Conventional laser frequency stabilization techniques such as table-lookup or heuristic methods have significant limitations due to intrinsic hysteresis and stochastic mode competition. To overcome this challenge, we introduce a simple hysteresis-aware protocol and a tailored image-based reinforcement learning (RL) framework. This approach enables robust mode hop recovery in external-cavity diode lasers (ECDLs). Using a Rainbow deep Q-network (DQN) trained entirely in simulation, our RL agent achieves 100% recovery success rate across all 163 continuous temperature drifts produced under deliberately extreme perturbations during a three-day stress test. Under challenging discrete test conditions with abrupt current jumps, the success probability reaches 99.9%, with only one failure recorded out of one thousand trials. The controller generalizes well across environmental perturbations, such as temperature fluctuations, without requiring additional calibration. Our approach provides real-time adaptive control with minimal human intervention, marking a step toward fully autonomous operation in quantum experiments and precision optical systems.
Real-world social contagions exhibit significant multi-scale features, where behavioral adoption is driven by both microscopic synergistic pressure within tight-knit groups and mesoscopic prevalence across diverse social circles, yet existing studies treat these mechanisms in isolation. Here, we propose a unified multi-scale higher-order contagion model integrating micro-local clustering and meso-structural diversity, and develops a dynamic message passing method to accurately analyze system dynamics. We rigorously derive tricritical points defining the topological boundary between second-order and first-order phase transitions, beyond which significant bistability and hysteresis emerge. While the higher-order effects have a limited impact on the forward threshold, they significantly lower the backward threshold, thereby expanding the active region of propagation. Crucially, structural diversity dually regulates contagion through a competition mechanism between single-component size fragmentation and component quantity gain. This leads to a significant non-monotonic U-shaped variation of the steady-state density with the structural diversity, proving the existence of an optimal structural diversity capable of minimizing the infection scale.
While the Vicsek model is widely used to understand active systems, the explicit relationship between structural evolution and the order transition remains an open question. Here we investigate this relationship in the original Vicsek system. We uncover a structure–order relationship across the investigated densities and noise strengths at fixed velocity and particle number, in which the polar order parameter exhibits a general correlation with the average interaction number. Furthermore, we reveal underlying structural self–similarities: cluster–level and system–level interaction number distributions show consistent normalized profiles, alongside a correlation between cluster size and orientation. Building on these correlations, we develop a phenomenological framework that quantitatively relates the order parameter to structural statistics. Moreover, over the investigated range of velocities, the structural features are maintained, whereas the structural–order correlation is augmented by a velocity factor. This work provides a structural perspective on the Vicsek model and suggests a quantitative relationship between microscopic structural organization and macroscopic collective behavior. We investigate the relationship between structural organization and collective order in the original Vicsek model. We uncover a universal structure–order relationship and develop a phenomenological framework linking microscopic structural statistics to macroscopic order, with velocity incorporated through an effective interaction number.
Kagome superconductors AV3Sb5 (A = Cs, K, Rb) host intertwined orders arising from electronic correlations and lattice geometry, but the nature of the high-temperature electronic state from which these phases emerge remains poorly understood. Although numerous experiments have reported rotational symmetry breaking, it is still intensely debated whether this may be a simple consequence of the symmetry of the underlying 2 × 2 charge density wave (CDW) or an entirely different mechanism. Here we use spectroscopic imaging scanning tunneling microscopy to track the evolution of electronic structure in CsV3Sb5 as the CDW is intentionally suppressed through two distinct chemical substitution routes—Sn on the Sb site and Ti on the V site. Across a wide doping range, we uncover persistent electronic rotational-symmetry breaking—referred to here as electronic nematicity—forming nanoscale domains with orientations along three crystalline directions. These results demonstrate that electronic nematicity is a persistent feature of the Kagome phase diagram, distinct from the 2 × 2 CDW.
Droplets would move following the designed wettability gradient on the surface, toward the position with high surface energy, which is vital for various applications like ink printing, biological detection, and water collection. Anomalously, here we have found that the core of the overlaid droplet shows anti-wettability-gradient movement on the wettability boundary. The core droplet would perform different directional motions after the impact on the same established surface, depending on the impact dynamics and the composition ratio of the overlaid droplet. The macroscopic motion preference of the overlaid droplet is related to the wetting preference of the overlayer on the heterogeneous surface. Competitive wetting/dewetting of different components of the overlayer droplet induces a special shuttle motion of the core droplet. The phenomenon would provide new insight into wetting and droplet control, being promising for broad application scenarios.
