With the rapid development of 6G space–air–ground integrated communication networks, low Earth orbit (LEO) satellite constellations, leveraging their advantages of wide-area coverage and freedom from geographic constraints, have become key infrastructure for achieving global seamless connectivity. However, due to the relative motion among satellites in different orbits, inter-satellite links (ISLs) exhibit periodic dynamic on–off characteristics, among which a portion of the interruptions are predictable topological changes. Conventional Open Shortest Path First (OSPF) protocols compute shortest paths solely based on link distance, without considering link effective duration or bandwidth constraints, rendering them inadequate for adapting to the dynamic topological characteristics of satellite networks. Although fast reroute strategies can address sudden link failures, they consume substantial bandwidth resources and cannot provide protection for all nodes across the entire network. Therefore, how to proactively switch service paths before predictable link interruptions occur, so as to minimize service disruption and resource overhead, has become a core issue in ensuring service continuity in LEO satellite networks.

With growing concerns over the impact threat of near-Earth small bodies and the utilization of space resources, the orbital evolution of binary asteroid systems has become an important subject in space science. When describing the full two-body dynamics of such systems, the gravitational potential of irregular bodies is determined by both their positions and attitudes, leading to coupling between translational and rotational motions, and the resulting model complexity significantly exceeds that of the classical two-body problem. Although existing numerical methods, such as explicit Runge–Kutta integrators, are widely used, they fail to preserve the symplectic structure and Lie group geometric properties of the system. In long-term simulations, key conserved quantities such as total energy and angular momentum are prone to numerical drift, severely undermining the long-term credibility of orbital predictions. While Lie group variational integrators can preserve geometric structure to a certain extent, their implicit equations are formulated on Lie group elements, which incurs substantial computational overhead. Therefore, how to construct a high-performance integration method that simultaneously achieves numerical accuracy, structure preservation, and computational efficiency has become a core challenge in the long-term evolutionary simulation of binary asteroid systems.

With the intensifying space confrontation in geostationary orbit (GEO), the U.S. GSSAP (Geosynchronous Space Situational Awareness Program) satellites have conducted hundreds of close-range observation operations on dozens of on-orbit satellites in the vicinity of GEO. The acquisition of multi-aspect information from non-cooperative targets has thus become a critical component of space security assessment. Close-range spacecraft operations, which employ relative motion configurations such as fly-around, hovering, and drifting flight, provide an effective technical means for approaching and observing targets to obtain multi-aspect payload information. However, existing studies predominantly focus on the control design of a single relative motion configuration, which fails to satisfy the complex mission requirements of multi-aspect observation. The combination of multiple models for observation presents multiple challenges, including smooth switching between modes, fuel optimization, strategy design algorithms, and analysis of payload parameter effects. Therefore, how to coordinately plan a sequential combination of multiple close-range operation models under minimum fuel constraints to efficiently acquire multi-aspect information of non-cooperative targets has become a key bottleneck in enhancing space situational awareness capabilities.

Researchers have developed a chip-scale platform for ultrawide-angle, two-dimensional optical beam steering. The system integrates a silicon photonic integrated circuit, freeform micro-optical reflectors, and a metasurface to transform guided light into high-quality free-space beams and direct them across a measured 161° field-of-view while maintaining nearly diffraction-limited beam quality. This compact, scalable architecture offers a pathway toward inter-satellite optical links, airborne LiDAR, point-to-point optical wireless communications, and other applications requiring agile, wide-angle beam control.

UK: An eye surgeon with a passion for space since childhood predicts that as astronauts start to make journeys to the Moon and Mars in the near future, eye surgery in space will eventually become a necessity. Speaking at the 44^th Congress of the European Society of Cataract and Refractive Surgeons (ESCRS), Dr Morgan Micheletti said that cataract surgery, in particular, will be needed as people travel through space and stay in space stations for longer periods of time. Therefore, it was vital to know how medical supplies such as intraocular lenses (IOLs) and the other equipment needed for surgery could best be packed, transported, stored and protected from the space environment.

As orbital space resources become increasingly scarce, the problem of orbital pursuit-evasion games among spacecraft has attracted widespread attention. In multi-to-one pursuit-evasion scenarios, multiple pursuit spacecraft are required to cooperatively capture a non-cooperative evasive target under impulsive maneuver and fuel constraints, giving rise to an optimal control problem characterized by strong nonlinearity and complex constraints. Existing differential game methods suffer from high computational complexity and poor real-time performance; numerical optimization approaches are sensitive to initial guesses and struggle to handle long-duration constraints; and although deep reinforcement learning has demonstrated advantages in some scenarios, it lacks proactive prediction capability when confronting unknown evasion strategies, thereby limiting pursuit performance. Consequently, how to predict the actions of the evading spacecraft in multi-to-one scenarios and accordingly optimize the cooperative strategies of multiple pursuers has become a key challenge for improving pursuit efficiency in complex orbital games.