arXiv subjects

Ke Huang

Publications and source records attributed to Ke Huang.

At least 55 records · Page 3Linked to original sources

arXiv2023

Incommensurate many-body localization in the presence of long-range hopping and single-particle mobility edge

We study many-body localization (MBL) in the quasiperiodic $t_1$-$t_2$ model, focusing on the role of next-nearest-neighbor (NNN) hopping $t_2$, which introduces a single-particle mobility edge. The calculated phase diagram can be divided into three distinct regimes, depending on the strength of the short-range interaction $U$. For weak interactions ($U\ll t_1$), this model is always nonthermal. For intermediate interactions ($U\sim t_1$), the thermal-MBL phase transition in this model is qualitatively the same as that of the Aubry-Andre (AA) model, which is consistent with existing experimental observations. For strong interactions $(U\gg t_1)$, the NNN hopping produces qualitatively new physics because it breaks down the Hilbert space fragmentation present in the AA model. The NNN hopping is thus irrelevant when the interaction is intermediate but relevant for strong interactions.

cond-mat.dis-nn↗

arXiv2022

Multi-Projection Fusion and Refinement Network for Salient Object Detection in 360° Omnidirectional Image

Salient object detection (SOD) aims to determine the most visually attractive objects in an image. With the development of virtual reality technology, 360° omnidirectional image has been widely used, but the SOD task in 360° omnidirectional image is seldom studied due to its severe distortions and complex scenes. In this paper, we propose a Multi-Projection Fusion and Refinement Network (MPFR-Net) to detect the salient objects in 360° omnidirectional image. Different from the existing methods, the equirectangular projection image and four corresponding cube-unfolding images are embedded into the network simultaneously as inputs, where the cube-unfolding images not only provide supplementary information for equirectangular projection image, but also ensure the object integrity of the cube-map projection. In order to make full use of these two projection modes, a Dynamic Weighting Fusion (DWF) module is designed to adaptively integrate the features of different projections in a complementary and dynamic manner from the perspective of inter and intra features. Furthermore, in order to fully explore the way of interaction between encoder and decoder features, a Filtration and Refinement (FR) module is designed to suppress the redundant information between the feature itself and the feature. Experimental results on two omnidirectional datasets demonstrate that the proposed approach outperforms the state-of-the-art methods both qualitatively and quantitatively.

cs.CV↗

arXiv2022

Phase diagram of superconducting vortex ratchet motion in a superlattice with noncentrosymmetry

Ratchet motion of superconducting vortices, which is a directional flow of vortices in superconductors, is highly useful for exploring quantum phenomena and developing superconducting devices, such as superconducting diode and microwave antenna. However, because of the challenges in the quantitative characterization of the dynamic motion of vortices, a phase diagram of the vortex ratchet motion is still missing, especially in the superconductors with low dimensional structures. Here we establish a quantitative phase diagram of the vortex ratchet motion in a highly anisotropic superlattice superconductor, (SnS)1.17NbS2, using nonreciprocal magnetotransport. The (SnS)1.17NbS2, which possesses a layered atomic structure and noncentrosymmetry, exhibits nonreciprocal magnetotransport in a magnetic field perpendicular and parallel to the plane, which is considered a manifest of ratchet motion of superconducting vortices. We demonstrated that the ratchet motion is responsive to current excitation, magnetic field and thermal perturbation. Furthermore, we extrapolated a giant nonreciprocal coefficient (γ), which quantitatively describes the magnitude of the vortex ratchet motion, and eventually established phase diagrams of the ratchet motion of the vortices with a quantitative description. Last, we propose that the ratchet motion originates from the coexistence of pancake vortices (PVs) and Josephson vortices (JVs). The phase diagrams are desirable for controlling the vortex motion in superlattice superconductors and developing next-generation energy-efficient superconducting devices.

cond-mat.supr-con↗

arXiv2022

Aharonov-Bohm oscillations in bilayer graphene edge state Fabry-Pérot interferometers

