arXiv subjects

Qiang Gao

Publications and source records attributed to Qiang Gao.

At least 91 records · Page 5Linked to original sources

arXiv2022

Semiclassical dynamics of electrons in space-time crystal: Magnetization, polarization, and current response

A space-time crystal is defined as a quantum mechanical system with both spatial and temporal periodicity. Such a system can be described by the Floquet-Bloch (FB) theory. We first formulate a semiclassical theory by constructing a wave-packet through the superposition of the FB wave functions and derive the equations of motion of FB electrons subjected to slowly varying external fields (not to be confused with the fast-changing Floquet drive), revealing behaviors similar to ordinary Bloch electrons but with quantities modified in the Floquet context. Specifically, we study local magnetic moment due to the self-rotation of the wave-packet, a contribution to total magnetization from the Berry curvature in k-space, and the polarization of a fully occupied FB band. Based on the semiclassical theory, we can also show the fingerprint of the energy flow in such an energy-non-conserved system. We then discuss the density matrix of a FB system attached to a thermal bath, which allows us to investigate quantities involving many electrons in the non-interacting limit. As an application, we calculate the intrinsic current response in an oblique spacetime metal showing the non-equilibrium nature of the FB system. The current response can also be related to the acoustoelectric effect. Overall, we develop a systematic approach for studying space-time crystals and provide a powerful tool to explore the electronic properties of this exotic system with coupled space and time.

cond-mat.mes-hall↗

arXiv2022

Predicting Human Mobility via Self-supervised Disentanglement Learning

Deep neural networks have recently achieved considerable improvements in learning human behavioral patterns and individual preferences from massive spatial-temporal trajectories data. However, most of the existing research concentrates on fusing different semantics underlying sequential trajectories for mobility pattern learning which, in turn, yields a narrow perspective on comprehending human intrinsic motions. In addition, the inherent sparsity and under-explored heterogeneous collaborative items pertaining to human check-ins hinder the potential exploitation of human diverse periodic regularities as well as common interests. Motivated by recent advances in disentanglement learning, in this study we propose a novel disentangled solution called SSDL for tackling the next POI prediction problem. SSDL primarily seeks to disentangle the potential time-invariant and time-varying factors into different latent spaces from massive trajectories data, providing an interpretable view to understand the intricate semantics underlying human diverse mobility representations. To address the data sparsity issue, we present two realistic trajectory augmentation approaches to enhance the understanding of both the human intrinsic periodicity and constantly-changing intents. In addition, we devise a POI-centric graph structure to explore heterogeneous collaborative signals underlying historical check-ins. Extensive experiments conducted on four real-world datasets demonstrate that our proposed SSDL significantly outperforms the state-of-the-art approaches -- for example, it yields up to 8.57% improvements on ACC@1.

cs.LG↗

arXiv2022

High-Fidelity Simulation and Novel Data Analysis of the Bubble Creation and Sound Generation Processes in Breaking Waves

Recent increases in computing power have enabled the numerical simulation of many complex flow problems that are of practical and strategic interest for naval applications. A noticeable area of advancement is the computation of turbulent, two-phase flows resulting from wave breaking and other multiphase flow processes such as cavitation that can generate underwater sound and entrain bubbles in ship wakes, among other effects. Although advanced flow solvers are sophisticated and are capable of simulating high Reynolds number flows on large numbers of grid points, challenges in data analysis remain. Specifically, there is a critical need to transform highly resolved flow fields described on fine grids at discrete time steps into physically resolved features for which the flow dynamics can be understood and utilized in naval applications. This paper presents our recent efforts in this field. In previous works, we developed a novel algorithm to track bubbles in breaking wave simulations and to interpret their dynamical behavior over time (Gao et al., 2021a). We also discovered a new physical mechanism driving bubble production within breaking wave crests (Gao et al., 2021b) and developed a model to relate bubble behaviors to underwater sound generation (Gao et al., 2021c). In this work, we applied our bubble tracking algorithm to the breaking waves simulations and investigated the bubble trajectories, bubble creation mechanisms, and bubble acoustics based on our previous works.

physics.flu-dyn↗

arXiv2022

Untwisting moiré physics: Almost ideal bands and fractional Chern insulators in periodically strained monolayer graphene

