arXiv subjects

Biao Xiong

Publications and source records attributed to Biao Xiong.

11 recordsLinked to original sources

arXiv2026

FROD: Feature Matching Residual Denoising Oracle Bone Decipher

Oracle bone script (OBS), one of the earliest Chinese writing systems, plays an important role in the study of Chinese etymology. Traditional decipherment relies heavily on domain experts who analyze characters through semantic context and structural evolution. To assist this labor-intensive process, we formulate OBS decipherment assistance as a cross-era image translation task and propose FROD (Feature Matching Residual Denoising Oracle Bone Decipher). Although many OBS characters differ substantially from their modern counterparts, they often preserve local topological invariants at the radical level. During training, FROD leverages fast feature matching to provide gated segmentation supervision: paired samples with sufficient matches are processed patch-wise to align fine-grained radicals, whereas low-similarity pairs are trained holistically to avoid mismatched artifacts. In addition, a Residual Denoising Diffusion Model (RDDM) jointly estimates noise and residual signals, thereby reducing the positional drift and stroke disorder commonly observed in standard diffusion models. Finally, a multi-stage font stylization refinement network refines the generated images by eliminating edge noise and stabilizing stroke structures. On our augmented character-disjoint dataset, FROD achieves higher Top-1 recognition accuracy than the evaluated baselines, with a 3.8% absolute gain over OBSD.

cs.CV↗

arXiv2026

Pulse-Controlled Topologically Protected Quantum Batteries

Quantum batteries have emerged as a promising new generation of energy-storage devices for powering quantum technologies. Long-distance charging is particularly attractive because it minimizes interference between the charger and the battery, thereby attracting considerable interest. Here, we propose a topologically protected long-distance charging protocol for quantum batteries based on a pulse-controlled superconducting qubit chain. By dynamically modulating the pulse-mediated couplings, we realize topologically protected energy transfer from the charger to the battery. We show that the charging process is free of energy backflow and remains robust against imperfections in pulse control. Moreover, the energy stored in the battery at the target time is fully extractable, and the protocol remains effective for relatively large system sizes. To further accelerate charging, we optimize the pulse shape and elucidate the underlying physical mechanism. Our pulse-controlled topological quantum battery protocol provides a versatile framework for implementing long-distance topological charging and establishes a theoretical foundation for designing optimal-control strategies to enhance quantum battery performance.

quant-ph↗

arXiv2026

TLC-Plan: A Two-Level Codebook Based Network for End-to-End Vector Floorplan Generation

Automated floorplan generation aims to improve design quality, architectural efficiency, and sustainability by jointly modeling global spatial organization and precise geometric detail. However, existing approaches operate in raster space and rely on post hoc vectorization, which introduces structural inconsistencies and hinders end-to-end learning. Motivated by compositional spatial reasoning, we propose TLC-Plan, a hierarchical generative model that directly synthesizes vector floorplans from input boundaries, aligning with human architectural workflows based on modular and reusable patterns. TLC-Plan employs a two-level VQ-VAE to encode global layouts as semantically labeled room bounding boxes and to refine local geometries using polygon-level codes. This hierarchy is unified in a CodeTree representation, while an autoregressive transformer samples codes conditioned on the boundary to generate diverse and topologically valid designs, without requiring explicit room topology or dimensional priors. Extensive experiments show state-of-the-art performance on RPLAN dataset (FID = 1.84, MSE = 2.06) and leading results on LIFULL dataset. The proposed framework advances constraint-aware and scalable vector floorplan generation for real-world architectural applications. Source code and trained models are released at https://github.com/rosolose/TLC-PLAN.

cs.CV↗

arXiv2025

CAGE: Continuity-Aware edGE Network Unlocks Robust Floorplan Reconstruction

We present CAGE (Continuity-Aware edGE) network, a robust framework for reconstructing vector floorplans directly from point-cloud density maps. Traditional corner-based polygon representations are highly sensitive to noise and incomplete observations, often resulting in fragmented or implausible layouts.Recent line grouping methods leverage structural cues to improve robustness but still struggle to recover fine geometric details. To address these limitations,we propose a native edge-centric formulation, modeling each wall segment as a directed, geometrically continuous edge. This representation enables inference of coherent floorplan structures, ensuring watertight, topologically valid room boundaries while improving robustness and reducing artifacts. Towards this design, we develop a dual-query transformer decoder that integrates perturbed and latent queries within a denoising framework, which not only stabilizes optimization but also accelerates convergence. Extensive experiments on Structured3D and SceneCAD show that CAGE achieves state-of-the-art performance, with F1 scores of 99.1% (rooms), 91.7% (corners), and 89.3% (angles). The method also demonstrates strong cross-dataset generalization, underscoring the efficacy of our architectural innovations. Code and pretrained models are available on our project page: https://github.com/ee-Liu/CAGE.git.

cs.CV↗

arXiv2025

VF-Plan: Bridging the Art Gallery Problem and Static LiDAR Scanning with Visibility Field Optimization

