arXiv subjects

Shihao Zhang

Publications and source records attributed to Shihao Zhang.

At least 55 records · Page 3Linked to original sources

arXiv2024

Promoting and imaging intervalley coherent order in rhombohedral tetralayer graphene on MoS2

Multilayer rhombohedral graphene (RG) has recently emerged as a new, structurally simple flat-band system, which facilitates the exploration of interaction-driven correlation states with highly ordered electron arrangements. Despite a variety of many-body order behaviors observed in RG by transport measurements, the direct microscopic visualization of such correlated phases in real space is still lacking. Here, we show the discovery of a robust intervalley coherent order, a long-predicted ground state in RG, at 77 K in tetralayer RG placed on MoS2 via imaging atomic-scale spatial reconstruction of wave functions for correlated states. By using scanning tunnelling microscopy, we observe spectroscopic signatures of electronic correlations at partially filled flat bands, where distinct splitting appears. At ~60% and ~70% fillings of the flat bands, we visualize atomic-scale reconstruction patterns with a 3 x 3 supercell on graphene lattice at liquid nitrogen temperature, which indicates a robust intervalley coherent phase of the interacting electrons. The 3 x 3 pattern is observed in MoS2-supported RG, while it is absent in hBN-based ones under the same experimental conditions, suggesting the significant influence of spin-orbit proximity effect. Our results provide microscopic insights into the correlated phases in tetralayer RG and highlight the significant potential for realizing highly accessible collective phenomena through Van der Waals proximity.

cond-mat.mes-hall↗

arXiv2024

Quantitative regularity for the MHD equations via the localization technique in frequency space

In this paper, we employ the localization technique in frequency space developed by Tao in \cite{MR4337421} to investigate the quantitative estimates for the MHD equations. With the help of quantitative Carleman inequalities given by Tao in \cite{MR4337421} and the pigeonhole principle, we establish the quantitative regularity for the critical $L^3$ norm bounded solutions which enables us explicitly quantify the blow-up behavior in terms of $L^3$ norm near a potential first-time singularity. Some technical innovations, such as introducing the corrector function, are required due to the fact that the scales are inconsistent between the magnetic field and the vorticity field.

math.AP↗

arXiv2024

Layer-dependent evolution of electronic structures and correlations in rhombohedral multilayer graphene

The recent discovery of superconductivity and magnetism in trilayer rhombohedral graphene (RG) establishes an ideal, untwisted platform to study strong correlation electronic phenomena. However, the correlated effects in multilayer RG have received limited attention, and, particularly, the evolution of the correlations with increasing layer number remains an unresolved question. Here, we show the observation of layer-dependent electronic structures and correlations, under surprising liquid nitrogen temperature, in RG multilayers from 3 to 9 layers by using scanning tunneling microscopy and spectroscopy. We explicitly determine layer-enhanced low-energy flat bands and interlayer coupling strengths. The former directly demonstrates the further flattening of low-energy bands in thicker RG, and the latter indicates the presence of varying interlayer interactions in RG multilayers. Moreover, we find significant splittings of the flat bands, ranging from ~50-80 meV, at 77 K when they are partially filled, indicating the emergence of interaction-induced strongly correlated states. Particularly, the strength of the correlated states is notably enhanced in thicker RG and reaches its maximum in the six-layer, validating directly theoretical predictions and establishing abundant new candidates for strongly correlated systems. Our results provide valuable insights into the layer dependence of the electronic properties in RG and demonstrate it as a suitable system for investigating robust and highly accessible correlated phases.

cond-mat.mes-hall↗

arXiv2024

Magnetization dependent anisotropic topological properties in EuCuP

The correlation between magnetism and nontrivial topological band structure serves as a unique venue for discovering exotic topological properties. Combining magnetotransport measurements and first-principles calculations, we unveil herein that the hexagonal EuCuP holds topologically trivial state in the paramagnetic structure, while strong magnetization dependent anisotropic topological states in the spin-polarization structures. Specifically, it hosts a trivial topological state in the in-plane spin-polarization structure, while a Weyl semimetal state in the out-of-plane spin-polarization structure. Our scaling analysis suggests that the intrinsic Berry curvature in the spin-polarization structures can account for the observed large anisotropic anomalous Hall effect. First-principles calculations show that the magnetization and the spin-orbit coupling simultaneously play essential roles for the appearance of the four pairs of Weyl points in the out-of-plane spin-polarization structure. Our work therefore establishes in EuCuP the intimate relation between magnetism and the nontrivial topological states, which would be instructive for future study on this key issue of topological physics.

