arXiv subjects

Qing Chen

Publications and source records attributed to Qing Chen.

At least 37 records · Page 2Linked to original sources

arXiv2024

Beyond Numbers: Creating Analogies to Enhance Data Comprehension and Communication with Generative AI

Unfamiliar measurements usually hinder readers from grasping the scale of the numerical data, understanding the content, and feeling engaged with the context. To enhance data comprehension and communication, we leverage analogies to bridge the gap between abstract data and familiar measurements. In this work, we first conduct semi-structured interviews with design experts to identify design problems and summarize design considerations. Then, we collect an analogy dataset of 138 cases from various online sources. Based on the collected dataset, we characterize a design space for creating data analogies. Next, we build a prototype system, AnalogyMate, that automatically suggests data analogies, their corresponding design solutions, and generated visual representations powered by generative AI. The study results show the usefulness of AnalogyMate in aiding the creation process of data analogies and the effectiveness of data analogy in enhancing data comprehension and communication.

cs.HC↗

arXiv2023

The space of germs of extremal K\" ahler metrics in one dimension comprises three distinct ${\Bbb R}^3$ components

In the 1980s, Eugenio Calabi introduced the concept of {\it extremal K\" ahler metrics} as critical points of the $L^2$-norm functional of scalar curvature in the space of K\" ahler metrics belonging to a fixed Kähler class of a compact complex manifold $X$. Calabi demonstrated that extremal K\" ahler metrics always degenerate into Einstein metrics on compact Riemann surfaces. We define a Kähler metric $g$ on a domain of ${\Bbb C}^n$ as a {\it local extremal Kähler metric} of dimension $n$ if it satisfies the Euler-Lagrange equation of this functional, i.e. holomorphic is the $(1,0)$-part of the gradient vector field of the scalar curvature of $g$, in the domain. Our main result establishes that the space of all germs of local extremal, non-Einstein Kähler metrics of dimension one comprises three components, each diffeomorphic to ${\Bbb R}^3$.

math.DG↗

arXiv2023

Bi-gravity Portal Dark Matter

We consider a model where the interaction between dark matter and the Standard Model particles are mediated by a ghost-free bi-gravity portal. The bi-gravity model invokes a massive spin-2 particle coupled to the usual massless graviton as well as generic bi-metric matter couplings. The cross-sections for dark matter direct detection are computed and confronted with the experimental bounds. The presence of the massive spin-2 mediator resolves the core-cusp problem, which in turn significantly constrains the dark matter coupling in such a bi-gravity theory. Yet, there remains a window of the parameter space where the model can be tested in the upcoming direct detection experiments such as XENONnT and PandaX-30T. The model also predicts a reheating temperature of the order of $10^6$ GeV.

hep-ph↗

arXiv2023

General Heavy WIMP Nucleon Elastic Scattering

Heavy WIMP (weakly-interacting-massive-particle) effective field theory is used to compute the WIMP-nucleon scattering rate for general heavy electroweak multiplets through order $m_W/M$, where $m_W$ and $M$ denote the electroweak and WIMP mass scales. The lightest neutral component of such an electroweak multiplet is a candidate dark matter particle, either elementary or composite. Existing computations for certain representations of electroweak $\mathrm{SU(2)}_W\times \mathrm{U(1)}_Y$ reveal a cancellation of amplitudes from different effective operators at leading and subleading orders in $1/M$, yielding small cross sections that are below current dark matter direct detection experimental sensitivities. We extend those computations and consider all low-spin (spin-0, spin-1/2, spin-1, spin-3/2) heavy electroweak multiplets with arbitrary $\mathrm{SU(2)}_W\times \mathrm{U(1)}_Y$ representations and provide benchmark cross section results for dark matter direct detection experiments. For most self-conjugate TeV WIMPs with isospin $\le 3$, the cross sections are below current experimental limits but within reach of next-generation experiments. An exception is the case of pure electroweak doublet, where WIMPs are hidden below the neutrino floor.

hep-ph↗

arXiv2023

Calliope-Net: Automatic Generation of Graph Data Facts via Annotated Node-link Diagrams

Graph or network data are widely studied in both data mining and visualization communities to review the relationship among different entities and groups. The data facts derived from graph visual analysis are important to help understand the social structures of complex data, especially for data journalism. However, it is challenging for data journalists to discover graph data facts and manually organize correlated facts around a meaningful topic due to the complexity of graph data and the difficulty to interpret graph narratives. Therefore, we present an automatic graph facts generation system, Calliope-Net, which consists of a fact discovery module, a fact organization module, and a visualization module. It creates annotated node-link diagrams with facts automatically discovered and organized from network data. A novel layout algorithm is designed to present meaningful and visually appealing annotated graphs. We evaluate the proposed system with two case studies and an in-lab user study. The results show that Calliope-Net can benefit users in discovering and understanding graph data facts with visually pleasing annotated visualizations.

cs.HC↗

arXiv2023

Decoding the Mechanisms of Reversibility Loss in Rechargeable Zinc-Air Batteries

Attaining high reversibility of electrodes and electrolyte is essential for the longevity of secondary batteries. Rechargeable zinc-air batteries (RZABs), however, encounter drastic irreversible changes in the zinc anodes and air cathodes during cycling. To uncover the mechanisms of reversibility loss in RZABs, we investigate the evolution of zinc anode, alkaline electrolyte, and air electrode through experiments and first-principles calculations. Morphology diagrams of zinc anodes under versatile operating conditions reveal that the nano-sized mossy zinc dominates the later cycling stage. Such anodic change is induced by the increased zincate concentration due to hydrogen evolution, which is catalyzed by the mossy structure and results in oxide passivation on electrodes, and eventually leads to low true Coulombic efficiencies and short lifespans of batteries. Inspired by these findings, we finally present a novel overcharge-cycling protocol to compensate the Coulombic efficiency loss caused by hydrogen evolution and significantly extend the battery life.

cond-mat.mtrl-sci↗

arXiv2023

Urania: Visualizing Data Analysis Pipelines for Natural Language-Based Data Exploration

Exploratory Data Analysis (EDA) is an essential yet tedious process for examining a new dataset. To facilitate it, natural language interfaces (NLIs) can help people intuitively explore the dataset via data-oriented questions. However, existing NLIs primarily focus on providing accurate answers to questions, with few offering explanations or presentations of the data analysis pipeline used to uncover the answer. Such presentations are crucial for EDA as they enhance the interpretability and reliability of the answer, while also helping users understand the analysis process and derive insights. To fill this gap, we introduce Urania, a natural language interactive system that is able to visualize the data analysis pipelines used to resolve input questions. It integrates a natural language interface that allows users to explore data via questions, and a novel data-aware question decomposition algorithm that resolves each input question into a data analysis pipeline. This pipeline is visualized in the form of a datamation, with animated presentations of analysis operations and their corresponding data changes. Through two quantitative experiments and expert interviews, we demonstrated that our data-aware question decomposition algorithm outperforms the state-of-the-art technique in terms of execution accuracy, and that Urania can help people explore datasets better. In the end, we discuss the observations from the studies and the potential future works.

cs.HC↗

arXiv2023

Talk2Data: A Natural Language Interface for Exploratory Visual Analysis via Question Decomposition

Through a natural language interface (NLI) for exploratory visual analysis, users can directly "ask" analytical questions about the given tabular data. This process greatly improves user experience and lowers the technical barriers of data analysis. Existing techniques focus on generating a visualization from a concrete question. However, complex questions, requiring multiple data queries and visualizations to answer, are frequently asked in data exploration and analysis, which cannot be easily solved with the existing techniques. To address this issue, in this paper, we introduce Talk2Data, a natural language interface for exploratory visual analysis that supports answering complex questions. It leverages an advanced deep-learning model to resolve complex questions into a series of simple questions that could gradually elaborate on the users' requirements. To present answers, we design a set of annotated and captioned visualizations to represent the answers in a form that supports interpretation and narration. We conducted an ablation study and a controlled user study to evaluate Talk2Data's effectiveness and usefulness.

cs.HC↗

arXiv2023

Datamator: An Intelligent Authoring Tool for Creating Datamations via Data Query Decomposition

Datamation is designed to animate an analysis pipeline step by step, which is an intuitive and effective way to interpret the results from data analysis. However, creating a datamation is not easy. A qualified datamation needs to not only provide a correct analysis result but also ensure that the data flow and animation are coherent. Existing animation authoring tools focus on either leveraging algorithms to automatically generate an animation based on user-provided charts or building graphical user interfaces to provide a programming-free authoring environment for users. None of them are able to help users translate an analysis task into a series of data operations to form an analysis pipeline and visualize them as a datamation. To fill this gap, we introduce Datamator, an intelligent authoring tool developed to support datamation design and generation. It leverages a novel data query decomposition model to allow users to generate an initial datamation by simply inputting a data query in natural language. The initial datamation can be refined via rich interactions and a feedback mechanism is utilized to update the decomposition model based on user knowledge and preferences. Our system produces an animated sequence of visualizations driven by a set of low-level data actions. It supports unit visualizations, which provide a mapping from each data item to a unique visual mark. We demonstrate the effectiveness of Datamator via a series of evaluations including case studies, performance validation, and a controlled user study.

