activity
20082026
most citedFingerprints of Galactic Loop I on the Cosmic Microwave Background

82 citations · 462 across the 39 of their papers we have counts for

collaborators

39 papers

astro-ph.CO2026

Do We Have Sufficient Knowledge of the Galactic Foreground Emission in Cosmic Microwave Background Science?

Jia-Rui Li, Peibo Yuan, Yi-Fu Cai +1

Galactic foreground emission plays a key role in cosmic microwave background (CMB) science, particularly for detecting primordial gravitational waves. A well-known lesson is the ``…

astro-ph.HE2023★ 6 cited

A new variability pattern in GRS 1915+105 with NICER and Insight-HXMT observations

Zhihong Shi, Qingwen Wu, Zhen Yan +2

We explore the timing and spectral properties of GRS 1915+105 based on X-ray observations of NICER and Insight-HXMT during the long outburst from 2017 to 2021. We find a new class…

gr-qc2023★ 1 cited

Self-supervised learning for gravitational wave signal identification

Hao-Yang Liu, Yu-Tong Wang

The computational cost of searching for gravitational wave (GW) signals in low latency has always been a matter of concern. We present a self-supervised learning model applicable t…

astro-ph.HE2022★ 11 cited

Coevolution of broad emission lines and X-ray spectrum in changing-look AGNs

Hao Liu, Qingwen Wu, Bing Lyu

Changing-look active galactic nuclei (CLAGNs) show the disappearance and reappearance of broad emission lines in a few years, which challenges the orientation-based AGN unification…

astro-ph.CO2021★ 1 cited

Pixel domain multi-resolution minimum variance painting of CMB maps

Hao Liu

This work introduces an unbiased minimum variance painting of the pixel domain CMB maps for both the missing and available sky regions. In the missing region, it generates CMB real…

astro-ph.CO2020

Comparison of the Planck 2018 CMB polarization maps in the BICEP2/Keck region

Hao Liu, James Creswell, Pavel Naselsky

We examine the statistical properties of polarization maps from Planck 2018 within the patch of sky observed by the BICEP2/Keck experiment using the one point distribution function…