arXiv subjects

Shihao Zhang

Publications and source records attributed to Shihao Zhang.

71 records · Page 4Linked to original sources

arXiv2022

Observation of Coexisting Dirac Bands and Moiré Flat Bands in Magic-Angle Twisted Trilayer Graphene

Moiré superlattices that consist of two or more layers of two-dimensional materials stacked together with a small twist angle have emerged as a tunable platform to realize various correlated and topological phases, such as Mott insulators, unconventional uperconductivity and quantum anomalous Hall effect. Recently, the magic-angle twisted trilayer graphene (MATTG) has shown both robust superconductivity similar to magic-angle twisted bilayer graphene (MATBG) and other unique properties, including the Pauli-limit violating and re-entrant superconductivity. These rich properties are deeply rooted in its electronic structure under the influence of distinct moiré potential and mirror symmetry. Here, combining nanometer-scale spatially resolved angle-resolved photoemission spectroscopy (nano-ARPES) and scanning tunneling microscopy/spectroscopy (STM/STS), we systematically measure the yet unexplored band structure of MATTG near charge neutrality. Our measurements reveal the coexistence of the distinct dispersive Dirac band with the emergent moiré flat band, showing nice agreement with the theoretical calculations. These results serve as a stepstone for further understanding of the unconventional superconductivity in MATTG.

cond-mat.mtrl-sci↗

arXiv2022

Quantum algorithm for learning secret strings and its experimental demonstration

In this paper, we consider the secret-string-learning problem in the teacher-student setting: the teacher has a secret string $s\in {\{0,1\}^{n}}$, and the student wants to learn the secret $s$ by question-answer interactions with the teacher, where at each time, the student can ask the teacher with a pair $(x, q) \in {\{0,1\}^{n}}\times\{0,1,\cdots, n-1\}$ and the teacher returns a bit given by the oracle $f_{s}(x,q)$ that indicates whether the length of the longest common prefix of $s$ and $x$ is greater than $q$ or not. Our contributions are as follows. (i) We prove that any classical deterministic algorithm needs at least $n$ queries to the oracle $f_{s}$ to learn the $n$-bit secret string $s$ in both the worst case and the average case, and also present an optimal classical deterministic algorithm learning any $s$ using $n$ queries. (ii) We obtain a quantum algorithm learning the $n$-bit secret string $s$ with certainty using $\left\lceil n/2\right\rceil$ queries to the oracle $f_s$, thus proving a double speedup over classical counterparts. (iii) Experimental demonstrations of our quantum algorithm on the IBM cloud quantum computer are presented, with average success probabilities of $85.3\%$ and $82.5\%$ for all cases with $n=2$ and $n=3$ , respectively.

quant-ph↗

arXiv2022

Correlated insulators, density wave states, and their nonlinear optical response in magic-angle twisted bilayer graphene

The correlated insulator (CI) states and the recently discovered density wave (DW) states in magic-angle twisted bilayer graphene (TBG) have stimulated intense research interest. However, up to date, the nature of these "featureless" correlated states with zero Chern numbers are still elusive, and are lack of characteristic experimental signature. Thus, an experimental probe to identify the characters of these featureless CI and DW states are urgently needed. In this work, we theoretically study the correlated insulators and density-wave states at different integer and fractional fillings of the flat bands in magic-angle TBG based on extended unrestricted Hartree-Fock calculations including the Coulomb screening effects from the remote bands. We further investigate the nonlinear optical response of the various correlated states, and find that the nonlinear optical conductivities can be used to identify the nature of these CI and DW states at most of the fillings. Therefore, we propose that nonlinear optical response can serve as a promising experimental probe to unveil the nature of the CI and DW states observed in magic-angle TBG.

cond-mat.str-el↗

arXiv2021

Isospin competitions and valley polarized correlated insulators in twisted double bilayer graphene

