Journal of Astronomy and Space Sciences

The Korean Space Science Society (한국우주과학회)
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Search for Dark Photon in e+e- → A'A' Using Future Collider Experiments

  • Kihong Park (University of Science and Technology) ;
  • Kyungho Kim (Korea Institute of Science and Technology Information) ;
  • Alexei Sytov (Korea Institute of Science and Technology Information) ;
  • Kihyeon Cho (University of Science and Technology)
  • Received : 2023.10.17
  • Accepted : 2023.11.19
  • Published : 2023.12.15
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Abstract

The Standard Model (SM) does not provide an information for 26% of dark matter of the universe. In the dark sector, dark matter is supposed to be linked with the hypothetical particles called dark photons that have similar role to photons in electromagnetic interaction in the SM. Besides astronomical observation, there are studies to find dark matter candidates using accelerators. In this paper, we searched for dark photons using future electron-positron colliders, including Circular Electron Positron Collider (CEPC)/CEPC, Future Circular Collider (FCC-ee)/Innovative Detector for Electron-positron Accelerator (IDEA), and International Linear Collider (ILC)/International Large Detector (ILD). Using the parameterized response of the detector simulation of Delphes, we studied the sensitivity of a double dark photon mode at each accelerator/detector. The signal mode is double dark photon decay channel, e+e- → A'A', where A' (dark photon with spin 1) decaying into a muon pair. We used MadGraph5 to generate Monte Carlo (MC) events by means of a Simplified Model. We found the dark photon mass at which the cross-sections were the highest for each accelerator to obtain the maximum number of events. In this paper we show the expected number of dark photon signal events and the detector efficiency of each accelerator. The results of this study can facilitate in the dark photon search by future electron-positron accelerators.

Keywords

Acknowledgement

This study was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No. 2021R1F1A1064008). This study was also supported by the major institutional R&D program, KISTI (No. K-23-L02-C04-S01) and National Supercomputing Center with supercomputing resources including technical support (KSC-2023-CHA-0005). A. Sytov acknowledges support by the European Commission through the H2020-MSCA-IF TRILLION project (GA. 101032975).

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