papers

Publications (37)

astro-ph.HE2023

SN 2022vqz: A Peculiar Subluminous Type Ia Supernova with Prominent Early Excess Emission

Gaobo Xi, Xiaofeng Wang, Gaici Li +22

We present extensive photometric and spectroscopic observations of the peculiar Type Ia supernova (SN Ia) 2022vqz. It shares many similarities with the SN 2002es-like SNe Ia, such…

astro-ph.HE2026

AT 2024wpp: the most luminous fast-evolving optical transient linked to the merger explosion of a black-hole binary

Jialian Liu, Bao Wang, Xiaofeng Wang +48

Fast blue optical transients (FBOTs) represent one of the most exotic astrophysical transients, exhibiting unusually strong emission across X-ray, optical, and radio wavelengths. T…

astro-ph.SR2023

Minute-cadence Observations of the LAMOST Fields with the TMTS: III. Statistic Study of the Flare Stars from the First Two Years

Qichun Liu, Jie Lin, Xiaofeng Wang +22

Tsinghua University-Ma Huateng Telescopes for Survey (TMTS) aims to detect fast-evolving transients in the Universe, which has led to the discovery of thousands of short-period var…

astro-ph.HE2021

The Peculiar Transient AT2018cow: A Possible Origin of A Type Ibn/IIn Supernova

Danfeng Xiang, Xiaofeng Wang, Weili Lin +47

We present our photometric and spectroscopic observations on the peculiar transient AT2018cow. The multi-band photometry covers from peak to 70 days and the spectroscopy rang…

astro-ph.HE2026

SN 2022erq: A Superluminous Thermonuclear Supernova with Escalating Preexplosion Mass Loss

Qian Zhai, Jujia Zhang, Xiaofeng Wang +51

We present a photometric and spectroscopic study of the superluminous Type Ia supernova SN 2022erq. Its early spectra, dominated by iron-group elements with weak intermediate-mass…

eess.IV2021

Learning MRI Artifact Removal With Unpaired Data

Siyuan Liu, Kim-Han Thung, Liangqiong Qu +3

Retrospective artifact correction (RAC) improves image quality post acquisition and enhances image usability. Recent machine learning driven techniques for RAC are predominantly ba…

eess.IV2020

Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge

Yue Sun, Kun Gao, Zhengwang Wu +30

To better understand early brain growth patterns in health and disorder, it is critical to accurately segment infant brain magnetic resonance (MR) images into white matter (WM), gr…

astro-ph.HE2023

A Superluminous Supernova Lightened by Collisions with Pulsational Pair-instability Shells

Weili Lin, Xiaofeng Wang, Lin Yan +23

Superluminous supernovae are among the most energetic stellar explosions in the Universe, but their energy sources remain an open question. Here we present long-term observations o…

astro-ph.HE2022

Observations of the Very Young Type Ia Supernova 2019np with Early-excess Emission

Hanna Sai, Xiaofeng Wang, Nancy Elias-Rosa +30

Early-time radiative signals from type Ia supernovae (SNe Ia) can provide important constraints on the explosion mechanism and the progenitor system. We present observations and an…

astro-ph.HE2021

SN 2015bf: a fast declining type II supernova with flash-ionised signatures

Han Lin, Xiaofeng Wang, Jujia Zhang +19

We present optical and ultraviolet photometry, as well as optical spectra, for the type II supernova (SN) 2015bf. Our observations cover the phases from to d af…

astro-ph.IM2021

Minute-cadence Observations of the LAMOST Fields with the TMTS: I. Methodology of Detecting Short-period Variables and Results from the first-year Survey

Jie Lin, Xiaofeng Wang, Jun Mo +18

Tsinghua University-Ma Huateng Telescopes for Survey (TMTS), located at Xinglong Station of NAOC, has a field of view upto 18 deg^2. The TMTS has started to monitor the LAMOST sky…

astro-ph.HE2021

Supernova luminosity powered by magnetar-disk system

Weili Lin, Xiaofeng Wang, Lingjun Wang +1

Magnetars are one of the potential power sources for some energetic supernova explosions such as type I superluminous supernovae (SLSNe I) and broad-lined type Ic supernovae (SNe I…

eess.IV2022

Longitudinal Prediction of Postnatal Brain Magnetic Resonance Images via a Metamorphic Generative Adversarial Network