New phase of matter usually emerges when a given symmetry breaks spontaneously, which can involve charge, spin, and valley degree of freedoms. Here, we report an observation of new correlated insulators evolved from spin polarized states to valley polarized states in AB-BA stacked twisted double bilayer graphene (TDBG). The transition of the isospin polarization is a result of the competition between spin and valley, driven by the displacement field (D). At a high field |D| > 0.7 V/nm, we observe valley polarized correlated insulators with a big Zeeman g factor of ~10, both at v = 2 in the moiré conduction band and more surprisingly at v = -2 in the moiré valence band. At a medium field |D| < 0.6 V/nm, by contrast, it is a conventional spin polarized correlated insulator at v = 2 and a featureless metal at v = -2. Moreover, we observe a valley polarized Chern insulator with C = 2 emanating at v = 2 in the electron side and a valley polarized Fermi surface around v = -2 in the hole side. The valley Chern insulator with C = 2 is evident from a well quantized Hall conductance plateau at 2e^2/h and correspondingly a vanishing longitudinal component. The valley polarized Fermi surface is topologically trivial with C = 0, and it shows a series of quantized Landau levels with v_LL = 0, 1, 2, 3, 4 and others. These observations are in good agreements with our band and topology calculations. Our results demonstrate a feasible way to realize isospin control and to obtain new phases of matter in TDBG by the displacement field, and might benefit other twisted or non-twisted multilayer systems.

cond-mat.mes-hall↗

arXiv2021

Spin polarized nematic order, quantum valley Hall states, and field tunable topological transitions in twisted multilayer graphene systems

We theoretically study the correlated insulator states, quantum anomalous Hall (QAH) states, and field-induced topological transitions between different correlated states in twisted multilayer graphene systems. Taking twisted bilayer-monolayer graphene and twisted double-bilayer graphene as examples, we show that both systems stay in spin polarized, $C_{3z}$-broken insulator states with zero Chern number at 1/2 filling of the flat bands under finite displacement fields. In some cases these spin polarized, nematic insulator states are in the quantum valley Hall phase by virtue of the nontrivial band topology of the systems. The spin polarized insulator state is quasi-degenerate with the valley polarized state if only the dominant intra-valley Coulomb interaction is included. Such quasi-degeneracy can be split by atomic on-site interactions such that the spin polarized, nematic state become the unique ground state. Such a scenario applies to various twisted multilayer graphene systems at 1/2 filling, thus can be considered as a universal mechanism. Moreover, under vertical magnetic fields, the orbital Zeeman splittings and the field-induced change of charge density in twisted multilayer graphene systems would compete with the atomic Hubbard interactions, which can drive transitions from spin polarized zero-Chern-number states to valley-polarized QAH states with small onset magnetic fields.

cond-mat.mes-hall↗

arXiv2021

Alternating twisted mutilayer graphene: generic partition rules, double flat bands, and orbital magnetoelectric effect

Twisted graphene systems have draw significant attention due to the discoveries of various correlated and topological phases. In particular, recently the alternating twisted trilayer graphene is discovered to exhibit unconventional superconductivity, which motivates us to study the electronic structures and possible interesting correlation effects of this class of alternating twisted graphene systems. In this work we consider generic alternating twisted multilayer graphene (ATMG) systems with $M$-$L$-$N$ stacking configurations, in which the $M$ ($L$) graphene layers and the $L$ ($N$) layers are twisted by an angle $θ$ (-$θ$). Based on analysis from a simplified $\textbf{k}\!\cdot\!\textbf{p}$ model approach, we analytically derive generic partition rules for the low-energy electronic structures, which exhibit various intriguing band dispersions including one pair of flat bands, two pairs of flat bands, as well as flat bands co-existing with with Dirac cones, quadratic bands, or more generally $E(\mathbf{k})\!\sim\!k^J$ dispersions ($J$ is positive integer) for each spin and valley. Such unusual non-interacting electronic structures may have unconventional correlation effects. Especially for a mirror symmetric ATMG system with two pairs of flat bands (per spin per valley), we find that Coulomb interactions may drive the system into a state breaking both time-reversal and mirror symmetries, which can exhibit a novel type of orbital magnetoelectric effect due to the interwining of electric polarization and orbital magnetization orders in the symmetry-breaking state.

