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Earlier sources: Space
Space research and engineering study the universe and build the systems used to reach and observe it. Follow astronomy, spacecraft, launch systems, satellites, exploration, and Earth observation.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗520 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
Satellite-based vessel detection under turbulence and jitter: a degradation-aware comparison ↗
Maritime domain awareness increasingly relies on satellite-based Earth observation (EO) for wide-area vessel monitoring. Low Earth orbit (LEO) platforms enable flexible acquisition, but optical imagery can be degraded by atmospheric turbulence and platform jitter. This paper presents a degradation-aware evaluation of deep learning-based maritime vessel detection that links algorithmic performance to the physical constraints of spaceborne optical imaging. Using real optical satellite imagery and physically motivated synthetic turbulence and jitter models, we compare YOLOv8, YOLOv11, RetinaNet,…
- OpenAlex · Published · First archived
Depth-driven UAV obstacle avoidance with teacher-guided exploration in cluttered environments ↗
Obstacle avoidance in cluttered environments presents a significant challenge, as it requires rapid perception and decision-making in partially observable three-dimensional space, particularly for unmanned aerial vehicles (UAVs) operating with constrained onboard vision. Compared with traditional map-based approaches, end-to-end methods based on deep reinforcement learning (DRL) directly learn a direct perception to control policy, but they often require large amounts of data and exhibit unstable exploration. To address these issues, we propose SAC-DGPF, a teacher-guided obstacle avoidance fra…
- OpenAlex · Published · First archived
VESTA: In-Vehicle Sensing with GNSS Satellite Signals ↗
Vehicles have become an indispensable part of modern life. Over the past decade, perception systems such as radar and LiDAR have become increasingly popular for out-vehicle sensing. In contrast, comparatively little attention has been paid to in-vehicle sensing. While camera-based solutions raise privacy concerns, wireless sensing-based approaches typically require dedicated transmitters, increasing deployment costs and potentially interfering with existing wireless communications. In this paper, we propose VESTA, an in-vehicle sensing system that leverages the ubiquity of GNSS signals. The ub…
- OpenAlex · Published · First archived
Inverse-Power-Law Scalar-Field Cosmology in (n+2) Dimensions: Slow-Roll Evolution and de Sitter-Like Asymptotics ↗
This study investigates a homogeneous canonical scalar field with an inverse-power-law potential in an (n+2)-dimensional spatially flat Friedmann-Robertson-Walker/Friedmann-Lemaître-Robertson Walker (FRW/FLRW) spacetime. The approximately 5% baryonic-matter, 25% dark-matter, and 70% dark-energy fractions are used only as present-day observational motivation and are not imposed as fixed weights in the scalar-field dynamics. Using the metric signature (+,-,...,-), the scalar-field definition and the higher-dimensional Friedmann, acceleration, Klein-Gordon, and conservation equations are formulat…
- OpenAlex · Published · First archived
A Low-Phase-Noise InGaAs/GaAs BiHEMT Balanced Colpitts VCO with Deep-Learning-Optimized On-Chip Inductor for Satellite Communication Applications ↗
In this communication, a balanced Colpitts VCO with low phase noise and a wide tuning range is presented, which was implemented using a 2 μm GaAs BiHEMT process. To improve phase noise, a noise-shifting technique introduced by the cross-coupled pair was applied. A deep-learning-assisted genetic algorithm was employed to optimize the quality factor of an on-chip inductor, further improving the phase noise. Additionally, three-bit switches were utilized to expand the tuning range of this VCO. Finally, a VCO prototype was implemented and fabricated for verification. The measurement results demons…
- OpenAlex · Published · First archived
Launching Expectations: Exploring the Role of the State in the Creation of New Space Launch Markets ↗
Our article examines how UK Governmental entities set out to establish a space launch market, by locating an empirical analysis of policy documents, reports, and reviews published by various governmental agencies, Parliamentary hearings, media reports, and investment data, within broader conceptual debates about “New Space.” We investigate expectations of UK policy actors about the prospects of developing this market, through the analysis of three linked “storylines” about technoeconomic, policy, and status expectations. We address the different roles UK Governmental agencies have played in re…
- GitHub · Repository created · First archived
lowlevelmetal/OpenSE4 ↗
Open source Space Empires 4 implementation
- arXiv · Published · First archived
A Probabilistic Trajectory and Dispersion Study of Martian Tumbleweed Rover Swarms in Global Dust Storm Conditions ↗
Global Dust Storms (GDSs) dominate the Martian climate, yet the mechanisms of dust lifting, transport, and deposition remain poorly constrained because in situ observations are limited: landers are stationary, and their Radioisotope Thermoelectric Generators (RTGs) contaminate local measurements. Our solution is a swarm of lightweight, wind-propelled spherical rovers -- Dust Rovers (DRs) -- that follow natural wind patterns to collect high-spatial-resolution in situ dust data during storms. Here, we quantify the dispersion and communication connectivity of this robotic architecture. Using 625…
- NASA · Source date · First archived
NASA Opens 2027 Human Lander Challenge for Lunar Communications ↗
3 min read Preparations for Next Moonwalk Simulations Underway (and Underwater) Banner image for 2027 Human Lander Challenge. NASA NASA’s 2027 Human Lander Challenge is seeking ideas from college and university students to help address one of the most critical needs for sustained lunar exploration: reliable communications. As NASA prepares for long-term human presence on the Moon through the Artemis and Moon Base programs, communications systems will be just as important as spacecraft and rockets. A resilient communications system will connect astronauts, rovers, habitats, landers, mission sup…
- arXiv · Published · First archived
aRieL - Reinforcement Learning for the Ariel Space Telescope Scheduling ↗
The Ariel mission will conduct a population level survey of hundreds of exoplanet atmospheres, requiring observations to be scheduled across a large and diverse catalogue of potential targets. By framing Ariel scheduling as a long-horizon optimisation problem in which individual decisions affect both mission time and the scientific opportunities available later in the survey, Reinforcement Learning (RL) can be utilised as a framework for target selection. We introduce aRieL, a simulated observing environment coupled to a Set Transformer Proximal Policy Optimisation (PPO) agent that is trained…
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about Space
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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