arXiv subjects

Dachuan Chen

Publications and source records attributed to Dachuan Chen.

9 recordsLinked to original sources

arXiv2026

Glivenko--Cantelli Theorems for Integrated Volatility Functionals in Pure-Jump Semimartingales with an Application to Cryptocurrency Markets

We develop a two-step procedure for estimating integrated volatility functionals, defined through the occupation measure of the latent spot volatility process, when the asset price is a pure-jump semimartingale. In the first step, block-based estimators formed from absolute powers of high-frequency increments uniformly approximate local averages of powers of volatility. In the second step, these estimates are aggregated into an empirical occupation measure. Since price increments have infinite variance in this setting, arguments based on local Gaussianity are unavailable, and the uniform theory instead rests on maximal inequalities tailored to the stable regime. We establish Glivenko--Cantelli-type uniform consistency over classes of bounded monotone, Lipschitz-in-parameter, and locally H\"older test functions. These results deliver consistent estimation of volatility occupation times and quantiles, together with an argmax-consistency theory for $M$-estimators built on nonparametrically recovered latent processes. We further propose a stability-based rule for selecting the power index of the volatility estimator, which tracks an infeasible ex ante optimal choice closely in Monte Carlo experiments. An application to high-frequency cryptocurrency markets illustrates the framework in a jump-dominated, heavy-tailed environment.

math.ST↗

arXiv2026

Nonparametric inference for spot volatility in pure-jump semimartingales

We provide a comprehensive analysis of spot volatility inference in pure-jump semimartingales under two asymptotic settings: fixed-$k$, where each local window uses a fixed number of observations, and large-$k$, where this number grows with sampling frequency. For both active- and possibly inactive-jump settings, we derive generally nonstandard, typically non-Gaussian limit distributions and establish valid inference, including when the jump-activity index is consistently estimated. Simulations show that fixed-$k$ asymptotics offer markedly better finite-sample accuracy, underscoring their practical advantage for nonparametric spot volatility inference.

math.ST↗

arXiv2025

Temperature-driven structural phase transitions in SmNiO$_3$: insights from deep potential molecular dynamics simulations

The metal-insulator transition (MIT) in rare-earth nickelates exemplifies the intricate coupling between lattice dynamics and electronic effects. This strong interplay makes it challenging to disentangle their individual roles in driving the transition in RNiO3. Here, we isolate the structure response from electronic effect by employing molecular dynamics (MD) simulations based on a machine-learned interatomic potential. Taking SmNiO3 as a prototypical system, our simulations show that the structural phase transition is intrinsically temperature-driven and occurs spontaneously via collective lattice distortions. The simulated critical temperature is 340 K and can be further tuned by pressure. These findings provide atomistic insights into the understanding of structural evolution in triggering the phase transition and hence the MIT in RNiO3.

cond-mat.mtrl-sci↗

arXiv2023

Asymptotic Independence of the Quadratic form and Maximum of Independent Random Variables with Applications to High-Dimensional Tests

This paper establishes the asymptotic independence between the quadratic form and maximum of a sequence of independent random variables. Based on this theoretical result, we find the asymptotic joint distribution for the quadratic form and maximum, which can be applied into the high-dimensional testing problems. By combining the sum-type test and the max-type test, we propose the Fisher's combination tests for the one-sample mean test and two-sample mean test. Under this novel general framework, several strong assumptions in existing literature have been relaxed. Monte Carlo simulation has been done which shows that our proposed tests are strongly robust to both sparse and dense data.

stat.ME↗

arXiv2023

Rank Based Tests for High Dimensional White Noise

The development of high-dimensional white noise test is important in both statistical theories and applications, where the dimension of the time series can be comparable to or exceed the length of the time series. This paper proposes several distribution-free tests using the rank based statistics for testing the high-dimensional white noise, which are robust to the heavy tails and do not quire the finite-order moment assumptions for the sample distributions. Three families of rank based tests are analyzed in this paper, including the simple linear rank statistics, non-degenerate U-statistics and degenerate U-statistics. The asymptotic null distributions and rate optimality are established for each family of these tests. Among these tests, the test based on degenerate U-statistics can also detect the non-linear and non-monotone relationships in the autocorrelations. Moreover, this is the first result on the asymptotic distributions of rank correlation statistics which allowing for the cross-sectional dependence in high dimensional data.

math.ST↗

arXiv2023

Spatial-sign based High Dimensional White Noises Test

A spatial-sign based test procedure is proposed for high dimensional white noise test in this paper. We establish the limit null distribution and give the asymptotical relative efficient of our test with respect to the test proposed by Feng et al. (2022) under some special alternative hypothesis. Simulation studies also demonstrate the efficiency and robustness of our test for heavy-tailed distributions.

math.ST↗

arXiv2023

Topotactic-hydrogen forms chains in $AB$O$_2$ nickelate superconductors

Despite enormous experimental and theoretical efforts, obtaining generally accepted conclusions regarding the intrinsic magnetic and electronic properties of superconducting nickelates remains exceptionally challenging. Experiments show a significant degree of uncertainty, indicating hidden factors in the synthesized films, which call for further investigations. One of those "hidden factors" is the possibility of intercalating hydrogen during the chemical reduction process from Nd(La)NiO$_3$ to Nd(La)NiO$_2$ using CaH$_2$. While hydrogen has been detected in experimental samples, not much is known about its distribution through the crystal and its influence on the electronic environment. Here, we show the tendency toward the formation of one-dimensional hydrogen chains in infinite-layers LaNiO$_2$ superconductors using density-functional theory (DFT) supplemented by dynamical mean-field theory (DMFT). The formation of such hydrogen chains induces a coexistence of different oxidation states of Ni and competing magnetic phases, and possibly explains the recently observed charge order states in nickelate superconductors. Furthermore, it contributes to the difficulty of synthesizing homogeneous nickelates and determining their ground states. The smoking gun to detect excess hydrogen in nickelates are flat phonon modes, which are infrared active and quite insensitive to the exact arrangement of the H atoms.

cond-mat.mtrl-sci↗

arXiv2022

Magnetism in doped infinite-layer NdNiO2 studied by combined density functional theory and dynamical mean-field theory

The recent observation of superconductivity in infinite-layer nickelates has brought intense debate on the established knowledge of unconventional superconductivity based on the cuprates. Despite many similarities, the nickelates differ from the cuprates in many characteristics, the most notable one among which is the magnetism. Instead of a canonical antiferromagnetic Mott insulator as the undoped cuprates, from which the superconductivity is generally believed to arise upon doping, the undoped nickelates show no sign of magnetic ordering in experiments. Through a combined density functional theory, dynamical mean-field theory, and model study, we show that although the increased energy splitting between O-$p$ orbital and Cu/Ni-$d$ orbital ($Δ_{dp}$) results in larger magnetic moment in nickelates, it also leads to stronger antiferromagnetism/ferromagnetism competition, and weaker magnetic exchange coupling. Meanwhile, the self-doping effect caused by Nd-$d$ orbital screens the magnetic moment of Ni. The Janus-faced effect of $Δ_{dp}$ and self-doping effect together give a systematic understanding of magnetic behavior in nickelates and explain recent experimental observations.

cond-mat.supr-con↗

arXiv2019

Stacking tunable interlayer magnetism in bilayer CrI3

Diverse interlayer tunability of physical properties of two-dimensional layers mostly lies in the covalent-like quasi-bonding that is significant in electronic structures but rather weak for energetics. Such characteristics result in various stacking orders that are energetically comparable but may significantly differ in terms of electronic structures, e.g. magnetism. Inspired by several recent experiments showing interlayer anti-ferromagnetically coupled CrI3 bilayers, we carried out first-principles calculations for CrI3 bilayers. We found that the anti-ferromagnetic coupling results from a new stacking order with the C2/m space group symmetry, rather than the graphene-like one with R3 as previously believed. Moreover, we demonstrated that the intra- and inter-layer couplings in CrI3 bilayer are governed by two different mechanisms, namely ferromagnetic super-exchange and direct-exchange interactions, which are largely decoupled because of their significant difference in strength at the strong- and weak-interaction limits. This allows the much weaker interlayer magnetic coupling to be more feasibly tuned by stacking orders solely. Given the fact that interlayer magnetic properties can be altered by changing crystal structure with different stacking orders, our work opens a new paradigm for tuning interlayer magnetic properties with the freedom of stacking order in two dimensional layered materials.

cond-mat.mtrl-sci↗