Collaborative Research: NSF-BSF: Continuation of the XENON Program at LNGS

合作研究：NSF-BSF：LNGS 氙气项目的延续

• 批准号: 2112801
• 负责人: Christopher Tunnell
• 金额: $ 25.8万
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2112801&HistoricalAwards=false
• 关键词: Collaborative; Research; NSF; BSF; Continuation

Identifying the nature of dark matter remains one of the most pressing problems in physics today. The direct search for dark matter particles with the XENON family of experiments using liquid xenon time projection chambers (LXeTPCs) of increasing target mass and decreasing background has led to the most stringent constraints on many different dark matter candidates, over a broad range of mass, type of coupling, cross-section, and particle type. Building on the success of the first multi-tonne LXeTPC, XENON1T, this collaboration has expanded the scientific reach of this technology by building a new LXeTPC, XENONnT, of larger target mass and with lower intrinsic background but re-using infrastructure and already tested systems.Liquid xenon detector technologies are unique training grounds for undergraduate and graduate students, and postdoctoral scientists, in that they combine significant hardware involvement with advanced data analysis skills. Technologies span from sophisticated detector design to cyber-infrastructure and innovative data analysis, with applications in other fields such as medical imaging and nuclear nonproliferation. The entire project employs an open data policy to foster benefits in other areas of research and education. the participating groups facilitate and encourage public interest in science through targeted talks and outreach activities with particular focus to support members of underrepresented and underserved groups.The XENONnT experiment, with its multi-tonnes fiducial mass and ultra-low background will reach a sensitivity to various dark matter models more than an order of magnitude beyond current knowledge. XENONnT will be sensitive to a variety of interactions, including spin-independent, spin-dependent, and other couplings; to a variety of particles, including WIMPs, axion-like particles, solar axions and dark photons; and at the same time, XENONnT will cover particle masses ranging from kilo-electronvolts almost up to the Planck mass. It will also be an observatory for other highly interesting physics. Examples in neutrino physics include a measurement of the Solar neutrino luminosity through pp neutrinos and a first measurement of the Solar metallicity through boron-8 neutrinos. The detector might also observe neutrinos from a Galactic supernova and potentially issue early multi-messenger alerts to telescopes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

确定暗物质的性质仍然是当今物理学中最紧迫的问题之一。使用液体氙时间投影室（LXETPC）的实验家族直接搜索暗物质颗粒，以增加目标质量和下降背景，从而在许多不同的暗物质候选者上造成了最严格的限制，在广泛的质量，类型的耦合，横截面和粒子类型和类型的范围内。这项合作以第一个多量LXETPC Xenon1t的成功为基础，通过构建一个较大的目标质量和较低固有背景的新的LXETPC（Xenonnt）来扩大该技术的科学影响力，但具有较低的固有背景，但重新使用基础设施，但已经测试过的系统和已经测试的系统。硬件参与高级数据分析技能。技术从复杂的探测器设计到网络基础结构和创新数据分析，并在其他领域（例如医学成像和核不扩散）进行了应用。整个项目采用开放数据政策来促进研究和教育其他领域的利益。参与小组通过有针对性的谈判和宣传活动促进和鼓励公众对科学的兴趣，特别是支持代表性不足和服务不足的群体的成员。Xenonnt实验，其多吨基准的基础质量和超低背景将达到对各种暗物质模型的敏感性，而不是当前知识超出当前知识。 Xenonnt将对各种相互作用敏感，包括独立于自旋，旋转依赖性和其他耦合；到各种颗粒，包括wimps，轴突状颗粒，太阳轴和深色光子；同时，Xenonnt将覆盖粒子质量，范围从千电子伏特（Kilo-Electronvolts）几乎到普朗克质量。这也将是其他非常有趣的物理学的天文台。中微子物理学中的例子包括通过PP中微子测量太阳中微子的光度，以及通过硼龙-8中微子对太阳金属性的首次测量。该探测器还可以观察到银河系超新星的中微子，并可能向望远镜发出早期的多通讯社警报。该奖项反映了NSF的法定任务，并且认为值得通过基金会的知识分子优点和更广泛的审查标准通过评估来进行评估。

项目成果

GPU-based optical simulation of the DARWIN detector

• DOI: 10.1088/1748-0221/17/07/p07018
• 发表时间: 2022-03
• 期刊: Journal of Instrumentation
• 影响因子: 1.3
• 作者: L. Althueser;B. Antunović;E. Aprile;D. Bajpai;L. Baudis;D. Baur;A. Baxter;L. Bellagamba;R. Biondi;Y. Biondi;A. Bismark;A. Brown;R. Budnik;A. Chauvin;A. Colijn;J. J. Cuenca-García-J.;V. D’Andrea;P. Di Gangi;J. Dierle;S. Diglio;M. Doerenkamp;K. Eitel;S. Farrell;A. Ferella;C. Ferrari;C. Findley;H. Fischer;M. Galloway;F. Girard;R. Glade-Beucke;L. Grandi;M. Guida;S. Hansmann-Menzemer;F. Jörg;L. Jones;P. Kavrigin;L. Krauss;B. von Krosigk;F. Kuger;H. Landsman;R. Lang;S. Li;S. Liang;M. Lindner;J. Loizeau;F. Lombardi;T. Marrodán Undagoitia;J. Masbou;E. Masson;J. Matias-Lopes;S. Milutinović;C. Monteiro;M. Murra;K. Ni;U. Oberlack;I. Ostrovskiy;M. Pandurović;R. Peres;J. Qin;M. Rajado Silva;D. Ramírez García;P. Sanchez-Lucas;J. D. dos Santos;M. Schumann;M. Selvi;F. Semeria;H. Simgen;M. Steidl;P. Tan;A. Terliuk;K. Thieme;R. Trotta;C. Tunnell;F. Tönnies;K. Valerius;S. Vetter;G. Volta;W. Wang;C. Wittweg;Y. Xing