cond-mat.str-el↗

arXiv2024

Deep Regression Representation Learning with Topology

Most works studying representation learning focus only on classification and neglect regression. Yet, the learning objectives and, therefore, the representation topologies of the two tasks are fundamentally different: classification targets class separation, leading to disconnected representations, whereas regression requires ordinality with respect to the target, leading to continuous representations. We thus wonder how the effectiveness of a regression representation is influenced by its topology, with evaluation based on the Information Bottleneck (IB) principle. The IB principle is an important framework that provides principles for learning effective representations. We establish two connections between it and the topology of regression representations. The first connection reveals that a lower intrinsic dimension of the feature space implies a reduced complexity of the representation Z. This complexity can be quantified as the conditional entropy of Z on the target Y, and serves as an upper bound on the generalization error. The second connection suggests a feature space that is topologically similar to the target space will better align with the IB principle. Based on these two connections, we introduce PH-Reg, a regularizer specific to regression that matches the intrinsic dimension and topology of the feature space with the target space. Experiments on synthetic and real-world regression tasks demonstrate the benefits of PH-Reg. Code: https://github.com/needylove/PH-Reg.

cs.LG↗

arXiv2024

Direct visualization of the impurity occupancy roadmap in Ni-substituted van der Waals ferromagnet Fe3GaTe2

Impurity substitution is a general strategy to study the intrinsic properties of a quantum material. However, when the target element has more than one Wyckoff position in the lattice, it is a big challenge but with extreme necessity to know the exact position and order of the occupancy of impurity atoms. Via comprehensive experimental and theoretical investigations, we establish herein the roadmap for Ni substitution in Fe3GaTe2, a van der Waals ferromagnet with the Curie temperature TC even reaching ~ 380 K. The results unambiguously reveal that in (Fe1-xNix)3GaTe2, Ni atoms initially form an van der Waals interlayer gap Ni3 sites when x < 0.1, and then gradually occupy the Fe2 sites. After replacing the Fe2 sites at x of ~ 0.75, they start to substitute for the Fe1 sites and eventually realize a full occupation at x = 1.0. Accordingly, TC and saturation magnetic moments of (Fe1-xNix)3GaTe2 both show nonlinear decrease, which is tightly tied to the Ni occupancy order as well as the different roles of Ni3, Fe1 and Fe2 sites in the spin Hamiltonian. The results not only yield fruitful insights into the essential roles of different Fe sites in producing the above room temperature high TC, but also set a paradigm for future impurity substitution study on other quantum materials.

cond-mat.str-el↗

arXiv2024

Learning to Generate Training Datasets for Robust Semantic Segmentation

Semantic segmentation methods have advanced significantly. Still, their robustness to real-world perturbations and object types not seen during training remains a challenge, particularly in safety-critical applications. We propose a novel approach to improve the robustness of semantic segmentation techniques by leveraging the synergy between label-to-image generators and image-to-label segmentation models. Specifically, we design Robusta, a novel robust conditional generative adversarial network to generate realistic and plausible perturbed images that can be used to train reliable segmentation models. We conduct in-depth studies of the proposed generative model, assess the performance and robustness of the downstream segmentation network, and demonstrate that our approach can significantly enhance the robustness in the face of real-world perturbations, distribution shifts, and out-of-distribution samples. Our results suggest that this approach could be valuable in safety-critical applications, where the reliability of perception modules such as semantic segmentation is of utmost importance and comes with a limited computational budget in inference. We release our code at https://github.com/ENSTA-U2IS-AI/robusta.

cs.CV↗

arXiv2023

Highly efficient and transferable interatomic potentials for α-iron and α-iron/hydrogen binary systems using deep neural networks

