Galactic and Extragalactic Cosmic Rays, Neutrinos and Gamma Rays

银河系和河外宇宙线、中微子和伽马射线

• 批准号: 2013199
• 负责人: Glennys Farrar
• 金额: $ 45.85万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2013199&HistoricalAwards=false
• 关键词: Galactic; Extragalactic; Cosmic; Rays; Neutrinos

The highest energy particle-messengers in the Universe are Ultrahigh Energy Cosmic Rays (UHECR) and Very High Energy (VHE) neutrinos and gamma rays. Discovering their origin is arguably the most important current problem in high energy astrophysics. This project is working towards that goal on four different fronts: 1) constraining source properties from the observed UHECR spectra and composition, and the astrophysical neutrino and VHE gamma ray spectra; 2) density of UHECR sources and source of VHE Galactic cosmic rays, from anisotropies; 3) deep machine learning to extract more information from UHECR observations; and 4) improved multi-messenger arrival direction studies. The new probabilistic methods of event reconstruction will have implications for pattern recognition problems more broadly. The PI mentors students and junior researchers, and runs a summer research collective for women high-school students that meets in person in summer and virtually during the academic year.The details will only be known as the work progresses, but the approaches are clear. 1)The combined multi-messenger information from the observed UHECR spectra and composition, and the astrophysical neutrino and VHE gamma ray spectra, powerfully constrains several properties of the source environment, and likely excludes many candidate source classes. 2)Improving the treatment of magnetic deflections and considering the anisotropies will better test the Galactic transient hypothesis and address the density of UHECR sources and the source of VHE Galactic cosmic rays. 3)Deep machine learning will extract more information from UHECR observations, reducing some of the difficulties and complexity of interpreting those data. For a precious 10% of the events there are air fluorescence data, and training Convolutional Neural Nets on this 10% will allow extraction of currently inaccessible information embedded in the ground signals of the 90%. 4)Improved multi-messenger arrival direction studies will use a new state-of-the-art Galactic magnetic field model. The UHECR source directions will be combined with the neutral neutrino and gamma ray messengers to produce a multi-messenger astrophysics dataset, which will greatly enhance the source-finding-power relative to using neutrinos and gamma-rays only.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.

宇宙中能量最高的粒子信使是超高能宇宙射线（UHECR）和极高能（VHE）中微子和伽马射线。 发现它们的起源可以说是当前高能天体物理学中最重要的问题。 该项目正在四个不同方面努力实现这一目标：1）根据观测到的 UHECR 光谱和成分以及天体物理中微子和 VHE 伽马射线光谱来限制源属性； 2) UHECR源和VHE银河宇宙射线源的各向异性密度； 3）深度机器学习，从UHECR观测中提取更多信息； 4）改进了多信使到达方向研究。 事件重建的新概率方法将对模式识别问题产生更广泛的影响。 PI 指导学生和初级研究人员，并为女高中生管理一个夏季研究小组，该小组在夏季和学年期间进行面对面的聚会。具体细节只有随着工作的进展才会得知，但方法是明确的。 1）来自观测到的 UHECR 光谱和成分以及天体物理中微子和 VHE 伽马射线光谱的综合多信使信息，有力地限制了源环境的几个属性，并且可能排除了许多候选源类别。 2）改进磁偏转处理并考虑各向异性，将更好地检验银河瞬变假说，解决UHECR源的密度和VHE银河宇宙线源的问题。 3）深度机器学习将从UHECR观测中提取更多信息，减少解释这些数据的一些困难和复杂性。 对于宝贵的 10% 的事件，有空气荧光数据，并且在这 10% 的事件上训练卷积神经网络将允许提取嵌入在 90% 的地面信号中的当前无法访问的信息。 4）改进的多信使到达方向研究将使用新的最先进的银河磁场模型。 UHECR源方向将与中微子和伽马射线信使相结合，产生多信使天体物理学数据集，相对于仅使用中微子和伽马射线，这将大大提高源发现能力。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Gas-rich dwarf galaxies as a new probe of dark matter interactions with ordinary matter

• DOI: 10.1103/physrevd.103.123028
• 发表时间: 2019-03
• 期刊: Physical Review D
• 影响因子: 5
• 作者: D. Wadekar;G. Farrar

Ultra high energy cosmic rays The intersection of the Cosmic and Energy Frontiers

• DOI: 10.1016/j.astropartphys.2023.102819
• 发表时间: 2023-02-27
• 期刊: ASTROPARTICLE PHYSICS
• 影响因子: 3.5
• 作者: Coleman，A.;Eser，J.;Zotov，M.
• 通讯作者: Zotov，M.