Moiré systems have emerged in recent years as a rich platform to study strong correlations. Here, we will discuss a simple, experimentally feasible setup based on periodically strained graphene that reproduces several key aspects of twisted moiré heterostructures -- but without introducing a twist. We consider a monolayer graphene sheet subject to a $C_2$-breaking periodic strain-induced psuedomagnetic field (PMF) with period $L_M \gg a$, along with a scalar potential of the same period. This system has {\it almost ideal} flat bands with valley-resolved Chern number $\pm 1$, where the deviation from ideal band geometry is analytically controlled and exponentially small in the dimensionless ratio $(L_M/l_B)^2$ where $l_B$ is the magnetic length corresponding to the maximum value of the PMF. Moreover, the scalar potential can tune the bandwidth far below the Coulomb scale, making this a very promising platform for strongly interacting topological phases. Using a combination of strong-coupling theory and self-consistent Hartree fock, we find quantum anomalous Hall states at integer fillings. At fractional filling, exact diagonaliztion reveals a fractional Chern insulator at parameters in the experimentally feasible range. Overall, we find that this system has larger interaction-induced gaps, smaller quasiparticle dispersion, and enhanced tunability compared to twisted graphene systems, even in their ideal limit.

cond-mat.mes-hall↗

arXiv2022

Incorporating Interactive Facts for Stock Selection via Neural Recursive ODEs

Stock selection attempts to rank a list of stocks for optimizing investment decision making, aiming at minimizing investment risks while maximizing profit returns. Recently, researchers have developed various (recurrent) neural network-based methods to tackle this problem. Without exceptions, they primarily leverage historical market volatility to enhance the selection performance. However, these approaches greatly rely on discrete sampled market observations, which either fail to consider the uncertainty of stock fluctuations or predict continuous stock dynamics in the future. Besides, some studies have considered the explicit stock interdependence derived from multiple domains (e.g., industry and shareholder). Nevertheless, the implicit cross-dependencies among different domains are under-explored. To address such limitations, we present a novel stock selection solution -- StockODE, a latent variable model with Gaussian prior. Specifically, we devise a Movement Trend Correlation module to expose the time-varying relationships regarding stock movements. We design Neural Recursive Ordinary Differential Equation Networks (NRODEs) to capture the temporal evolution of stock volatility in a continuous dynamic manner. Moreover, we build a hierarchical hypergraph to incorporate the domain-aware dependencies among the stocks. Experiments conducted on two real-world stock market datasets demonstrate that StockODE significantly outperforms several baselines, such as up to 18.57% average improvement regarding Sharpe Ratio.

q-fin.ST↗

arXiv2022

Electronic Origin of High-Tc Maximization and Persistence in Trilayer Cuprate Superconductors

In high temperature cuprate superconductors, it was found that the superconducting transition temperature Tc depends on the number of CuO2 planes (n) in the structural unit and the maximum Tc is realized in the trilayer system (n=3). It was also found that the trilayer superconductors exhibit an unusual phase diagram that Tc keeps nearly constant in the overdoped region which is in strong contrast to the Tc decrease usually found in other cuprate superconductors. The electronic origin of the Tc maximization in the trilayer superconductors and its high Tc persistence in the overdoped region remains unclear. By taking high resolution laser-based angle resolved photoemission (ARPES) measurements, here we report our revelation of the microscopic origin of the unusual superconducting properties in the trilayer superconductors. For the first time we have observed the trilayer splitting in Bi2Sr2Ca2Cu3O10+d (Bi2223) superconductor. The observed Fermi surface, band structures, superconducting gap and the selective Bogoliubov band hybridizations can be well described by a three-layer interaction model. Quantitative information of the microscopic processes involving intra- and interlayer hoppings and pairings are extracted. The electronic origin of the maximum Tc in Bi2223 and the persistence of the high Tc in the overdoped region is revealed. These results provide key insights in understanding high Tc superconductivity and pave a way to further enhance Tc in the cuprate superconductors.

cond-mat.supr-con↗

arXiv2022

Magnetic Excitations in Strained Infinite-layer Nickelate PrNiO2

Strongly correlated materials often respond sensitively to the external perturbations. In the recently discovered superconducting infinite-layer nickelates, the superconducting transition temperature can be dramatically enhanced via only ~1% compressive strain-tuning enabled by substrate design. However, the root of such enhancement remains elusive. While the superconducting pairing mechanism is still not settled, magnetic Cooper pairing - similar to the cuprates has been proposed. Using resonant inelastic x-ray scattering, we investigate the magnetic excitations in infinite-layer PrNiO2 thin films for different strain conditions. The magnon bandwidth of PrNiO2 shows only marginal response to strain-tuning, in sharp contrast to the striking enhancement of the superconducting transition temperature Tc in the doped superconducting samples. These results suggest the enhancement of Tc is not mediated by spin excitations and thus provide important empirics for the understanding of superconductivity in infinite-layer nickelates.

