arXiv subjects

Yingjian Wang

Publications and source records attributed to Yingjian Wang.

At least 19 recordsLinked to original sources

arXiv2026

Seasonal Variability of Pluto's Haze Formation Revealed by Laboratory Simulations

Pluto possesses a thin atmosphere primarily composed of N2, with minor constituents including CO and CH4. Photochemical processes generate distinct haze layers as observed by the New Horizons spacecraft. However, the mechanisms governing haze formation, as well as the composition and physical properties of the hazes, remain poorly constrained. Due to Pluto's highly eccentric orbit and obliquity, its surface temperature and atmospheric composition undergo substantial seasonal variations, but it is unclear how such seasonal variations impact the chemical pathways and efficiency of haze formation in Pluto's atmosphere. To address this, we conducted a laboratory simulation of Pluto's atmospheric photochemistry, in which N2/CH4/CO gas mixtures with CH4 concentrations varying from 0.1% to 5% were exposed to a glow discharge to initiate photochemical reactions. Gas-phase composition was monitored in situ using a residual gas analyzer (RGA), while the solid-phase products were characterized by atomic force microscopy (AFM), a gas pycnometer, infrared spectroscopy (IR), and very high-resolution mass spectrometry (VHRMS) to determine particle sizes, density, and composition, respectively. Our results show that increasing the CH4 mixing ratio significantly enhances the yield of gas and solid products. Under low CH4 conditions, nitrogen is primarily incorporated into solids as cyanide groups; whereas CH4-rich conditions favor the formation of amino groups, greatly promoting nitrogen incorporation into organic solids. These findings not only shed light on how seasonal variations into Pluto's atmosphere composition influence haze formation pathways, but also provide critical parameters to interpret observational data and to improve photochemical and microphysical models of planetary hazes.

astro-ph.EP↗

arXiv2026

Influence of CO versus CH$_4$ on organic haze formation in atmospheres of diverse terrestrial exoplanets

Context. Terrestrial exoplanets are expected to host secondary, high-metallicity atmospheres derived from outgassing of volatiles such as N2, CO2, H2O, CH4, and CO. Photochemical organic hazes are likely to form in such environments, significantly affecting atmospheric observations and planetary habitability. Aims. We investigate haze formation in representative terrestrial exoplanet atmospheres and assess how CH4 versus CO as the primary carbon source affects haze production rates, particle properties, and chemical complexity. Methods. We performed six laboratory simulations by exposing gas mixtures at a few mbar to glow discharge at 300 K. Each atmosphere contained 75% N2, CO2, or H2O, 10% of each of the other two gases, and 5% CH4 or CO. Gas-phase products were analyzed with a residual gas analyzer, and solid products were characterized by production rate, particle density, atomic force microscopy, Fourier-transform infrared spectroscopy, and very high-resolution mass spectrometry. Results. CH4 experiments produced more diverse gas-phase species and much higher haze yields than the corresponding CO experiments. CO-derived hazes showed a narrow particle size range of 10-80 nm, whereas CH4-derived hazes were denser and chemically more complex. The identified molecular formulas suggest growth pathways linked to gaseous precursors such as HCN, CH2O, and C2H4. Conclusions. The atmospheric redox state critically controls haze formation in simulated terrestrial exoplanet atmospheres. CH4 is significantly more effective than CO in initiating organic growth, leading to higher haze production rates and greater chemical complexity. These results provide useful constraints for exoplanet atmospheric modeling and spectral interpretation, and further support the possibility that reducing atmospheres may facilitate prebiotic organic chemistry relevant to the emergence of life.

astro-ph.EP↗

arXiv2026

Quantifying Building Blocks of Life in Planetary Analog Materials: Implications for Prebiotic Chemistry and Biosignature Identification

