{"title":"贝尔二号新的图神经网络味道标记和 B0→J/ψKS0 衰变中 sin 2ϕ1 的测量","authors":"I. Adachiet al.(Belle II Collaboration)","doi":"10.1103/physrevd.110.012001","DOIUrl":null,"url":null,"abstract":"We present GFlaT, a new algorithm that uses a graph-neural-network to determine the flavor of neutral <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi>B</mi></math> mesons produced in <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi mathvariant=\"normal\">ϒ</mi><mo stretchy=\"false\">(</mo><mn>4</mn><mi>S</mi><mo stretchy=\"false\">)</mo></math> decays. It improves previous algorithms by using the information from all charged final-state particles and the relations between them. We evaluate its performance using <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi>B</mi></math> decays to flavor-specific hadronic final states reconstructed in a <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mn>362</mn><mtext> </mtext><mtext> </mtext><msup><mi>fb</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></math> sample of electron-positron collisions collected at the <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi mathvariant=\"normal\">ϒ</mi><mo stretchy=\"false\">(</mo><mn>4</mn><mi>S</mi><mo stretchy=\"false\">)</mo></math> resonance with the Belle II detector at the SuperKEKB collider. We achieve an effective tagging efficiency of <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mo stretchy=\"false\">(</mo><mn>37.40</mn><mo>±</mo><mn>0.43</mn><mo>±</mo><mn>0.36</mn><mo>%</mo><mo stretchy=\"false\">)</mo></math>, where the first uncertainty is statistical and the second systematic, which is 18% better than the previous Belle II algorithm. Demonstrating the algorithm, we use <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><msup><mi>B</mi><mn>0</mn></msup><mo stretchy=\"false\">→</mo><mrow><mi>J</mi><mo>/</mo><mi>ψ</mi></mrow><msubsup><mi>K</mi><mi mathvariant=\"normal\">S</mi><mn>0</mn></msubsup></math> decays to measure the mixing-induced and direct <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi>C</mi><mi>P</mi></math> violation parameters, <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi>S</mi><mo>=</mo><mo stretchy=\"false\">(</mo><mn>0.724</mn><mo>±</mo><mn>0.035</mn><mo>±</mo><mn>0.009</mn><mo stretchy=\"false\">)</mo></math> and <math display=\"inline\" xmlns=\"http://www.w3.org/1998/Math/MathML\"><mi>C</mi><mo>=</mo><mo stretchy=\"false\">(</mo><mo>−</mo><mn>0.035</mn><mo>±</mo><mn>0.026</mn><mo>±</mo><mn>0.029</mn><mo stretchy=\"false\">)</mo></math>.","PeriodicalId":20167,"journal":{"name":"Physical Review D","volume":null,"pages":null},"PeriodicalIF":5.0000,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"New graph-neural-network flavor tagger for Belle II and measurement of sin 2ϕ1 in B0→J/ψKS0 decays\",\"authors\":\"I. Adachiet al.(Belle II Collaboration)\",\"doi\":\"10.1103/physrevd.110.012001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present GFlaT, a new algorithm that uses a graph-neural-network to determine the flavor of neutral <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mi>B</mi></math> mesons produced in <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mi mathvariant=\\\"normal\\\">ϒ</mi><mo stretchy=\\\"false\\\">(</mo><mn>4</mn><mi>S</mi><mo stretchy=\\\"false\\\">)</mo></math> decays. It improves previous algorithms by using the information from all charged final-state particles and the relations between them. We evaluate its performance using <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mi>B</mi></math> decays to flavor-specific hadronic final states reconstructed in a <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mn>362</mn><mtext> </mtext><mtext> </mtext><msup><mi>fb</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></math> sample of electron-positron collisions collected at the <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mi mathvariant=\\\"normal\\\">ϒ</mi><mo stretchy=\\\"false\\\">(</mo><mn>4</mn><mi>S</mi><mo stretchy=\\\"false\\\">)</mo></math> resonance with the Belle II detector at the SuperKEKB collider. We achieve an effective tagging efficiency of <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mo stretchy=\\\"false\\\">(</mo><mn>37.40</mn><mo>±</mo><mn>0.43</mn><mo>±</mo><mn>0.36</mn><mo>%</mo><mo stretchy=\\\"false\\\">)</mo></math>, where the first uncertainty is statistical and the second systematic, which is 18% better than the previous Belle II algorithm. Demonstrating the algorithm, we use <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><msup><mi>B</mi><mn>0</mn></msup><mo stretchy=\\\"false\\\">→</mo><mrow><mi>J</mi><mo>/</mo><mi>ψ</mi></mrow><msubsup><mi>K</mi><mi mathvariant=\\\"normal\\\">S</mi><mn>0</mn></msubsup></math> decays to measure the mixing-induced and direct <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mi>C</mi><mi>P</mi></math> violation parameters, <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mi>S</mi><mo>=</mo><mo stretchy=\\\"false\\\">(</mo><mn>0.724</mn><mo>±</mo><mn>0.035</mn><mo>±</mo><mn>0.009</mn><mo stretchy=\\\"false\\\">)</mo></math> and <math display=\\\"inline\\\" xmlns=\\\"http://www.w3.org/1998/Math/MathML\\\"><mi>C</mi><mo>=</mo><mo stretchy=\\\"false\\\">(</mo><mo>−</mo><mn>0.035</mn><mo>±</mo><mn>0.026</mn><mo>±</mo><mn>0.029</mn><mo stretchy=\\\"false\\\">)</mo></math>.\",\"PeriodicalId\":20167,\"journal\":{\"name\":\"Physical Review D\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2024-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physical Review D\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://doi.org/10.1103/physrevd.110.012001\",\"RegionNum\":2,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Physics and Astronomy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physical Review D","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1103/physrevd.110.012001","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Physics and Astronomy","Score":null,"Total":0}
引用次数: 0
摘要
我们提出了一种新算法GFlaT,它使用图神经网络来确定在ϒ(4S)衰变中产生的中性B介子的味道。它利用所有带电终态粒子的信息以及它们之间的关系改进了以前的算法。我们利用在超级KEKB对撞机的Belle II探测器的ϒ(4S)共振中收集到的362 fb-1电子-正电子对撞样本中重建的B衰变到特定味道的强子终态来评估它的性能。我们实现了(37.40±0.43±0.36%)的有效标记效率,其中第一个不确定性是统计不确定性,第二个不确定性是系统不确定性,这比之前的 Belle II 算法提高了 18%。为了演示该算法,我们利用B0→J/ψKS0衰变测量了混合诱导和直接CP违反参数S=(0.724±0.035±0.009)和C=(-0.035±0.026±0.029)。
New graph-neural-network flavor tagger for Belle II and measurement of sin 2ϕ1 in B0→J/ψKS0 decays
We present GFlaT, a new algorithm that uses a graph-neural-network to determine the flavor of neutral mesons produced in decays. It improves previous algorithms by using the information from all charged final-state particles and the relations between them. We evaluate its performance using decays to flavor-specific hadronic final states reconstructed in a sample of electron-positron collisions collected at the resonance with the Belle II detector at the SuperKEKB collider. We achieve an effective tagging efficiency of , where the first uncertainty is statistical and the second systematic, which is 18% better than the previous Belle II algorithm. Demonstrating the algorithm, we use decays to measure the mixing-induced and direct violation parameters, and .
期刊介绍:
Physical Review D (PRD) is a leading journal in elementary particle physics, field theory, gravitation, and cosmology and is one of the top-cited journals in high-energy physics.
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