cond-mat.mes-hall↗

arXiv2021

Tunable intrinsic ferromagnetic topological phases in bulk van der Waals crystal MnSb6Te10

Intrinsic ferromagnetism is a crucial ingredient to realize quantum anomalous Hall effect in quasi two dimensional materials, thus the search of intrinsic ferromagnetic topological materials is one of the most concerned issues in the field of topological phases of matter. In this work, combining magnetotransport measurements, first principles calculations, and angle-resolved photoemission spectroscopy studies, we find that in MnSb6Te10, the n = 2 member of the MnSb2Te4/(Sb2Te3)n family, the strong magnetic competition realizes a fragile ferromagnetic ground state, which whereas easily enters into ferrimagnetic and the Z_2 antiferromagnetic topological insulator phase with warming to higher temperature. Interestingly, the system stays in an inversion-symmetry-protected axion insulator phase in the ferromagnetic ground state as well as in the external magnetic field driven spin-polarized FM phase and can be converted into a Weyl semimetal with multiple Weyl nodes in the valence bands with hole doping, which are manifested by the measured notable intrinsic anomalous Hall effect. Our work thus provides an intrinsic magnetic topological material which is highly tunable into versatile topological phases by temperature, magnetic field, as well as carrier doping.

cond-mat.mtrl-sci↗

arXiv2021

Imaging topological torus lattice from an electron crystal in twisted mono-bilayer graphene

A variety of exotic quantum phases of matter have been created by Van der Waals heterostructures. Moreover, these twisted heterostructures provide a feasible way of braiding correlation effect and nontrivial band topology together. Here, through a comprehensive spectrum study, we report the discovery of topological torus lattice in twisted mono-bilayer graphene. The strong Coulomb correlations give rise to an unusual charge localization behavior within the moiré supercell, leading to an electron crystal. The nontrivial band topology is encoded into the electron crystal, which would result in spatial modulated Chern numbers, and is evidenced by an emergent topological torus lattice state. Our result illustrates an efficient strategy for entwining and engineering topological physics with a strong electron correlation.

cond-mat.mes-hall↗

arXiv2021

High-performance parallel classical scheme for simulating shallow quantum circuits

Recently, constant-depth quantum circuits are proved more powerful than their classical counterparts at solving certain problems, e.g., the two-dimensional (2D) hidden linear function (HLF) problem regarding a symmetric binary matrix. To further investigate the boundary between classical and quantum computing models, in this work we propose a high-performance two-stage classical scheme to solve a full-sampling variant of the 2D HLF problem, which combines traditional classical parallel algorithms and a gate-based classical circuit model together for exactly simulating the target shallow quantum circuits. Under reasonable parameter assumptions, a theoretical analysis reveals our classical simulator consumes less runtime than that of near-term quantum processors for most problem instances. Furthermore, we demonstrate the typical all-connected 2D grid instances by moderate FPGA circuits, and show our designed parallel scheme is a practically scalable, high-efficient and operationally convenient tool for simulating and verifying graph-state circuits performed by current quantum hardware.