Yunzhi Huang, Sahar Ahmad, Luyi Han +6

Missing scans are inevitable in longitudinal studies due to either subject dropouts or failed scans. In this paper, we propose a deep learning framework to predict missing scans fr…

q-bio.NC2021

A Few-shot Learning Graph Multi-Trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint

Alaa Bessadok, Ahmed Nebli, Mohamed Ali Mahjoub +4

Charting the baby connectome evolution trajectory during the first year after birth plays a vital role in understanding dynamic connectivity development of baby brains. Such analys…

cs.CV2020

Real-Time Quality Assessment of Pediatric MRI via Semi-Supervised Deep Nonlocal Residual Neural Networks

Siyuan Liu, Kim-Han Thung, Weili Lin +2

In this paper, we introduce an image quality assessment (IQA) method for pediatric T1- and T2-weighted MR images. IQA is first performed slice-wise using a nonlocal residual neural…

astro-ph.HE2024

A Shock Flash Breaking Out of a Dusty Red Supergiant

Gaici Li, Maokai Hu, Wenxiong Li +41

Shock breakout emission is light that arises when a shockwave, generated by core-collapse explosion of a massive star, passes through its outer envelope. Hitherto, the earliest det…

astro-ph.HE2021

ASASSN-14ms:the Most Energetic Known Explosion of a Type Ibn Supernova and its Physical Origin

Xiaofeng Wang, Weili Lin, Jujia Zhang +14

ASASSN-14ms may represent the most luminous Type Ibn supernova (SN~Ibn) ever detected, with an absolute U-band magnitude brighter than -22.0 mag and a total bolometric luminosity >…

astro-ph.SR2024

Minute-Cadence Observations of the LAMOST Fields with the TMTS V. Machine Learning Classification of TMTS Catalogues of Periodic Variable Stars

Fangzhou Guo, Jie Lin, Xiaofeng Wang +17

Periodic variables are always of great scientific interest in astrophysics. Thanks to the rapid advancement of modern large-scale time-domain surveys, the number of reported variab…

physics.med-ph2020

Multifold Acceleration of Diffusion MRI via Slice-Interleaved Diffusion Encoding (SIDE)

Yoonmi Hong, Wei-Tang Chang, Geng Chen +4

Diffusion MRI (dMRI) is a unique imaging technique for in vivo characterization of tissue microstructure and white matter pathways. However, its relatively long acquisition time im…

q-bio.NC2020

Co-evolution of Functional Brain Network at Multiple Scales during Early Infancy

Xuyun Wen, Liming Hsu, Weili Lin +2

The human brains are organized into hierarchically modular networks facilitating efficient and stable information processing and supporting diverse cognitive processes during the c…

physics.med-ph2020

Probing Tissue Microarchitecture of the Baby Brain via Spherical Mean Spectrum Imaging

Khoi Minh Huynh, Tiantian Xu, Ye Wu +7

During the first years of life, the human brain undergoes dynamic spatially-heterogeneous changes, involving differentiation of neuronal types, dendritic arborization, axonal ingro…

astro-ph.SR2023

Minute-Cadence Observations of the LAMOST Fields with the TMTS: II. Catalogues of Short-Period Variable Stars from the First Two-Year Surveys

Jie Lin, Xiaofeng Wang, Jun Mo +25

Over the past few years, wide-field time-domain surveys like ZTF and OGLE have led to discoveries of various types of interesting short-period stellar variables, such as ultracompa…

physics.med-ph2018

Angular Upsampling in Infant Diffusion MRI Using Neighborhood Matching in x-q Space

Geng Chen, Bin Dong, Yong Zhang +3

Diffusion MRI requires sufficient coverage of the diffusion wavevector space, also known as the q-space, to adequately capture the pattern of water diffusion in various directions…

cs.CV2019

Spherical U-Net on Cortical Surfaces: Methods and Applications

Fenqiang Zhao, Shunren Xia, Zhengwang Wu +6

Convolutional Neural Networks (CNNs) have been providing the state-of-the-art performance for learning-related problems involving 2D/3D images in Euclidean space. However, unlike i…

astro-ph.HE2026

Spectral Dataset of Stripped-Envelope Supernovae from the Tsinghua Supernova Group

Danfeng Xiang, Xiaofeng Wang, Jujia Zhang +40

The extent of envelope stripping in the progenitor stars is directly reflected in the diversity of spectral features observed in stripped-envelope supernovae (SESNe). Through exten…

q-bio.NC2024

Predicting Infant Brain Connectivity with Federated Multi-Trajectory GNNs using Scarce Data

