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  • Letter

Implications for the non-Gaussianity of curvature perturbation from pulsar timing arrays

Lang Liu1,2,‡, Zu-Cheng Chen3,4,1,2,*, and Qing-Guo Huang5,6,7,†

  • 1Department of Astronomy, Beijing Normal University, Beijing 100875, China
  • 2Advanced Institute of Natural Sciences, Beijing Normal University, Zhuhai 519087, China
  • 3Department of Physics and Synergetic Innovation Center for Quantum Effects and Applications, Hunan Normal University, Changsha, Hunan 410081, China
  • 4Institute of Interdisciplinary Studies, Hunan Normal University, Changsha, Hunan 410081, China
  • 5CAS Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing 100190, China
  • 6School of Physical Sciences, University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China
  • 7School of Fundamental Physics and Mathematical Sciences, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China

  • *Corresponding author: zuchengchen@gmail.com
  • †Corresponding author: huangqg@itp.ac.cn
  • ‡liulang@bnu.edu.cn

Phys. Rev. D 109, L061301 – Published 4 March, 2024

DOI: https://doi.org/10.1103/PhysRevD.109.L061301

Abstract

The recently released data by pulsar timing array (PTA) collaborations present strong evidence for a stochastic signal consistent with a gravitational-wave background. Assuming this signal originates from scalar-induced gravitational waves, we jointly use the PTA data from the NANOGrav 15-yr dataset, PPTA DR3, and EPTA DR2 to probe the small-scale non-Gaussianity. We put the first-ever constraint on the non-Gaussianity parameter, finding |FNL|≲13.9 for a lognormal power spectrum of the curvature perturbations. Furthermore, we obtain −13.9≲FNL≲−0.1 to prevent excessive production of primordial black holes. Moreover, the multiband observations with the space-borne gravitational-wave detectors, such as LISA/Taiji/TianQin, will provide a complementary investigation of primordial non-Gaussianity. Our findings pave the way to constrain inflation models with PTAs.

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