Building blocks of life such as amino acids, nucleobases, and fatty acids are central to prebiotic chemistry and represent key targets in the search for planetary biosignatures. In planetary materials, biomolecules typically occur at trace levels within complex matrices, posing substantial analytical challenges, particularly for quantitative characterization. Here we develop a gas chromatography tandem mass spectrometry method that enables robust qualitative and quantitative analysis of 56 prebiotically relevant molecules. The method is applied to a Titan aerosol analog and, for the first time, to a Martian gypsum analog from the Qaidam Basin, revealing diverse inventories of amino acids, nucleobases, and fatty acids in both samples. In the Titan aerosol analog, the first detection of phenylalanine and an extensive inventory of fatty acids, together with elevated nucleobase abundances, offers new insights into atmospheric photochemical synthesis of prebiotic molecules. In the Martian analog sample, amino acids are detectable and exhibit pronounced biotic abiotic contrasts in abundance patterns relative to those observed in the Titan aerosol analog, whereas fatty acids show more overlapping abiotic and biotic signatures, highlighting the potential of amino acids as robust biosignatures. These results provide quantitative constraints on prebiotic chemical evolution and underscore the utility of GC-MS-MS for biosignature identification in planetary exploration.

astro-ph.EP↗

arXiv2025

The impact of organic hazes and graphite on the observation of CO2-rich sub-Neptune atmospheres

Many sub-Neptune and super-Earth exoplanets are expected to develop metal-enriched atmospheres due to atmospheric loss processes such as photoevaporation or core-powered mass loss. Thermochemical equilibrium calculations predict that at high metallicity and a temperature range of 300-700 K, CO2 becomes the dominant carbon species, and graphite may be the thermodynamically favored condensate under low-pressure conditions. Building on prior laboratory findings that such environments yield organic haze rather than graphite, we measured the transmittance spectra of organic haze analogues and graphite samples, and computed their optical constants across the measured wavelength range from 0.4 to 25 μm. The organic haze exhibits strong vibrational absorption bands, notably at 3.0, 4.5, and 6.0 μm, while graphite shows featureless broadband absorption. The derived optical constants of haze and graphite provide the first dataset for organic haze analogues formed in CO2-rich atmospheres and offer improved applicability over prior graphite data derived from bulk reflectance or ellipsometry. We implemented these optical constants into the Virga and PICASO cloud and radiative transfer models to simulate transit spectra for GJ 1214b. The synthetic spectra with organic hazes reproduce the muted spectral features in the NIR observed by Hubble and general trends observed by JWST for GJ 1214b, while graphite models yield flat spectra across the observed wavelengths. This suggests haze features may serve as observational markers of carbon-rich atmospheres, whereas graphite's opacity could lead to radius overestimation, offering a possible explanation for super-puff exoplanets. Our work supplies essential optical to infrared data for interpreting observations of CO2-rich exoplanet atmospheres.

astro-ph.EP↗

arXiv2025

Formation of organic hazes in CO$_2$-rich sub-Neptune atmospheres within the graphite-stability regime

Super-Earths and sub-Neptunes are the most common exoplanets, with a "radius valley" suggesting that super-Earths may form by shedding sub-Neptunes' gaseous envelopes. Exoplanets that lie closer to the super-Earth side of the valley are more likely to have lost a significant fraction of their original H/He envelopes and become enriched in heavier elements with CO$_2$ gaining in abundance. It remains unclear which types of haze would form in such atmospheres, potentially significantly affecting spectroscopic observations. To investigate this, we performed laboratory simulations of two CO$_2$-rich gas mixtures (with 2000 times solar metallicity at 300 K and 500 K). We found that under plasma irradiation, organic hazes were produced at both temperatures with higher haze production rate at 300 K probably because condensation occurs more readily at lower temperature. Gas-phase analysis demonstrates the formation of various hydrocarbons, oxygen- and nitrogen-containing species, including reactive gas precursors like C$_2$H$_4$, CH$_2$O, and HCN, for haze formation. The compositional analysis of the haze particles reveals various functional groups and molecular formulas in both samples. The 500 K haze sample has larger average molecular sizes, higher degree of unsaturation with more double or triple bonds presence, and higher nitrogen content incorporated as N-H, C=N bonds, indicating different haze formation pathways. These findings not only improve the haze formation theories in CO$_2$-rich exoplanet atmospheres but also offer important implications for the interpretation of future observational data.