cond-mat.supr-con↗

arXiv2022

Symmetry Origin of Lattice Vibration Modes in Twisted Multilayer Graphene: Phasons vs Moiré Phonons

Lattice dynamics play a crucial role in the physics of Moiré systems. In twisted bilayer graphene (TBG), it was shown that, in addition to the graphene phonons, there is another set of gapless excitations termed Moiré Phonons [Phys. Rev. B, 075416, 2019] reflecting the lattice dynamics at the Moire superlattice level. These modes were later suggested to be phasons due to the incommensurate stacking of the two graphene layers [Phys. Rev. B, 155426, 2019]. In this work, we elucidate the equivalence of these two seemingly distinct perspectives by identifying an underlying symmetry, which we dub mismatch symmetry, that exists for any twist angle. For commensurate angles, this is a discrete symmetry whereas for incommensurate angles, it is equivalent to a continuous phase symmetry giving rise to phason modes. In the small angle limit, such symmetry becomes a continuous local symmetry whose spontaneous breaking gives rise to Moiré phonons as its Goldstone mode. We derive an effective field theory for these collective modes in TBG in precise agreement with the full model and discuss their different properties. Our analysis is then generalized to twisted multilayer graphene (TMG) where we identify higher order mismatch and deduce the count of gapless modes including graphene phonons, Moiré phonons and phasons. Especially, we study twisted mirror-symmetric trilayer graphene with an alternating twist angle $θ$ and find that it can be mapped to a TBG with the re-scaled twist angle $\sqrt{2/3}θ$, hosting the same Moiré phonon modes in the even mirror sector with an additional set of gapped modes in the odd sector. Our work presents a systematic study of lattice symmetries in TMG providing insights into its unique lattice dynamics.

cond-mat.mes-hall↗

arXiv2022

PMUSpill: The Counters in Performance Monitor Unit that Leak SGX-Protected Secrets

Performance Monitor Unit (PMU) is a significant hardware module on the current processors, which counts the events launched by processor into a set of PMU counters. Ideally, the events triggered by instructions that are executed but the results are not successfully committed (transient execution) should not be recorded. However, in this study, we discover that some PMU events triggered by the transient execution instructions will actually be recorded by PMU. Based on this, we propose the PMUSpill attack, which enables attackers to maliciously leak the secret data that are loaded during transient executions. The biggest challenge is how to encode the secret data into PMU events. We construct an instruction gadget to solve this challenge, whose execution path that can be identified by PMU counters represents what values the secret data are. We successfully implement the PMUSpill attack to leak the secret data stored in Intel Software Guard Extensions (SGX) (a Trusted Execution Environment (TEE) in the Intel's processors) through real experiments. Besides, we locate the vulnerable PMU counters and their trigger instructions by iterating all the valid PMU counters and instructions. The experiment results demonstrate that there are up to 20 PMU counters available to implement the PMUSpill attack. We also provide some possible hardware and software-based countermeasures for addressing the PMUSpill attack, which can be utilized to enhance the security of processors in future.

cs.CR↗

arXiv2022

Conservation of the particle-hole symmetry in the pseudogap state in optimally-doped Bi2Sr2CuO6+δ superconductor

The pseudogap state is one of the most enigmatic characteristics in the anomalous normal state properties of the high temperature cuprate superconductors. A central issue is to reveal whether there is a symmetry breaking and which symmetries are broken across the pseudogap transition. By performing high resolution laser-based angle-resolved photoemission measurements on the optimally-doped Bi2Sr1.6La0.4CuO6+δ superconductor, we report the observations of the particle-hole symmetry conservation in both the superconducting state and the pseudogap state along the entire Fermi surface. These results provide key insights in understanding the nature of the pseudogap and its relation with high temperature superconductivity.

cond-mat.supr-con↗

arXiv2022

Forgetting Prevention for Cross-regional Fraud Detection with Heterogeneous Trade Graph

