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Expected tracking performance of the ATLAS Inner Tracker at the High-Luminosity LHC

JOURNAL OF INSTRUMENTATION 2025年第2期20卷 P02018-P02018页

作者： Aad, G. Aakvaag, E. Abbott, B. Abdelhameed, S. Abeling, K. Abicht, N. J. Abidi, S. H. Aboelela, M. Aboulhorma, A. Abramowicz, H. Abulaiti, Y. Acharya, B. S. Ackermann, A. Bourdarios, C. Adam Adamczyk, L. Addepalli, S. V. Addison, M. J. Adelman, J. Adiguzel, A. Adye, T. Affolder, A. A. Afik, Y. Agaras, M. N. Aggarwal, A. Agheorghiesei, C. Ahmadov, F. Ahuja, S. Ai, X. Aielli, G. Aikot, A. Tamlihat, M. Ait Aitbenchikh, B. Akbiyik, M. Akesson, T. P. A. Akimov, A. V. Akiyama, D. Akolkar, N. N. Aktas, S. Alberghi, G. L. Albert, J. Albicocco, P. Albouy, G. L. Alderweireldt, S. Alegria, Z. L. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexopoulos, T. Alfonsi, F. Algren, M. Alhroob, M. Ali, B. Ali, H. M. J. Ali, S. Alibocus, S. W. Aliev, M. Alimonti, G. Alkakhi, W. Allaire, C. Allbrooke, B. M. M. Allen, J. S. Allen, J. F. Allport, P. P. Aloisio, A. Alonso, F. Alpigiani, C. Alsolami, Z. M. K. Fernandez, A. Alvarez Cardoso, M. Alves Alviggi, M. G. Aly, M. Amaral Coutinho, Y. Ambler, A. Amelung, C. Amerl, M. Ames, C. G. Amidei, D. Amini, B. Amirie, K. J. Amirkhanov, A. Amor Dos Santos, S. P. Amos, K. R. Amperiadou, D. An, S. Ananiev, V. Anastopoulos, C. Andeen, T. Anders, J. K. Anderson, A. C. Andreazza, A. Angelidakis, S. Angerami, A. Anisenkov, A. V. Annovi, A. Antel, C. Antipov, E. Antonelli, M. Anulli, F. Aoki, M. Aoki, T. Aparo, M. A. Bella, L. Aperio Appelt, C. Apyan, A. Val, S. J. Arbiol Arcangeletti, C. Arce, A. T. H. Arguin, J-F. Argyropoulos, S. Arling, J. -H. Arnaez, O. Arnold, H. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N. A. Pickering, R. A. Ashby Aslam, A. M. Assamagan, K. Astalos, R. Astrand, K. S. V. Atashi, S. Atkin, R. J. Atmani, H. Atmasiddha, P. A. Augsten, K. Auriol, A. D. Austrup, V. A. Avolio, G. Axiotis, K. Azuelos, G. Azzam, A. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Bachmann, E. Backes, M. J. Badea, A. Baer, T. M. Bagnaia, P. Bahmani, M. Bahner, D. Bai, K. Baines, J. T. Baines, L. Baker, O. K. Bakos, E. Gupta, D. Bakshi Balabram Filho, L. E. Balakrishnan, V. Balasubramanian, R. Baldin, E. M. Univ Adelaide Dept Phys Adelaide SA Australia Univ Alberta Dept Phys Edmonton AB Canada Ankara Univ Dept Phys Ankara Turkiye TOBB Univ Econ & Technol Div Phys Ankara Turkiye Univ Savoie Mt Blanc CNRS IN2P3 LAPP Annecy France Univ Paris Cite CNRS IN2P3 APC Paris France Argonne Natl Lab Div High Energy Phys Argonne IL 60439 USA Univ Arizona Dept Phys Tucson AZ 85721 USA Univ Texas Arlington Dept Phys POB 19059 Arlington TX 76019 USA Natl & Kapodistrian Univ Athens Dept Phys Athens Greece Natl Tech Univ Athens Dept Phys Zografos Greece Univ Texas Austin Dept Phys Austin TX 78712 USA Azerbaan Acad Sci Inst Phys Baku Azerbaijan Barcelona Inst Sci & Technol Inst Fis Altes Energies IFAE Barcelona Spain Chinese Acad Sci Inst High Energy Phys Beijing Peoples R China Tsinghua Univ Dept Phys Beijing Peoples R China Univ Belgrade Inst Phys Belgrade Serbia Univ Bergen Dept Phys & Technol Bergen Norway Lawrence Berkeley Natl Lab Div Phys Berkeley CA USA Univ Calif Berkeley Berkeley CA 94720 USA Humboldt Univ Inst Phys Berlin Germany Univ Bern Albert Einstein Ctr Fundamental Phys Bern Switzerland Univ Bern High Energy Phys Lab Bern Switzerland Univ Birmingham Sch Phys & Astron Birmingham W Midlands England Bogazici Univ Dept Phys Istanbul Turkiye Gaziantep Univ Dept Engn Phys Gaziantep Turkiye Istanbul Univ Dept Phys Istanbul Turkiye Univ Antonio Narino Fac Ciencias Bogota Colombia Univ Antonio Narino Ctr Invest Bogota Colombia Univ Nacl Colombia Dept Fis Bogota Colombia Univ Bologna Dipartimento Fis & Astron A Righi Bologna Italy INFN Sez Bologna Bologna Italy Univ Bonn Phys Inst Bonn Germany Boston Univ Dept Phys 590 Commonwealth Ave Boston MA 02215 USA Brandeis Univ Dept Phys Waltham MA 02254 USA Transilvania Univ Brasov Brasov Romania Horia Hulubei Natl Inst Phys & Nucl Engn Bucharest Romania Alexandru Ioan Cuza Univ Dept Phys Iasi Romania Natl Inst Res & Dev Isotop & Mol Technol Dept Phys Cluj Napoca Ro

