课题基金 / 基金详情

Probing tau neutrino appearance with ORCA and determination of the leptonic CP-phase with Super-ORCA

Probing tau neutrino appearance with ORCA and determination of the leptonic CP-phase with Super-ORCA
用 ORCA 探测 tau 中微子的出现并用 Super-ORCA 测定轻子 CP 相
批准号:
339011373
负责人:
Privatdozent Dr. Thomas Eberl
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2017
资助国家:
德国
项目状态:
已结题
起止时间:
2016-12-31 至 2019-12-31

项目摘要

项目成果

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中文摘要
翻译
中微子物理学正在进入一个精确测量的时代。中微子物理学中一些最重要的问题是中微子质量本征态的排序,已建立的三味模型的混合矩阵的么正性检验和CP破坏轻子Dirac相的确定(深渊中宇宙的振荡研究)是一个百万吨级的水-目前正在地中海建造的切伦科夫探测器将精确测量能量范围内大气中微子的能量和天顶角相关振荡概率从3到50 GeV。该实验将在几年的数据采集时间内确定中微子的质量排序,并提供τ中微子在探测器中出现率的高统计测量。该资助申请追求两个主要目标。首先,我们将参与ORCA探测器第一阶段的数据采集和分析,该探测器有7个探测单元(第一阶段)。基于我们早期的事件重建算法的ORCA的发展,我们将开发必要的工具来检测tau中微子作为一个过剩的级联事件在ORCA阶段-1和完整的阶段-2检测器与115个检测单元。这将使我们能够以高的意义和精度测量可能的偏差从通量归一化的3味模型,从而提供了一个重要的测试的幺正性假设的混合matrix.The第二个目标是调查的可行性,确定轻子CP阶段使用大气中微子和百万吨级的水切伦科夫探测器在地中海。我们想研究一个更密集的仪器检测器-称为超级ORCA-将允许测量μ子和电子中微子的快速振荡和可能的CP相位诱导的相移低于2 GeV的大小。为此,我们将优化探测器的几何形状与新开发的重建算法。优化将集中在检测CP相位偏离零的灵敏度上。此外,我们将确定事件和检测器对重建算法可达到的分辨率的固有限制,这将为事件重建开发和检测器优化提供重要指导。最后,我们将研究我们对大气中微子通量以及中微子与核子和原子核相互作用横截面的知识中的系统不确定性如何限制可达到的灵敏度。
英文摘要
Neutrino physics is entering an era of precision measurements. Some of the most important questions of neutrino physics are the ordering of neutrino mass eigenstates, tests of the unitarity of the mixing matrix of the well established 3-flavour model and the determination of the CP-violating leptonic Dirac phase.ORCA (Oscillation Research with Cosmics in the Abyss) is a megaton-sized water-Cherenkov detector currently under construction in the Mediterranean Sea that will precisely measure the energy and zenith angle dependent oscillation probabilities of atmospheric neutrinos in the energy range from 3 to 50 GeV. This experiment will allow to determine the neutrino mass ordering within a few years of data taking and provide a high statistics measurement of the rate of tau neutrino appearance in the detector.This grant application pursues 2 main goals.Firstly, we will participate in the data taking and analysis of the first construction phase of the ORCA detector with 7 detection units (phase-1). Based on our earlier developments of event reconstruction algorithms for ORCA, we will develop the necessary tools to detect tau neutrinos as an excess of cascade-like events in ORCA phase-1 and with the full phase-2 detector with 115 detection units. This will allow us to measure with high significance and precision possible deviations from the flux normalization given by the 3-flavour model and thus provide an important test of the unitarity assumption for the mixing matrix.The second goal is to investigate the feasibility of determining the leptonic CP-phase using atmospheric neutrinos and a megaton-sized water-Cherenkov detector in the Mediterranean Sea. We want to investigate if a more densly instrumented detector - called Super-ORCA - will allow to measure the rapid oscillations of muon and electron neutrinos and the size of a possible CP-phase induced phase shift below 2 GeV. To this end, we will optimize the detector geometry together with newly developed reconstruction algorithms. The optimization will focus on the sensitivity to detect a deviation of the CP-phase from zero.Furthermore, we will determine the event and detector intrinsic limitations on the attainable resolutions of reconstruction algorithms which will provide an important guideline for the event reconstruction development and detector optimization. Finally, we will study how the systematic uncertainties in our knowledge of the atmospheric neutrino flux and of the cross sections of neutrino interactions with the nucleon and the nucleus limit the attainable sensitivity.