astro-ph.EP↗

arXiv2024

An Efficient Error Estimation Method in Quantum Key Distribution

Error estimation is an important step for error correction in quantum key distribution. Traditional error estimation methods require sacrificing a part of the sifted key, forcing a trade-off between the accuracy of error estimation and the size of the partial sifted key to be used and discarded. In this paper, we propose a hybrid approach that aims to preserve the entire sifted key after error estimation while preventing Eve from gaining any advantage. The entire sifted key, modified and extended by our proposed method, is sent for error estimation in a public channel. Although accessible to an eavesdropper, the modified and extended sifted key ensures that the number of attempts to crack it remains the same as when no information is leaked. The entire sifted key is preserved for subsequent procedures, indicating the efficient utilization of quantum resources.

quant-ph↗

arXiv2024

Meta-Modelling in Formal Concept Analysis

Formal Concept Analysis starts from a very basic data structure comprising objects and their attributes. Sometimes, however, it is beneficial to also define attributes of attributes, viz., meta-attributes. In this paper, we use Triadic Formal Concept Analysis, a triadic approach to Formal Concept Analysis, to develop a framework for this kind of meta-modelling in Formal Concept Analysis, including formal definitions and appropriate visualizations.

math.LO↗

arXiv2024

Preserving Relative Localization of FoV-Limited Drone Swarm via Active Mutual Observation

Relative state estimation is crucial for vision-based swarms to estimate and compensate for the unavoidable drift of visual odometry. For autonomous drones equipped with the most compact sensor setting -- a stereo camera that provides a limited field of view (FoV), the demand for mutual observation for relative state estimation conflicts with the demand for environment observation. To balance the two demands for FoV limited swarms by acquiring mutual observations with a safety guarantee, this paper proposes an active localization correction system, which plans camera orientations via a yaw planner during the flight. The yaw planner manages the contradiction by calculating suitable timing and yaw angle commands based on the evaluation of localization uncertainty estimated by the Kalman Filter. Simulation validates the scalability of our algorithm. In real-world experiments, we reduce positioning drift by up to 65% and managed to maintain a given formation in both indoor and outdoor GPS-denied flight, from which the accuracy, efficiency, and robustness of the proposed system are verified.

cs.RO↗

arXiv2024

GS-Planner: A Gaussian-Splatting-based Planning Framework for Active High-Fidelity Reconstruction

Active reconstruction technique enables robots to autonomously collect scene data for full coverage, relieving users from tedious and time-consuming data capturing process. However, designed based on unsuitable scene representations, existing methods show unrealistic reconstruction results or the inability of online quality evaluation. Due to the recent advancements in explicit radiance field technology, online active high-fidelity reconstruction has become achievable. In this paper, we propose GS-Planner, a planning framework for active high-fidelity reconstruction using 3D Gaussian Splatting. With improvement on 3DGS to recognize unobserved regions, we evaluate the reconstruction quality and completeness of 3DGS map online to guide the robot. Then we design a sampling-based active reconstruction strategy to explore the unobserved areas and improve the reconstruction geometric and textural quality. To establish a complete robot active reconstruction system, we choose quadrotor as the robotic platform for its high agility. Then we devise a safety constraint with 3DGS to generate executable trajectories for quadrotor navigation in the 3DGS map. To validate the effectiveness of our method, we conduct extensive experiments and ablation studies in highly realistic simulation scenes.

cs.RO↗

arXiv2024

FACT: Fast and Active Coordinate Initialization for Vision-based Drone Swarms

Swarm robots have sparked remarkable developments across a range of fields. While it is necessary for various applications in swarm robots, a fast and robust coordinate initialization in vision-based drone swarms remains elusive. To this end, our paper proposes a complete system to recover a swarm's initial relative pose on platforms with size, weight, and power (SWaP) constraints. To overcome limited coverage of field-of-view (FoV), the drones rotate in place to obtain observations. To tackle the anonymous measurements, we formulate a non-convex rotation estimation problem and transform it into a semi-definite programming (SDP) problem, which can steadily obtain global optimal values. Then we utilize the Hungarian algorithm to recover relative translation and correspondences between observations and drone identities. To safely acquire complete observations, we actively search for positions and generate feasible trajectories to avoid collisions. To validate the practicability of our system, we conduct experiments on a vision-based drone swarm with only stereo cameras and inertial measurement units (IMUs) as sensors. The results demonstrate that the system can robustly get accurate relative poses in real time with limited onboard computation resources. The source code is released.