The high-luminosity phase of LHC operations (HL-LHC), will feature a large increase in simultaneous proton-proton interactions per bunch crossing up to 200, compared with a typical leveling target of 64 in Run 3. Such an increase will create a very challenging environment in which to perform charged particle trajectory reconstruction, a task crucial for the success of the ATLAS physics program, and will exceed the capabilities of the current ATLAS Inner Detector (ID). A new all-silicon Inner Tracker (ITk) will replace the current ID in time for the start of the HL-LHC. To ensure successful use of the ITk capabilities in Run 4 and beyond, the ATLAS tracking software has been successfully adapted to achieve state-of-the-art track reconstruction in challenging high-luminosity conditions with the ITk detector. This paper presents the expected tracking performance of the ATLAS ITk based on the latest available developments since the ITk technical design reports.

关键词： Gaseous imaging and tracking detectors Particle tracking detectors (Solid-state detectors) Pattern recognition cluster finding calibration and fitting methods Vertexing algorithms

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Parallel CPU- and GPU-based connected component algorithms for event building for hybrid pixel detectors

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JOURNAL OF INSTRUMENTATION 2025年第1期20卷 C01041-C01041页

作者： Celko, T. Mraz, F. Bergmann, B. Manek, P. Charles Univ Prague Dept Comp Sci Educ Malostranske Nam 25 Prague 1 Czech Republic Czech Tech Univ Inst Expt & Appl Phys Husova 240-5 Prague 1 Czech Republic UCL Dept Phys & Astron Gower St London WC1E 6BT England

The latest generation of Timepix series hybrid pixel detectors enhance particle tracking with high spatial and temporal resolution. However, their high hit-rate capability poses challenges for data processing, particularly in multidetector configurations or systems like Timepix4. Storing and processing each hit offline is inefficient for such high data throughput. To efficiently group partly unsorted pixel hits into clusters for particle event characterization, we explore parallel approaches for online clustering to enable real-time data reduction. Although using multiple CPU cores improved throughput, scaling linearly with the number of cores, load-balancing issues between processing and I/O led to occasional data loss. We propose a parallel connected component labeling algorithm using a union-find structure with path compression optimized for zero-suppression data encoding. Our GPU implementation achieved a throughput of up to 300 million hits per second, providing a two-order-of-magnitude speedup over compared CPU-based methods while also freeing CPU resources for I/O handling and reducing the data loss.

