页

作者： Li, Chen Cai, Hao Jiang, Xianyang Wuhan Univ Sch Phys & Technol Bayi Rd Wuhan Peoples R China

Neutrino Events Reconstruction has always been crucial for IceCube Neutrino Observatory. In the Kaggle competition "IceCube - Neutrinos in Deep Ice", many solutions use Transformer. We present ISeeCube, a pure Transformer model based on TorchScale (the backbone of BEiT-3). When having relatively same amount of total trainable parameters, our model outperforms the 2 nd place solution. By using TorchScale , the lines of code drop sharply by about 80% and a lot of new methods can be tested by simply adjusting configs. We compared two fundamental models for predictions on a continuous space, regression and classification, trained with MSE Loss and CE Loss respectively. We also propose a new metric, overlap ratio, to evaluate the performance of the model. Since the model is simple enough, it has the potential to be used for more purposes such as energy reconstruction, and many new methods such as combining it with GraphNeT can be tested more easily. The code and pretrained models are available at https://***/ChenLi2049/ISeeCube.

关键词： data processing methods Neutrino detectors

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ALICE luminosity determination for Pb-Pb collisions at √sNN=5.02 TeV

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JOURNAL OF INSTRUMENTATION 2024年第2期19卷 P02039页

作者： Acharya, S. Adamova, D. Adler, A. Rinella, G. Aglieri Agnello, M. Agrawal, N. Ahammed, Z. Ahmad, S. Ahn, S. U. Ahuja, I Akindinov, A. Al-Turany, M. Aleksandrov, D. Alessandro, B. Alfanda, H. M. Molina, R. Alfaro Ali, B. Ali, Y. Alici, A. Alizadehvandchali, N. Alkin, A. Alme, J. Alocco, G. Alt, T. Altsybeev, I. Anaam, M. N. Andrei, C. Andronic, A. Anguelov, V. Antinori, F. Antonioli, P. Anuj, C. Apadula, N. Aphecetche, L. Appelshauser, H. Arcelli, S. Arnaldi, R. Arsene, I. C. Arslandok, M. Augustinus, A. Averbeck, R. Aziz, S. Azmi, M. D. Badala, A. Baek, Y. W. Bai, X. Bailhache, R. Bailung, Y. Bala, R. Balbino, A. Baldisseri, A. Balis, B. Banerjee, D. Banoo, Z. Barbera, R. Barioglio, L. Barlou, M. Barnafoldi, G. G. Barnby, L. S. Barret, V. Barreto, L. Bartels, C. Barth, K. Bartsch, E. Baruffaldi, F. Bastid, N. Basu, S. Batigne, G. Battistini, D. Batyunya, B. Bauri, D. Alba, J. L. Bazo Bearden, I. G. Beattie, C. Becht, P. Behera, D. Belikov, I. Hechavarria, A. D. C. Bell Bellini, F. Bellwied, R. Belokurova, S. Belyaev, V. Bencedi, G. Beole, S. Bercuci, A. Berdnikov, Y. Berdnikova, A. Bergmann, L. Besoiu, M. G. Betev, L. Bhaduri, P. P. Bhasin, A. Bhat, I. R. Bhat, M. A. Bhattacharjee, B. Bianchi, L. Bianchi, N. Bielcik, J. Bielcikova, J. Biernat, J. Bilandzic, A. Biro, G. Biswas, S. Blair, J. T. Blau, D. Blidaru, M. B. Bluhme, N. Blume, C. Boca, G. Bock, F. Bodova, T. Bogdanov, A. Boi, S. Bok, J. Boldizsar, L. Bolozdynya, A. Bombara, M. Bond, P. M. Bonomi, G. Borel, H. Borissov, A. Bossi, H. Botta, E. Bratrud, L. Braun-Munzinger, P. Bregant, M. Broz, M. Bruno, G. E. Buckland, M. D. Budnikov, D. Buesching, H. Bufalino, S. Bugnon, O. Buhler, P. Buthelezi, Z. Butt, J. B. Bylinkin, A. Bysiak, S. A. Cai, M. Caines, H. Caliva, A. Villar, E. Calvo Camacho, J. M. M. Camerini, P. Canedo, F. D. M. Carabas, M. Carnesecchi, F. Caron, R. Castellanos, J. Castillo Catalano, F. Sanchez, C. Ceballos Chakaberia, I. Chakraborty, P. Chandra, S. Chapeland, S. Chartier, M. Chattopadhyay, S. Chattopadhyay, S. Chavez, T. G. Cheng, T. Chesh AI Alikhanyan Natl Sci Lab Yerevan Phys Inst Fdn Yerevan Armenia AGH Univ Krakow Krakow Poland Natl Acad Sci Ukraine Bogolyubov Inst Theoret Phys Kiev Ukraine Bose Inst Dept Phys Kolkata India Ctr Astroparticle Phys & Space Sci CAPSS Kolkata India Calif Polytech State Univ San Luis Obispo San Luis Obispo CA USA Cent China Normal Univ Wuhan Peoples R China Ctr Aplicac Tecnol & Desarrollo Nucl CEADEN Havana Cuba Ctr Invest & Estudios Avanzados CINVESTAV Mexico City DF Mexico Ctr Invest & Estudios Avanzados CINVESTAV Merida Mexico Chicago State Univ Chicago IL USA China Inst Atom Energy Beijing Peoples R China Chungbuk Natl Univ Cheongju South Korea Comenius Univ Fac Math Phys & Informat Bratislava Slovakia COMSATS Univ Islamabad Islamabad Pakistan Creighton Univ Omaha NE USA Aligarh Muslim Univ Dept Phys Aligarh Uttar Pradesh India Pusan Natl Univ Dept Phys Pusan South Korea Sejong Univ Dept Phys Seoul South Korea Univ Calif Berkeley Dept Phys Berkeley CA USA Univ Oslo Dept Phys Oslo Norway Univ Bergen Dept Phys & Technol Bergen Norway Univ Pavia Dipartimento Fis Pavia Italy Univ Cagliari Dipartimento Fis Cagliari Italy Sezione Ist Nazl Fis Nucl Cagliari Italy Univ Trieste Dipartimento Fis Trieste Italy Sezione Ist Nazl Fis Nucl Trieste Italy Univ Turin Dipartimento Fis Turin Italy Sezione Ist Nazl Fis Nucl Turin Italy Univ Bologna Dipartimento Fis & Astron Bologna Italy Sezione Ist Nazl Fis Nucl Bologna Italy Univ Catania Dipartimento Fis & Astron Catania Italy Sezione Ist Nazl Fis Nucl Catania Italy Univ Padua Dipartimento Fis & Astron Padua Italy Sezione Ist Nazl Fis Nucl Padua Italy Univ Salerno Dipartimento Fis ER Caianiello Salerno Italy Grp Collegato INFN Salerno Italy Politecn Torino Dipartimento DISAT Turin Italy Sezione Ist Nazl Fis Nucl Turin Italy Univ Messina Dipartimento Sci MIFT Messina Italy Dipartimento Interateneo Fis M Merlin Bari Italy Sezione Ist Nazl Fis Nucl Bari Italy European Org Nucl Re