cs.HC↗

arXiv2023

How Does Automation Shape the Process of Narrative Visualization: A Survey of Tools

In recent years, narrative visualization has gained much attention. Researchers have proposed different design spaces for various narrative visualization genres and scenarios to facilitate the creation process. As users' needs grow and automation technologies advance, increasingly more tools have been designed and developed. In this study, we summarized six genres of narrative visualization (annotated charts, infographics, timelines & storylines, data comics, scrollytelling & slideshow, and data videos) based on previous research and four types of tools (design spaces, authoring tools, ML/AI-supported tools and ML/AI-generator tools) based on the intelligence and automation level of the tools. We surveyed 105 papers and tools to study how automation can progressively engage in visualization design and narrative processes to help users easily create narrative visualizations. This research aims to provide an overview of current research and development in the automation involvement of narrative visualization tools. We discuss key research problems in each category and suggest new opportunities to encourage further research in the related domain.

cs.HC↗

arXiv2022

Theory of QED radiative corrections to neutrino scattering at accelerator energies

Control over quantum electrodynamics (QED) radiative corrections is critical for precise determination of neutrino oscillation probabilities from observed (anti)neutrino detection rates. It is particularly important to understand any difference between such corrections for different flavors of (anti)neutrinos in charged-current interactions. We provide theoretical foundations for calculating these corrections. Using effective field theory, the corrections are shown to factorize into soft, collinear, and hard functions. The soft and collinear functions contain large logarithms in perturbation theory but are computable from QED. The hard function parametrizes hadronic structure but is free from large logarithms. Using a simple model for the hard function, we investigate the numerical impact of QED corrections in charged-current (anti)neutrino-nucleon elastic cross sections and cross-section ratios at GeV energies. We consider the implications of mass singularity theorems that govern the lepton-mass dependence of cross sections for sufficiently inclusive observables and demonstrate the cancellation of leading hadronic and nuclear corrections in phenomenologically relevant observables.

hep-ph↗

arXiv2022

The Chart Excites Me! Exploring How Data Visualization Design Influences Affective Arousal

As data visualizations have been increasingly applied in mass communication, designers often seek to grasp viewers immediately and motivate them to read more. Such goals, as suggested by previous research, are closely associated with the activation of emotion, namely affective arousal. Given this motivation, this work takes initial steps toward understanding the arousal-related factors in data visualization design. We collected a corpus of 265 data visualizations and conducted a crowdsourcing study with 184 participants during which the participants were asked to rate the affective arousal elicited by data visualization design (all texts were blurred to exclude the influence of semantics) and provide their reasons. Based on the collected data, first, we identified a set of arousal-related design features by analyzing user comments qualitatively. Then, we mapped these features to computable variables and constructed regression models to infer which features are significant contributors to affective arousal quantitatively. Through this exploratory study, we finally identified four design features (e.g., colorfulness, the number of different visual channels) cross-validated as important features correlated with affective arousal.

cs.HC↗

arXiv2022

On instability and stability of a quasi-linear hyperbolic-parabolic model for vasculogenesis

In this paper, we are concerned with the instability and stability of a quasi-linear hyperbolic-parabolic system modeling vascular networks. Under the assumption that the pressure satisfies $\frac{νP'(\barρ)}{γ\barρ} < β$, we first show that the steady-state is linear unstable (i.e., the linear solution grows in time in $L^2$) by constructing an unstable solution. Then based on the lower grow estimates on the solution to the linear system, we prove that the steady-state is nonlinear unstable in the sense of Hadamard. On the contrary, if the pressure satisfies $\frac{νP'(\barρ)}{γ\barρ} > β$, we establish the global existence for small perturbations and the optimal convergent rates for all-order derivatives of the solution by slightly getting rid of the condition proposed in [Liu-Peng-Wang, SIAM J. MATH. ANAL 54:1313--1346, 2022].