关键词： Data processing methods Data reduction methods Pattern recognition cluster finding calibration and fitting methods

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Design of a Novel Predictive Technique to Estimate Liquid Level and Concentration Using Multi-Sensor Data Fusion

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IEEE ACCESS 2024年 12卷 98787-98802页

作者： Hanni, Jayalaxmi Rajesh Santhosh, K. V. Srinidhi, N. N. Manipal Acad Higher Educ MAHE Manipal Inst Technol Bengaluru Dept Elect & Elect Engn Manipal 576104 India Manipal Acad Higher Educ MAHE Manipal Inst Technol Ctr Cyber Phys Syst Dept Instrumentat & Control Engn Manipal 576104 India Manipal Acad Higher Educ MAHE Manipal Inst Technol Bengaluru Dept Comp Sci & Engn Manipal 576104 India

Level is one of the important parameters to be measured in many of the industrial applications, in which Capacitance Level Sensors (CLS) play an important role in measuring liquid level because of its ruggedness. But CLS is inept at measuring levels irrespective of liquid types hence this work proposes a novel technique to overcome the demerits of conventional measurement of CLS. This paper aims to develop a novel predictive technique to measure the liquid level along with its concentration. The predictive technique comprises a Level Predictive Model (LPM) and a Concentration Predictive Model (CPM). LPM predicts an accurate level for the change in liquid type and CPM predicts the change in sugar concentration of a liquid. An experimental setup was established for the model development. LPM was developed by infusing the data fusion technique from the data obtained by three different sensors CLS, Pressure Level Sensor (PLS) and Ultrasonic Level Sensor (ULS) for adaptive level measurement. CPM was developed using a Support Vector Machine (SVM) model for predicting the changes in sugar concentration in a liquid. The work was validated by implementing the developed LPM and CPM on a real-time system. System validation results showed that LPM detected the level with an error of -6 to 0.0001 cm, and CPM gave an accurate result for predicting the sugar concentration in liquid with an error between +/-0.8%. The obtained results of models catered to the objectives of the work with enhanced accuracy and avoided the re-calibration of CLS-based Liquid Level Measurement Systems (LLMS).

关键词： Liquids Sensors Capacitance Permittivity Sensor phenomena and characterization calibration Data analysis Multisensor systems Measurement calibration and fitting methods concentration measurement data analysis liquid level measurement multi-sensor data fusion

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Method for stabilizing the detection efficiency of grazing angle incidence boron-lined neutron detectors

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JOURNAL OF INSTRUMENTATION 2024年第5期19卷 P05032页

作者： Liu, Lixing Yu, Yangyi Zhang, Zhi Yang, Yigang Tsinghua Univ Dept Engn Phys Qinghuayuan 1 Beijing 100084 Peoples R China Tsinghua Univ Key Lab Particle & Radiat Imaging Minist Educ Qinghuayuan 1 Beijing 100084 Peoples R China

Boron -lined gaseous neutron detectors intrinsically suffer from the "self-absorption" effect and hence their neutron detection efficiencies might be nonconstant, when the threshold of them undergoes unexpected variation. To address this problem, we propose a maximum likelihood estimation -based threshold determining method, via which the pulse height spectra acquired under different high voltages could be rescaled to the same abscissa axis of deposited energies. Monte Carlo simulations were conducted to study the relationship between the precision of the threshold determination and the counting statistics, as well as the energy deposition spectrum, indicating that the grazing angle incidence neutron detector can achieve a fairly small relative standard variation for a spectrum with a modest total neutron counts. A prototype grazing angle incidence neutron detector has been constructed and tested under high voltages ranging from 500 V to 950 V. The experimental results show that, with the maximum likelihood estimation -based method, the threshold's relative standard deviations are less than 10% even with a total neutron counts as low as 100. As a result, the maximum relative variance of the counting plateau curve is 4.8% in the region of [ 500 V , 900 V ] when the detector operates at a grazing angle of 1 . 8 degrees . The results presented in this study indicate that combining the grazing angle incidence and the maximum likelihood estimation -based threshold determining method would be a promising way to achieve stable neutron detection efficiency for neutron detectors with the boron layer as the neutron convertor.