quant-ph↗

arXiv2021

Multiple magnetic topological phases in bulk van der Waals crystal MnSb4Te7

The magnetic van der Waals crystals MnBi2Te4/(Bi2Te3)n have drawn significant attention due to their rich topological properties and the tunability by external magnetic field. Although the MnBi2Te4/(Bi2Te3)n family have been intensively studied in the past few years, their close relatives, the MnSb2Te4/(Sb2Te3)n family, remain much less explored. In this work, combining magnetotransport measurements, angle-resolved photoemission spectroscopy, and first principles calculations, we find that MnSb4Te7, the n = 1 member of the MnSb2Te4/(Sb2Te3)n family, is a magnetic topological system with versatile topological phases which can be manipulated by both carrier doping and magnetic field. Our calculations unveil that its A-type antiferromagnetic (AFM) ground state stays in a Z_2 AFM topological insulator phase, which can be converted to an inversion-symmetry-protected axion insulator phase when in the ferromagnetic (FM) state. Moreover, when this system in the FM phase is slightly carrier doped on either the electron or hole side, it becomes a Weyl semimetal with multiple Weyl nodes in the highest valence bands and lowest conduction bands, which are manifested by the measured notable anomalous Hall effect. Our work thus introduces a new magnetic topological material with different topological phases which are highly tunable by carrier doping or magnetic field.

cond-mat.str-el↗

arXiv2020

e-TLD: Event-based Framework for Dynamic Object Tracking

This paper presents a long-term object tracking framework with a moving event camera under general tracking conditions. A first of its kind for these revolutionary cameras, the tracking framework uses a discriminative representation for the object with online learning, and detects and re-tracks the object when it comes back into the field-of-view. One of the key novelties is the use of an event-based local sliding window technique that tracks reliably in scenes with cluttered and textured background. In addition, Bayesian bootstrapping is used to assist real-time processing and boost the discriminative power of the object representation. On the other hand, when the object re-enters the field-of-view of the camera, a data-driven, global sliding window detector locates the object for subsequent tracking. Extensive experiments demonstrate the ability of the proposed framework to track and detect arbitrary objects of various shapes and sizes, including dynamic objects such as a human. This is a significant improvement compared to earlier works that simply track objects as long as they are visible under simpler background settings. Using the ground truth locations for five different objects under three motion settings, namely translation, rotation and 6-DOF, quantitative measurement is reported for the event-based tracking framework with critical insights on various performance issues. Finally, real-time implementation in C++ highlights tracking ability under scale, rotation, view-point and occlusion scenarios in a lab setting.

cs.CV↗

arXiv2020

AGE Challenge: Angle Closure Glaucoma Evaluation in Anterior Segment Optical Coherence Tomography

Angle closure glaucoma (ACG) is a more aggressive disease than open-angle glaucoma, where the abnormal anatomical structures of the anterior chamber angle (ACA) may cause an elevated intraocular pressure and gradually lead to glaucomatous optic neuropathy and eventually to visual impairment and blindness. Anterior Segment Optical Coherence Tomography (AS-OCT) imaging provides a fast and contactless way to discriminate angle closure from open angle. Although many medical image analysis algorithms have been developed for glaucoma diagnosis, only a few studies have focused on AS-OCT imaging. In particular, there is no public AS-OCT dataset available for evaluating the existing methods in a uniform way, which limits progress in the development of automated techniques for angle closure detection and assessment. To address this, we organized the Angle closure Glaucoma Evaluation challenge (AGE), held in conjunction with MICCAI 2019. The AGE challenge consisted of two tasks: scleral spur localization and angle closure classification. For this challenge, we released a large dataset of 4800 annotated AS-OCT images from 199 patients, and also proposed an evaluation framework to benchmark and compare different models. During the AGE challenge, over 200 teams registered online, and more than 1100 results were submitted for online evaluation. Finally, eight teams participated in the onsite challenge. In this paper, we summarize these eight onsite challenge methods and analyze their corresponding results for the two tasks. We further discuss limitations and future directions. In the AGE challenge, the top-performing approach had an average Euclidean Distance of 10 pixels (10um) in scleral spur localization, while in the task of angle closure classification, all the algorithms achieved satisfactory performances, with two best obtaining an accuracy rate of 100%.