Galaxy Rotation Curves Disfavor Traditional and Self-interacting Dark Matter Halos, Preferring a Disk Component or Einasto Function

星系旋转曲线不喜欢传统的自相互作用暗物质晕，更喜欢圆盘组件或 Einasto 函数

• DOI: 10.3847/2041-8213/ac1bb7
• 发表时间: 2021
• 期刊: The Astrophysical Journal Letters
• 作者: Loizeau, Nicolas;Farrar, Glennys R.
• 通讯作者: Farrar, Glennys R.

Calibration of the underground muon detector of the Pierre Auger Observatory

皮埃尔奥格天文台地下μ介子探测器的校准

• DOI: 10.1088/1748-0221/16/04/p04003
• 发表时间: 2021
• 期刊: Journal of Instrumentation
• 影响因子: 1.3
• 作者: Aab, A.;Abreu, P.;Aglietta, M.;Albury, J.M.;Allekotte, I.;Almela, A.;Alvarez-Muñiz, J.;Alves Batista, R.;Anastasi, G.A.;Anchordoqui, L.
• 通讯作者: Anchordoqui, L.

A Search for Ultra-high-energy Neutrinos from TXS 0506+056 Using the Pierre Auger Observatory

• DOI: 10.3847/1538-4357/abb476
• 发表时间: 2020-10
• 期刊: The Astrophysical Journal
• 作者: T. P. A. C. A. Aab-T.-P.-A.-C.-A.-Aab-103010298;P. Abreu;M. Aglietta;J. Albury;I. Allekotte;A. Almela;J. Alvarez-Muñiz;R. A. Batista;G. A. Anastasi;L. Anchordoqui;B. Andrada;S. Andringa;C. Aramo;P. Ferreira;Hernán Asorey;P. Assis;G. Avila;A. M. Badescu;A. Bakalová;A. Bălăceanu;F. Barbato;R. Luz;K. Becker;J. Bellido;C. Bérat;M. Bertaina;X. Bertou;P. L. Biermann;T. Bister;J. Biteau;J. Blazek;C. Bleve;M. Boh'avcov'a;D. Boncioli;C. Bonifazi;L. Arbeletche;N. Borodai;A. M. Botti;J. Brack;T. Bretz;F. Briechle;P. Buchholz;A. Bueno;S. Buitink;M. Buscemi;K. Caballero-Mora;L. Caccianiga;L. Calcagni;A. Cancio;F. Canfora;I. Caracas;J. Carceller;R. Caruso;A. Castellina;F. Catalani;G. Cataldi;L. Cazon;M. Cerda;J. Chinellato;K. Choi;J. Chudoba;L. Chytka;R. Clay;A. Cerutti;R. Colalillo;A. Coleman;M. Coluccia;R. Conceiccao;A. Condorelli;G. Consolati;F. Contreras;F. Convenga;C. Covault;S. Dasso;K. Daumiller;B. Dawson;J. A. Day;R. M. Almeida;J. D. Jes'us;S. D. Jong;G. D. Mauro;J. D. M. Neto;I. Mitri;J. D. Oliveira;D. Franco;V. Souza;E. D. Vito;J. Debatin;M. D. R'io;O. Deligny;N. Dhital;A. Matteo;C. Dobrigkeit;J. D'Olivo;Q. Dorosti;R. Anjos;M. Dova;J. Ebr;R. Engel;I. Epicoco;M. Erdmann;C. Escobar;A. Etchegoyen;H. Falcke;J. Farmer;G. Farrar;A. C. Fauth;N. Fazzini;F. Feldbusch;F. Fenu;B. Fick;J. M. Figueira;A. Filipvcivc;T. Fodran;M. Freire;T. Fujii;A. Fuster;C. Galea;C. Galelli;B. Garc'ia;A. Vegas;H. Gemmeke;F. Gesualdi;A. Gherghel-Lascu;P. Ghia;U. Giaccari;M. Giammarchi;M. Giller;J. Glombitza;F. Gobbi;F. Gollan;G. Golup;M. G. Berisso;P. Vitale;J. P. Gongora;N. Gonz'alez;I. Goos;D. G'ora;A. Gorgi;M. Gottowik;T. D. Grubb;F. Guarino;G. Guedes;E. Guido;