arXiv subjects

Xiaoyi Yang

Publications and source records attributed to Xiaoyi Yang.

7 recordsLinked to original sources

arXiv2026

Temperature-Controlled Resonance in a Heteronuclear Quantum Gas Mixture

Single-channel resonances are fundamental processes in scattering of atoms, yet their occurrence is largely incidental and lacks systematic control. In this Letter, we propose a mechanism to realize a continuously tunable single-channel resonance by controlling the temperature of the heteronuclear mixture. By extending the Casimir-like mediated interaction to finite temperature, we demonstrate that thermal smearing of the Fermi surface reshapes the effective potential between impurities, giving rise to a temperature-controlled resonance (TCR) over a wide parameter range. As a direct consequence, the resonance position shifts systematically with temperature variation, providing a clear experimental signature of this mechanism. We further investigate the quench dynamics of a Bose gas immersed in a Fermi sea and demonstrate that the observed temperature-dependent loss features in recent experiments are consistent with the TCR mechanism. Our results establish temperature as a simple and experimentally accessible control knob for single-channel resonances in ultracold quantum gases.

cond-mat.quant-gas↗

arXiv2026

Object Fidelity Diffusion for Remote Sensing Image Generation

High-precision controllable remote sensing image generation is both meaningful and challenging. Existing diffusion models often produce low-fidelity images due to their inability to adequately capture morphological details, which may affect the robustness and reliability of object detection models. To enhance the accuracy and fidelity of generated objects in remote sensing, this paper proposes Object Fidelity Diffusion (OF-Diff), which effectively improves the fidelity of generated objects. Specifically, we are the first to extract the prior shapes of objects based on the layout for diffusion models in remote sensing. Then, we introduce a dual-branch diffusion model with diffusion consistency loss, which can generate high-fidelity remote sensing images without providing real images during the sampling phase. Furthermore, we introduce DDPO to fine-tune the diffusion process, making the generated remote sensing images more diverse and semantically consistent. Comprehensive experiments demonstrate that OF-Diff outperforms state-of-the-art methods in the remote sensing across key quality metrics. Notably, the performance of several polymorphic and small object classes shows significant improvement. For instance, the mAP increases by 8.3%, 7.7%, and 4.0% for airplanes, ships, and vehicles, respectively.

cs.CV↗

arXiv2025

EMRA-proxy: Enhancing Multi-Class Region Semantic Segmentation in Remote Sensing Images with Attention Proxy

High-resolution remote sensing (HRRS) image segmentation is challenging due to complex spatial layouts and diverse object appearances. While CNNs excel at capturing local features, they struggle with long-range dependencies, whereas Transformers can model global context but often neglect local details and are computationally expensive.We propose a novel approach, Region-Aware Proxy Network (RAPNet), which consists of two components: Contextual Region Attention (CRA) and Global Class Refinement (GCR). Unlike traditional methods that rely on grid-based layouts, RAPNet operates at the region level for more flexible segmentation. The CRA module uses a Transformer to capture region-level contextual dependencies, generating a Semantic Region Mask (SRM). The GCR module learns a global class attention map to refine multi-class information, combining the SRM and attention map for accurate segmentation.Experiments on three public datasets show that RAPNet outperforms state-of-the-art methods, achieving superior multi-class segmentation accuracy.

cs.CV↗

arXiv2023

Variational principle for weighted amenable topological pressure

This paper aims to investigate the thermodynamic formalism of weighted amenable topological pressure for factor maps of amenable group actions. Following the approach of Tsukamoto [\emph{Ergodic Theory Dynam. Syst.} \textbf{43}(2023), 1004-1034.], we introduce the notion of weighted amenable topological pressure for factor maps of amenable group actions, and establish a variational principle for it. As the application of variational principle, we show weighted amenable measure-theoretic entropy can be determined by weighted amenable topological pressure. Equilibrium states of weighted topological pressure are also involved.

math.DS↗

arXiv2023

Quench Dynamics of Thermal Bose Gases Across Wide and Narrow Feshbach

Using high-temperature virial expansion, we study the quench dynamics of the thermal Bose gases near a wide, narrow, and intermediate Feshbach resonance. Our results show that the shallow bound state near Feshbach resonance leads to interesting phenomena. Near the wide Feshbach resonance, the long-time $\hat{n}_{\bf k}$ oscillates when the scattering length $a_{s}$ is quenched from zero to large but with finite positive values. The oscillation frequency $ω=E_{\rm b}/\hbar$ with $E_{\rm b}$ being the binding energy. When $a_{s}$ is quenched to infinity or negative value, the oscillation vanishes. Near the narrow Feshbach resonance, the interaction should be characterized by a two-channel model. When the background scattering length $a_{\rm bg}\gtrsimλ$, there is an oscillation in the long-time dynamics, and the frequency is determined by the energy of the shallow bound state in the open channel. When $a_{\rm bg}<0$ or $0<a_{\rm bg}\llλ$, there is no shallow bound state in the open channel, hence no long-time oscillation. We check our conclusion using some realistic systems, and the results are consistent with our conclusion.

cond-mat.quant-gas↗

arXiv2022

Quantum Dynamics of Cold Atomic Gas with $SU(1,1)$ Symmetry

Motivated by recent advances in quantum dynamics, we investigate the dynamics of the system with $SU(1,1)$ symmetry. Instead of performing the time-ordered integral for the evolution operator of the time-dependent Hamiltonian, we show that the time evolution operator can be expressed as an $SU(1,1)$ group element. Since the $SU(1,1)$ group describes the "rotation" on a hyperbolic surface, the dynamics can be visualized on a Poincaré disk, a stereographic projection of the upper hyperboloid. As an example, we present the trajectory of the revival of Bose-Einstein condensation and that of the scale-invariant Fermi gas on the Poincaré disk. Further considering the quantum gas in the oscillating lattice, we also study the dynamics of the system with time-dependent single-particle dispersion. Our results are hopefully to be checked in current experiments.

cond-mat.quant-gas↗

arXiv2020

Learning Social Networks from Text Data using Covariate Information

Describing and characterizing the impact of historical figures can be challenging, but unraveling their social structures perhaps even more so. Historical social network analysis methods can help and may also illuminate people who have been overlooked by historians but turn out to be influential social connection points. Text data, such as biographies, can be a useful source of information about the structure of historical social networks but can also introduce challenges in identifying links. The Local Poisson Graphical Lasso model leverages the number of co-mentions in the text to measure relationships between people and uses a conditional independence structure to model a social network. This structure will reduce the tendency to overstate the relationship between "friends of friends", but given the historical high frequency of common names, without additional distinguishing information, we can still introduce incorrect links. In this work, we extend the Local Poisson Graphical Lasso model with a (multiple) penalty structure that incorporates covariates giving increased link probabilities to people with shared covariate information. We propose both greedy and Bayesian approaches to estimate the penalty parameters. We present results on data simulated with characteristics of historical networks and show that this type of penalty structure can improve network recovery as measured by precision and recall. We also illustrate the approach on biographical data of individuals who lived in early modern Britain, targeting the period from 1500 to 1575.

stat.AP↗