arXiv subjects

Shuhua Deng

Publications and source records attributed to Shuhua Deng.

6 recordsLinked to original sources

arXiv2026

No Prompt, No Leaks: A Robust Generative Steganography Framework via Prompt-Free Diffusion

Generative image steganography synthesizes stego images directly from secret information to achieve inherent security advantages. Latent Diffusion Models (LDMs) have recently emerged as a fundamental image steganography framework that modulates secret latent representations with text prompts. Limited by the inflexibility of text prompts, these methods still struggle to generate high-quality stego images and accurately recover secret images. In this work, we propose a prompt-free diffusion image steganography framework that integrates style semantic priors to control more robust and reliable stego image generation. Specifically, a Cascaded Affine Coupling Module (CACM) establishes a bijective, deterministic mapping between a secret image and its latent representation. Then, style semantics are integrated into the diffusion process to control latent representation and ensure visual imperceptibility in the generated stego images. To mitigate trajectory deviations stemming from the unconditioned reverse process, a predictor-corrector mechanism is introduced to iteratively refine the generation trajectory via feedback from the current and predicted next states. Extensive experimental results show that the proposed method achieves competitive performance compared to state-of-the-art methods in terms of security, secret image reconstruction accuracy and controllability.

cs.CV↗

arXiv2026

Capture velocities for direct loading of heavy molecules into conveyor-belt magneto-optical traps

Conveyor-belt magneto-optical traps (CB-MOTs) use blue-detuned polarization-gradient forces to provide simultaneous cooling, confinement, and loading on type-II molecular transitions. Recent experiments with \baf{138} showed that this mechanism can directly load a slowed molecular beam with an efficiency exceeding that of a conventional red-detuned MOT. Here we use established optical-Bloch-equation force calculations and classical trajectory propagation to ask whether this direct-loading strategy should extend beyond the specific molecule used in the first demonstration. For \baf{138}, the calculation reproduces the experimentally observed trend that the CB-MOT capture velocity increases with laser intensity. We then apply the same framework to two closely related but experimentally distinct cases: \baf{137}, whose dense hyperfine structure complicates a conventional dual-frequency MOT, and \bah{138}, whose narrower linewidth and longer wavelength reduce the available radiative force. In both cases, the CB-MOT retains a broad region of nonzero capture velocity. These results identify the molecular conditions under which direct CB-MOT loading should remain effective and show that the dipole-force-dominated conveyor-belt mechanism provides a practical loading route for heavy laser-coolable molecules whose MOT performance is otherwise limited by photon recoil, scattering rate, or hyperfine complexity.

physics.atom-ph↗

arXiv2026

Focus-to-Perceive Representation Learning: A Cognition-Inspired Hierarchical Framework for Endoscopic Video Analysis

Endoscopic video analysis is essential for early gastrointestinal screening but remains hindered by limited high-quality annotations. While self-supervised video pre-training shows promise, existing methods developed for natural videos prioritize dense spatio-temporal modeling and exhibit motion bias, overlooking the static, structured semantics critical to clinical decision-making. To address this challenge, we propose Focus-to-Perceive Representation Learning (FPRL), a cognition-inspired hierarchical framework that emulates clinical examination. FPRL first focuses on intra-frame lesion-centric regions to learn static semantics, and then perceives their evolution across frames to model contextual semantics. To achieve this, FPRL employs a hierarchical semantic modeling mechanism that explicitly distinguishes and collaboratively learns both types of semantics. Specifically, it begins by capturing static semantics via teacher-prior adaptive masking (TPAM) combined with multi-view sparse sampling. This approach mitigates redundant temporal dependencies and enables the model to concentrate on lesion-related local semantics. Following this, contextual semantics are derived through cross-view masked feature completion (CVMFC) and attention-guided temporal prediction (AGTP). These processes establish cross-view correspondences and effectively model structured inter-frame evolution, thereby reinforcing temporal semantic continuity while preserving global contextual integrity. Extensive experiments on 11 endoscopic video datasets show that FPRL achieves superior performance across diverse downstream tasks, demonstrating its effectiveness in endoscopic video representation learning. The code is available at https://github.com/MLMIP/FPRL.

cs.CV↗

arXiv2025

Optical pumping and laser slowing of a heavy molecule

Precision measurements of the electron's electric dipole moment (eEDM) are critical for testing fundamental symmetries in particle physics, and heavy polar molecules-such as barium monofluoride (BaF)-have emerged as promising candidates for advancing the sensitivity. However, the achievement of a 3D magneto-optical trap (MOT) required slowing BaF molecules to near-zero velocity by scattering over 10^4 photons per molecule, demanding a quasi-cycling transition with minimal leakage. We present a detailed study of the leakage channels, including higher vibrational and rotational states. By combining microwave remixing with optical pumping of rotational and vibrational dark states, we reduced the total leakage fraction to 10^-5. Using frequency-chirped laser slowing, we slowed a subset of buffer-gas-cooled BaF molecules from approximately 80 m/s to near-zero velocity, which is critical for efficient MOT loading. This work establishes the technical foundation for precision eEDM measurements using laser-cooled heavy molecules.

physics.atom-ph↗

arXiv2025

Blue-detuned Magneto-optical Trap of BaF molecules

We report the realization of a blue-detuned magneto-optical trap (BDM) of BaF molecules. The (1 + 1) type BDM and (1 + 2) type conveyor-belt MOT are explored. While the (1+1) BDM provides only weak trapping force, the conveyor-belt MOT significantly compresses the molecular cloud, achieving a radius of 320(20) μm, a temperature of 240(60) μK, and a peak density of 1.3{\times}10^7 cm^{-3}, representing a significant improvement over the red MOT. Interestingly, the conveyor-belt MOT of BaF exhibits a large capture velocity, and the loading efficiency from red MOT reaches near unity even without gray molasses. We confirm this by directly loading slowed molecules into the conveyor-belt MOT.

physics.atom-ph↗

arXiv2024

Three-dimensional Magneto-optical Trapping of Barium Monofluoride

As a heavy molecule, barium monofluoride (BaF) presents itself as a promising candidate for measuring permanent electric dipole moment. The precision of such measurements can be significantly enhanced by utilizing a cold molecular sample. Here we report the realization of three-dimensional magneto-optical trapping (MOT) of BaF molecules. Through the repumping of all the vibrational states up to $v=3$, and rotational states up to $N=3$, we effectively close the transition to a leakage level lower than $10^{-5}$. This approach enables molecules to scatter a sufficient number of photons required for laser cooling and trapping. By employing a technique that involves chirping the slowing laser frequency, BaF molecules are decelerated to near-zero velocity, resulting in the capture of approximately $3\times 10^3$ molecules in a dual-frequency MOT setup. Our findings represent a significant step towards the realization of ultracold BaF molecules and the conduct of precision measurements with cold molecules.

physics.atom-ph↗