Chrome Extension
WeChat Mini Program
Use on ChatGLM

Limit on the Production of a Low-Mass Vector Boson in E+e-→Uγ, U→e+e- with the KLOE Experiment

Physics Letters B(2016)

National Laboratory of Frascati | National Centre for Nuclear Research | INFN Sezione di Roma III | Uppsala University | INFN Sezione di Catania | Jagiellonian University | INFN Sezione di Roma I | INFN Sezione di Roma Tre Dipartimento di Matematica e Fisica dell' | INFN Sezione di Roma Dipartimento di Fisica dell' | Laboratori Nazionali di Frascati dell'INFN | INFN Sezione di Roma Tor Vergata Dipartimento di Fisica dell' | Jagiellonian University Institute of Physics | Uppsala University Department of Physics and Astronomy | Boston University Department of Physics | INFN Sezione di Roma Tre | INFN Sezione di Bari

Cited 110|Views24
Abstract
The existence of a new force beyond the Standard Model is compelling because it could explain several striking astrophysical observations which fail standard interpretations. We searched for the light vector mediator of this dark force, the U boson, with the KLOE detector at the DA Phi NE e(+)e(-) collider. Using an integrated luminosity of 1.54 fb(-1), we studied the process e(+)e(-) -> U gamma, with U -> e(+)e(-), using radiative return to search for a resonant peak in the dielectron invariant-mass distribution. We did not find evidence for a signal, and set a 90% CL upper limit on the mixing strength between the Standard Model photon and the dark photon, epsilon(2), at 10(-6)-10(-4) in the 5-520 MeV/c(2) mass range. (C) 2015 The Authors. Published by Elsevier B.V.
More
Translated text
Key words
Dark matter,Dark forces,Dark photon,U boson,A′
PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Try using models to generate summary,it takes about 60s
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers
C Boem,P Fayet
2004

被引用538 | 浏览

G. Aad, T. Abajyan, B. Abbott, J. Abdallah, S. Abdel Khalek, A. A. Abdelalim, O. Abdinov, R. Aben, B. Abi, M. Abolins, U. S. AbouZeid, H. Abramowicz,
2012

被引用12042 | 浏览

J. H. Kühn, A. Santamaria
1990

被引用483 | 浏览

Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest