arXiv subjects

Miao Tian

Publications and source records attributed to Miao Tian.

12 recordsLinked to original sources

arXiv2026

Separation of bi-dispersed microspheres in dusty plasma ratchet experiments

It is demonstrated experimentally that the effective separation of bi-dispersed microspheres (dust particles) in the underdamped and strongly-coupled regime is realized using a designed dusty plasma ratchet. Experimental findings reveal that these dust particles can undergo directional transport at varying speeds, even moving in opposite directions depending on the discharge conditions, enabling successful particle separation. Numerical simulations of the plasma environment surrounding the dust particles are performed using fluid simulations of the capacitively coupled discharge of Argon. The simulation results indicate that the bi-dispersed dust particles are suspended at different balance heights within the plasma sheath and experience distinct ratchet potentials that govern their directional transport, resulting in varied flow velocities. The discovery of height-dependent transport of dust particles here provides insights of transport fundamental of underdamped strongly-coupled particles in dusty plasma ratchets.

physics.plasm-ph↗

arXiv2025

Revisiting the Li abundances of Stars with and without Detected Planets from the High Resolution Spectroscopy

Whether the presence of planets affects the lithium (Li) abundance of their host stars is still an open question. To investigate the difference of the Li abundance between planet-host stars (HS) and isolated stars (IS) with no detected planets, we analyze a large sample of stars with temperatures ranging from 4600 to 6600 K and metallicity ranging from -0.55 to +0.50. The sample consists of 279 HS whose spectra were taken from the California-Kepler Survey (CKS), which followed up planets detected by Kepler, and 171 IS whose spectra were taken from the Keck archive. The non-local thermodynamic equilibrium (non-LTE) effects were taken into consideration. It is found that the distribution of Li abundances in both the HS and IS groups are generally consistent with each other. This suggests that the presence of Kepler-like planets does not have a significant impact on Li depletion. We also found that the non-LTE corrections can not be neglected for stars with A(Li) over ~ 2.5 dex.

astro-ph.SR↗

arXiv2025

Cavity magnon-polariton interface for strong spin-spin coupling

Strong coupling between single qubits is crucial for quantum information science and quantum computation. However, it is still challenged, especially for single solid-state qubit. Here, we propose a hybrid quantum system, consisting of a coplanar waveguide (CPW) resonator weakly coupled to a single nitrogen-vacancy spin in diamond and a yttrium-iron-garnet (YIG) nanosphere holding Kerr magnons, to realize strong long-distance spin-spin coupling. With a strong driving field on magnons, the Kerr effect can squeeze magnons, and {thus the coupling between the CPW resonator and the sequeezed magnons is exponentially enhanced}, which produces two cavity-magnon polaritons, i.e., the high-frequency polariton (HP) and low-frequency polariton (LP). When the enhanced cavity-magnon coupling {approaches} the critical value (i.e., the frequency of the LP becomes zero), the spin is fully decoupled from the HP, while the coupling between the spin and the LP is significantly improved. In the dispersive regime, a strong spin-spin coupling mediated by the LP is achieved with accessible parameters. Our proposal indicates that the critical cavity-magnon polarition is a potential interface to realize strong spin-spin coupling and manipulates remote solid spins.

quant-ph↗

arXiv2024

AI-Driven Anonymization: Protecting Personal Data Privacy While Leveraging Machine Learning

The development of artificial intelligence has significantly transformed people's lives. However, it has also posed a significant threat to privacy and security, with numerous instances of personal information being exposed online and reports of criminal attacks and theft. Consequently, the need to achieve intelligent protection of personal information through machine learning algorithms has become a paramount concern. Artificial intelligence leverages advanced algorithms and technologies to effectively encrypt and anonymize personal data, enabling valuable data analysis and utilization while safeguarding privacy. This paper focuses on personal data privacy protection and the promotion of anonymity as its core research objectives. It achieves personal data privacy protection and detection through the use of machine learning's differential privacy protection algorithm. The paper also addresses existing challenges in machine learning related to privacy and personal data protection, offers improvement suggestions, and analyzes factors impacting datasets to enable timely personal data privacy detection and protection.

cs.CR↗

arXiv2024

The Random Forest Model for Analyzing and Forecasting the US Stock Market in the Context of Smart Finance

The stock market is a crucial component of the financial market, playing a vital role in wealth accumulation for investors, financing costs for listed companies, and the stable development of the national macroeconomy. Significant fluctuations in the stock market can damage the interests of stock investors and cause an imbalance in the industrial structure, which can interfere with the macro level development of the national economy. The prediction of stock price trends is a popular research topic in academia. Predicting the three trends of stock pricesrising, sideways, and falling can assist investors in making informed decisions about buying, holding, or selling stocks. Establishing an effective forecasting model for predicting these trends is of substantial practical importance. This paper evaluates the predictive performance of random forest models combined with artificial intelligence on a test set of four stocks using optimal parameters. The evaluation considers both predictive accuracy and time efficiency.

q-fin.TR↗

arXiv2024

Optimizing Portfolio Management and Risk Assessment in Digital Assets Using Deep Learning for Predictive Analysis

Portfolio management issues have been extensively studied in the field of artificial intelligence in recent years, but existing deep learning-based quantitative trading methods have some areas where they could be improved. First of all, the prediction mode of stocks is singular; often, only one trading expert is trained by a model, and the trading decision is solely based on the prediction results of the model. Secondly, the data source used by the model is relatively simple, and only considers the data of the stock itself, ignoring the impact of the whole market risk on the stock. In this paper, the DQN algorithm is introduced into asset management portfolios in a novel and straightforward way, and the performance greatly exceeds the benchmark, which fully proves the effectiveness of the DRL algorithm in portfolio management. This also inspires us to consider the complexity of financial problems, and the use of algorithms should be fully combined with the problems to adapt. Finally, in this paper, the strategy is implemented by selecting the assets and actions with the largest Q value. Since different assets are trained separately as environments, there may be a phenomenon of Q value drift among different assets (different assets have different Q value distribution areas), which may easily lead to incorrect asset selection. Consider adding constraints so that the Q values of different assets share a Q value distribution to improve results.

q-fin.CP↗

arXiv2022

Strong Long-Range Spin-Spin Coupling via a Kerr Magnon Interface

Strong long-range coupling between distant spins is crucial for spin-based quantum information processing. However, achieving such a strong spin-spin coupling remains challenging. Here we propose to realize a strong coupling between two distant spins via the Kerr effect of magnons in a yttrium-iron-garnet nanosphere. By applying a microwave field on this nanosphere, the Kerr effect of magnons can induce the magnon squeezing, so that the coupling between the spin and the squeezed magnons can be exponentially enhanced. This in turn allows the spin-magnon distance to increase from nano- to micrometer scale. By considering the virtual excitation of the squeezed magnons in the dispersive regime, strong spin-spin coupling mediated by the squeezed magnons can be achieved, and a remote quantum-state transfer, as well as the nonlocal two-qubit ISWAP gate with high fidelity becomes implementable. Our approach offers a feasible scheme to perform quantum information processing among distant spins.

quant-ph↗

arXiv2021

Improving auto-encoder novelty detection using channel attention and entropy minimization

Novelty detection is a important research area which mainly solves the classification problem of inliers which usually consists of normal samples and outliers composed of abnormal samples. Auto-encoder is often used for novelty detection. However, the generalization ability of the auto-encoder may cause the undesirable reconstruction of abnormal elements and reduce the identification ability of the model. To solve the problem, we focus on the perspective of better reconstructing the normal samples as well as retaining the unique information of normal samples to improve the performance of auto-encoder for novelty detection. Firstly, we introduce attention mechanism into the task. Under the action of attention mechanism, auto-encoder can pay more attention to the representation of inlier samples through adversarial training. Secondly, we apply the information entropy into the latent layer to make it sparse and constrain the expression of diversity. Experimental results on three public datasets show that the proposed method achieves comparable performance compared with previous popular approaches.

cs.CV↗

arXiv2016

Wavemaker theories for acoustic-gravity waves over a finite depth

Acoustic-gravity waves (hereafter AGWs) in ocean have received much interest recently, mainly with respect to early detection of tsunamis as they travel at near the speed of sound in water which makes them ideal candidates for early detection of tsunamis. While the generation mechanisms of AGWs have been studied from the perspective of vertical oscillations of seafloor and triad wave-wave interaction, in the current study we are interested in their generation by wave-structure interaction with possible implication to the energy sector. Here, we develop two wavemaker theories to analyze different wave modes generated by impermeable (the classic Havelock's theory) and porous (porous wavemaker theory) plates in weakly compressible fluids. Slight modification has been made to the porous theory so that, unlike the previous theory, the new solution depends on the geometry of the plate. The expressions for three different types of plates (piston, flap, delta-function) are introduced. Analytical solutions are also derived for the potential amplitude of the gravity, acoustic-gravity, evanescent waves, as well as the surface elevation, velocity distribution, and pressure for AGWs. Both theories reduce to previous results for incompressible flow when the compressibility is neglected. We also show numerical examples for AGWs generated in a wave flume as well as in deep ocean. Our current study sets the theoretical background towards remote sensing by AGWs, for optimized deep ocean wave-power harnessing, among others.

physics.flu-dyn↗

arXiv2015

Effects of high-order operators in non-relativistic Lifshitz holography

In this paper, we study the effects of high-order operators on the non-relativistic Lifshitz holography in the framework of the Hořava-Lifshitz (HL) theory of gravity, which naturally contains high-order operators in order for the theory to be power-counting renormalizble, and provides an ideal place for such studies. In particular, we show that the Lifshitz space-time is still a solution of the full theory of the HL gravity. The effects of the high-oder operators on the space-time itself is simply to shift the Lifshitz dynamical exponent. However, while in the infrared the asymptotic behavior of a (probe) scalar field near the boundary is similar to that studied in the literature, it gets dramatically modified in the UV limit, because of the presence of the high-order operators in this regime. Then, according to the gauge/gravity duality, this in turn affects the two-point correlation functions.

hep-th↗

arXiv2015

Gravitational collapse and formation of universal horizons

In this paper, we first generalize the definition of stationary universal horizons to dynamical ones, and then show that (dynamical) universal horizons can be formed from realistic gravitational collapse. This is done by constructing analytical models of a collapsing spherically symmetric star with finite thickness in Einstein-aether theory.

gr-qc↗

arXiv2014

On The Quasi-streamfunction Formalism for Waves and Vorticity

The quasi-streamfunction (Psi) formalism proposed by Kim et. al. (J.W. Kim, K.J. Bai, R.C. Ertekin, W.C. Webster, J. Eng. Math. 40, 17 (2001)) provides a natural framework for systematically studying zero-vorticity waves over arbitrary bathymetry. The modified Psi-formalism developed here discards the original constraints of zero-vorticity by allowing for vertical vorticity which is the case of most interest for coastal dynamics. The problem is reformulated in terms of two dynamical equations on the boundary supplemented by one equation that represents a kinematic constraint in the interior of the domain. In this framework, the kinematic constraint can be solved to express Psi in terms of canonically-conjugated variables. The formalism is demonstrated for horizontally homogeneous flows over mild topography, where asymptotic formulations for the Hamiltonian and Lagrangian functions are derived based on the Helmholz-Hodge decomposition. For potential flows, the asymptotic form of the Hamiltonian is identical to previous results. The Lagrangian function is also expressed as an expansion in terms of the surface height and its time derivative and compared with Zakharov's formalism where agreement is found for one-dimensional wave scattering.

physics.flu-dyn↗