The charge and exchange statistics of an elementary excitation manifest in quantum coherent oscillations that can be explored in interferometry measurements. Quantum Hall interferometers are primary tools to uncover unconventional quantum statistics associated with fractional and non-Abelian anyons of a two-dimensional system, the latter being the foundation of topological quantum computing. Graphene interferometers offer new avenues to explore the physics of exotic excitations due to their relatively small charging energies and sharp confinement potentials. Bilayer graphene possesses a true band gap to facilitate the formation of quantum confinement and exhibits the most robust even-denominator fractional quantum Hall states that may host non-Abelian anyons. Here we present the design and fabrication of a split-gated bilayer graphene Fabry-Pérot interferometer and experimental evidence of Aharonov-Bohm interference at multiple integer quantum Hall states. The versatility of the device allows us to study a wide range of scenarios, determine the velocities of edge states, and assess dephasing mechanisms of the interferometer. These results pave the way to the quest of non-Abelian statistics in this promising device platform.

cond-mat.mes-hall↗

arXiv2022

AdaTest:Reinforcement Learning and Adaptive Sampling for On-chip Hardware Trojan Detection

This paper proposes AdaTest, a novel adaptive test pattern generation framework for efficient and reliable Hardware Trojan (HT) detection. HT is a backdoor attack that tampers with the design of victim integrated circuits (ICs). AdaTest improves the existing HT detection techniques in terms of scalability and accuracy of detecting smaller Trojans in the presence of noise and variations. To achieve high trigger coverage, AdaTest leverages Reinforcement Learning (RL) to produce a diverse set of test inputs. Particularly, we progressively generate test vectors with high reward values in an iterative manner. In each iteration, the test set is evaluated and adaptively expanded as needed. Furthermore, AdaTest integrates adaptive sampling to prioritize test samples that provide more information for HT detection, thus reducing the number of samples while improving the sample quality for faster exploration. We develop AdaTest with a Software/Hardware co-design principle and provide an optimized on-chip architecture solution. AdaTest's architecture minimizes the hardware overhead in two ways:(i) Deploying circuit emulation on programmable hardware to accelerate reward evaluation of the test input; (ii) Pipelining each computation stage in AdaTest by automatically constructing auxiliary circuit for test input generation, reward evaluation, and adaptive sampling. We evaluate AdaTest's performance on various HT benchmarks and compare it with two prior works that use logic testing for HT detection. Experimental results show that AdaTest engenders up to two orders of test generation speedup and two orders of test set size reduction compared to the prior works while achieving the same level or higher Trojan detection rate.

cs.AI↗

arXiv2022

An Adaptive Black-box Backdoor Detection Method for Deep Neural Networks

With the surge of Machine Learning (ML), An emerging amount of intelligent applications have been developed. Deep Neural Networks (DNNs) have demonstrated unprecedented performance across various fields such as medical diagnosis and autonomous driving. While DNNs are widely employed in security-sensitive fields, they are identified to be vulnerable to Neural Trojan (NT) attacks that are controlled and activated by stealthy triggers. In this paper, we target to design a robust and adaptive Trojan detection scheme that inspects whether a pre-trained model has been Trojaned before its deployment. Prior works are oblivious of the intrinsic property of trigger distribution and try to reconstruct the trigger pattern using simple heuristics, i.e., stimulating the given model to incorrect outputs. As a result, their detection time and effectiveness are limited. We leverage the observation that the pixel trigger typically features spatial dependency and propose the first trigger approximation based black-box Trojan detection framework that enables a fast and scalable search of the trigger in the input space. Furthermore, our approach can also detect Trojans embedded in the feature space where certain filter transformations are used to activate the Trojan. We perform extensive experiments to investigate the performance of our approach across various datasets and ML models. Empirical results show that our approach achieves a ROC-AUC score of 0.93 on the public TrojAI dataset. Our code can be found at https://github.com/xinqiaozhang/adatrojan

cs.CR↗

arXiv2022

Fermionic many-body localization for random and quasiperiodic systems in the presence of short- and long-range interactions

We study many-body localization (MBL) for interacting one-dimensional lattice fermions in random (Anderson) and quasiperiodic (Aubry-Andre) models, focusing on the role of interaction range. We obtain the MBL quantum phase diagrams by calculating the experimentally relevant inverse participation ratio (IPR) at half-filling using exact diagonalization methods and extrapolating to the infinite system size. For short-range interactions, our results produce in the phase diagram a qualitative symmetry between weak and strong interaction limits. For long-range interactions, no such symmetry exists as the strongly interacting system is always many-body localized, independent of the effective disorder strength, and the system is analogous to a pinned Wigner crystal. We obtain various scaling exponents for the IPR, suggesting conditions for different MBL regimes arising from interaction effects.