math.AP↗

arXiv2022

QED radiative corrections for accelerator neutrinos

Neutrino oscillation experiments at accelerator energies aim to establish charge-parity violation in the neutrino sector by measuring the energy-dependent rate of $ν_e$ appearance and $ν_μ$ disappearance in a $ν_μ$ beam. These experiments can precisely measure $ν_μ$ cross sections at near detectors, but $ν_e$ cross sections are poorly constrained and require theoretical inputs. In particular, quantum electrodynamics radiative corrections are different for electrons and muons. These corrections are proportional to the small quantum electrodynamics coupling $α\approx 1/137$; however, the large separation of scales between the neutrino energy and the proton mass ($\sim{\rm GeV}$), and the electron mass and soft-photon detection thresholds ($\sim{\rm MeV}$) introduces large logarithms in the perturbative expansion. The resulting flavor differences exceed the percent-level experimental precision and depend on nonperturbative hadronic structure. We establish a factorization theorem for exclusive charged-current (anti)neutrino scattering cross sections representing them as a product of two factors. The first factor is flavor universal; it depends on hadronic and nuclear structure and can be constrained by high-statistics $ν_μ$ data. The second factor is non-universal and contains logarithmic enhancements, but can be calculated exactly in perturbation theory. For charged-current elastic scattering, we demonstrate the cancellation of uncertainties in the predicted ratio of $ν_e$ and $ν_μ$ cross sections. We point out the potential impact of non-collinear energetic photons and the distortion of the visible lepton spectra and provide precise predictions for inclusive observables.

hep-ph↗

arXiv2022

VizBelle: A Design Space of Embellishments for Data Visualization

Visual embellishments, as a form of non-linguistic rhetorical figures, are used to help convey abstract concepts or attract readers' attention. Creating data visualizations with appropriate and visually pleasing embellishments is challenging since this process largely depends on the experience and the aesthetic taste of designers. To help facilitate designers in the ideation and creation process, we propose a design space, VizBelle, based on the analysis of 361 classified visualizations from online sources. VizBelle consists of four dimensions, namely, communication goal to fit user intention, object to select the target area, strategy and technique to offer potential approaches. We further provide a website to present detailed explanations and examples of various techniques. We conducted a within-subject study with 20 professional and amateur design enthusiasts to evaluate the effectiveness of our design space. Results show that our design space is illuminating and useful for designers to create data visualizations with embellishments.

cs.HC↗

arXiv2022

Network nonlocality sharing via weak measurements in the generalized star network configuration

Network nonlocality exhibits completely novel quantum correlations compared to standard quantum nonlocality. It has been shown that network nonlocality can be shared in a generalized bilocal scenario via weak measurements [Phys. Rev. A. 105, 042436 (2022)]. In this paper, we investigate network nonlocality sharing via weak measurements in a generalized star-shaped network configuration with arbitrary numbers of unbiased dichotomic input $k$, which includes $n$ branches and adds ($m$-1) more parties in each branch to the original star network $(n, m=1, k=2)$ scenario. It is shown that network nonlocality sharing among all observers can be revealed from simultaneous violation of $2^n$ inequalities in the ($n, m=2, k=2$) and ($n, m=2, k=3$) scenarios for any $n$ branches. The noise resistance of network nonlocality sharing with a precise noise model is also analyzed.

quant-ph↗

arXiv2022

Dynamic Spanning Trees for Connectivity Queries on Fully-dynamic Undirected Graphs (Extended version)

Answering connectivity queries is fundamental to fully dynamic graphs where edges and vertices are inserted and deleted frequently. Existing work proposes data structures and algorithms with worst-case guarantees. We propose a new data structure, the dynamic tree (D-tree), together with algorithms to construct and maintain it. The D-tree is the first data structure that scales to fully dynamic graphs with millions of vertices and edges and, on average, answers connectivity queries much faster than data structures with worst case guarantees.

cs.DS↗

arXiv2022

Authentication of quantum key distribution with post-quantum cryptography and replay attacks

With the development of quantum computers, traditional cryptographic systems are facing more and more serious security threats. Fortunately, quantum key distribution (QKD) and post-quantum cryptography (PQC) are two cryptographic mechanisms with quantum-resistant security, and both will become important solutions for future information security. However, neither of them is perfect, and they are complementary. Quantum key distribution has unconditional security that post-quantum cryptography does not have, and PQC can provide secure and convenient authentication for QKD networks. In this paper, we propose two protocols based on PQC to realize the full authentication of the QKD data post-processing, and we only need to assume the short-term security of PQC algorithm to ensure the long-term quantum resistant security of distributed keys. We found that for the above two authentication protocols, attackers cannot successfully implement replay attacks. These authentication protocols can solve the problems of the current pre-shared key authentication in the application of large-scale quantum key distribution networks, and are expected to realize a key distribution mechanism with practical operability and quantum resistant security, which will be beneficial to promote the deployment and application of quantum key distribution networks.

quant-ph↗