arXiv subjects

Xinlong Du

Publications and source records attributed to Xinlong Du.

4 recordsLinked to original sources

arXiv2026

Magnetic Breakdown Reshapes Quantum Oscillations in Kagome Metals

Recent quantum-oscillation experiments on kagome metals have revealed markedly different phase offsets even among systems with nearly identical band structures and Fermi-surface geometries. Using a tight-binding model, we show that weak orbital hybridization can slightly modify the hybridization gaps. Small variations in these gaps can substantially alter the measured oscillation phase, despite leaving the overall electronic structure nearly unchanged. This phase shift originates from magnetic breakdown, which reconstructs cyclotron trajectories and can mask the nontrivial phase of an isolated orbit, yielding a trivial phase offset. Moreover, uniaxial strain can tune the relevant hybridization gaps and thereby weaken magnetic breakdown. This restores the nontrivial phase offset that magnetic breakdown otherwise masks, providing an experimentally accessible knob for controlling the oscillation phase. These results identify magnetic breakdown as the key mechanism controlling the phase shift and provide a plausible explanation for recent experimental phase discrepancies in kagome metals.

cond-mat.mes-hall↗

arXiv2026

Neural Diffusion Intensity Models for Point Process Data

Cox processes model overdispersed point process data via a latent stochastic intensity, but both nonparametric estimation of the intensity model and posterior inference over intensity paths are typically intractable, relying on expensive MCMC methods. We introduce Neural Diffusion Intensity Models, a variational framework for Cox processes driven by neural SDEs. Our key theoretical result, based on enlargement of filtrations, shows that conditioning on point process observations preserves the diffusion structure of the latent intensity with an explicit drift correction. This guarantees the variational family contains the true posterior, so that ELBO maximization coincides with maximum likelihood estimation under sufficient model capacity. We design an amortized encoder architecture that maps variable-length event sequences to posterior intensity paths by simulating the drift-corrected SDE, replacing repeated MCMC runs with a single forward pass. Experiments on synthetic and real-world data demonstrate accurate recovery of latent intensity dynamics and posterior paths, with orders-of-magnitude speedups over MCMC-based methods.

cs.LG↗

arXiv2025

Effect of Spin-Orbit Coupling on Anomalous Quantum Oscillations in InAs/GaSb Quantum Wells

We theoretically study the effect of spin-orbit coupling (SOC) on anomalous quantum oscillations in InAs/GaSb quantum wells. By comparing different cases, we show that SOC induces two opposing effects on anomalous quantum oscillations: it suppresses the oscillations in the clean case, while enhancing them in the disordered case. Using an effective model, we analyze in detail the origins of anomalous oscillations in both clean and disordered cases. Based on these origins, we explain why SOC suppresses or enhances the anomalous oscillations in different cases, thereby extending the understanding of the conventional theory. Moreover, in the disordered case, SOC can induce a phase shift of the anomalous oscillations. We further identify a parameter window where the anomalous oscillations are significantly enhanced in the presence of both disorder and SOC. These results provide a theoretical basis for understanding the role of SOC in anomalous quantum oscillations.

cond-mat.mes-hall↗

arXiv2024

Renewal Processes Represented as Doubly Stochastic Poisson Processes

This paper gives an elementary proof for the following theorem: a renewal process can be represented by a doubly-stochastic Poisson process (DSPP) if and only if the Laplace-Stieltjes transform of the inter-arrival times is of the following form: $$ϕ(θ)=λ\left[λ+θ+k\int_0^\infty\left(1-e^{-θz}\right)\,dG(z)\right]^{-1},$$ for some positive real numbers $λ, k$, and some distribution function $G$ with $G(\infty)=1$. The intensity process $Λ(t)$ of the corresponding DSPP jumps between $λ$ and $0$, with the time spent at $λ$ being independent random variables that are exponentially distributed with mean $1/k$, and the time spent at $0$ being independent random variables with distribution function $G$.

math.PR↗