Universe

To address the challenges associated with the complex spatiotemporal variations of global ionospheric total electron content (TEC), this study proposes a Dual-domain Filtered-label Wavelet-based Spatiotemporal Attention Network (DFL-WT-STANet) for global TEC forecasting. The proposed framework integrates wavelet-based multi-scale feature extraction, ConvLSTM-based spatiotemporal modeling, and decoupled temporal and spatial Transformer branches to capture local and global dependencies in TEC variations. A dual-domain optimization strategy is further introduced to jointly constrain prediction errors in the time and frequency domains, enhancing the representation of temporal variations and disturbance-related characteristics. Kp, Dst, F10.7, and SSN are incorporated as auxiliary solar and geomagnetic activity features. The global TEC data from 2003 to 2024 were used for experimental evaluation, with 2015, 2019, and 2024 selected as representative test years under different solar activity conditions. DFL-WT-STANet achieves RMSE values of 2.96 and 4.81 TECU in the high-solar-activity years of 2015 and 2024, respectively, while the RMSE decreases to 1.15 TECU in the low-solar-activity year of 2019. Compared with the CODE 1-day-ahead prediction product (C1PG), DFL-WT-STANet reduces the RMSE by 26.75%, 22.06%, and 25.29% in 2015, 2019, and 2024, respectively. During a severe geomagnetic storm with a minimum Dst of $-406$ nT, the proposed model further reduces the storm-day RMSE and MAE by 8.93% and 11.32%, respectively, compared with WT-STANet. Monthly and latitude-dependent evaluations further show that the forecasting advantage is consistently maintained across different months and a broad range of latitude regions. These results demonstrate that DFL-WT-STANet provides accurate and robust global TEC forecasting under different solar and geomagnetic activity conditions, with particular advantages during pronounced ionospheric disturbances.

We investigate the shadow of a rotating black hole in the infrared limit of asymptotically safe gravity (ASG), focusing on how different plasma distributions affect photon propagation and shadow properties. Using the Hamilton–Jacobi formalism, we derive the photon equations of motion in plasma and calculate the shadow boundary for three different plasma distributions. Relative to the case without plasma, a homogeneous plasma increases the shadow size, whereas radially and angularly inhomogeneous plasma distributions reduce it. The inhomogeneous plasma models make the shadow more circular, whereas the effect of a homogeneous plasma on the shadow shape depends on the ASG parameter $\tilde{\xi }$. The angularly inhomogeneous plasma has a stronger effect on the shadow size, whereas the radially inhomogeneous plasma has a greater influence on the shadow shape. For fixed plasma parameters, increasing $\tilde{\xi }$ reduces the shadow size and increases its departure from circularity. Overall, plasma has a more pronounced effect on the shadow size than on its shape. Finally, we use the EHT observations of Sgr A* to constrain the parameter space for the radially inhomogeneous plasma model. Under the conditions adopted in this work, the EHT observations mainly disfavor regions where both $\tilde{\xi }$ and $K_r$ take relatively large values.

Bosonic particles beyond the Standard Model, such as axions, are among the leading candidates for dark matter. If such particles have a small mass, they are usually described as a purely classical field. However, it was recently shown that this description is incomplete: their inherent gravitational self-interactions result in the squeezing of the field, which is a quantum characteristic that is beyond the classical description. Here we analyze squeezing of light dark matter in the presence of decoherence. We show that squeezing is continuously generated rapidly enough to survive dissipation, and it may also remain present under thermal fluctuations and dephasing. Our results demonstrate that dark matter might possess persistent quantum features and motivate further investigation of their implications for dark matter detection.