Artificial neural network potentials (NNPs) have emerged as effective tools for understanding atomic interactions at the atomic scale in various phenomena. Recently, we developed highly transferable NNPs for α-iron and α-iron/hydrogen binary systems (Physical Review Materials 5 (11), 113606, 2021). These potentials allowed us to investigate deformation and fracture in α-iron under the influence of hydrogen. However, the computational cost of the NNP remains relatively high compared to empirical potentials, limiting their applicability in addressing practical issues related to hydrogen embrittlement. In this work, building upon our prior research on iron-hydrogen NNP, we developed a new NNP that not only maintains the excellent transferability but also significantly improves computational efficiency (more than 40 times faster). We applied this new NNP to study the impact of hydrogen on the cracking of iron and the deformation of polycrystalline iron. We employed large-scale through-thickness {110}<110> crack models and large-scale polycrystalline α-iron models. The results clearly show that hydrogen atoms segregated at crack tips promote brittle-cleavage failure followed by crack growth. Additionally, hydrogen atoms at grain boundaries facilitate the nucleation of intergranular nanovoids and subsequent intergranular fracture. We anticipate that this high-efficiency NNP will serve as a valuable tool for gaining atomic-scale insights into hydrogen embrittlement.

cond-mat.mtrl-sci↗

arXiv2023

Constructing the Fulde-Ferrell-Larkin-Ovchinnikov state in antiferromagnetic insulator CrOCl

Time reversal symmetry breaking in superconductors, resulting from external magnetic fields or spontaneous magnetization, often leads to unconventional superconducting properties. In this way, a conventional Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) state, characterized by the Cooper pairs with nonzero total momentum, may be realized by the Zeeman effect caused from external magnetic fields. Here, we report the observation of superconductivity in a few-layer antiferromagnetic insulator CrOCl by utilizing superconducting proximity effect with NbSe2 flakes. The superconductivity demonstrates a considerably weak gap of about 0.12 meV and the in-plane upper critical field reveals as behavior of the FFLO state at low temperature. Our first-principles calculations indicate that the proximitized superconductivity may exist in the CrOCl layer with Cr vacancies or line-defects. Moreover, the FFLO state could be induced by the inherent larger spin splitting in the CrOCl layer. Our findings not only demonstrate the fascinating interaction between superconductivity and magnetism, but also provide a possible path to construct FFLO state by intrinsic time reversal symmetry breaking and superconducting proximity effect.

cond-mat.supr-con↗

arXiv2023

Synergistic correlated states and nontrivial topology in coupled graphene-insulator heterostructures

In this work, we study the synergistic correlated states in two distinct types of interacting electronic systems coupled by interlayer Coulomb interactions. We propose that this scenario can be realized in a type of Coulomb-coupled graphene-insulator heterostructures with gate tunable band alignment. We find that, by virtue of the interlayer Coulomb coupling between the interacting electrons in the two layers, electronic states that cannot be revealed in either individual layer would emerge in a cooperative and synergistic manner. Specifically, as a result of the band alignment, charge carriers can be transferred between graphene and the substrate under the control of gate voltages, which can yield a long-wavelength electronic crystal at the surface of the substrate. This electronic crystal exerts a superlattice Coulomb potential on the Dirac electrons in graphene, which generates subbands with reduced non-interacting Fermi velocity. As a result, $e$-$e$ Coulomb interactions within graphene would play a more important role, giving rise to a gapped Dirac state at the charge neutrality point, accompanied by interaction-enhanced Fermi velocity. Moreover, the superlattice potential can give rise to topologically nontrivial subband structures which are tunable by superlattice's constant and anisotropy. Reciprocally, the electronic crystal formed in the substrate can be substantially stabilized in such coupled bilayer heterostructure by virtue of the cooperative interlayer Coulomb coupling. We further perform high-throughput first principles calculations to identify a number of promising insulating materials as candidate substrates for graphene to demonstrate these effects.

cond-mat.mes-hall↗

arXiv2023

Characterization, synthesis, and optimization of quantum circuits over multiple-control $\textit{Z}$-rotation gates: A systematic study