Viewpoint planning is critical for efficient 3D data acquisition in applications such as 3D reconstruction, building life-cycle management, navigation, and interior decoration. However, existing methods often neglect key optimization objectives specific to static LiDAR systems, resulting in redundant or disconnected viewpoint networks. The viewpoint planning problem (VPP) extends the classical Art Gallery Problem (AGP) by requiring full coverage, strong registrability, and coherent network connectivity under constrained sensor capabilities. To address these challenges, we introduce a novel Visibility Field (VF) that accurately captures the directional and range-dependent visibility properties of static LiDAR scanners. We further observe that visibility information naturally converges onto a 1D skeleton embedded in the 2D space, enabling significant searching space reduction. Leveraging these insights, we develop a greedy optimization algorithm tailored to the VPP, which constructs a minimal yet fully connected Viewpoint Network (VPN) with low redundancy. Experimental evaluations across diverse indoor and outdoor scenarios confirm the scalability and robustness of our method. Compared to expert-designed VPNs and existing state-of-the-art approaches, our algorithm achieves comparable or fewer viewpoints while significantly enhancing connectivity. In particular, it reduces the weighted average path length by approximately 95%, demonstrating substantial improvements in compactness and structural efficiency. Code is available at https://github.com/xiongbiaostar/VFPlan.

cs.RO↗

arXiv2021

Suppressing laser phase noise in an optomechanical system

We propose a scheme to suppress the laser phase noise without increasing the optomechanical single-photon coupling strength. In the scheme, the parametric amplification terms, created by Kerr and Duffing nonlinearities, can restrain laser phase noise and strengthen the effective optomechanical coupling, respectively. Interestingly, decreasing laser phase noise leads to increasing thermal noise, which is inhibited by bringing in a broadband-squeezed vacuum environment. To reflect the superiority of the scheme, we simulate quantum memory and stationary optomechanical entanglement as examples, and the corresponding numerical results demonstrate that the laser phase noise is extremely suppressed. Our method can pave the way for studying other quantum phenomena.

quant-ph↗

arXiv2020

Accurate phonon blockade detector composed of a quadratically coupled optomechanical system

The observation of phonon blockade in a nanomechanical oscillator is clear evidence of its quantum nature. However, it is still a severe challenge to measure the strong phonon blockade in an optomechanical system with effective nonlinear coupling. In this paper, we propose a theoretical proposal for detecting the phonon blockade effect in a quadratically coupled optomechanical system by exploiting supervised machine learning. The detected optical signals are injected into the neural network as the input, while the output is the mechanical equal-time second-order correlation. Our results show our scheme performs superior performance on detecting phonon blockade. Specifically, it is efficient for nonlinear coupling systems; it performs a high precision for strong photon blockade; it is robust against the small disturbance of system parameters. Our work opens a promising way to build a phonon blockade detector.

quant-ph↗

arXiv2020

Remote weak signal measurement via bound states in optomechanical system

A scheme for remote weak signal sensor is proposed in which a coupled resonator optical waveguide~(CROW), as a transmitter, couples to a hybrid optomechanical cavity and an observing cavity, respectively. The non-Markovian theory is employed to study the weak force sensor by treating the CROW as a non-Markovian reservoir of the cavity fields, and the negative-effective-mass~(NEM) oscillator is introduced to cancel the back-action noise. Under certain conditions, dissipationless bound states can be formed such that weak signal can be transferred in the CROW without dissipation. Our results show that ultrahigh sensitivity can be achieved with the assistance of the bound states under certain parameters regime.

quant-ph↗

arXiv2019

Optomechanical quadrature squeezing in the non-Markovian regime

Squeezing of quantum fluctuation plays an important role in fundamental quantum physics and has marked influence on ultrasensitive detection. We propose a scheme to generate and enhance the squeezing of mechanical mode by exposing the optomechanical system to a non-Markovian environment. It is shown that the effective parametric resonance term of mechanical mode can be induced due to the interaction with cavity and non-Markovian reservoir, thus resulting in quadrature squeezing of the mechanical resonator. And jointing the two kinds of interactions can enhance the squeezing effect. Comparing with the usual Markovian regime, we can obtain stronger squeezing, and significantly the squeezing can approach a low asymptotic stable value.

quant-ph↗

arXiv2018

Improve Microwave Quantum Illumination Via Optical Parametric Amplifier

Quantum illumination is a quantum-optical sensing technique in which an entangled source is exploited to improve the detection of a low-reflectivity object that is immersed in a bright thermal background. Entangled sources between microwave and optical fields can be exploited to improve detection in microwave quantum illumination technique. We proposed a scheme to enhance the entanglement between the output fields of microwave and optical cavity by introducing optical parametric amplifier medium in cavity optomechanical system. We show that improving signal-to-noise ratio and decreasing error probability of detection can be obtained consequently even for objects with low reflectivity in the presence of optical parametric amplifier.

quant-ph↗

arXiv2017

Optomechanical Force Sensor in non-Markovian Regime

The optomechanical force sensor in non-Markovian environment for a mechanical oscillator is presented. By performing homodyne detection we obtain an generally expression for the output signal. It is shown that the weak force detection is sensitive to the non-Markovian environment. The additional noise can be obviously reduced comparing to the Markovian condition. Moreover, the optimal additional noise can be maintained in a rather low level without using assistant system or squeezing under available experimental condition in unsolved sideband regime. Our results provides a promising platform for reducing the additional noise by using engineered non-Markovian reservoir in ultrasensitive detection.

quant-ph↗