arXiv subjects

Baichuan Yang

Publications and source records attributed to Baichuan Yang.

3 recordsLinked to original sources

arXiv2025

Metasurface Holography on a Relative-Phase Manifold for Stable and High Fidelity Tweezer-Array Generation

We present a new holographic approach for generating large scale, polarization resolved optical tweezer arrays. By analyzing the ideal Jones fields that realize a target pattern, we identify that the fundamental degrees of freedom are the relative phases of the individual tweezers, rather than the full spatial phase profile. Leveraging this insight, we formulate a reverse projection optimization that adjusts only a small set of phase parameters to approximate the ideal operator within the physical constraints of a metasurface. This produces significantly higher fidelity and robustness than Gerchberg_Saxton type algorithms. Experimentally, we demonstrate H, V, L, and R polarized tweezer arrays using a single layer metasurface. A key advantage of our method is its phase stability, yielding strong resistance to optical aberrations and enabling coherent global phase modulation such as forming vortex tweezer lattice, without degrading trap quality. This framework provides a conceptually clear and experimentally powerful route for scalable optical field synthesis.

physics.optics↗

arXiv2025

ChemVTS-Bench: Evaluating Visual-Textual-Symbolic Reasoning of Multimodal Large Language Models in Chemistry

Chemical reasoning inherently integrates visual, textual, and symbolic modalities, yet existing benchmarks rarely capture this complexity, often relying on simple image-text pairs with limited chemical semantics. As a result, the actual ability of Multimodal Large Language Models (MLLMs) to process and integrate chemically meaningful information across modalities remains unclear. We introduce \textbf{ChemVTS-Bench}, a domain-authentic benchmark designed to systematically evaluate the Visual-Textual-Symbolic (VTS) reasoning abilities of MLLMs. ChemVTS-Bench contains diverse and challenging chemical problems spanning organic molecules, inorganic materials, and 3D crystal structures, with each task presented in three complementary input modes: (1) visual-only, (2) visual-text hybrid, and (3) SMILES-based symbolic input. This design enables fine-grained analysis of modality-dependent reasoning behaviors and cross-modal integration. To ensure rigorous and reproducible evaluation, we further develop an automated agent-based workflow that standardizes inference, verifies answers, and diagnoses failure modes. Extensive experiments on state-of-the-art MLLMs reveal that visual-only inputs remain challenging, structural chemistry is the hardest domain, and multimodal fusion mitigates but does not eliminate visual, knowledge-based, or logical errors, highlighting ChemVTS-Bench as a rigorous, domain-faithful testbed for advancing multimodal chemical reasoning. All data and code will be released to support future research.

cs.AI↗

arXiv2025

Unveiling Hierarchical Invariants in Multiphoton Linear Optics

Linear optical networks driven by quantum states of light are important building blocks of photonic quantum technologies. They access large bosonic Hilbert spaces through multiphoton interference. At the same time, their dynamics are generated by single-particle mode transformations, thereby defining a highly structured subset of multiphoton unitaries and setting boundary on linear optics capability. To elucidate this boundary, we reveal an underlying fine-grained symmetry structure that partitions the multiphoton operator space into invariant subspaces and generates a hierarchy of invariants. We experimentally confirm the conservation of high-order invariants and demonstrate their operational utility in characterizing state reachability and the metrological capability of multiphoton probes. Our framework provides a symmetry-based perspective for understanding and harnessing structured multiphoton dynamics across photonic quantum technologies.

quant-ph↗