cs.RO↗

arXiv2024

Certifiable Mutual Localization and Trajectory Planning for Bearing-Based Robot Swarm

Bearing measurements,as the most common modality in nature, have recently gained traction in multi-robot systems to enhance mutual localization and swarm collaboration. Despite their advantages, challenges such as sensory noise, obstacle occlusion, and uncoordinated swarm motion persist in real-world scenarios, potentially leading to erroneous state estimation and undermining the system's flexibility, practicality, and robustness.In response to these challenges, in this paper we address theoretical and practical problem related to both mutual localization and swarm planning.Firstly, we propose a certifiable mutual localization algorithm.It features a concise problem formulation coupled with lossless convex relaxation, enabling independence from initial values and globally optimal relative pose recovery.Then, to explore how detection noise and swarm motion influence estimation optimality, we conduct a comprehensive analysis on the interplay between robots' mutual spatial relationship and mutual localization. We develop a differentiable metric correlated with swarm trajectories to explicitly evaluate the noise resistance of optimal estimation.By establishing a finite and pre-computable threshold for this metric and accordingly generating swarm trajectories, the estimation optimality can be strictly guaranteed under arbitrary noise. Based on these findings, an optimization-based swarm planner is proposed to generate safe and smooth trajectories, with consideration of both inter-robot visibility and estimation optimality.Through numerical simulations, we evaluate the optimality and certifiablity of our estimator, and underscore the significance of our planner in enhancing estimation performance.The results exhibit considerable potential of our methods to pave the way for advanced closed-loop intelligence in swarm systems.

cs.RO↗

arXiv2023

Simultaneous Time Synchronization and Mutual Localization for Multi-robot System

Mutual localization stands as a foundational component within various domains of multi-robot systems. Nevertheless, in relative pose estimation, time synchronization is usually underappreciated and rarely addressed, although it significantly influences estimation accuracy. In this paper, we introduce time synchronization into mutual localization to recover the time offset and relative poses between robots simultaneously. Under a constant velocity assumption in a short time, we fuse time offset estimation with our previous bearing-based mutual localization by a novel error representation. Based on the error model, we formulate a joint optimization problem and utilize semi-definite relaxation (SDR) to furnish a lossless relaxation. By solving the relaxed problem, time synchronization and relative pose estimation can be achieved when time drift between robots is limited. To enhance the application range of time offset estimation, we further propose an iterative method to recover the time offset from coarse to fine. Comparisons between the proposed method and the existing ones through extensive simulation tests present prominent benefits of time synchronization on mutual localization. Moreover, real-world experiments are conducted to show the practicality and robustness.

cs.RO↗

arXiv2023

CREPES: Cooperative RElative Pose Estimation System

Mutual localization plays a crucial role in multi-robot cooperation. CREPES, a novel system that focuses on six degrees of freedom (DOF) relative pose estimation for multi-robot systems, is proposed in this paper. CREPES has a compact hardware design using active infrared (IR) LEDs, an IR fish-eye camera, an ultra-wideband (UWB) module and an inertial measurement unit (IMU). By leveraging IR light communication, the system solves data association between visual detection and UWB ranging. Ranging measurements from the UWB and directional information from the camera offer relative 3-DOF position estimation. Combining the mutual relative position with neighbors and the gravity constraints provided by IMUs, we can estimate the 6-DOF relative pose from a single frame of sensor measurements. In addition, we design an estimator based on the error-state Kalman filter (ESKF) to enhance system accuracy and robustness. When multiple neighbors are available, a Pose Graph Optimization (PGO) algorithm is applied to further improve system accuracy. We conduct enormous experiments to demonstrate CREPES' accuracy between robot pairs and a team of robots, as well as performance under challenging conditions.

cs.RO↗

arXiv2022

Bearing-based Relative Localization for Robotic Swarm with Partially Mutual Observations