Luminosity determination within the ALICE experiment is based on the measurement, in van der Meer scans, of the cross sections for visible processes involving one or more detectors (visible cross sections). In 2015 and 2018, the Large Hadron Collider provided Pb-Pb collisions at a centre-of-mass energy per nucleon pair of root s(NN) = 5.02 TeV. Two visible cross sections, associated with particle detection in the Zero Degree Calorimeter (ZDC) and in the V0 detector, were measured in a van der Meer scan. This article describes the experimental set-up and the analysis procedure, and presents the measurement results. The analysis involves a comprehensive study of beam-related effects and an improved fitting procedure, compared to previous ALICE studies, for the extraction of the visible cross section. The resulting uncertainty of both the ZDC-based and the V0-based luminosity measurement for the full sample is 2.5%. The inelastic cross section for hadronic interactions in Pb-Pb collisions at root s(NN) = 5.02 TeV, obtained by efficiency correction of the V0-based visible cross section, was measured to be 7.67 +/- 0.25 b, in agreement with predictions using the Glauber model.

关键词： Analysis and statistical methods data processing methods

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40 MHz triggerless readout of the CMS Drift Tube muon detector

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JOURNAL OF INSTRUMENTATION 2024年第2期19卷 C02050页

作者： Migliorini, M. Pazzini, J. Triossi, A. Zanetti, M. Padova Univ Dept Phys & Astron Via Francesco Marzolo Padua Italy Natl Inst Nucl Phys Padova Div Via Francesco Marzolo Padua Italy Padova Univ Dept Ind Engn Via Giovanni Gradenigo Padua Italy Padova Univ Dept Informat Engn Via Giovanni Gradenigo Padua Italy

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 collected from the detector front-end, whenever the throughput is manageable. In this work, the triggerless readout of the CMS Drift Tubes (DT) detector is presented. This is realized by reading a sector of the DT which has been equipped with the preproduction of Phase -2 upgrade front-end boards. A Xilinx VCU118 acts as a concentrator of the Phase -2 demonstrator lpGBT links and transmits data to a server via 100G TCP/IP. First results coming from a test -stand mimicking the sector demonstrator are shown.

