Publications (28)
Probing the physics of newly born magnetars through observation of superluminous supernovae
Quan Cheng, Shuang-Nan Zhang, Yun-Wei Yu +1
The central engines of some superluminous supernovae (SLSNe) are generally suggested to be newly born fast rotating magnetars, which spin down mainly through magnetic dipole radiat…
Via Negativa for AI Alignment: Why Negative Constraints Are Structurally Superior to Positive Preferences
Quan Cheng
Recent empirical results have demonstrated that training large language models (LLMs) with negative-only feedback can match or exceed standard reinforcement learning from human fee…
PDAGENT-BENCH: Characterizing, Grounding, and Architecting LLM/VLM Agents for VLSI Physical Design
Qiufeng Li, Rongqian Chen, Quan Cheng +6
The paper presents PDAGENT-BENCH, a benchmark suite and workflow framework for evaluating large language model and vision‑language model agents on VLSI physical design tasks, cover…
Constraints on the internal physics of neutron stars from the observational data of several young pulsars: the role of a power-law decaying dipole magnetic field
Yu-Long Yan, Quan Cheng, Xiao-Ping Zheng
The observational data (e.g., the timing data and magnetic tilt angles ) of young pulsars can be used to probe some critical issues about the internal physics of neutron stars…
Why the Valuable Capabilities of LLMs Are Precisely the Unexplainable Ones
Quan Cheng
This paper proposes and argues for a counterintuitive thesis: the truly valuable capabilities of large language models (LLMs) reside precisely in the part that cannot be fully capt…
Constraining mechanism associated with fast radio burst and glitch from SGR J1935
Wei-Hua Wang, Heng Xu, Wei-Yang Wang +4
The discovery of fast radio burst (FRB) 200428 from galactic SGR J1935+2154 makes it possible to measure rotational changes accompanied by FRBs and to test several FRB models which…
Stable Routing for Mixture-of-Experts in Class-Incremental Learning
Zirui Guo, Quan Cheng, Da-Wei Zhou +1
Class-incremental learning (CIL) requires models to learn new classes sequentially while preserving prior knowledge. Recently, approaches that combine pre-trained models with mixtu…
Investigating the neutron star physics through observations of several young pulsars in the dipole-field re-emergence scenario
Yu-Long Yan, Quan Cheng, Xiao-Ping Zheng
The observed timing data, magnetic tilt angle , and age of young pulsars could be used to probe some important issues about neutron star (NS) physics, e.g., the NS internal mag…
Exploring Superfluid Angular Momentum Reservoir Effect on Pulsar Glitches and Forecasting Next Glitches of the Crab Pulsar
Pei-Xin Zhu, Xiao-Ping Zheng, Quan Cheng +2
Pulsar glitches are generally viewed as stochastic events driven by sudden angular momentum transfer from the neutron star's superfluid interior to its crust. Except two peculiar p…
A possible origin of the Galactic Center magnetar SGR 1745-2900
Quan Cheng, Shuang-Nan Zhang, Xiao-Ping Zheng
Since a large population of massive O/B stars and putative neutron stars (NSs) located in the vicinity of the Galactic center (GC), intermediate-mass X-ray binaries (IMXBs) constit…
Stochastic gravitational wave background from magnetic deformation of newly born magnetars
Quan Cheng, Yun-Wei Yu, Xiao-Ping Zheng
Newly born magnetars are promising sources for gravitational wave (GW) detection due to their ultra-strong magnetic fields and high spin frequencies. Within the scenario of a growi…
Continuous Subspace Optimization for Continual Learning
Quan Cheng, Yuanyu Wan, Lingyu Wu +2
Continual learning aims to learn multiple tasks sequentially while preserving prior knowledge, but faces the challenge of catastrophic forgetting when adapting to new tasks. Recent…
Bondi accretion of dark matter by neutron stars
Xi Huang, Jian-Feng Liu, Wei-Hua Wang +2
In this paper, we have compared two different accretion mechanisms of dark matter particles by a canonical neutron star with and , and shown the ef…
Could the stochastic gravitational wave background from newborn magnetars be detected by the advanced LIGO and Einstein Telescope?
