International MEGATRON project links space telescope observations of the infant Universe with the chemical fossil record of the Milky Way.

A packaged self-injection-locked fiber Fabry–Pérot Kerr microcomb was used to generate coherent terahertz signals for both wireless transmission and multi-carrier operation. The system demonstrated 5-meter free-space communication at terahertz using 16-QAM and 64-QAM modulation at symbol rates up to 15 GBd, while also generating a coherent terahertz frequency comb. The results highlight the potential of compact microcomb sources for scalable high-capacity terahertz communication and related photonic applications.

A team of astronomers from the Einstein Probe (EP) collaboration has uncovered a previously hidden stage in the aftermath of one of the Universe’s most violent events—the merger of two compact stars. Designated EP250704a/GRB 250704B, the fleeting cosmic explosion was jointly captured by the China-led EP mission, the SVOM, and the Insight-HXMT, enabling astronomers to follow this transient simultaneously in gamma rays and soft X-rays from the very onset of the emission. Led by the EP fast extragalactic transients working group, a study published in Science Bulletin reports that, although the short gamma-ray burst (GRB) produced by the compact star merger lasted only about half a second, the source continued shining in soft X-rays for nearly ten minutes after the gamma-ray flash had faded. The discovery reveals that the merger remnant releases substantial energy well beyond the initial short GRB traditionally used to identify these events, allowing compact star mergers—the same cosmic collisions that also produce gravitational waves—to appear as minute-long fast X-ray transients. These X-ray transients therefore provide an electromagnetic counterpart to gravitational-wave events, offering a new probe for multi-messenger astronomy.

A team of researchers led by the National Astronomical Observatory of Japan discovered unexpectedly intricate magnetic structures above quiet-Sun regions, by observing the Sun with the balloon-borne solar observatory Sunrise-III.

A new University of Washington study using improved methods for analyzing satellite data shows that the north pole of Mars contains less dust than scientists thought, which has implications for its climate and the search for life.

Satellites that navigate by talking to each other slowly lose their sense of direction, because nothing in a purely Earth-orbiting network provides a fixed reference in space.

With the continuous advancement of spaceborne synthetic aperture radar (SAR) technology, L-band SAR has come to play an increasingly important role in Earth observation; however, its imaging, interferometric, and polarimetric performance are susceptible to ionospheric disturbances. In equatorial nighttime data, amplitude streak artifacts induced by equatorial plasma bubbles frequently occur and have traditionally been regarded as interference factors in SAR imaging. Nevertheless, these artifacts essentially carry critical information on ionospheric irregularities and can be exploited to retrieve physical parameters such as scintillation intensity and turbulence spectral indices. Existing methods either rely on comparisons between disturbed and undisturbed images or are limited to preliminary one-dimensional parameter estimation along the track, making it difficult to achieve two-dimensional fine-scale retrieval of scintillation structures, and lacking systematic validation of their spatial correlation with equatorial ionospheric anomalies. Therefore, how to extract the two-dimensional spatial distribution of ionospheric scintillation parameters from amplitude streak artifacts and reveal their intrinsic relationship with regions of enhanced electron density has become an important scientific question in the field of ionospheric remote sensing.

With the advancement of deep-space missions such as crewed lunar exploration and Mars exploration, artificial intelligence (AI) technologies are being increasingly embedded into aerospace engineering management processes, and managers' AI competency has become a critical factor affecting mission delivery performance and safety compliance. However, traditional project management competency models have been primarily constructed around process control and redundancy design within deterministic systems, failing to explicitly address governance challenges introduced by AI integration—including black-box opacity, accountability allocation, traceable review of AI outputs, and accountability mechanisms for assisted decision-making. Although existing NASA and ESA frameworks provide fundamental support for aerospace project delivery, AI-related competencies in aerospace management exhibit inherent interdependencies. Managers are required to continuously balance delivery schedules and cost pressures against mission assurance obligations such as verification and validation, configuration control, and compliance, making it impossible to simply represent AI competency as a linear list of attributes. Therefore, how to construct an AI competency assessment framework that captures governance priorities and multi-attribute interdependencies has become a critical issue urgently to be addressed in aerospace engineering management in the AI era.