Proceedings of Particles and Nuclei International Conference 2021 — PoS(PANIC2021)最新文献_第10页

Results overview from the DAMPE space mission in orbit DAMPE在轨空间任务的结果概述

Proceedings of Particles and Nuclei International Conference 2021 — PoS(PANIC2021) Pub Date : 2022-03-02 DOI: 10.22323/1.380.0310

D. Kyratzis

{"title":"Results overview from the DAMPE space mission in orbit","authors":"D. Kyratzis","doi":"10.22323/1.380.0310","DOIUrl":"https://doi.org/10.22323/1.380.0310","url":null,"abstract":"The Dark Matter Particle Explorer (DAMPE), is a space–borne detector designed for precise galactic Cosmic Ray (CR) studies in a wide energy range (up to 100 TeV), along with detailed measurements of high–energy gamma–rays and indirect searches of Dark Matter (DM) annihilation/decay to detectable particles. The satellite was launched into a sun–synchronous orbit at 500 km, on December 17th 2015 and has been successfully acquiring data ever since. The instrument consists of four sub-detectors, namely: a Plastic Scintillator Detector (PSD), a Silicon TracKerconverter (STK), a deep Bismuth Germanate (BGO) calorimeter 32 X0, 1.6 λI ) and a NeUtron Detector (NUD). DAMPE provided valuable insight on the cosmic-ray electron+positron (CRE) spectrum, unveiling a clear spectral break at 0.9 TeV with unprecedented energy resolution. Moreover, recent results regarding CR protons reveal a spectral hardening (at few hundred GeV) followed by a softening feature at 10 TeV. These features are well described by a smoothly-broken power law (SBPL), which differs from the paradigm of a unique power law (PL) spectrum extending up to PeV energies, hence necessitating a careful reconsideration of prevailing CR models. Additional insights concerning spectral measurements of helium, medium (i.e, boron, carbon, nitrogen, oxygen) and heavier mass nuclei (iron), will be presented in this work. Preliminary results on secondary-over-primary ratios (i.e., B/C and B/O) crucial in deciphering the nature of CR propagation in the Galaxy, will also be discussed, including a general synopsis of the mission status.","PeriodicalId":135659,"journal":{"name":"Proceedings of Particles and Nuclei International Conference 2021 — PoS(PANIC2021)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131552339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Strange, charm and bottom hadron flow in pp, pPb and PbPb collisions pp, pPb和PbPb碰撞中的奇异、魅力和底强子流

Proceedings of Particles and Nuclei International Conference 2021 — PoS(PANIC2021) Pub Date : 2022-03-02 DOI: 10.22323/1.380.0262

R. Pradhan

引用次数: 0

A study of the nuclear structure in the even-even Yb isotopes 偶偶Yb同位素的核结构研究

Proceedings of Particles and Nuclei International Conference 2021 — PoS(PANIC2021) Pub Date : 2022-03-02 DOI: 10.22323/1.380.0424

A. Zyriliou, T. Mertzimekis, A. Chalil, P. Vasileiou, E. Mavrommatis, D. Bonatsos, A. Martinou, S. Peroulis, N. Minkov

引用次数: 0

Cross section of the $^{13}$C($alpha$,n)$^{16}$O reaction at low energies in the framework of LUNA collaboration LUNA协作框架下$^{13}$C($alpha$，n)$^{16}$O低能反应截面

Proceedings of Particles and Nuclei International Conference 2021 — PoS(PANIC2021) Pub Date : 2022-03-02 DOI: 10.22323/1.380.0318

G. F. Ciani, "Francesco Barile", "Laszlo Csedreki", "David Rapagnani", "Andreas Best"

引用次数: 0

Recent XYZ studies at BESIII 最近在BESIII的XYZ研究

Proceedings of Particles and Nuclei International Conference 2021 — PoS(PANIC2021) Pub Date : 2022-03-02 DOI: 10.22323/1.380.0183

W. Imoehl

引用次数: 0

Effect of finite system size on the thermodynamics of hot and magnetized hadron resonance gas 有限系统尺寸对热磁化强子共振气体热力学的影响

Proceedings of Particles and Nuclei International Conference 2021 — PoS(PANIC2021) Pub Date : 2022-03-02 DOI: 10.22323/1.380.0236

D. Atta, Snigdha Ghosh

引用次数: 0

ATLAS results on charmonium production and $B_c$ production and decays ATLAS对charmonium产生和$B_c$产生和衰变的结果

Proceedings of Particles and Nuclei International Conference 2021 — PoS(PANIC2021) Pub Date : 2022-03-02 DOI: 10.22323/1.380.0389

S. Turchikhin

引用次数: 0

Interaction of the pseudoscalar glueball with (pseudo)scalar mesons and their first excited states 伪标量胶球与(伪)标量介子的相互作用及其第一激发态

Proceedings of Particles and Nuclei International Conference 2021 — PoS(PANIC2021) Pub Date : 2022-03-02 DOI: 10.22323/1.380.0173

W. Eshraim

引用次数: 1

Extraction of S-matrix pole structure using deep learning 基于深度学习的s矩阵极点结构提取

Proceedings of Particles and Nuclei International Conference 2021 — PoS(PANIC2021) Pub Date : 2022-03-02 DOI: 10.22323/1.380.0175

Denny Lane B. Sombillo

{"title":"Extraction of S-matrix pole structure using deep learning","authors":"Denny Lane B. Sombillo","doi":"10.22323/1.380.0175","DOIUrl":"https://doi.org/10.22323/1.380.0175","url":null,"abstract":"In this paper, we demonstrate how deep learning can be used as a unified model-selection tool in the analysis of hadron-hadron scattering. We consider the problem of finding the number of poles in each unphysical Riemann sheet to reproduce the elastic πN amplitude. The model space is constructed using 35 pole-based models with a maximum of 4 poles distributed in each Riemann sheet. The uncertainty due to the limited energy resolution is included in the generation of training amplitudes. The learning of the deep neural network is initiated using the curriculum technique, achieving a final training and testing accuracies of 76.5% and 80.4%, respectively. Due to the presence of error bars on the amplitude, it is expected that the experimental data can be described by more than one model. Thus, to realize the multiple descriptions of a given experimental data in our analysis, we utilize the error bars and generate 106 inference amplitudes to be fed directly to the trained neural network. Out of the 35 models, only 4 models are identified by the trained deep neural network to describe the πN scattering data. The most favored pole structure for the πN amplitude is one pole in each nearby sheet and two poles in the remote sheet. Further numerical analyses show that the deep learning framework is also robust and does not depend on how the inference amplitudes are generated from the experimental data.","PeriodicalId":135659,"journal":{"name":"Proceedings of Particles and Nuclei International Conference 2021 — PoS(PANIC2021)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125186072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The muon to electron conversion process and the Mu2e experiment at Fermilab 费米实验室的介子到电子的转换过程和Mu2e实验

Proceedings of Particles and Nuclei International Conference 2021 — PoS(PANIC2021) Pub Date : 2022-03-02 DOI: 10.22323/1.380.0422

S. Donati

引用次数: 0