cond-mat.dis-nn↗

arXiv2022

FaceSigns: Semi-Fragile Neural Watermarks for Media Authentication and Countering Deepfakes

Deepfakes and manipulated media are becoming a prominent threat due to the recent advances in realistic image and video synthesis techniques. There have been several attempts at combating Deepfakes using machine learning classifiers. However, such classifiers do not generalize well to black-box image synthesis techniques and have been shown to be vulnerable to adversarial examples. To address these challenges, we introduce a deep learning based semi-fragile watermarking technique that allows media authentication by verifying an invisible secret message embedded in the image pixels. Instead of identifying and detecting fake media using visual artifacts, we propose to proactively embed a semi-fragile watermark into a real image so that we can prove its authenticity when needed. Our watermarking framework is designed to be fragile to facial manipulations or tampering while being robust to benign image-processing operations such as image compression, scaling, saturation, contrast adjustments etc. This allows images shared over the internet to retain the verifiable watermark as long as face-swapping or any other Deepfake modification technique is not applied. We demonstrate that FaceSigns can embed a 128 bit secret as an imperceptible image watermark that can be recovered with a high bit recovery accuracy at several compression levels, while being non-recoverable when unseen Deepfake manipulations are applied. For a set of unseen benign and Deepfake manipulations studied in our work, FaceSigns can reliably detect manipulated content with an AUC score of 0.996 which is significantly higher than prior image watermarking and steganography techniques.

cs.CV↗

arXiv2022

Nonreciprocal transport in a bilayer of MnBi2Te4 and Pt

MnBi2Te4 (MBT) is the first intrinsic magnetic topological insulator with the interaction of spin-momentum locked surface electrons and intrinsic magnetism, and it exhibits novel magnetic and topological phenomena. Recent studies suggested that the interaction of electrons and magnetism can be affected by the Mn-doped Bi2Te3 phase at the surface due to inevitable structural defects. Here we report an observation of nonreciprocal transport, i.e. current-direction-dependent resistance, in a bilayer composed of antiferromagnetic MBT and nonmagnetic Pt. The emergence of the nonreciprocal response below the Néel temperature confirms a correlation between nonreciprocity and intrinsic magnetism in the surface state of MBT. The angular dependence of the nonreciprocal transport indicates that nonreciprocal response originates from the asymmetry scattering of electrons at the surface of MBT mediated by magnon. Our work provides an insight into nonreciprocity arising from the correlation between magnetism and Dirac surface electrons in intrinsic magnetic topological insulators.

cond-mat.mes-hall↗

arXiv2021

Stability of scar states in 2D PXP model against random disorders

Recently a class of quantum systems exhibiting weak ergodicity breaking has attracted much attention. These systems feature a special band of eigenstates called quantum many-body scar states in the energy spectrum. In this work we study the fate of quantum many-body scar states in a two-dimensional lattice against random disorders. We show that in both the square lattice and the honeycomb lattice the scar states can persist up to a finite disorder strength, before eventually being erased by the disorder. We further study the localization properties of the system in the presence of even stronger disorders and show that whether a full localization transition occurs depends on the type of disorder we introduce. Our study thus reveals the fascinating interplay between disorder and quantum many-body scarring in a two-dimensional system.

cond-mat.dis-nn↗

arXiv2021

Nano-engineering the evolution of skyrmion crystal in synthetic antiferromagnets

The evolution of skyrmion crystal encapsulates skyrmion critical behaviors, such as nucleation, deformation and annihilation. Here, we achieve a tunable evolution of artificial skyrmion crystal in nanostructured synthetic antiferromagnet multilayers, which are comprised of perpendicular magnetic multilayers and nanopatterned arrays of magnetic nanodots. The out-of-plane magnetization hysteresis loops and first-order reversal curves show that the nucleation and annihilation of the artificial skyrmion can be controlled by tuning the diameter of and spacing between the nanodots. Moreover, when the bottom layer thickness increases, the annihilation of skyrmion shifts from evolving into a ferromagnetic spin texture to evolving into an antiferromagnetic spin texture. Most significantly, non-volatile multiple states are realized at zero magnetic field via controlling the proportion of the annihilated skyrmions in the skyrmion crystal. Our results demonstrate the tunability and flexibility of the artificial skyrmion platform, providing a promising route to achieve skyrmion-based multistate devices, such as neuromorphic spintronic devices.