We conduct a systematic study of quantum circuits composed of multiple-control $Z$-rotation (MCZR) gates as primitives, since they are widely-used components in quantum algorithms and also have attracted much experimental interest in recent years. Herein, we establish a circuit-polynomial correspondence to characterize the functionality of quantum circuits over the MCZR gate set with continuous parameters. An analytic method for exactly synthesizing such quantum circuit to implement any given diagonal unitary matrix with an optimal gate count is proposed, which also enables the circuit depth optimal for specific cases with pairs of complementary gates. Furthermore, we present a gate-exchange strategy together with a flexible iterative algorithm for effectively optimizing the depth of any MCZR circuit, which can also be applied to quantum circuits over any other commuting gate set. Besides the theoretical analysis, the practical performances of our circuit synthesis and optimization techniques are further evaluated by numerical experiments on two typical examples in quantum computing, including diagonal Hermitian operators and Quantum Approximate Optimization Algorithm (QAOA) circuits with tens of qubits, which can demonstrate a reduction in circuit depth by 33.40\% and 15.55\% on average over relevant prior works, respectively. Therefore, our methods and results provide a pathway for implementing quantum circuits and algorithms on recently developed devices.

quant-ph↗

arXiv2023

Improving Deep Regression with Ordinal Entropy

In computer vision, it is often observed that formulating regression problems as a classification task often yields better performance. We investigate this curious phenomenon and provide a derivation to show that classification, with the cross-entropy loss, outperforms regression with a mean squared error loss in its ability to learn high-entropy feature representations. Based on the analysis, we propose an ordinal entropy loss to encourage higher-entropy feature spaces while maintaining ordinal relationships to improve the performance of regression tasks. Experiments on synthetic and real-world regression tasks demonstrate the importance and benefits of increasing entropy for regression.

cs.CV↗

arXiv2023

Effective manipulation and realization of a colossal nonlinear Hall effect in an electric-field tunable moiré system

The second-order nonlinear Hall effect illuminates a frequency-doubling transverse current emerging in quantum materials with broken inversion symmetry even when time-reversal symmetry is preserved. This nonlinear response originates from both the Berry curvature dipole and the chiral Bloch electron skew scatterings, reflecting various information of the lattice symmetries, band dispersions, and topology of the electron wavefunctions. Even though many efforts have been put in detecting the nonlinear Hall effect in diverse condensed matter systems, effective manipulation of the two principal mechanisms in a single system has been lacking, and the reported response is relatively weak. Here, we report effective manipulation of the nonlinear Hall effect and realization of a colossal second-order Hall conductivity, $\sim500 μmSV^{-1}$, orders of magnitudes higher than the reported values, in AB-BA stacked twisted double bilayer graphene. A Berry-curvature-dipole-dominated nonlinear Hall effect, as well as its controllable transition to skew-scattering-dominated response, is identified near the band edge. The colossal response, on the other hand, is detected near the van Hove singularities, mainly determined by the skew scattering of the chiral Bloch electrons. Our findings establish electrically tunable moiré systems promising for nonlinear Hall effect manipulations and applications.

cond-mat.mes-hall↗

arXiv2022

A brief introduction to quantum algorithms

Quantum algorithms are demonstrated to outperform classical algorithms for certain problems and thus are promising candidates for efficient information processing. Herein we aim to provide a brief and popular introduction to quantum algorithms for both the academic community and the general public with interest. We start from elucidating quantum parallelism, the basic framework of quantum algorithms and the difficulty of quantum algorithm design. Then we mainly focus on a historical overview of progress in quantum algorithm research over the past three to four decades. Finally, we clarify two common questions about the study of quantum algorithms, hoping to stimulate readers for further exploration.

quant-ph↗

arXiv2022

Automatic Depth-Optimized Quantum Circuit Synthesis for Diagonal Unitary Matrices with Asymptotically Optimal Gate Count

Current noisy intermediate-scale quantum (NISQ) devices can only execute small circuits with shallow depth, as they are still constrained by the presence of noise: quantum gates have error rates and quantum states are fragile due to decoherence. Hence, it is of great importance to optimize the depth/gate-count when designing quantum circuits for specific tasks. Diagonal unitary matrices are well-known to be key building blocks of many quantum algorithms or quantum computing procedures. Prior work has discussed the synthesis of diagonal unitary matrices over the primitive gate set $\{\text{CNOT}, R_Z\}$. However, the problem has not yet been fully understood, since the existing synthesis methods have not optimized the circuit depth. In this paper, we propose a depth-optimized synthesis algorithm that automatically produces a quantum circuit for any given diagonal unitary matrix. Specially, it not only ensures the asymptotically optimal gate-count, but also nearly halves the total circuit depth compared with the previous method. Technically, we discover a uniform circuit rewriting rule well-suited for reducing the circuit depth. The performance of our synthesis algorithm is both theoretically analyzed and experimentally validated by evaluations on two examples. First, we achieve a nearly 50\% depth reduction over Welch's method for synthesizing random diagonal unitary matrices with up to 16 qubits. Second, we achieve an average of 22.05\% depth reduction for resynthesizing the diagonal part of specific quantum approximate optimization algorithm (QAOA) circuits with up to 14 qubits.