Mutual localization provides a consensus of reference frame as an essential basis for cooperation in multirobot systems. Previous works have developed certifiable and robust solvers for relative transformation estimation between each pair of robots. However, recovering relative poses for robotic swarm with partially mutual observations is still an unexploited problem. In this paper, we present a complete algorithm for it with optimality, scalability and robustness. Firstly, we fuse all odometry and bearing measurements in a unified minimization problem among the Stiefel manifold. Furthermore, we relax the original non-convex problem into a semi-definite programming (SDP) problem with a strict tightness guarantee. Then, to hold the exactness in noised cases, we add a convex (linear) rank cost and apply a convex iteration algorithm. We compare our approach with local optimization methods on extensive simulations with different robot amounts under various noise levels to show our global optimality and scalability advantage. Finally, we conduct real-world experiments to show the practicality and robustness.

cs.RO↗

arXiv2022

Fast localization and single-pixel imaging of the moving object using time-division multiplexing

When imaging moving objects, single-pixel imaging produces motion blur. This paper proposes a new single-pixel imaging method, which can achieve anti-motion blur imaging of a fast-moving object. The geometric moment patterns and Hadamard patterns are used to alternately encode the position information and the image information of the object with time-division multiplexing. In the reconstruction process, the object position information is extracted independently and combining motion-compensation reconstruction algorithm to decouple the object motion from image information. As a result, the anti-motion blur image and the high frame rate object positions are obtained. Experimental results show that for a moving object with an angular velocity of up to 0.5rad/s relative to the imaging system, the proposed method achieves a localization frequency of 5.55kHz, and gradually reconstructs a clear image of the fast-moving object with a pseudo resolution of 512x512. The method has application prospects in single-pixel imaging of the fast-moving object.

eess.IV↗

arXiv2022

Meeting-Merging-Mission: A Multi-robot Coordinate Framework for Large-Scale Communication-Limited Exploration

This letter presents a complete framework Meeting-Merging-Mission for multi-robot exploration under communication restriction. Considering communication is limited in both bandwidth and range in the real world, we propose a lightweight environment presentation method and an efficient cooperative exploration strategy. For lower bandwidth, each robot utilizes specific polytopes to maintains free space and super frontier information (SFI) as the source for exploration decision-making. To reduce repeated exploration, we develop a mission-based protocol that drives robots to share collected information in stable rendezvous. We also design a complete path planning scheme for both centralized and decentralized cases. To validate that our framework is practical and generic, we present an extensive benchmark and deploy our system into multi-UGV and multi-UAV platforms.

cs.RO↗

arXiv2022

Certifiably Optimal Mutual Localization with Anonymous Bearing Measurements

Mutual localization is essential for coordination and cooperation in multi-robot systems. Previous works have tackled this problem by assuming available correspondences between measurements and received odometry estimations, which are difficult to acquire, especially for unified robot teams. Furthermore, most local optimization methods ask for initial guesses and are sensitive to their quality. In this paper, we present a certifiably optimal algorithm that uses only anonymous bearing measurements to formulate a novel mixed-integer quadratically constrained quadratic problem (MIQCQP). Then, we relax the original nonconvex problem into a semidefinite programming (SDP) problem and obtain a certifiably global optimum using with off-the-shelf solvers. As a result, our method can determine bearing-pose correspondences and furthermore recover the initial relative poses between robots under a certain condition. We compare the performance with local optimization methods on extensive simulations under different noise levels to show our advantage in global optimality and robustness. Real-world experiments are conducted to show the practicality and robustness.

cs.RO↗

arXiv2021

Autonomous Flights in Dynamic Environments with Onboard Vision

In this paper, we introduce a complete system for autonomous flight of quadrotors in dynamic environments with onboard sensing. Extended from existing work, we develop an occlusion-aware dynamic perception method based on depth images, which classifies obstacles as dynamic and static. For representing generic dynamic environment, we model dynamic objects with moving ellipsoids and fuse static ones into an occupancy grid map. To achieve dynamic avoidance, we design a planning method composed of modified kinodynamic path searching and gradient-based optimization. The method leverages manually constructed gradients without maintaining a signed distance field (SDF), making the planning procedure finished in milliseconds. We integrate the above methods into a customized quadrotor system and thoroughly test it in realworld experiments, verifying its effective collision avoidance in dynamic environments.

cs.RO↗