arXiv subjects

Jie Jian

Publications and source records attributed to Jie Jian.

14 recordsLinked to original sources

arXiv2026

Dynamic Latent Space Modeling of Inhomogeneous Poisson Network Processes with Applications to International Relations

We study continuous-time relational event data, where time-stamped dyadic interactions reflect both individual node propensities and evolving relational proximity. We propose a dynamic latent space model for inhomogeneous Poisson processes, where event intensities depend on node-specific activity parameters and time-varying latent distances modeled via flexible B-splines. We prove model identifiability by decoupling baseline activity from latent position, ensuring high interaction volumes do not warp the spatial map. For scalability, we develop a minibatch stochastic gradient algorithm with stable initialization and geometric anchoring, alongside an effective-degrees-of-freedom BIC for tuning model complexity. Simulations confirm accurate parameter recovery and out-of-sample prediction. Applied to cooperative diplomatic events among 60 major economies (1995--2022), the model uncovers shifting patterns of international cooperation and isolates mobile geopolitical actors from stationary institutional anchors.

stat.AP↗

arXiv2026

Bayesian Poisson-Randomized Gamma Tensor Factorization with Application to International Trade Flows

We study sparse semi-continuous tensor data with excess zeros, heavy right tails, and slice-specific dispersion. Such features arise naturally in monetary-valued multi-way data, such as international trade, where most exporter--importer--product--year cells are zero while positive values are continuous and highly variable. To model these data, we propose a Bayesian hierarchical tensor factorization model that places a low-rank CP structure on a latent Poisson rate tensor and couples it with a conditional Gamma model for positive outcomes, with rate parameters that can vary across slices within a mode. The model therefore separates the occurrence and magnitude of positive observations while borrowing strength across all tensor dimensions through a shared low-rank latent structure. To scale posterior inference to large arrays, we develop a hybrid variational--Monte Carlo algorithm that combines efficient coordinate ascent updates with a partially collapsed augmented-data sampler. Applied to approximately 60 million trade flows, the method surfaces multiway dependence across exporters, importers, products, and years that is difficult to recover from gravity-type or pairwise network analyses, which do not jointly model the product and temporal dimensions.

stat.ME↗

arXiv2025

Understanding the Impact of Seasonal Climate Change on Canada's Economy by Region and by Sector

To assess the impact of climate change on the Canadian economy, we investigate the relationship between seasonal climate variables and economic growth across provinces and economic sectors. We also provide projections of climate change impacts up to the year of 2050, taking into account the diverse climate change patterns and economic conditions across Canada. Our results indicate that rising Winter temperature anomalies have a notable adverse impact on Canadian economic growth. Province-wide, Quebec, Manitoba, and Ontario are anticipated to experience larger negative impacts, whereas British Columbia is less vulnerable. Industry-wide, Finance and Real Estate, Science and Technology, and Information, Culture and Recreation are consistently projected to see mild benefits, while adverse effects are predicted for Manufacturing, Agriculture, and Mining. The disparities of climate change effects between provinces and industries highlight the need for governments to tailor their policies accordingly, and offer targeted assistance to regions and industries that are particularly vulnerable in the face of climate change. Targeted approaches to climate change mitigation are likely to be more effective than one-size-fits-all policies for the whole economy.

stat.AP↗

arXiv2025

A Preliminary Survey of Semantic Descriptive Model for Images

Considering the lack of a unified framework for image description and deep cultural analysis at the subject level in the field of Ancient Chinese Paintings (ACP), this study utilized the Beijing Palace Museum's ACP collections to develop a semantic model integrating the iconological theory with a new workflow for term extraction and mapping. Our findings underscore the model's effectiveness. SDM can be used to support further art-related knowledge organization and cultural exploration of ACPs.

cs.DL↗

arXiv2024

Criteria for nilpotency of fusion systems

Let $p$ be an odd prime and let $\mathcal{F}$ be a fusion system over a finite $p$-group $P$. A fusion system $\mathcal{F}$ is said to be nilpotent if $\mathcal{F}=\mathcal{F}_{P}(P)$. In this paper we provide new criteria for saturated fusion systems $\mathcal{F}$ to be nilpotent, which can be viewed as extension of the $p$-nilpotency theorem of Glauberman and Thompson for fusion systems attributed to Kessar and Linckelmann.

math.GR↗

arXiv2024

The kernels of powers of linear operator via Weyr characteristic

The adjoint of a matrix in the Lie algebra associated with a matrix algebra is a fundamental operator, which can be generalized to a more general operator $φ_{AB}: X\rightarrow AX-XB$ by two matrices $A$ and $B$. The kernel of the operator is very well-known and it can be found in Gantmacher's book. The formulas for the dimensions of the kernels of arbitrary powers of the operator $φ_{AB}$ were given in terms of the Segre characteristics of these two matrices by the second and third authors in this paper and their collaborators. This paper provides an alternative approach to this problem via the Weyr characteristic in a more essential method. We obtain formulas for the dimensions of the kernels of arbitrary powers of the operator in terms of the Weyr characteristics. Furthermore, the basis for kernel of each power of the operator is described explicitly. As a consequence, for arbitrary square matrices $A$ and $B$ over an algebraically closed field, the dimension of the kernel of each power of the operator $φ_{A-λI,B}$ for eigenvalues $λ$ of $φ_{AB}$ can be viewed as a similarity invariant of the operator $φ_{AB}$, so we characterise the operator within similarity, which should be of interest to a number of people (including physicists).

math.RA↗

arXiv2023

Restricted Tweedie Stochastic Block Models

The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of non-negative zero-inflated continuous edge weights. To model the international trading network, where edge weights represent trading values between countries, we propose an innovative SBM based on a restricted Tweedie distribution. Additionally, we incorporate nodal information, such as the geographical distance between countries, and account for its dynamic effect on edge weights. Notably, we show that given a sufficiently large number of nodes, estimating this covariate effect becomes independent of community labels of each node when computing the maximum likelihood estimator of parameters in our model. This result enables the development of an efficient two-step algorithm that separates the estimation of covariate effects from other parameters. We demonstrate the effectiveness of our proposed method through extensive simulation studies and an application to real-world international trading data.

stat.ML↗

arXiv2023

Tunable Chirality-dependent Nonlinear Electrical Responses in 2D Tellurium

Tellurium (Te) is an elemental semiconductor with a simple chiral crystal structure. Te in a two-dimensional (2D) form synthesized by solution-based method shows excellent electrical, optical, and thermal properties. In this work, the chirality of hydrothermally grown 2D Te is identified and analyzed by hot sulfuric acid etching and high-angle tilted high-resolution scanning transmission electron microscopy. The gate-tunable nonlinear electrical responses, including the nonreciprocal electrical transport in the longitudinal direction and the nonlinear planar Hall effect in the transverse direction, are observed in 2D Te under a magnetic field. Moreover, the nonlinear electrical responses have opposite signs in left- and right-handed 2D Te due to the opposite spin polarizations ensured by the chiral symmetry. The fundamental relationship between the spin-orbit coupling and the crystal symmetry in two enantiomers provides a viable platform for realizing chirality-based electronic devices by introducing the chirality degree of freedom into electron transport.

cond-mat.mtrl-sci↗

arXiv2022

Effects of network topology and trait distribution on collective decision making

Social networks play an important role in analyzing the impact of individual-level interactions on societal or economic outcomes. We model interactive decision making for a community of individuals with different traits, represented by a social network with trait-attributed nodes. We develop a deterministic process generating a sequence of choices for each individual based on a trait-attributed social network, initial choices of individuals and a set of predetermined trait-dependent rules for making decisions. The object of interest is the sequence of cumulative sum of choices over all individuals, which we call the cumulative sequence and consider as an index of collective decisions. We observe that, in a time period, a cumulative sequence can be unpredictable or predictable showing a repeated pattern either escalating to an extreme or constantly oscillating. We consider that predictable cumulative sequences represent unstable collective decisions of communities either extremizing or internally conflicting, while unpredictable cumulative sequences show stable changes. We analyze the effects of network topology and trait distribution on the probability of cumulative sequences being predictable, escalating and oscillating by simulations. Our findings include that unstable collective decisions are more probable as network density increases, that centralized networks are more likely to have unstable collective decisions and that networks with excessively clustered or scattered conformists and rebels tend to produce unstable cumulative sequences. We discuss the potential of the model as a framework for studying individuals with different traits on a social network directly and indirectly interacting in decision making.

physics.soc-ph↗

arXiv2022

Two Gaussian regularization methods for time-varying networks

We model time-varying network data as realizations from multivariate Gaussian distributions with precision matrices that change over time. To facilitate parameter estimation, we require not only that each precision matrix at any given time point be sparse, but also that precision matrices at neighboring time points be similar. We accomplish this with two different algorithms, by generalizing the elastic net and the fused LASSO, respectively. Our main focuses are efficient computational algorithms and convenient degree-of-freedom formulae for choosing tuning parameters. We illustrate our methods with two simulation studies. By applying them to an fMRI data set, we also detect some interesting differences in brain connectivity between healthy individuals and ADHD patients.

stat.ME↗

arXiv2020

Raman Response and Transport Properties of One-Dimensional van der Waals Tellurium Nanowires

Tellurium can form nanowires of helical atomic chains. Given their unique one-dimensional van der Waals structure, these nanowires are expected to show remarkably different physical and electronic properties than bulk tellurium. Here we show that few-chain and single-chain van der Waals tellurium nanowires can be isolated using carbon nanotube and boron nitride nanotube encapsulation. With the approach, the number of atomic chains can be controlled by the inner diameter of the nanotube. The Raman response of the structures suggests that the interaction between a single-atomic tellurium chain and a carbon nanotube is weak, and that the inter-chain interaction becomes stronger as the number of chains increases. Compared with bare tellurium nanowires on SiO2, nanowires encapsulated in boron nitride nanotubes exhibit a dramatically enhanced current-carrying capacity, with a current density of 1.5*10^8 A cm-2, which exceeds that of most semiconducting nanowires. We also use our tellurium nanowires encapsulated in boron nitride nanotubes to create field-effect transistors that have a diameter of only 2 nm.

cond-mat.mes-hall↗

arXiv2020

A Ferroelectric Semiconductor Field-Effect Transistor

Ferroelectric field-effect transistors employ a ferroelectric material as a gate insulator, the polarization state of which can be detected using the channel conductance of the device. As a result, the devices are of potential to use in non-volatile memory technology, but suffer from short retention times, which limits their wider application. Here we report a ferroelectric semiconductor field-effect transistor in which a two-dimensional ferroelectric semiconductor, indium selenide (α-In2Se3), is used as the channel material in the device. α-In2Se3 was chosen due to its appropriate bandgap, room temperature ferroelectricity, ability to maintain ferroelectricity down to a few atomic layers, and potential for large-area growth. A passivation method based on the atomic-layer deposition of aluminum oxide (Al2O3) was developed to protect and enhance the performance of the transistors. With 15-nm-thick hafnium oxide (HfO2) as a scaled gate dielectric, the resulting devices offer high performance with a large memory window, a high on/off ratio of over 108, a maximum on-current of 862 μA μm-1, and a low supply voltage.

physics.app-ph↗

arXiv2019

Room Temperature Electrocaloric Effect in Layered Ferroelectric CuInP2S6 for Solid State Refrigeration

A material with reversible temperature change capability under an external electric field, known as the electrocaloric effect (ECE), has long been considered as a promising solid-state cooling solution. However, electrocaloric (EC) performance of EC materials generally is not sufficiently high for real cooling applications. As a result, exploring EC materials with high performance is of great interest and importance. Here, we report on the ECE of ferroelectric materials with van der Waals layered structure (CuInP2S6 or CIPS in this work in particular). Over 60% polarization charge change is observed within a temperature change of only 10 K at Curie temperature. Large adiabatic temperature change (|ΔT|) of 3.3 K, isothermal entropy change (|ΔS|) of 5.8 J kg-1 K-1 at |ΔE|=142.0 kV cm-1 at 315 K (above and near room temperature) are achieved, with a large EC strength (|ΔT|/|ΔE|) of 29.5 mK cm kV-1. The ECE of CIPS is also investigated theoretically by numerical simulation and a further EC performance projection is provided.

cond-mat.mtrl-sci↗

arXiv2017

Controlled Growth of a Large-Size 2D Selenium Nanosheet and Its Electronic and Optoelectronic Applications

Selenium has attracted intensive attention as a promising material candidate for future optoelectronic applications. However, selenium has a strong tendency to grow into nanowire forms due to its anisotropic atomic structure, which has largely hindered the exploration of its potential applications. In this work, using a physical vapor deposition method, we have demonstrated the synthesis of large-size, high-quality 2D selenium nanosheets, the minimum thickness of which could be as thin as 5 nm. The Se nanosheet exhibits a strong in-plane anisotropic property, which is determined by angle-resolved Raman spectroscopy. Back-gating field-effect transistors based on a Se nanosheet exhibit p-type transport behaviors with on-state current density around 20 mA/mm at Vds = 3 V. Four-terminal field effect devices are also fabricated to evaluate the intrinsic hole mobility of the selenium nanosheet, and the value is determined to be 0.26 cm2 Vs at 300 K. The selenium nanosheet phototransistors show an excellent photoresponsivity of up to 263 A/W, with a rise time of 0.1 s and fall time of 0.12 s. These results suggest that crystal selenium as a 2D form of a 1D van der Waals solid opens up the possibility to explore device applications.

cond-mat.mtrl-sci↗