期刊论文(9)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1140/epjc/s10052-019-7259-5
发表时间: 2019-02
期刊: The European Physical Journal C
影响因子: --
作者: [A. V. Akindinov;E. Anassontzis;G. Anton;M. Ardid;J. Aublin;B. Baret;V. Bertin;S. Bourret;C. Bozza;M. Bruchner;R. Bruijn;J. Brunner;M. Chabab;N. Chau;A. Chepurnov;M. C. Molla;P. Coyle;A. Creusot;G. Wasseige;A. Domi;C. Donzaud;T. Eberl;A. Enzenhofer;M. Fayfman;M. Filipovi'c;L. Fusco;V. Garkusha;T. Gál;S. Gozzini;K. Graf;T. Gr'egoire;G. Grella;S. Hallmann;A. Heijboer;J. Hern'andez-Rey;J. Hofestadt;S. Ivanov;C. James;M. Jong;P. Jong;P. Kalaczy'nski;I. Kakorin;U. Katz;N. R. K. Chowdhury;M. Kirsanov;A. Kouchner;V. Kulikovskiy;K. Kuzmin;R. Breton;O. Lebedev;M. Lincetto;E. Litvinovich;D. López-Coto;C. Markou;A. Maximov;K. Melis;V. Naumov;S. Navas;L. Nauta;C. Nielsen;F. Novoskoltsev;B. Fearraigh;Mukharbek Organokov;G. Papalashvili;M. Perrin-Terrin;C. Poirè;T. Pradier;L. Quinn;D. Samtleben;M. Sanguineti;J. Seneca;R. Shanidze;E. Shirokov;A. Sinopoulou;R. Sinyukov;M. Skorokhvatov;I. Sokalski;A. Sokolov;B. Spisso;S. Stellacci;B. Strandberg;M. Taiuti;T. Thakore;E. Tzamariudaki;V. Elewyck;E. Wolf;D. Zaborov;A. Zaitsev;J. Zornoza;J. Z'uniga]
通讯作者: A. V. Akindinov;E. Anassontzis;G. Anton;M. Ardid;J. Aublin;B. Baret;V. Bertin;S. Bourret;C. Bozza;M. Bruchner;R. Bruijn;J. Brunner;M. Chabab;N. Chau;A. Chepurnov;M. C. Molla;P. Coyle;A. Creusot;G. Wasseige;A. Domi;C. Donzaud;T. Eberl;A. Enzenhofer;M. Fayfman;M. Filipovi'c;L. Fusco;V. Garkusha;T. Gál;S. Gozzini;K. Graf;T. Gr'egoire;G. Grella;S. Hallmann;A. Heijboer;J. Hern'andez-Rey;J. Hofestadt;S. Ivanov;C. James;M. Jong;P. Jong;P. Kalaczy'nski;I. Kakorin;U. Katz;N. R. K. Chowdhury;M. Kirsanov;A. Kouchner;V. Kulikovskiy;K. Kuzmin;R. Breton;O. Lebedev;M. Lincetto;E. Litvinovich;D. López-Coto;C. Markou;A. Maximov;K. Melis;V. Naumov;S. Navas;L. Nauta;C. Nielsen;F. Novoskoltsev;B. Fearraigh;Mukharbek Organokov;G. Papalashvili;M. Perrin-Terrin;C. Poirè;T. Pradier;L. Quinn;D. Samtleben;M. Sanguineti;J. Seneca;R. Shanidze;E. Shirokov;A. Sinopoulou;R. Sinyukov;M. Skorokhvatov;I. Sokalski;A. Sokolov;B. Spisso;S. Stellacci;B. Strandberg;M. Taiuti;T. Thakore;E. Tzamariudaki;V. Elewyck;E. Wolf;D. Zaborov;A. Zaitsev;J. Zornoza;J. Z'uniga
Event reconstruction for KM3NeT/ORCA using convolutional neural networks
使用卷积神经网络对 KM3NeT/ORCA 进行事件重建
DOI: 10.1088/1748-0221/15/10/p10005
发表时间:
期刊: Journal of Instrumentation
影响因子: 1.3
作者: [S. Aiello]
通讯作者: S. Aiello
Machine Learning for KM3NeT/ORCA
KM3NeT/ORCA 机器学习
DOI: 10.22323/1.358.0904
发表时间: 2019
期刊: Proceedings of 36th International Cosmic Ray Conference — PoS(ICRC2019)
影响因子: --
作者: [S. Hallmann, M. Moser, S. Reck, T. Eberl]
通讯作者: T. Eberl
Tau neutrino appearance with KM3NeT / ORCA
KM3NeT / ORCA 中的 Tau 中微子外观
DOI: 10.22323/1.301.1025
发表时间: 2017
期刊:
影响因子: --
作者: [T. Eberl, S. Hallmann, J. Hofestädt]
通讯作者: J. Hofestädt
共 8 条
    国内基金
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    腹侧海马Calb1神经元tau蛋白聚集在阿尔茨海默样社交记忆障碍中的作用及机制研究
    • 批准号:
      JCZRQNB202600714
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2026
    • 负责人:
    • 依托单位:
    P2X7 受体调控小胶质细胞外泌体分泌参与阿尔茨海默病 tau 病理传播的过程及机制研究
    • 批准号:
      ZCLQN26C0901
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2026
    • 负责人:
      赵帅
    • 依托单位:
    AEP剪切SET参与阿尔茨海默症Tau病变机制研究
    基于多尺度MD和AI解析阿尔茨海默病Tau蛋白相分离失衡分子机制及靶向构象调控策略
    • 批准号:
      JCZRLH202600201
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2026
    • 负责人:
    • 依托单位: