arXiv subjects

Wei Yan

Publications and source records attributed to Wei Yan.

At least 37 records · Page 2Linked to original sources

arXiv2025

Three-Dimensional Isotropic STED Nanoscopy using a Single Objective

Accurate three-dimensional (3D) imaging requires an isotropic point spread function (PSF). However, the inherent missing aperture of a single objective lens results in an elongated, cigar-like PSF, which has rendered isotropic resolution in fluorescence microscopy seemingly insurmountable without a 4π configuration for decades. To address this long-standing challenge, we introduce ISO-STED (Isotropic Single-Objective STED) Nanoscopy, a novel approach that employs a single objective lens and a single depletion beam. By utilizing a hollow depletion focus, ISO-STED achieves an isotropic PSF without relying on a 4π configuration. This innovative design enables uniform fluorescence suppression in all directions, thereby yielding an isotropic 3D resolution of approximately 70 nm. Our work not only demonstrates the potential of ISO-STED Nanoscopy to provide a compact and versatile solution for isotropic 3D imaging in complex specimens but also paves the way for more accessible and practical applications in various research fields, including biomedical research and neuroscience.

physics.optics↗

arXiv2025

Text2VP: Generative AI for Visual Programming and Parametric Modeling

The integration of generative artificial intelligence (AI) into architectural design has advanced significantly, enabling the generation of text, images, and 3D models. However, prior AI applications lack support for text-to-parametric models, essential for generating and optimizing diverse parametric design options. This study introduces Text-to-Visual Programming (Text2VP) GPT, a novel generative AI derived from GPT-4.1, designed to automate graph-based visual programming workflows, parameters, and their interconnections. Text2VP leverages detailed documentation, specific instructions, and example-driven few-shot learning to reflect user intentions accurately and facilitate interactive parameter adjustments. Testing demonstrates Text2VP's capability in generating functional parametric models, although higher complexity models present increased error rates. This research highlights generative AI's potential in visual programming and parametric modeling, laying groundwork for future improvements to manage complex modeling tasks. Ultimately, Text2VP aims to enable designers to easily create and modify parametric models without extensive training in specialized platforms like Grasshopper.

cs.HC↗

arXiv2025

An obscured quasar census with the 4MOST IR AGN survey: design, predicted properties, and scientific goals

We present the 4MOST IR AGN survey, the first large-scale optical spectroscopic survey characterizing mid-infrared (MIR) selected obscured active galactic nuclei (AGN). The survey targets $\approx 212,000$ obscured infrared (IR) AGN candidates over $\approx 10,000 \rm \: deg^2$ down to a magnitude limit of $r_{\rm AB}=22.8 \, \rm mag$ and will be $\approx 100 \times$ larger than any existing obscured IR AGN spectroscopic sample. We select the targets using a MIR colour criterion applied to the unWISE catalogue from the WISE all-sky survey, and then apply a $r-W2\geq 5.9 \rm \: mag$ cut; we demonstrate that this selection will mostly identify sources obscured by $N_{\rm H}>10^{22} \rm \: cm^{-2}$. The survey complements the 4MOST X-ray survey, which will follow up $\sim 1\rm M$ eROSITA-selected (typically unobscured) AGN. We perform simulations to predict the quality of the spectra that we will obtain and validate our MIR-optical colour-selection method using X-ray spectral constraints and UV-to-far IR spectral energy distribution (SED) modelling in four well-observed deep-sky fields. We find that: (1) $\approx 80-87\%$ of the WISE-selected targets are AGN down to $r_{\rm AB}=22.1-22.8 \: \rm mag$ of which $\approx 70\%$ are obscured by $N_{\rm H}>10^{22} \: \rm cm^{-2}$, and (2) $\approx 80\%$ of the 4MOST IR AGN sample will remain undetected by the deepest eROSITA observations due to extreme absorption. Our SED fitting results show that the 4MOST IR AGN survey will primarily identify obscured AGN and quasars ($\approx 55\%$ of the sample is expected to have $L_{\rm AGN,IR}>10^{45} \rm \: erg \: s^{-1}$) residing in massive galaxies ($M_{\star}\approx 10^{10}-10^{12} \rm \: M_{\odot}$) at $z\approx 0.5-3.5$ with $ \approx 33\%$ expected to be hosted by starburst galaxies.

astro-ph.GA↗

arXiv2025

A Case Study on Evaluating Genetic Algorithms for Early Building Design Optimization: Comparison with Random and Grid Searches

In early-stage architectural design, optimization algorithms are essential for efficiently exploring large and complex design spaces under tight computational constraints. While prior research has benchmarked various optimization methods, their findings often lack generalizability to real-world, domain-specific problems, particularly in early building design optimization for energy performance. This study evaluates the effectiveness of Genetic Algorithms (GAs) for early design optimization, focusing on their ability to find near-optimal solutions within limited timeframes. Using a constrained case study, we compare a simple GA to two baseline methods, Random Search (RS) and Grid Search (GS), with each algorithm tested 10 times to enhance the reliability of the conclusions. Our findings show that while RS may miss optimal solutions due to its stochastic nature, it was unexpectedly effective under tight computational limits. Despite being more systematic, GS was outperformed by RS, likely due to the irregular design search space. This suggests that, under strict computational constraints, lightweight methods like RS can sometimes outperform more complex approaches like GA. As this study is limited to a single case under specific constraints, future research should investigate a broader range of design scenarios and computational settings to validate and generalize the findings. Additionally, the potential of Random Search or hybrid optimization methods should be further investigated, particularly in contexts with strict computational limitations.

cs.NE↗

arXiv2025

Performance optimization of Nernst-based thermionic engines

In this paper, we examine the power and efficiency of the thermionic device utilizing the Nernst effect, with a specific focus on its potential application as an engine. The device operates by utilizing the vertical heat current to generate a horizontal particle current against the chemical potential. By considering the influence of a strong magnetic field, we derive analytical expressions for the current and heat flux. These expressions are dependent on the temperature and chemical potential of heat reservoirs, providing valuable insights into the device performance. The impact of driving temperatures on the performance of the thermionic engine has been assessed through numerical analysis. The research findings will guide the experimental design of Nernst-based thermionic engines.

cond-mat.stat-mech↗

arXiv2025

Roadmap on Nonlocality in Photonic Materials and Metamaterials

Photonic technologies continue to drive the quest for new optical materials with unprecedented responses. A major frontier in this field is the exploration of nonlocal (spatially dispersive) materials, going beyond the local, wavevector-independent assumption traditionally made in optical material modeling. On one end, the growing interest in plasmonic, polaritonic and quantum materials has revealed naturally occurring nonlocalities, emphasizing the need for more accurate models to predict and design their optical responses. This has major implications also for topological, nonreciprocal, and time-varying systems based on these material platforms. Beyond natural materials, artificially structured materials--metamaterials and metasurfaces--can provide even stronger and engineered nonlocal effects, emerging from long-range interactions or multipolar effects. This is a rapidly expanding area in the field of photonic metamaterials, with open frontiers yet to be explored. In the case of metasurfaces, in particular, nonlocality engineering has become a powerful tool for designing strongly wavevector-dependent responses, enabling enhanced wavefront control, spatial compression, multifunctional devices, and wave-based computing. Furthermore, nonlocality and related concepts play a critical role in defining the ultimate limits of what is possible in optics, photonics, and wave physics. This Roadmap aims to survey the most exciting developments in nonlocal photonic materials, highlight new opportunities and open challenges, and chart new pathways that will drive this emerging field forward--toward new scientific discoveries and technological advancements.

cond-mat.mes-hall↗

arXiv2025

AI's Spatial Intelligence: Evaluating AI's Understanding of Spatial Transformations in PSVT:R and Augmented Reality

Spatial intelligence is important in Architecture, Construction, Science, Technology, Engineering, and Mathematics (STEM), and Medicine. Understanding three-dimensional (3D) spatial rotations can involve verbal descriptions and visual or interactive examples, illustrating how objects change orientation in 3D space. Recent studies show Artificial Intelligence (AI) with language and vision capabilities still face limitations in spatial reasoning. In this paper, we have studied generative AI's spatial capabilities of understanding rotations of objects utilizing its image and language processing features. We examined the spatial intelligence of the GPT-4 model with vision in understanding spatial rotation process with diagrams based on the Revised Purdue Spatial Visualization Test: Visualization of Rotations (Revised PSVT:R). Next, we incorporated a layer of coordinate system axes on Revised PSVT:R to study the variations in GPT-4's performance. We also examined GPT-4's understanding of 3D rotations in Augmented Reality (AR) scenes that visualize spatial rotations of an object in 3D space and observed increased accuracy of GPT-4's understanding of the rotations by adding supplementary textual information depicting the rotation process or mathematical representations of the rotation (e.g., matrices). The results indicate that while GPT-4 as a major current Generative AI model lacks the understanding of a spatial rotation process, it has the potential to understand the rotation process with additional information that can be provided by methods such as AR. By combining the potentials in spatial intelligence of AI with AR's interactive visualization abilities, we expect to offer enhanced guidance for students' spatial learning activities. Such spatial guidance can benefit understanding spatial transformations and additionally support processes like assembly, fabrication, and manufacturing.

cs.AI↗

arXiv2025

A comprehensive approach to incorporating intermolecular dispersion into the openCOSMO-RS model. Part 2: Atomic polarizabilities

openCOSMO-RS is an open-source predictive thermodynamic model that can be applied to a broad range of systems in various chemical and biochemical engineering domains. This study focuses on improving openCOSMO-RS by introducing a new dispersion term based on atomic polarizabilities. We evaluate different methods for processing polarizability data, including scaling and combining it to compute segment-segment dispersion interaction energies, with a focus on halocarbon systems. The results demonstrate that the modified model outperforms our previous method developed in the first part of this work (Grigorash et al., 2024) , while at the same time requiring fewer adjustable parameters. The approach was applied to a broad dataset of over 50,000 data points, consistently increasing the accuracy across a variety of data types. These findings suggest that atomic polarizability is a valuable descriptor for refining dispersion interactions in predictive thermodynamic models.

cond-mat.soft↗

arXiv2025

Improving Undergraduate Astronomy Students' Skills with Research Literature via Accessible Summaries: An Exploratory Case Study with Astrobites-based Reading Assignments

Undergraduate physics and astronomy students are expected to engage with scientific literature as they begin their research careers, but reading comprehension skills are rarely explicitly taught in major courses. We seek to determine the efficacy of a reading assignment designed to improve undergraduate astronomy (or related) majors' perceived ability to engage with research literature by using accessible summaries of current research written by experts in the field. During the 2022-2023 academic year, faculty members from six institutions incorporated reading assignments using accessible summaries from Astrobites into their undergraduate astronomy major courses, surveyed their students before and after the activities, and participated in follow-up interviews with our research team. Quantitative and qualitative survey data from 52 students show that students' perceptions of their abilities with jargon and identifying main takeaways of a paper significantly improved with use of the tested assignment template. Additionally, students report increased confidence of their abilities within astronomy after exposure to these assignments, and instructors valued a ready-to-use resource to incorporate reading comprehension in their pedagogy. This exploratory case study with Astrobites-based assignments suggests that incorporating current research in the undergraduate classroom through accessible literature summaries may increase students' confidence and ability to engage with research literature, assisting in their preparation for participation in research careers.

physics.ed-ph↗

arXiv2025

Nonreciprocal Optical Routing in Multi-port Magneto-Optical Devices on Silicon

Nonreciprocal optical devices are key components in photonic integrated circuits for light reflection blocking and routing. Most reported silicon integrated nonreciprocal optical devices to date were unit devices. To allow complex signal routing between multi-ports in photonic networks, multi-port magneto-optical (MO) nonreciprocal photonic devices are desired. In this study, we report experimental demonstration of a silicon integrated 5*5 multiport nonreciprocal photonic device based on magneto-optical waveguides. By introducing different nonreciprocal phase shift effect to planar photonic waveguides, the device focuses light to different ports for both forward and backward propagation. The device shows designable nonreciprocal transmission between 5*5 ports, achieving 16 dB isolation ratio and -18 dB crosstalk.

physics.optics↗

arXiv2024

Point Cloud-Assisted Neural Image Compression

High-efficient image compression is a critical requirement. In several scenarios where multiple modalities of data are captured by different sensors, the auxiliary information from other modalities are not fully leveraged by existing image-only codecs, leading to suboptimal compression efficiency. In this paper, we increase image compression performance with the assistance of point cloud, which is widely adopted in the area of autonomous driving. We first unify the data representation for both modalities to facilitate data processing. Then, we propose the point cloud-assisted neural image codec (PCA-NIC) to enhance the preservation of image texture and structure by utilizing the high-dimensional point cloud information. We further introduce a multi-modal feature fusion transform module (MMFFT) to capture more representative image features, remove redundant information between channels and modalities that are not relevant to the image content. Our work is the first to improve image compression performance using point cloud and achieves state-of-the-art performance.

eess.IV↗

arXiv2024

Strichartz estimates for orthonormal functions and probabilistic convergence of density functions of compact operators on manifolds

In this paper, we establish some Strichartz estimates for orthonormal functions and probabilistic convergence of density functions related to compact operators on manifolds. Firstly, we present the suitable bound of $\int_{a\leq|s|\leq b}e^{isx}s^{-1+iγ}ds$ for the cases $γ\in \mathbb{R},a\geq0,b>0,$ $γ\in \mathbb{R},γ\neq0,a,b\in \mathbb{R}$ and $γ\in \mathbb{R}$, which extends the result of Page 204 of Vega (199-211,IMA Vol. Math. Appl., 42, 1992.) Secondly, we prove that $\left|γ\int_{a}^{b}e^{isx}s^{-1+iγ}ds\right|\leq C(1+|γ|)^{2}(γ\in \mathbb{R},a,b\in \mathbb{R}),$ where $C$ is independent of $γ,a, b$, which extends Lemma 1 of Bez et al. (Forum of Mathematics, Sigma, 9(2021), 1-52). Thirdly, we extend the result of Theorems 8, 9 of R. Frank, J. Sabin (Amer. J. Math. 139(2017), 1649-1691.) with the aid of the suitable bound of the above complex integrals established in this paper. Fourthly, we establish the Strichartz estimates for orthonormal functions related to Boussinesq operator on the real line for both small time interval and large time interval and on the torus with small time interval; we also establish the convergence result of some compact operators in Schatten norm. Fifthly, we establish the convergence result related to nonlinear part of the solution to some operator equations in Schatten spaces. Finally, inspired by the work of Hadama and Yamamoto (Probabilistic Strichartz estimates in Schatten classes and their applications to Hartree equation, arxiv:2311.02713v1.), for $γ_{0}\in \mathfrak{S}^{2}$, we establish the probabilistic convergence of density functions of compact operator on manifolds with full randomization, which improves the result of Corollary 1.2 of Bez et al. (Selecta Math. 26(2020), 24 pp) in the probabilistic sense.

math.PR↗

arXiv2024

Strichartz estimates for orthonormal functions and convergence problem of density functions of Boussinesq operator on manifolds

This paper is devoted to studying the maximal-in-time estimates and Strichartz estimates for orthonormal functions and convergence problem of density functions related to Boussinesq operator on manifolds. Firstly, we present the pointwise convergence of density function related to Boussinesq operator with $γ_{0}\in\mathfrak{S}^β(\dot{H}^{\frac{1}{4}}(\mathbf{R}))(β<2)$ with the aid of the maximal-in-time estimate related to Boussinesq operator with orthonormal function on $\R$. Secondly, we present the pointwise convergence of density function related to Boussinesq operator with $γ_{0}\in\mathfrak{S}^β(\dot{H}^{s})(\frac{d}{4}\leq s<\frac{d}{2},\, 0<α\leq d, 1\leqβ<\fracα{d-2s})$ with the aid of the maximal-in-time estimates related to Boussinesq operator with orthonormal function on the unit ball $\mathbf{B}^{d}(d\geq1)$ established in this paper; we also present the Hausdorff dimension of the divergence set of density function related to Boussinesq operator $dim_{H}D(γ_{0})\leq (d-2s)β$. Thirdly, we show the Strichartz estimates for orthonormal functions and Schatten bound with space-time norms related to Boussinesq operator on $\mathbf{T}$ with the aid of the noncommutative-commutative interpolation theorems established in this paper, which are just Lemmas 3.1-3.4 in this paper; we also prove that Theorems 1.5, 1.6 are optimal. Finally, by using full randomization, we present the probabilistic convergence of density function related to Boussinesq operator on $\R$, $\mathbf{T}$ and $Θ=\{x\in\R^{3}:|x|<1\}$ with $γ_{0}\in\mathfrak{S}^{2}$.

math.AP↗

arXiv2024

Global weak solutions with higher regularity to the compressible Navier-Stokes equations under Dirichlet boundary conditions

In this manuscript, we aim to establish global existence of weak solutions with higher regularity to the compressible Navier-Stokes equations under no-slip boundary conditions. Though Lions\cite{L1} and Feireisl\cite{F1} have established global weak solutions with finite energy under Dirichelet boundary conditions by making use of so called effective viscous flux and oscillation defect measure,Hoff has investigated global weak solutions with higher regularity in \cite{H1,Hof2} when the domain is either whole space or half space with Navier-slip boundary conditions, yet the existence theory of global weak solution with higher regularity under Dirichlet boundary conditions remains unknown. In this paper we prove that the system will admit at least one global weak solutions with higher regularity as long as the initial energy is suitably small when the domain is a 2D solid disc. This is achieved by exploiting the structure of the exact Green function of the disc to decompose the effective viscous flux into three parts, which corresponds to the pressure term, boundary term and the remaining term respectively. In order to control the boundary term, one of the key observations is to use the geometry of the domain which sucessfully to bound the integral of the effective viscous flux where $L^1$ norm is always unbounded.

math.AP↗

arXiv2024

Finite time blowup of strong solutions to the two dimensional MHD equations

Whether the smooth solution of the multi-dimensional viscous compressible fluids will blow-up in finite time has always been a chanllenging problem. In the recent work\cite{FM}, Merle et al. proved that there are smooth solutions to the 2D radially symmetric compressible Navier-Stokes equations which will inevitably form shell singularities in finite time.\\ \indent In this article, we first prove the existence of local strong solutions that allow vacuum for the two-dimensional viscous compressible MHD equations on bounded domains without magnetic diffusion. Furthermore, it is shown that if the initial data are radial symmetric and its vacuum set contains a ball centered at the origin where the total magnetic field is non-trivial, then the radial symmetric strong solution to the initial boundary value problem will definitely blow up in finite time. This is the first example for the formation of finite time singularity of strong solutions that allows interior vacuum of a viscous compressible fluid.

math.AP↗

arXiv2024

An Approach to Detect Abnormal Submissions for CodeWorkout Dataset

Students interactions while solving problems in learning environments (i.e. log data) are often used to support students learning. For example, researchers use log data to develop systems that can provide students with personalized problem recommendations based on their knowledge level. However, anomalies in the students log data, such as cheating to solve programming problems, could introduce a hidden bias in the log data. As a result, these systems may provide inaccurate problem recommendations, and therefore, defeat their purpose. Classical cheating detection methods, such as MOSS, can be used to detect code plagiarism. However, these methods cannot detect other abnormal events such as a student gaming a system with multiple attempts of similar solutions to a particular programming problem. This paper presents a preliminary study to analyze log data with anomalies. The goal of our work is to overcome the abnormal instances when modeling personalizable recommendations in programming learning environments.

cs.CY↗

arXiv2024

A comprehensive approach to incorporating intermolecular dispersion into the openCOSMO-RS model. Part 1: Halocarbons

The COSMO-RS (Conductor-like Screening Model for Real Solvents) is a predictive thermodynamic model that has found diverse applications in various domains like chemical engineering, environmental chemistry, nanotechnology, material science, and biotechnology. Its core concept involves calculating the screening charge density on the surface of each molecule and letting these surface patches interact with each other to calculate thermodynamic properties. In this study, we aim to enhance the performance of the open-source implementation openCOSMO-RS by incorporating dispersive interactions between the paired segments. Several parametrizations were systematically evaluated through the extensive regression analysis using a comprehensive database of Vapor-Liquid Equilibrium (VLE), Liquid-Liquid Equilibrium (LLE) and Infinite Dilution Activity Coefficients (IDACs). Furthermore, the influence of different combinatorial terms on the model performance was investigated. Our findings indicate that incorporating dispersive interactions significantly improves the accuracy of phase equilibrium predictions for halocarbons and refrigerant mixtures.

cond-mat.soft↗

arXiv2024

An ALE numerical method with HLLC-2D solver for the two-phase flow ejecta transporting model

This work presents an arbitrary Lagrangian Eulerian (ALE) method for the compressible two-phase flow ejecta transporting model with the HLLC-2D Riemann solver. We focus on researching the precise equation to describe the interactions between particle phase and flow phase. The calculation of the momentum and energy exchange across two phases is the key point during the procedure, which can be capable of maintaining the conservation of this system. For particles, tracking their trajectories within the mesh and elements is essential. Thereafter an ALE method instead of Lagrangian scheme is derived for the discretization of the equation to perform better with the complex motion of particles and flow. We apply the HLLC-2D Riemann solver to substitute the HLLC solver which relaxes the limitation for continuous fluxes along the edge. Meanwhile we propose a method for searching particles and provide a CFL-like condition based on this. Finally, we show some numerical tests to analysis the influence of particles on fluid and get a following effect between two phases. The model and the numerical method are validated through numerical tests to show its robustness and accuracy.

math.NA↗