关键词： Neutron detectors (cold thermal fast neutrons) Pattern recognition cluster finding calibration and fitting methods Gaseous detectors

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Shower separation in five dimensions for highly granular calorimeters using machine learning

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JOURNAL OF INSTRUMENTATION 2024年第10期19卷 P10027-P10027页

作者： Lai, S. Wilhahn, A. Fouz, M. C. Bach, O. Brianne, E. Ebrahimi, A. Gadow, K. Goettlicher, P. Hartbrich, O. Heuchel, D. Irles, A. Krueger, K. Kvasnicka, J. Lu, S. Neubueser, C. Provenza, A. Reinecke, M. Sefkow, F. Schuwalow, S. De Silva, M. Sudo, Y. Tran, H. L. Liu, L. Masuda, R. Murata, T. Ootani, W. Seino, T. Takatsu, T. Tsuji, N. Poschl, R. Richard, F. Zerwas, D. Hummer, F. Simon, F. Boudry, V. Brient, J-C. Nanni, J. Videau, H. Buhmann, E. Garutti, E. Huck, S. Kasieczka, G. Martens, S. Rolph, J. Wellhausen, J. Bilki, B. Northacker, D. Onel, Y. Emberger, L. Graf, C. Georg August Univ Gottingen Phys Inst H Friedrich Hund Pl 1 D-37077 Gottingen Germany CIEMAT Ctr Invest Energet Medioambient & Tecnol Madrid Spain DESY Notkestr 85 D-22603 Hamburg Germany Univ Tokyo ICEPP 7-3-1 HongoBunkyo Ku Tokyo 1130033 Japan Univ Paris Saclay CLab CNRS IN2P3 F-91405 Orsay France Karlsruhe Inst Technol Inst Data Proc & Elect Kaiserstr 12 D-76131 Karlsruhe Germany Inst Polytech Paris Ecole Polytech CNRS Lab Leprince Ringuet LLR F-91120 Palaiseau France Univ Hamburg Dept Phys Inst Expt Phys Luruper Chaussee 149 D-22761 Hamburg Germany Univ Iowa Dept Phys & Astron 203 Van Allen Hall Iowa City IA 52242 USA Max Planck Inst Phys & Astrophys Fohringer Ring 6 D-80805 Munich Germany Oak Ridge Natl Lab 1 Bethel Valley Rd Oak Ridge TN 37830 USA Inst Fis Corpuscular Parque CientCatedratico Jose Beltran 2 E-46980 Paterna Spain Czech Acad Sci Inst Phys Prague Czech Republic

To achieve state-of-the-art jet energy resolution for Particle Flow, sophisticated energy clustering algorithms must be developed that can fully exploit available information to separate energy deposits from charged and neutral particles. Three published neural network-based shower separation models were applied to simulation and experimental data to measure the performance of the highly granular CALICE Analogue Hadronic Calorimeter (AHCAL) technological prototype in distinguishing the energy deposited by a single charged and single neutral hadron for Particle Flow. The performance of models trained using only standard spatial, energy and charged track position information from an event was compared to models trained using timing information available from AHCAL, which is expected to improve sensitivity to shower development and, therefore, aid in clustering. Both simulation and experimental data were used to train and test the models and their performances were compared. The best-performing neural network achieved significantly superior event reconstruction when timing information was utilised in training for the case where the charged hadron had more energy than the neutral one, motivating temporally sensitive calorimeters. All models under test were observed to tend to allocate energy deposited by the more energetic of the two showers to the less energetic one. Similar shower reconstruction performance was observed for a model trained on simulation and applied to data and a model trained and applied to data.