S. Hahn;R. Halliday;M. Hampel;P. Hansen;D. Harari;V. M. Harvey;A. Haungs;T. Hebbeker;D. Heck;G. Hill;C. Hojvat;J. Horandel;P. Horváth;M. Hrabovsk'y;T. Huege;J. Hulsman;A. Insolia;P. G. Isar;J. Johnsen;J. Juryšek;A. Kaapa;K. Kampert;B. Keilhauer;J. Kemp;H. Klages;M. Kleifges;J. Kleinfeller;M. Kopke;G. K. Mezek;B. Lago;D. LaHurd;R. Lang;N. Langner;M. Oliveira;V. Lenok;A. Letessier-Selvon;I. Lhenry-Yvon;D. L. Presti;L. Lopes;R. L'opez;R. Lorek;Q. Luce;A. Lucero;A. Payeras;G. Mancarella;D. Mandát;B. Manning;J. Manshanden;P. Mantsch;S. Marafico;A. Mariazzi;I. Marics;G. Marsella;D. Martello;H. Martinez;O. M. Bravo;M. Mastrodicasa;H. Mathes;J. Matthews;G. Matthiae;E. Mayotte;P. Mazur;G. Medina-Tanco;D. Melo;A. Menshikov;K. Merenda;S. Michal;M. Micheletti;L. Miramonti;D. Mockler;S. Mollerach;F. Montanet;C. Morello;M. Mostaf'a;A. Muller;M. Muller;K. Mulrey;R. Mussa;M. Muzio;W. M. Namasaka;L. Nellen;M. Niculescu-Oglinzanu;M. Niechciol;D. Nitz;D. Nosek;V. Novotny;L. Novzka;A. Nucita;L. A. N'unez;M. Palatka;J. Pallotta;P. Papenbreer;G. Parente;A. Parra;M. Pech;F. Pedreira;J. Pkekala;R. Pelayo;J. Peña-Rodríguez;J. P. Armand;M. Perlin;L. Perrone;S. Petrera;T. Pierog;M. Pimenta;V. Pirronello;M. Platino;B. Pont;M. Pothast;P. Privitera;M. Prouza;A. Puyleart;S. Querchfeld;J. Rautenberg;D. Ravignani;M. Reininghaus;J. Řídký;F. Riehn;M. Risse;P. Ristori;V. Rizi;W. Carvalho;J. Rojo;M. Roncoroni;M. Roth;E. Roulet;A. Rovero;P. Ruehl;S. Saffi;A. Săftoiu;F. Salamida;H. Salazar;G. Salina;J. S. Gomez;F. S'anchez;E. Santos;E. Santos;F. Sarazin;R. Sarmento;C. Sarmiento-Cano;R. Sato;P. Savina;C. Schafer;V. Scherini;H. Schieler;M. Schimassek;M. Schimp;F. Schluter;D. Schmidt;O. Scholten;P. Schov'anek;F. Schroder;S. Schroder;J. Schulte;S. Sciutto;M. Scornavacche;R. Shellard;G. Sigl;G. Silli;O. Sima;R. vSm'ida;P. Sommers;J. F. Soriano;J. Souchard;R. Squartini;M. Stadelmaier;D. Stanca;S. Stanivc;J. Stasielak;P. Stassi;A. Streich;M. Su'arez-Dur'an;T. Sudholz;T. Suomijarvi;A. Supanitsky;J. vSup'ik;Z. Szadkowski;A. Taboada;A. Tapia;C. Timmermans;O. Tkachenko;P. Tobiška;C. T. Peixoto;B. Tom'e;A. Travaini;P. Trávníček;C. Trimarelli;M. Trini;M. Tueros;R. Ulrich;M. Unger;L. Vaclavek;M. Vacula;J. F. V. Galicia;L. Valore;E. Varela;A. V'asquez-Ram'irez;D. Veberivc;C. Ventura;I. D. V. Quispe;V. Verzi;J. Vícha;J. Vink;S. Vorobiov;H. Wahlberg;A. Watson;M. Weber;A. Weindl;L. Wiencke;H. Wilczy'nski;T. Winchen;M. Wirtz;D. Wittkowski;B. Wundheiler;A. Yushkov;O. Zapparrata;E. Zas;D. Zavrtanik;M. Zavrtanik;L. Zehrer;A. Zepeda;M. Ziolkowski