With the booming growth of e-commerce, detecting financial fraud has become an urgent task to avoid transaction risks. Despite the successful applications of Graph Neural Networks (GNNs) in fraud detection, the existing solutions are only suitable for a narrow scope due to the limitation in data collection. Especially when expanding a business into new territory, e.g., new cities or new countries, developing a totally new model will bring the cost issue and result in forgetting previous knowledge. Moreover, recent works strive to devise GNNs to expose the implicit interactions behind financial transactions. However, most existing GNNs-based solutions concentrate on either homogeneous graphs or decomposing heterogeneous interactions into several homogeneous connections for convenience. To this end, this study proposes a novel solution based on heterogeneous trade graphs, namely HTG-CFD, to prevent knowledge forgetting of cross-regional fraud detection. In particular, the heterogeneous trade graph (HTG) is meticulously constructed from original transaction records to explore the complex semantics among different types of entities and relationships. And motivated by recent continual learning, we present a practical and task-oriented forgetting prevention method to alleviate knowledge forgetting in the context of cross-regional detection. Extensive experiments demonstrate that the proposed HTG-CFD not only promotes the performance in cross-regional scenarios but also significantly contributes to single-regional fraud detection.

cs.CE↗

arXiv2022

Turbulence-free computational ghost imaging

Turbulence-free images cannot be produced by conventional computational ghost imaging because calculated light is not affected by the same atmospheric turbulence as real light. In this article, we first addressed this issue by measuring the photon number fluctuation autocorrelation of the signals generated by a conventional computational ghost imaging device. Our results illustrate how conventional computational ghost imaging without structural changes can be used to produce turbulence-free images.

physics.optics↗

arXiv2022

Strain-induced enhancement of $T_c$ in infinite-layer Pr$_{0.8}$Sr$_{0.2}$NiO$_2$ films

The mechanism of unconventional superconductivity in correlated materials remains a great challenge in condensed matter physics. The recent discovery of superconductivity in infinite-layer nickelates, as analog to high-Tc cuprates, has opened a new route to tackle this challenge. By growing 8 nm Pr0.8Sr0.2NiO2 films on the (LaAlO3)0.3(Sr2AlTaO6)0.7 substrate, we successfully raise the transition temperature Tc from 9 K in the widely studied SrTiO3-substrated nickelates into 15 K. By combining x-ray absorption spectroscopy with the first-principles and many-body simulations, we find a positive correlation between Tc and the pre-edge peak intensity, which can be attributed to the hybridization between Ni and O orbitals induced by the strain. Our result suggests that structural engineering can further enhance unconventional superconductivity, and the charge-transfer property plays a crucial role in the pairing strength.

cond-mat.supr-con↗

arXiv2022

DC Current Generation and Power Feature in Strongly Driven Floquet-Bloch Systems

We study the DC current generation in a periodically driven Bloch system connected to a heat bath. Under a relaxation time approximation, the density matrix for such a system is obtained, which is related to two equilibria: a Floquet quasi-equilibrium where the density matrix is diagonal under the Floquet-Bloch eigenbasis and an instantaneous Bloch thermal equilibrium. Then, the current responses and their power features, i.e. the power input behavior, are discussed in a unified manner, which reveals that there exist an intrinsic current and an extrinsic correction. Remarkably, the intrinsic part consumes no energy and corresponds to the Floquet quasi-equilibrium, while the extrinsic part needs a sustained energy input and originates from a shift between two equilibrium ensembles. We further investigate the role of the external driving field strength finding that large DC currents can be generated under a relatively strong but not too strong driving field.

cond-mat.mes-hall↗

arXiv2022

Ubiquitous Coexisting Electron-Mode Couplings in High Temperature Cuprate Superconductors

In conventional superconductors, the electron-phonon coupling plays a dominant role in pairing the electrons and generating superconductivity. In high temperature cuprate superconductors, the existence of the electron coupling with phonons and other boson modes and its role in producing high temperature superconductivity remain unclear. The evidence of the electron-boson coupling mainly comes from the angle-resolved photoemission (ARPES) observations of the ~70meV nodal dispersion kink and the ~40meV antinodal kink. However, the reported results are sporadic and the nature of the involved bosons are still under debate. Here we report new findings of ubiquitous two coexisting electron-mode couplings in cuprate superconductors. By taking ultra-high resolution laser-based ARPES measurements, combined with the improved second derivative analysis method, we discovered that the electrons are coupled simultaneously with two sharp phonon modes with energies of ~70meV and ~40meV in different superconductors with different doping levels, over the entire momentum space and at different temperatures above and below the superconducting transition temperature. The observed electron-phonon couplings are unusual because the associated energy scales do not exhibit an obvious change across the superconducting transition. We further find that the well-known "peak-dip-hump" structure, which has long been considered as a hallmark of superconductivity, is also omnipresent and consists of finer structures that originates from electron coupling with two sharp phonon modes. These comprehensive results provide a unified picture to reconcile all the reported observations and pinpoint the origin of the electron-mode couplings in cuprate superconductors. They provide key information to understand the role of the electron-phonon coupling in generating high temperature superconductivity.