关键词： Large detector systems for particle and astroparticle physics Pattern recognition cluster finding calibration and fitting methods Performance of High Energy Physics Detectors

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Determination of impact parameter for CEE with digi-input neural networks

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JOURNAL OF INSTRUMENTATION 2024年第5期19卷 P05009页

作者： Wang, Botan Wang, Yi Han, Dong Xiao, Zhigang Zhang, Yapeng Tsinghua Univ Dept Engn Phys Key Lab Particle & Radiat Imaging Beijing 100084 Peoples R China Tsinghua Univ Dept Phys Beijing 100084 Peoples R China Chinese Acad Sci Inst Modern Phys Lanzhou 730000 Peoples R China

The impact parameter characterizes the centrality in nucleus -nucleus collision geometry. The determination of impact parameters in real experiments is usually based on the reconstructed particle attributes or the derived event -level observables. For the scheduled Cooler -storage -ring External -target Experiment (CEE), the low beam energy reduces correlation between the impact parameter and charged particle multiplicity, which decreases the validity of the explicit determination methods. This work investigates a few neural network -based models that directly take the digitized signals from the external Time -of -flight detectors as input. The model with the best performance shows a mean absolute error of 0.479 fm with simulated U -U collisions at 0.5 AGeV. The performances of the models implemented with digi inputs are compared with reference models with phase space inputs, showing the capability of neural networks to handle the original but potentially interrelated digitized signal information.

关键词： Pattern recognition cluster finding calibration and fitting methods Timing detectors Instrumentation and methods for time-of-flight (TOF) spectroscopy

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Track reconstruction for the COMET Phase-II experiment with ACTS

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JOURNAL OF INSTRUMENTATION 2024年第1期19卷 P01011页

作者： Razquin, Amaia Lee, Myeongjae Sungkyunkwan Univ Dept Phys Suwon 16419 South Korea Karl Franzens Univ Graz Inst Phys A-8010 Graz Austria

An implementation of A Common Tracking Software (ACTS) toolkit for signal electron reconstruction for the COMET muon to electron conversion experiment is discussed. The COMET experiment in J-PARC, Japan, will search for neutrinoless conversion of muons into electrons in the field of an aluminium nucleus, a lepton flavour violating process, aiming target sensitivity of 10-17. To achieve its scientific goals, the experiment requires a reconstructed momentum resolution of lower than 150 keV/c. For the first time by applying ACTS to signal events in the 100 MeV energy range with multiple -turn trajectories in the presence of background events, it is found that the reconstruction efficiency is around 14% with no fake reconstructed events. The implementation details, performance, and issues of ACTS in the context of COMET are presented.

关键词： Data processing methods Large detector-systems performance Pattern recognition cluster finding calibration and fitting methods

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Study on deconvolution of alpha-particle spectra using metaheuristic optimization and multivariate analysis

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JOURNAL OF INSTRUMENTATION 2024年第1期19卷 P01016页

作者： Li, Xuebin Pan, Lantian Yang, Luchun Jin, Zhao Wuhan 2nd Ship Design & Res Inst Wuhan 430205 Hubei Peoples R China

To find a global optimal solution and obtain further insight into the parameters of the peak shape fitting function, metaheuristic optimization algorithms, and multivariate analysis techniques are employed to study the deconvolution of alpha -particle spectra. An improved peak shape model composed of the Bortels-Collaers function and Levy distribution function, which aims to handle the high-energy tailing, is proposed. A newly developed metaheuristic optimization method, Bonobo Optimizer (BO) is adopted to seek optimal parameters in the peak shape function. Multivariate analysis (MVA) techniques are used to find hidden information in the shape model. Pearson's correlation tells the mutual variation relationship among parameters, while Multidimensional scaling (MDS) shows similarities of parameters through a 2D plot. Effects of parameters upon the regression accuracy are obtained via the Student t -test. Self -organizing Mapping (SOM) is utilized to mine intrinsic relations among these parameters through visual images. AM243-1 test alpha spectra example is selected to examine the proposed methodology. The improved model is more accurate when handling the high-energy tailing features. Compared with traditional gradient -based optimization algorithms, BO can find global solutions without tedious work in initial solution setting and constraint handling. More information is mined through MVA and further understanding of the peak shape function is obtained.

