Is PSR J0514-4002E in a PBH-NS Binary?

Science China Physics, Mechanics & Astronomy（2025）

Hunan Normal University Institute of Interdisciplinary Studies | Advanced Institute of Natural Sciences Department of Astronomy

Cited 1|Views3

Abstract

Recent pulsar timing observations using MeerKAT of the eccentric binary millisecond pulsar, PSR J0514–4002E, have unveiled a companion with a mass in the mass gap, ranging from 2.09 M⊙ to 2.71 M⊙. This challenges conventional astrophysical scenarios for black hole formation. In this paper, we present an alternative explanation: PSR J0514–4002E could be in a PBH-NS binary, with the companion potentially being a primordial black hole formed during the early Universe’s first-order phase transition. The associated stochastic gravitational-wave background generated during this phase transition can account for the observed signal from the pulsar timing array, and the abundance of primordial black holes is consistent with constraints from LIGO-Virgo-KAGRA.

Translated text

Key words

PSR J0514–4002E,primordial black hole,pulsar timing array,first-order phase transition

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