cs.CV↗

arXiv2020

Retinal Image Segmentation with a Structure-Texture Demixing Network

Retinal image segmentation plays an important role in automatic disease diagnosis. This task is very challenging because the complex structure and texture information are mixed in a retinal image, and distinguishing the information is difficult. Existing methods handle texture and structure jointly, which may lead biased models toward recognizing textures and thus results in inferior segmentation performance. To address it, we propose a segmentation strategy that seeks to separate structure and texture components and significantly improve the performance. To this end, we design a structure-texture demixing network (STD-Net) that can process structures and textures differently and better. Extensive experiments on two retinal image segmentation tasks (i.e., blood vessel segmentation, optic disc and cup segmentation) demonstrate the effectiveness of the proposed method.

eess.IV↗

arXiv2019

Attention Guided Network for Retinal Image Segmentation

Learning structural information is critical for producing an ideal result in retinal image segmentation. Recently, convolutional neural networks have shown a powerful ability to extract effective representations. However, convolutional and pooling operations filter out some useful structural information. In this paper, we propose an Attention Guided Network (AG-Net) to preserve the structural information and guide the expanding operation. In our AG-Net, the guided filter is exploited as a structure sensitive expanding path to transfer structural information from previous feature maps, and an attention block is introduced to exclude the noise and reduce the negative influence of background further. The extensive experiments on two retinal image segmentation tasks (i.e., blood vessel segmentation, optic disc and cup segmentation) demonstrate the effectiveness of our proposed method.

eess.IV↗

arXiv2019

Efficient composite pulse sequences for arbitrarily accurate z-axis rotation gates

We propose various composite $π$-pulse sequences for implementing robust z-axis rotation gates widely used in quantum information processing (QIP) scenarios, and discuss their error tolerance of the pulse strength error (PSE) and off-resonance error (ORE), i.e., two typical systematic errors in NMR systems. Compared to existing composite gates, our designed composite pulses exhibit higher gate fidelity and shorter sequence time cost. Furthermore, such short pulse sequences are generalized by simple analytic formulas which can suppress these errors to any desired order simultaneously with linear length scaling, indicating an efficient construction of them with arbitrary accuracy.

quant-ph↗

arXiv2018

DART: Distribution Aware Retinal Transform for Event-based Cameras

We introduce a generic visual descriptor, termed as distribution aware retinal transform (DART), that encodes the structural context using log-polar grids for event cameras. The DART descriptor is applied to four different problems, namely object classification, tracking, detection and feature matching: (1) The DART features are directly employed as local descriptors in a bag-of-features classification framework and testing is carried out on four standard event-based object datasets (N-MNIST, MNIST-DVS, CIFAR10-DVS, NCaltech-101). (2) Extending the classification system, tracking is demonstrated using two key novelties: (i) For overcoming the low-sample problem for the one-shot learning of a binary classifier, statistical bootstrapping is leveraged with online learning; (ii) To achieve tracker robustness, the scale and rotation equivariance property of the DART descriptors is exploited for the one-shot learning. (3) To solve the long-term object tracking problem, an object detector is designed using the principle of cluster majority voting. The detection scheme is then combined with the tracker to result in a high intersection-over-union score with augmented ground truth annotations on the publicly available event camera dataset. (4) Finally, the event context encoded by DART greatly simplifies the feature correspondence problem, especially for spatio-temporal slices far apart in time, which has not been explicitly tackled in the event-based vision domain.

cs.CV↗

arXiv2017

Kill Two Birds With One Stone: Boosting Both Object Detection Accuracy and Speed With adaptive Patch-of-Interest Composition

Object detection is an important yet challenging task in video understanding & analysis, where one major challenge lies in the proper balance between two contradictive factors: detection accuracy and detection speed. In this paper, we propose a new adaptive patch-of-interest composition approach for boosting both the accuracy and speed for object detection. The proposed approach first extracts patches in a video frame which have the potential to include objects-of-interest. Then, an adaptive composition process is introduced to compose the extracted patches into an optimal number of sub-frames for object detection. With this process, we are able to maintain the resolution of the original frame during object detection (for guaranteeing the accuracy), while minimizing the number of inputs in detection (for boosting the speed). Experimental results on various datasets demonstrate the effectiveness of the proposed approach.

cs.CV↗