关键词： Pattern recognition cluster finding calibration and fitting methods Data processing methods Interaction of radiation with matter

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The track-length extension fitting algorithm for energy measurement of interacting particles in liquid argon TPCs and its performance with ProtoDUNE-SP data

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JOURNAL OF INSTRUMENTATION 2025年第2期20卷 P02021-P02021页

作者： Abud, A. Abed Abi, B. Acciarri, R. Acero, M. A. Adames, M. R. Adamov, G. Adamowski, M. Adams, D. Adinolfi, M. Adriano, C. Aduszkiewicz, A. Aguilar, J. Akbar, F. Alex, N. S. Allison, K. Monsalve, S. Alonso Alrashed, M. Alton, A. Alvarez, R. Alves, T. Amar, H. Amedo, P. Anderson, J. Andreopoulos, C. Andreotti, M. Andrews, M. P. Andrianala, F. Andringa, S. Anfimov, N. Ankowski, A. Antic, D. Antoniassi, M. Antonova, M. Antoshkin, A. Aranda-Fernandez, A. Arellano, L. Arrieta Diaz, E. Arroyave, M. A. Asaadi, J. Ashkenazi, A. Asner, D. Asquith, L. Atkin, E. Auguste, D. Aurisano, A. Aushev, V. Autiero, D. Azam, M. B. Azfar, F. Back, A. Back, H. Back, J. J. Bagaturia, I. Bagby, L. Balashov, N. Balasubramanian, S. Baldi, P. Baldini, W. Baldonedo, J. Baller, B. Bambah, B. Banerjee, R. Barao, F. Barbu, D. Barenboim, G. Alzas, P. Barham Barker, G. J. Barkhouse, W. Barr, G. Barranco Monarca, J. Barros, A. Barros, N. Barrow, D. Barrow, J. L. Basharina-Freshville, A. Bashyal, A. Basque, V. Batchelor, C. Bathe-Peters, L. Battat, J. B. R. Battisti, F. Bay, F. Bazetto, M. C. Q. Bazo Alba, J. L. L. Beacom, J. F. Bechetoille, E. Behera, B. Belchior, E. Bell, G. Bellantoni, L. Bellettini, G. Bellini, V. Beltramello, O. Benekos, N. Benitez Montiel, C. Benjamin, D. Bento Neves, F. Berger, J. Berkman, S. Bernal, J. Bernardini, P. Bersani, A. Bertolucci, S. Betancourt, M. Betancur Rodriguez, A. Bevan, A. Bezawada, Y. Bezerra, A. T. Bezerra, T. J. Bhat, A. Bhatnagar, V. Bhatt, J. Bhattacharjee, M. Bhattacharya, M. Bhuller, S. Bhuyan, B. Biagi, S. Bian, J. Biery, K. Bilki, B. Bishai, M. Bitadze, A. Blake, A. Blaszczyk, F. D. Blazey, G. C. Blucher, E. Bodek, A. Bogenschuetz, J. Boissevain, J. Bolognesi, S. Bolton, T. Bomben, L. Bonesini, M. Bonilla-Diaz, C. Bonini, F. Booth, A. Boran, F. Bordoni, S. Borges Merlo, R. Borkum, A. Bostan, N. Bouet, R. Boza, J. Bracinik, J. Brahma, B. Brailsford, D. Bramati, F. Branca, A. Brandt, A. Bremer, J. Brew, C. Brice, S. J. Brio, V. Brizzolari, C. Bromberg, C. Brooke, J. Bross, A. Brunetti, G. Brunetti, M Abilene Christian Univ Abilene TX 79601 USA SUNY Albany Albany NY 12222 USA Inst Nucl Phys Almaty Alma Ata 050032 Kazakhstan Univ Amsterdam NL-1098 XG Amsterdam Netherlands Antalya Bilim Univ TR-07190 Dosemealti Antalya Turkiye Univ Antananarivo Antananarivo 101 Madagascar Univ Antioquia Medellin Colombia Univ Antonio Narino Bogota Colombia Argonne Natl Lab Argonne IL 60439 USA Univ Arizona Tucson AZ 85721 USA Univ Nacl Asuncion San Lorenzo Paraguay Univ Athens GR-15784 Zografos Greece Univ Atlantico Barranquilla Colombia Augustana Univ Sioux Falls SD 57197 USA Univ Bern CH-3012 Bern Switzerland Beykent Univ Istanbul Turkiye Univ Birmingham Birmingham B15 2TT W Midlands England Univ Bologna I-40127 Bologna Italy Boston Univ Boston MA 02215 USA Univ Bristol Bristol BS8 1TL Avon England Brookhaven Natl Lab Upton NY 11973 USA Univ Bucharest Bucharest Romania Univ Calif Berkeley Berkeley CA 94720 USA Univ Calif Davis Davis CA 95616 USA Univ Calif Irvine Irvine CA 92697 USA Univ Calif Los Angeles Los Angeles CA 90095 USA Univ Calif Riverside Riverside CA 92521 USA Univ Calif Santa Barbara Santa Barbara CA 93106 USA CALTECH Pasadena CA 91125 USA Univ Cambridge Cambridge CB3 0HE England Univ Estadual Campinas BR-13083970 Campinas SP Brazil Univ Catania 2 I-95131 Catania Italy Univ Catolica Norte Antofagasta Chile Ctr Brasileiro Pesquisas Fis BR-22290180 Rio De Janeiro RJ Brazil Univ Paris Saclay IRFU CEA F-91191 Gif Sur Yvette France CERN European Org Nucl Res CH-1211 Meyrin Switzerland Charles Univ Prague Inst Particle & Nucl Phys Fac Math & Phys Prague 18000 8 Czech Republic Univ Chicago Chicago IL 60637 USA Chung Ang Univ Seoul 06974 South Korea Ctr Invest Energet Medioambientales & Tecnol E-28040 Madrid Spain Univ Cincinnati Cincinnati OH 45221 USA Inst Politecn Nacl Cinvestav Ctr Invest & Estudios Avanzados Mexico City DF Mexico Univ Colima Colima Mexico Univ Colorado Boulder Boulder CO 80309 USA Colorado State Univ