quant-ph↗

arXiv2022

Electronic Origin of Half-metal to Semiconductor Transition and Colossal Magnetoresistance in Spinel HgCr2Se4

Half-metals are ferromagnets hosting spin-polarized conducting carriers and crucial for spintronics applications. The chromium spinel HgCr2Se4 represents a unique type of half-metal, which features a half-metal to semiconductor transition (HMST) and exhibits colossal magnetoresistance (CMR) across the ferromagnetic-paramagnetic (FM-PM) transition. Using angle-resolved photoemission spectroscopy (ARPES), we find that the Fermi surface of n-type HgCr2Se4 (n-HgCr2Se4) consists of a single electron pocket which moves above the Fermi level (EF) upon the FM-PM transition, leading to the HMST. Such a Lifshitz transition manifests a giant band splitting which originates from the exchange interaction unveiled with a specific chemical nonstoichiometry. The exchange band splitting and the chemical nonstoichiometry are two key ingredients to the HMST and CMR, consistent with our ab-initio calculation. Our findings provide spectroscopic evidences of the electronic origin of the anomalous properties of HgCr2Se4, which address the unique phase transition in half-metals.

cond-mat.mtrl-sci↗

arXiv2022

Quantum Algorithms for Identifying Hidden Strings with Applications to Matroid Problems

In this paper, we explore quantum speedups for the problem, inspired by matroid theory, of identifying a pair of $n$-bit binary strings that are promised to have the same number of 1s and differ in exactly two bits, by using the max inner product oracle and the sub-set oracle. More specifically, given two string $s, s'\in\{0, 1\}^n$ satisfying the above constraints, for any $x\in\{0, 1\}^n$ the max inner product oracle $O_{max}(x)$ returns the max value between $s\cdot x$ and $s'\cdot x$, and the sub-set oracle $O_{sub}(x)$ indicates whether the index set of the 1s in $x$ is a subset of that in $s$ or $s'$. We present a quantum algorithm consuming $O(1)$ queries to the max inner product oracle for identifying the pair $\{s, s'\}$, and prove that any classical algorithm requires $Ω(n/\log_{2}n)$ queries. Also, we present a quantum algorithm consuming $\frac{n}{2}+O(\sqrt{n})$ queries to the subset oracle, and prove that any classical algorithm requires at least $n+Ω(1)$ queries. Therefore, quantum speedups are revealed in the two oracle models. Furthermore, the above results are applied to the problem in matroid theory of finding all the bases of a 2-bases matroid, where a matroid is called $k$-bases if it has $k$ bases.

quant-ph↗

arXiv2022

Quantum Hall phase in graphene engineered by interfacial charge coupling

Quantum Hall effect (QHE), the ground to construct modern conceptual electronic systems with emerging physics, is often much influenced by the interplay between the host two-dimensional electron gases and the substrate, sometimes predicted to exhibit exotic topological states. Yet the understanding of the underlying physics and the controllable engineering of this paradigm of interaction remain challenging. Here we demonstrate the observation of an unusual QHE, which differs markedly from the known picture, in graphene samples in contact with an anti-ferromagnetic insulator CrOCl equipped with dual gates. Owing to the peculiar interfacial coupling, Landau levels in monolayer graphene remain intact at negative filling fractions, but largely deviated for the positive gate-doping range. The latter QHE phase even presents in the limit of zero magnetic field, with the consequential Landau quantization following a parabolic relation between the displacement field $D$ and the magnetic field $B$. This characteristic prevails up to 100 K in a sufficiently wide effective doping range from 0 to 10$^{13}$ cm$^{-2}$. Our findings thus open up new routes for manipulating the quantum electronic states, which may find applications in such as quantum metrology.

cond-mat.mes-hall↗