Yu-Long Yan, Quan Cheng, Xiao-Ping Zheng +1
Newborn magnetars are important gravitational wave sources due to their ultra-strong magnetic fields and fast spins, and the entire population in the Universe may significantly con…
Physics of Strong Magnetism with eXTP
Mingyu Ge, Long Ji, Roberto Taverna +47
In this paper we present the science potential of the enhanced X-ray Timing and Polarimetry (eXTP) mission, in its new configuration, for studies of strongly magnetized compact obj…
Superfluid Angular Momentum Reservoir Effect in Pulsar Glitches and Crab Pulsar Glitch Time Prediction
Pei-Xin Zhu, Xiao-Ping Zheng, Quan Cheng +2
Pulsar glitches are usually regarded as stochastic, independent events triggered by sudden angular momentum transfer from the neutron star's superfluid interior to its crust. Howev…
What can PSR J1640-4631 tell us about the internal physics of this neutron star?
Quan Cheng, Shuang-Nan Zhang, Xiao-Ping Zheng +1
Gravitational wave emissions (GWEs) of pulsars could not only make them promising targets for continuous gravitational wave searches but also leave imprints in their timing data. W…
How can newly born rapidly rotating neutron stars become magnetars?
Quan Cheng, Yun-Wei Yu
In a newly born (high-temperature and Keplerian rotating) neutron star, r-mode instability can lead to stellar differential rotation, which winds the seed poloidal magnetic field (…
Could strange stars be in the color-flavor-locked phase: Tested by their thermal evolutions
Quan Cheng, Yun-Wei Yu, Xiao-Ping Zheng
The thermal evolution of strange stars in both normal and color-flavor-locked (CFL) phases are investigated together with the evolutions of the stellar rotation and the r-mode inst…
On the initial spin periods of magnetars born in weak supernova explosions and their gravitational wave radiation
Yu-Long Yan, Quan Cheng, Xiao-Ping Zheng +1
The initial spin periods of newborn magnetars are \textbf{strongly associated with the origin of their strong magnetic fields, both of which can affect the electromagnetic radiatio…
Dense Matter in Neutron Stars with eXTP
Ang Li, Anna L. Watts, Guobao Zhang +82
In this White Paper, we present the potential of the enhanced X-ray Timing and Polarimetry (eXTP) mission to constrain the equation of state of dense matter in neutron stars, explo…
Efficient Calibration for RRAM-based In-Memory Computing using DoRA
Weirong Dong, Kai Zhou, Zhen Kong +5
Resistive In-Memory Computing (RIMC) offers ultra-efficient computation for edge AI but faces accuracy degradation due to RRAM conductance drift over time. Traditional retraining m…
Stochastic gravitational wave background from newly born massive magnetars: The role of a dense matter equation of state
Quan Cheng, Shuang-Nan Zhang, Xiao-Ping Zheng
Newly born massive magnetars are generally considered to be produced by binary neutron star (NS) mergers, which could give rise to short gamma-ray bursts (SGRBs). The strong magnet…
Revealing the internal magnetic field configuration of magnetars via their associated periodic signals
Jie Shu, Quan Cheng, Xiao-Ping Zheng
The magnetic deformation of magnetars is affected by their internal magnetic fields, which are generally difficult to be measured directly through observations. In this work, the p…
Heterogeneity-Aware Microscaling for Efficient Low-Bit LLM Inference
Junyi Luo, Xinting Jiang, Tai-Hao Wen +9
Microscaling (MX) is now the standard for low-bit large language model (LLM) inference. Its 4-bit form MXFP4 still loses substantial accuracy, because existing MX formats fix eithe…
Studies on the spin and magnetic inclination evolution of magnetars Swift J1834.9-0846 under wind braking
Biaopeng Li, Zhifu Gao, Wenqi Ma +3
The magnetar Swift J1834.9-0846 presents a significant challenge to neutron star spin-down models. It exhibits two key anomalies: an insufficient rotational energy loss rate to pow…
VeRA+: Vector-Based Lightweight Digital Compensation for Drift-Resilient RRAM In-Memory Computing
Weirong Dong, Kai Zhou, Zhen Kong +8
RRAM-based in-memory computing (IMC) offers high energy efficiency but suffers from conductance drift that severely degrades long-term accuracy. Existing approaches including retra…
STAGER checklist: Standardized Testing and Assessment Guidelines for Evaluating Generative AI Reliability
Jinghong Chen, Lingxuan Zhu, Weiming Mou +5
Generative Artificial Intelligence (AI) holds immense potential in medical applications. Numerous studies have explored the efficacy of various generative AI models within healthca…