This paper introduces a novel track-length extension fitting algorithm for measuring the kinetic energies of inelastically interacting particles in liquid argon time projection chambers (LArTPCs). The algorithm finds the most probable offset in track length for a track-like object by comparing the measured ionization density as a function of position with a theoretical prediction of the energy loss as a function of the energy, including models of electron recombination and detector response. The algorithm can be used to measure the energies of particles that interact before they stop, such as charged pions that are absorbed by argon nuclei. The algorithm's energy measurement resolutions and fractional biases are presented as functions of particle kinetic energy and number of track hits using samples of stopping secondary charged pions in data collected by the ProtoDUNE-SP detector, and also in a detailed simulation. Additional studies describe the impact of the dE/dx model on energy measurement performance. The method described in this paper to characterize the energy measurement performance can be repeated in any LArTPC experiment using stopping secondary charged pions.

关键词： Neutrino detectors Pattern recognition cluster finding calibration and fitting methods

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A machine-learning based closed orbit feedback for a synchrotron light source

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JOURNAL OF INSTRUMENTATION 2023年第9期18卷 P09035页

作者： Li, Ruichun Zhang, Qinglei Jiang, Bocheng Zhao, Zhentang Li, Changliang Wang, Kun Chinese Acad Sci Shanghai Adv Res Inst Shanghai Synchrotron Radiat Facil Shanghai 201210 Peoples R China Chinese Acad Sci Shanghai Inst Appl Phys Shanghai 201800 Peoples R China ShanghaiTech Univ Sch Phys Sci & Technol Shanghai 201210 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chongqing Univ Lab Ultrafast Transient Facil Chongqing 401331 Peoples R China

In order to improve the stability of synchrotron radiation, we developed a new method of machine learning-based closed orbit feedback, and piloted it in the storage ring of the Shanghai Synchrotron Radiation Facility (SSRF). In our experiments, the machine learning-based closed orbit feedback can carry out horizontal, vertical and RF main frequency feedback simultaneously. What's more, the residual values of variations in the correctors' currents before vs. after correction can be almost ignored. This machine learning-based new method is expected to establish a new closed orbit feedback system and improve the orbit stability of the storage ring in daily operation.

关键词： Accelerator Applications Detector alignment and calibration methods (lasers sources particle-beams) Pattern recognition cluster finding calibration and fitting methods

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