collaborators

9 papers

gr-qc2026

Construction of an analytic multi-component accretion environment and its application to Kerr black hole imaging

Shiyang Hu, Dan Li, Chen Deng +2

The construction of accretion environments is fundamental to black hole imaging. From a purely geometric perspective, we construct a novel analytic accretion environment comprising…

gr-qc2026

Reshaping the inner shadow of a Kerr black hole by a torn accretion disk

Shiyang Hu, Dan Li, Chen Deng +1

The paper models torn accretion disks around a Kerr black hole and uses relativistic backward ray‑tracing to simulate how the inner shadow changes, revealing new shadow shapes such…

gr-qc2026

Gravitational emissions and light curves of quasi-periodic orbits in Schwarzschild spacetime embedded in a Dehnen-type dark matter halo

Shijie Tan, Chunhua Jiang, Dan Li +3

Timelike orbits in curved spacetimes encode intrinsic information about the background geometry and serve as critical probes for investigating gravitational theories and source dis…

gr-qc2026

Rational Orbits and Gravitational Waves in Static Spherical Spacetimes: An Open-Source Numerical Framework

Dan Li, Shiyang Hu, Chen Deng +2

Timelike orbits constitute a crucial probe for exploring the intrinsic properties of curved spacetimes, and the carried gravitational radiation signals provide a direct window into…

gr-qc2025

OCTOPUS: A Versatile, User-Friendly, and Extensible Public Code for General-Relativistic Ray-Tracing in Spherically Symmetric and Static Spacetimes

Shiyang Hu, Shijie Tan, Dan Li +3

This paper presents OCTOPUS, a relativistic ray-tracing algorithm developed within a Fortran-based, OpenMP-accelerated framework, designed for asymptotically flat, spherically symm…

gr-qc2025

Light Curves of Chaotic Charged Hot-Spots in Curved Spacetime: Opening an Observational Window to Chaos

Shiyang Hu, Dan Li, Chen Deng

The observed scarcity of chaotic phenomena in astronomy contrasts sharply with their theoretical significance, primarily due to the absence of a robust framework for detecting chao…