Application and modeling of an online distillation method to reduce krypton and argon in XENON1T

在线蒸馏方法减少 XENON1T 中氪和氩的应用和建模

• DOI: 10.1093/ptep/ptac074
• 发表时间: 2022
• 期刊: Progress of Theoretical and Experimental Physics
• 影响因子: 3.5
• 作者: 坂栗佳奈;他;E. Aprile et al. XENON collaboration
• 通讯作者: E. Aprile et al. XENON collaboration

First Dark Matter Search with Nuclear Recoils from the XENONnT Experiment

• DOI: 10.1103/physrevlett.131.041003
• 发表时间: 2023-07-28
• 期刊: PHYSICAL REVIEW LETTERS
• 影响因子: 8.6
• 作者: Aprile, E.;Abe, K.;Zhu, T.
• 通讯作者: Zhu, T.

Low-energy calibration of XENON1T with an internal $$^{{\textbf {37}}}$$Ar source

使用内部 $$^{{ extbf {37}}}$$Ar 源对 XENON1T 进行低能校准

• DOI: 10.1140/epjc/s10052-023-11512-z
• 发表时间: 2023
• 期刊: The European Physical Journal C
• 作者: Aprile, E.;Abe, K.;Agostini, F.;Ahmed Maouloud, S.;Alfonsi, M.;Althueser, L.;Andrieu, B.;Angelino, E.;Angevaare, J. R.;Antochi, V. C.
• 通讯作者: Antochi, V. C.

Detector signal characterization with a Bayesian network in XENONnT

• DOI: 10.1103/physrevd.108.012016
• 发表时间: 2023-04
• 期刊: Physical Review D
• 影响因子: 5
• 作者: X. C. E. Aprile;K. Abe;S. A. Maouloud;L. Althueser;B. Andrieu;E. Angelino;J. Angevaare;V. C. Antochi;D. A. Martin;F. Arneodo;L. Baudis;A. Baxter;M. Bazyk;L. Bellagamba;R. Biondi;A. Bismark;E. J. Brookes;A. Brown;S. Bruenner;G. Bruno;R. Budnik;T. Bui;C. Cai;J. Cardoso;D. Cichon;A. P. C. Chavez;A. Colijn;J. Conrad;J. Cuenca-Garc'ia;J. Cussonneau;V. D’Andrea;M. P. Decowski;P. Gangi;S. D. Pede;S. Diglio;K. Eitel;A. Elykov;S. Farrell;A. Ferella;C. Ferrari;H. Fischer;M. Flierman;W. Fulgione;C. Fuselli;P. Gaemers;R. Gaior;A. G. Rosso;M. Galloway;F. Gao;R. Glade-Beucke;L. Grandi;J. Grigat;H. Guan;M. Guida;R. Hammann;A. Higuera;C. Hils;L. Hoetzsch;N. Hood;J. Howlett;M. Iacovacci;Y. Itow;J. Jakob;F. Joerg;A. Joy;N. Kato;M. Kara;P. Kavrigin;S. Kazama;M. Kobayashi;G. Koltman;A. Kopec;F. Kuger;H. Landsman;R. Lang;L. Levinson;I. Li;S. Li;S. Liang;S. Lindemann;M. Lindner;K. Liu;J. Loizeau;F. Lombardi;J. Long;J. Lopes;Y. Ma;C. Macolino;J. Mahlstedt;A. Mancuso;L. Manenti;F. Marignetti;T. Undagoitia;K. Martens;J. Masbou;D. Masson;E. Masson;S. Mastroianni;M. Messina;K. Miuchi;K. Mizukoshi;A. Molinario;S. Moriyama;K. Morra;Y. Mosbacher;M. Murra;J. Muller;K. Ni;U. Oberlack;B. Paetsch;J. Palacio;Q. Pellegrini;R. Peres;C. Peters;J. Pienaar;M. Pierre;V. Pizzella;G. Plante;T. Pollmann;J. Qi;J. Qin;D. R. Garc'ia;R. Singh;L. Sanchez;J. Santos;I. Sarnoff;G. Sartorelli;J. Schreiner;D. Schulte;P. Schulte;H. Eissing;M. Schumann;L. Lavina;M. Selvi;F. Semeria;P. Shagin;S. Shi;E. Shockley;M. Silva;H. Simgen;A. Takeda;P. Tan;A. Terliuk;D. Thers;F. Toschi;G. Trinchero;C. Tunnell;F. Tonnies;K. Valerius;G. Volta;C. Weinheimer;M. Weiss;D. Wenz;C. Wittweg;Thomas Wolf;V. Wu;Y. Xing;D. Xu;Z. Xu;M. Yamashita;L. Yang;J. Ye;L. Yuan;G. Zavattini;M. Zhong;T. Zhu