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X. Hua

Publications and source records attributed to X. Hua.

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FLASH: Ultrafast beam quality characterization via spatial-to-temporal mapping

Accurate and real-time monitoring of spatial beam quality has emerged as the absolute prerequisite for intelligent optical field regulation and advanced laser applications. However, modern high-power and multimode optical systems exhibit highly complex, nonlinear, and transient behaviors. In these systems, the spatial beam profile undergoes dramatic reorganizations within extremely short timeframes. Phenomena such as spatio-temporal mode-locking, transient beam self-cleaning, and plasma-induced aberrations demand nanosecond-level dynamic characterization. Yet, capturing these ultrafast dynamics is fundamentally bottlenecked by the kilohertz frame rates of conventional two-dimensional image sensors. To break this dimensional and temporal barrier, we propose an ultrafast non-imaging beam quality monitoring technique, termed Fiber-based Laser Assessment via Spatial-to-temporal High-speed-mapping (FLASH). By utilizing a multimode fiber to encode spatial beam variations into high-dimensional speckle fingerprints and a multicore fiber delay line array to serialize these features, we transform two-dimensional spatial information into high-speed one-dimensional temporal pulse sequences. Empowered by a deep learning model to decipher the serialized signals, the FLASH system achieves an unprecedented 100 MHz measurement rate with a minimal mean relative error of 0.32%. Realizing a five-order-of-magnitude speed improvement over standard camera-based methods, this spatial-to-temporal mapping paradigm provides a transformative spatial oscilloscope. It unlocks new possibilities for real-time intelligent adaptive control and the exploration of complex multimode nonlinear physics.

physics.optics

Studying stellar populations in Omega Centauri with phylogenetics

The nature and formation history of our Galaxy's largest and most enigmatic stellar cluster, known as Omega Centauri (ocen) remains debated. Here, we offer a novel approach to disentangling the complex stellar populations within ocen based on phylogenetics methodologies from evolutionary biology. These include the Gaussian Mixture Model and Neighbor-Joining clustering algorithms applied to a set of chemical abundances of ocen stellar members. Instead of using the classical approach in astronomy of grouping them into separate populations, we focused on how the stars are related to each other. In this way, we could identify stars that likely formed in globular clusters versus those originating from prolonged in-situ star formation and how these stars interconnect. Our analysis supports the hypothesis that ocen might be a nuclear star cluster of a galaxy accreted by the Milky Way with a mass of about 10^9M_sun. Furthermore, we revealed the existence of a previously unidentified in-situ stellar population with a distinct chemical pattern unlike any known population found in the Milky Way to date. Our analysis of ocen is an example of the success of cross-disciplinary research and shows the vast potential of applying evolutionary biology tools to astronomical datasets, opening new avenues for understanding the chemical evolution of complex stellar systems.

astro-ph.GA