Michalis Pistos, Gang Li, Weili Lin +2

The understanding of the convoluted evolution of infant brain networks during the first postnatal year is pivotal for identifying the dynamics of early brain connectivity developme…

astro-ph.SR2022

An 18.9-minute Blue Large-Amplitude Pulsator Crossing the 'Hertzsprung Gap' of Hot Subdwarfs

Jie Lin, Chengyuan Wu, Xiaofeng Wang +28

Blue large-amplitude pulsators (BLAPs) represent a new and rare class of hot pulsating stars with unusually large amplitudes and short periods. Up to now, only 24 confirmed BLAPs h…

cs.CV2023

Source-Free Unsupervised Domain Adaptation: A Survey

Yuqi Fang, Pew-Thian Yap, Weili Lin +2

Unsupervised domain adaptation (UDA) via deep learning has attracted appealing attention for tackling domain-shift problems caused by distribution discrepancy across different doma…

astro-ph.HE2024

SN 2014C: a metamorphic supernova exploded in the intricate and hydrogen-rich surroundings

Qian Zhai, Jujia Zhang, Weili Lin +6

We present photometric and spectroscopic observations of supernova (SN) 2014C, primarily emphasizing the initial month after the explosion at approximately daily intervals. During…

astro-ph.HE2023

Discovery of the Closest Ultrastripped Supernova: SN 2021agco in UGC 3855

Shengyu Yan, Xiaofeng Wang, Xing Gao +16

We present the discovery and studies of the helium-rich, fast-evolving supernova (SN) 2021agco at a distance of 40 Mpc. Its early-time flux is found to rise from half peak t…

astro-ph.HE2024

A spectral data release for 104 Type II Supernovae from the Tsinghua Supernova Group

Han Lin, Xiaofeng Wang, Jujia Zhang +33

We present 206 unpublished optical spectra of 104 type II supernovae obtained by the Xinglong 2.16m telescope and Lijiang 2.4m telescope during the period from 2011 to 2018, spanni…

astro-ph.HE2021

Optical and Ultraviolet Monitoring of the Black Hole X-ray Binary MAXI J1820+070/ASASSN-18ey for 18 Months

Hanna Sai, Xiaofeng Wang, Jianfeng Wu +20

MAXI J1820+070 is a low-mass black hole X-ray binary system with high luminosity in both optical and X-ray bands during the outburst periods. We present extensive photometry in X-r…

astro-ph.HE2024

Light curves of the explosion of ONe WD+CO WD merger remnant and type Icn supernovae

Chengyuan Wu, Shuai Zha, Yongzhi Cai +6

Type Icn supernovae (SNe Icn) are a newly detected rare subtype of interacting stripped-envelope supernovae which show narrow P-Cygni lines of highly ionized carbon, oxygen, and ne…

physics.med-ph2020

Navigator-Free Submillimeter Diffusion Imaging using Multishot-encoded Simultaneous Multi-slice (MUSIUM)

Wei-Tang Chang, Khoi Minh Huynh, Pew-Thian Yap +1

The ability to achieve submillimter isotropic resolution diffusion MR imaging (dMRI) is critically important to study fine-scale brain structures, particularly in the cortex. One o…

cs.CV2019

FRNET: Flattened Residual Network for Infant MRI Skull Stripping

Qian Zhang, Li Wang, Xiaopeng Zong +3

Skull stripping for brain MR images is a basic segmentation task. Although many methods have been proposed, most of them focused mainly on the adult MR images. Skull stripping for…

astro-ph.SR2024

Minute-Cadence Observations of the LAMOST Fields with the TMTS: IV -- Catalog of Cataclysmic Variables from the First 3-yr Survey

Qichun Liu, Jie Lin, Xiaofeng Wang +24

The Tsinghua University--Ma Huateng Telescopes for Survey (TMTS) started to monitor the LAMOST plates in 2020, leading to the discovery of numerous short-period eclipsing binaries,…

stat.AP2013

Multiscale adaptive smoothing models for the hemodynamic response function in fMRI

Jiaping Wang, Hongtu Zhu, Jianqing Fan +2

In the event-related functional magnetic resonance imaging (fMRI) data analysis, there is an extensive interest in accurately and robustly estimating the hemodynamic response funct…