关键词： data acquisition concepts Trigger concepts and systems (hardware and software) data processing methods

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Offline data processing software for a Li2MoO4 bolometer demonstration experiment at China Jinping Underground Laboratory

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JOURNAL OF INSTRUMENTATION 2024年第6期19卷 P06032页

作者： Zhao, Kangkang Xue, Mingxuan Peng, Haiping Duan, Deyong Liu, Taiyuan Zhang, Yunlong Yang, Junfeng Lin, Qing Xu, Zizong Wang, Xiaolian Univ Sci & Technol China State Key Lab Particle Detect & Elect Hefei 230026 Peoples R China Univ Sci & Technol China Dept Modern Phys Hefei 230026 Peoples R China

A cryogenic scintillating bolometer demonstration experiment utilizing Li2MoO4 crystals is proposed for exploring neutrinoless double beta decay (0 nu beta beta) at China Jinping Underground Laboratory (CJPL). The hardware and software framework R&D for the entire detection system is currently in progress. In this study, we present a comprehensible offline data processing software designed for this project. The software facilitates event trigger and reconstruction by applying an optimal filter and Monte Carlo truth stream data generator. Based on the simulated stream data, a significant noise suppression and an increase on energy resolution are obtained, with an improvement of approximately 40% comparing to that estimated from the original pulse waveform.

关键词： data processing methods Simulation methods and programs Software architectures (event data models,frameworks and databases) Analysis and statistical methods

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Physics event classification using Large Language Models

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JOURNAL OF INSTRUMENTATION 2024年第7期19卷 C07011页

作者： Fanelli, C. Giroux, J. Moran, P. Nayak, H. Suresh, K. Walter, E. William & Mary Dept Data Sci Williamsburg VA 23185 USA William & Mary Informat & Technol Williamsburg VA 23185 USA

The 2023 AI4EIC hackathon was the culmination of the third annual AI4EIC workshop at The Catholic University of America. This workshop brought together researchers from physics, data science and computer science to discuss the latest developments in Artificial Intelligence (AI) and Machine Learning (ML) for the Electron Ion Collider (EIC), including applications for detectors, accelerators, and experimental control. The hackathon, held on the final day of the workshop, involved using a chatbot powered by a Large Language Model, ChatGPT-3.5, to train a binary classifier neutrons and photons in simulated data from the GLUEX Barrel Calorimeter. In total, six teams of up to four participants from all over the world took part in this intense educational and research event. This article highlights the hackathon challenge, the resources and methodology used, and the results and insights gained from analyzing physics data using the most cutting-edge tools in AI/ML.

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

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Automatic tracking of the energy spectrum areas of Po-218 and Po-214 at various temperatures

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JOURNAL OF INSTRUMENTATION 2024年第2期19卷 T02017页

作者： Yuan, Shuai Xie, Ruomei Liu, Shuaibin Li, Huiying Yi, Haibo Sun, Jiale Liu, Zhipeng Wu, Jiulin Lin, Fen Hu, Tao Mo, Yixiang Yuan, Hongzhi Tan, Yanliang Hengyang Normal Univ Coll Phys & Elect Engn Hengyang 421008 Hunan Peoples R China

Radon and its decay products emit internal radiation in the respiratory system upon inhalation, which is a significant contributor to the development of lung cancer in humans. Accurate measurement of radon concentration is undoubtedly very important. Among the commonly used radon measurement methods, the electrostatic collection method stands out. This method involves counting the energy spectrum peaks of alpha particles, generated by the decay of radon daughters Po-218 and Po-214, which are collected on the surface of a semiconductor detector to determine radon concentration. According to experimental findings, measurements at different ambient temperatures cause Po-218 and Po-214 to peak drift. This drift adversely affects the accuracy of radon measurement using traditional methods. This study focuses on the characteristics of alpha-energy spectra from Po-218 and Po-214. It calculates the peak heights for all alpha-energy spectra and identifies the two peaks with the highest heights. Subsequently, an algorithm is developed to automatically track the peak positions of Po-218 and Po-214, accurately locating their counting intervals. The results demonstrate that the algorithm successfully achieves the desired outcomes through experiments conducted at different temperatures and measurement durations, thus validating its effectiveness. This method holds significant practical value in ensuring the accuracy of radon measurement.

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

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