cond-mat.supr-con↗

arXiv2022

Electronic Nature of Charge Density Wave and Electron-Phonon Coupling in Kagome Superconductor KV$_3$Sb$_5$

The Kagome superconductors AV3Sb5 (A=K, Rb, Cs) have received enormous attention due to their nontrivial topological electronic structure, anomalous physical properties and superconductivity. Unconventional charge density wave (CDW) has been detected in AV3Sb5. High-precision electronic structure determination is essential to understand its origin. Here we unveil electronic nature of the CDW phase in our high-resolution angle-resolved photoemission measurements on KV3Sb5. We have observed CDW-induced Fermi surface reconstruction and the associated band folding. The CDW-induced band splitting and the associated gap opening have been revealed at the boundary of the pristine and reconstructed Brillouin zones. The Fermi surface- and momentum-dependent CDW gap is measured and the strongly anisotropic CDW gap is observed for all the V-derived Fermi surface. In particular, we have observed signatures of the electron-phonon coupling in KV3Sb5. These results provide key insights in understanding the nature of the CDW state and its interplay with superconductivity in AV3Sb5 superconductors.

cond-mat.supr-con↗

arXiv2021

Doping-dependence of the electron-phonon coupling in two families of bilayer superconducting cuprates

While electron-phonon coupling (EPC) is crucial for Cooper pairing in conventional superconductors, its role in high-$T_c$ superconducting cuprates is debated. Using resonant inelastic x-ray scattering at the oxygen $K$-edge, we studied the EPC in Bi$_2$Sr$_2$CaCu$_2$O$_{8+δ}$ (Bi2212) and Nd$_{1+x}$Ba$_{2-x}$Cu$_3$O$_{7-δ}$ (NBCO) at different doping levels ranging from heavily underdoped ($p =0.07$) to overdoped ($p=0.21$). We analyze the data with a localized Lang-Firsov model that allows for the coherent excitations of two phonon modes. While electronic band dispersion effects are non-negligible, we are able to perform a study of the relative values of EPC matrix elements in these cuprate families. In the case of NBCO, the choice of the excitation energy allows us to disentangle modes related to the CuO$_3$ chains and the CuO$_2$ planes. Combining the results from the two families, we find the EPC strength decreases with doping at $\mathbf{q_\parallel}=(-0.25, 0)$ r.l.u., but has a non-monotonic trend as a function of doping at smaller momenta. This behavior is attributed to the screening effect of charge carriers. We also find that the phonon intensity is enhanced in the vicinity of the charge-density-wave (CDW) excitations while the extracted EPC strength appears to be less sensitive to their proximity. By performing a comparative study of two cuprate families, we are able to identify general trends in the EPC for the cuprates and provide experimental input to theories invoking a synergistic role for this interaction in $d$-wave pairing.

cond-mat.supr-con↗

arXiv2021

Self-supervised Representation Learning for Trip Recommendation

Trip recommendation is a significant and engaging location-based service that can help new tourists make more customized travel plans. It often attempts to suggest a sequence of point of interests (POIs) for a user who requests a personalized travel demand. Conventional methods either leverage the heuristic algorithms (e.g., dynamic programming) or statistical analysis (e.g., Markov models) to search or rank a POI sequence. These procedures may fail to capture the diversity of human needs and transitional regularities. They even provide recommendations that deviate from tourists' real travel intention when the trip data is sparse. Although recent deep recursive models (e.g., RNN) are capable of alleviating these concerns, existing solutions hardly recognize the practical reality, such as the diversity of tourist demands, uncertainties in the trip generation, and the complex visiting preference. Inspired by the advance in deep learning, we introduce a novel self-supervised representation learning framework for trip recommendation -- SelfTrip, aiming at tackling the aforementioned challenges. Specifically, we propose a two-step contrastive learning mechanism concerning the POI representation, as well as trip representation. Furthermore, we present four trip augmentation methods to capture the visiting uncertainties in trip planning. We evaluate our SelfTrip on four real-world datasets, and extensive results demonstrate the promising gain compared with several cutting-edge benchmarks, e.g., up to 4% and 12% on F1 and pair-F1, respectively.

cs.IR↗