arXiv subjects

Zijun He

Publications and source records attributed to Zijun He.

7 recordsLinked to original sources

arXiv2026

Discovery and Characterization of the TOI-4468 Planetary System: A Transiting Hot Jupiter With a Lone Nearby Outer Companion

We report the discovery of two planets, a hot Jupiter and a nearby outer sub-Neptune, orbiting the star TOI-4468. This system is unique among the current exoplanet census in that it features a close outer companion to a hot Jupiter without an accompanying inner companion. By jointly fitting radial velocity measurements taken with the NEID spectrograph and transit photometry from TESS and several ground-based observatories, we constrain the orbital periods, masses, and radii of these two planets. We confirm the planetary nature of the hot Jupiter TOI-4468 b ($R = 1.01 R_J$, $m = 0.54 M_J$, $P = 2.77$ days). We also validate the outer planet TOI-4468 c ($R = 0.28 R_J$, $P = 7.01$ days) statistically, incorporating constraints from ground-based observations. We also identify, but cannot confirm, an additional radial velocity signal which may be due to an outer giant in this system with an orbital period of 624 days. From the observed geometry of this system, we argue that it must never have encountered an early secular resonance that is thought to excite the mutual inclination of other hot Jupiter/outer companion systems. We discuss the possibility of an undetected inner companion, as well as potential implications for hot Jupiter formation.

astro-ph.EP↗

arXiv2026

Introducing the transitional autonomous vehicle lane-changing dataset: Empirical Experiments

Transitional autonomous vehicles (tAVs), which operate beyond SAE Level 1-2 automation but short of full autonomy, are increasingly sharing the road with human-driven vehicles (HDVs). As these systems interact during complex maneuvers such as lane changes, new patterns may emerge with implications for traffic stability and safety. Assessing these dynamics, particularly during mandatory lane changes, requires high-resolution trajectory data, yet datasets capturing tAV lane-changing behavior are scarce. This study introduces the North Carolina Transitional Autonomous Vehicle Lane-Changing (NC-tALC) Dataset, a high-fidelity trajectory dataset designed to characterize tAV interactions during lane-changing maneuvers. The dataset includes two controlled experimental series. In the first, tAV lane-changing experiments, a tAV executes lane changes in the presence of adaptive cruise control (ACC) equipped target vehicles, enabling analysis of lane-changing execution. In the second, tAV responding experiments, two tAVs act as followers and respond to cut-in maneuvers initiated by another tAV, enabling analysis of follower response dynamics. The dataset contains 152 trials (72 lane-changing and 80 responding trials) sampled at 20 Hz with centimeter-level RTK-GPS accuracy. The NC-tALC dataset provides a rigorous empirical foundation for evaluating tAV decision-making and interaction dynamics in controlled mandatory lane-changing scenarios.

cs.RO↗

arXiv2025

Spectral Compressive Imaging via Chromaticity-Intensity Decomposition

In coded aperture snapshot spectral imaging (CASSI), the captured measurement entangles spatial and spectral information, posing a severely ill-posed inverse problem for hyperspectral images (HSIs) reconstruction. Moreover, the captured radiance inherently depends on scene illumination, making it difficult to recover the intrinsic spectral reflectance that remains invariant to lighting conditions. To address these challenges, we propose a chromaticity-intensity decomposition framework, which disentangles an HSI into a spatially smooth intensity map and a spectrally variant chromaticity cube. The chromaticity encodes lighting-invariant reflectance, enriched with high-frequency spatial details and local spectral sparsity. Building on this decomposition, we develop CIDNet, a Chromaticity-Intensity Decomposition unfolding network within a dual-camera CASSI system. CIDNet integrates a hybrid spatial-spectral Transformer tailored to reconstruct fine-grained and sparse spectral chromaticity and a degradation-aware, spatially-adaptive noise estimation module that captures anisotropic noise across iterative stages. Extensive experiments on both synthetic and real-world CASSI datasets demonstrate that our method achieves superior performance in both spectral and chromaticity fidelity. Code and models will be publicly available.

cs.CV↗

arXiv2025

Progressive Flow-inspired Unfolding for Spectral Compressive Imaging

Coded aperture snapshot spectral imaging (CASSI) retrieves a 3D hyperspectral image (HSI) from a single 2D compressed measurement, which is a highly challenging reconstruction task. Recent deep unfolding networks (DUNs), empowered by explicit data-fidelity updates and implicit deep denoisers, have achieved the state of the art in CASSI reconstruction. However, existing unfolding approaches suffer from uncontrollable reconstruction trajectories, leading to abrupt quality jumps and non-gradual refinement across stages. Inspired by diffusion trajectories and flow matching, we propose a novel trajectory-controllable unfolding framework that enforces smooth, continuous optimization paths from noisy initial estimates to high-quality reconstructions. To achieve computational efficiency, we design an efficient spatial-spectral Transformer tailored for hyperspectral reconstruction, along with a frequency-domain fusion module to gurantee feature consistency. Experiments on simulation and real data demonstrate that our method achieves better reconstruction quality and efficiency than prior state-of-the-art approaches.

cs.CV↗

arXiv2025

Texture-aware Intrinsic Image Decomposition with Model- and Learning-based Priors

This paper aims to recover the intrinsic reflectance layer and shading layer given a single image. Though this intrinsic image decomposition problem has been studied for decades, it remains a significant challenge in cases of complex scenes, i.e. spatially-varying lighting effect and rich textures. In this paper, we propose a novel method for handling severe lighting and rich textures in intrinsic image decomposition, which enables to produce high-quality intrinsic images for real-world images. Specifically, we observe that previous learning-based methods tend to produce texture-less and over-smoothing intrinsic images, which can be used to infer the lighting and texture information given a RGB image. In this way, we design a texture-guided regularization term and formulate the decomposition problem into an optimization framework, to separate the material textures and lighting effect. We demonstrate that combining the novel texture-aware prior can produce superior results to existing approaches.

cs.CV↗

arXiv2025

The Ambiguous Age and Tidal History for the Ultra-Hot Jupiter TOI-1937Ab

Ultra-short-period (USP) planets are a rare but dynamically significant subset of the exoplanet sample, and understanding their dynamical histories and migration processes is necessary to build a complete picture of the outcomes of planet formation. In this work, we present an analysis of system age constraints and the impact of tidal evolution in the TOI-1937A system, a component of a large-separation stellar binary with an ambiguous age constraint that hosts a massive (> 2 $M_{Jup}$) USP planetary companion. Through a suite of tidal evolution simulations and analysis of the transit timing variations present in the photometric data, we find that the ultra-hot Jupiter TOI-1937Ab is likely undergoing orbital decay driven by tidal interactions, and we place an observational upper limit on its decay rate of |$\dot{P}$| < 0.09. We consider three different hypotheses for the system age based on three distinct methods of age estimation. These three age limits are complemented by indirect evidence of the age of the star that comes from our dynamical and transit timing analyses. We discuss the possibility that future data will provide more concrete constraints on the tidal parameters of TOI-1937Ab and its host star.

astro-ph.EP↗

arXiv2022

Design of cycloidal rays in optical waveguides in analogy to the fastest descent problem

In this work, we present the design of cycloidal waveguides from a gradient refractive index (GRIN) medium in analogy to the fastest descending problem in classical mechanics. Light rays propagate along cycloids in this medium, of which the refractive index can be determined from relating to the descending speed under gravity force. It can be used as GRIN lenses or waveguides, and the frequency specific focusing and imaging properties have been discussed. The results suggest that the waveguide can be viewed as an optical filter. Its frequency response characteristics change with the refractive index profile and the device geometries.

physics.optics↗