cond-mat.str-el↗

arXiv2021

Tailoring magnetic order via atomically stacking 3d/5d electrons

The ability to tune magnetic orders, such as magnetic anisotropy and topological spin texture, is desired in order to achieve high-performance spintronic devices. A recent strategy has been to employ interfacial engineering techniques, such as the introduction of spin-correlated interfacial coupling, to tailor magnetic orders and achieve novel magnetic properties. We chose a unique polar-nonpolar LaMnO3/SrIrO3 superlattice because Mn (3d)/Ir (5d) oxides exhibit rich magnetic behaviors and strong spin-orbit coupling through the entanglement of their 3d and 5d electrons. Through magnetization and magnetotransport measurements, we found that the magnetic order is interface-dominated as the superlattice period is decreased. We were able to then effectively modify the magnetization, tilt of the ferromagnetic easy axis, and symmetry transition of the anisotropic magnetoresistance of the LaMnO3/SrIrO3 superlattice by introducing additional Mn (3d) and Ir (5d) interfaces. Further investigations using in-depth first-principles calculations and numerical simulations revealed that these magnetic behaviors could be understood by the 3d/5d electron correlation and Rashba spin-orbit coupling. The results reported here demonstrate a new route to synchronously engineer magnetic properties through the atomic stacking of different electrons, contributing to future applications.

cond-mat.str-el↗

arXiv2021

A new class of exact mobility edges in non-Hermitian quasiperiodic models

Quantum localization in 1D non-Hermitian systems, especially the search for exact single-particle mobility edges, has attracted considerable interest recently. While much progress has been made, the available methods to determine the ME of such models are still limited. In this work, we propose a new method to determine the exact mobility edge in a large class of 1D non-Hermitian quasiperiodic models with parity-time ($\mathcal{PT}$) symmetry. We illustrate our method by studying a specific model. We first use our method to determine the energy-dependent mobility edge as well as the spectrum for localized eigenstates in this model. We then demonstrate that the metal-insulator transition must occur simultaneously with the spontaneous $\mathcal{PT}$-symmetry breaking transition in this model. Finally, we propose an experimental protocol based on a 1D photonic lattice to distinguish the extended and localized single-particle states in our model.

cond-mat.dis-nn↗

arXiv2021

Enhanced metal-insulator transition in freestanding VO2 down to 5 nm thickness

Ultrathin freestanding membranes with a pronounced metal-insulator transition (MIT) provides huge potential in future flexible electronic applications as well as a unique aspect of the study of lattice-electron interplay. However, the reduction of the thickness to an ultrathin region (a few nm) is typically detrimental to the MIT in epitaxial films, and even catastrophic for their freestanding form. Here, we report an enhanced MIT in VO2-based freestanding membranes, with a lateral size up to millimetres and VO2 thickness down to 5 nm. The VO2-membranes were detached by dissolving a Sr3Al2O6 sacrificial layer between the VO2 thin film and c-Al2O3(0001) substrate, allowing a transfer onto arbitrary surfaces. Furthermore, the MIT in the VO2-membrane was greatly enhanced by inserting an intermediate Al2O3 buffer layer. In comparison to the best available ultrathin VO2-membranes, the enhancement of MIT is over 400% at 5 nm VO2 thickness and more than one order of magnitude for VO2 above 10 nm. Our study widens the spectrum of functionality in ultrathin and large-scale membranes, and enables the potential integration of MIT into flexible electronics and photonics.

cond-mat.mtrl-sci↗

arXiv2021

Bipolar conduction and giant positive magnetoresistance in doped metallic titanium oxide heterostructures

Empowering conventional materials with unexpected magnetoelectric properties is appealing to the multi-functionalization of existing devices and the exploration of future electronics. Recently, owing to its unique effect in modulating a matter's properties, ultra-small dopants, e.g. H, D, and Li, attract enormous attention in creating emergent functionalities, such as superconductivity, and metal-insulator transition. Here, we report an observation of bipolar conduction accompanied by a giant positive magnetoresistance in D-doped metallic Ti oxide (TiOxDy) films. To overcome the challenges in intercalating the D into a crystalline oxide, a series of TiOxDy were formed by sequentially doping Ti with D and surface/interface oxidation. Intriguingly, while the electron mobility of the TiOxDy increases by an order of magnitude larger after doping, the emergent holes also exhibit high mobility. Moreover, the bipolar conduction induces a giant magnetoresistance up to 900% at 6 T, which is ~6 times higher than its conventional phase. Our study paves a way to empower conventional materials in existing electronics and induce novel electronic phases.

cond-mat.mtrl-sci↗

arXiv2021

Gapless Spin Wave Transport through a Quantum Canted-Antiferromagnet

In the Landau levels of a two-dimensional electron system or when flat bands are present, e.g. in twisted van der Waals bilayers, strong electron-electron interaction gives rise to quantum Hall ferromagnetism with spontaneously broken symmetries in the spin and isospin sectors. Quantum Hall ferromagnets support a rich variety of low-energy collective excitations that are instrumental to understand the nature of the magnetic ground states and are also potentially useful as carriers of quantum information. Probing such collective excitations, especially their dispersion ω(k), has been experimentally challenging due to small sample size and measurement constraints. In this work, we demonstrate an all-electrical approach that integrates a Fabry-Pérot cavity with non-equilibrium transport to achieve the excitation, wave vector selection and detection of spin waves in graphene heterostructures. Our experiments reveal gapless, linearly dispersed spin wave excitations in the E = 0 Landau level of bilayer graphene, thus providing direct experimental evidence for a predicted canted antiferromagnetic order. We show that the gapless spin wave mode propagates with a high group velocity of several tens of km/s and maintains phase coherence over a distance of many micrometers. Its dependence on the magnetic field and temperature agree well with the hydrodynamic theory of spin waves. These results lay the foundation for the quest of spin superfluidity in this high-quality material. The resonant cavity technique we developed offers a powerful and timely method to explore the collective excitation of many spin and isospin-ordered many-body ground states in van der Waals heterostructures and open the possibility of engineering magnonic devices.

cond-mat.mes-hall↗

arXiv2020

Perturbative deflection angle, gravitational lensing in the strong field limit and the black hole shadow

A perturbative method to compute the deflection angle of both timelike and null rays in arbitrary static and spherically symmetric spacetimes in the strong field limit is proposed. The result takes a quasi-series form of $(1-b_c/b)$ where $b$ is the impact parameter and $b_c$ is its critical value, with coefficients of the series explicitly given. This result also naturally takes into account the finite distance effect of both the source and detector, and allows to solve the apparent angles of the relativistic images in a more precise way. From this, the BH angular shadow size is expressed as a simple formula containing metric functions and particle/photon sphere radius. The magnification of the relativistic images were shown to diverge at different values of the source-detector angular coordinate difference, depending on the relation between the source and detector distance from the lens. To verify all these results, we then applied them to the Hayward BH spacetime, concentrating on the effects of its charge parameter $l$ and the asymptotic velocity $v$ of the signal. The BH shadow size were found to decrease slightly as $l$ increase to its critical value, and increase as $v$ decreases from light speed. For the deflection angle and the magnification of the images however, both the increase of $l$ and decrease of $v$ will increase their values.

gr-qc↗

arXiv2020

Perturbative deflection angle for signal with finite distance and general velocities

We propose a perturbative method to compute the deflection angle of both null and massive particles for source and detector at finite distance. This method applies universally to the motion of particles with general velocity in the equatorial plane of stationary axisymmetric spacetimes or static spherical symmetric spacetimes that are asymptotically flat. The resultant deflection angle automatically arranges into a quasi-inverse series form of the impact parameter, with coefficients depending on the metric functions, the signal velocity and the source and detector locations through the apparent angles. In the large impact parameter limit, the series coefficients are reduced to rational functions of sine/cosine functions of the zero order apparent angle.

gr-qc↗