arXiv subjects

Yingjie Zhang

Publications and source records attributed to Yingjie Zhang.

49 records · Page 3Linked to original sources

arXiv2024

Pressure-induced color change arising from transformation between intra- and inter-band transitions in LuH$_{2\pm x}$N$_{y}$

The pressure-induced color change in the nitrogen-doped lutetium hydride has triggered extensive discussions about the underlying physics. Here, we study the optical response of LuH$_{2 \pm x}$N$_{y}$ in a broad frequency range at ambient pressure and its evolution with pressure in the visible spectral range. The broad-band optical spectra at ambient pressure reveal a Drude component associated with intra-band electronic transitions and two Lorentz components (L1 and L2) arising from inter-band electronic transitions. The application of pressure causes a spectral weight transfer from L1 to the Drude component, leading to a blue shift of the plasma edge in the reflectivity spectrum alongside a reduction of the high-frequency reflectivity. Our results suggest that the pressure-induced color change in LuH$_{2 \pm x}$N$_{y}$ is closely related to the transformation between intra- and inter-band electronic transitions, providing new insights into the mechanism of the pressure-induced color change in LuH$_{2 \pm x}$N$_{y}$.

cond-mat.supr-con↗

arXiv2023

Gradient Attention Balance Network: Mitigating Face Recognition Racial Bias via Gradient Attention

Although face recognition has made impressive progress in recent years, we ignore the racial bias of the recognition system when we pursue a high level of accuracy. Previous work found that for different races, face recognition networks focus on different facial regions, and the sensitive regions of darker-skinned people are much smaller. Based on this discovery, we propose a new de-bias method based on gradient attention, called Gradient Attention Balance Network (GABN). Specifically, we use the gradient attention map (GAM) of the face recognition network to track the sensitive facial regions and make the GAMs of different races tend to be consistent through adversarial learning. This method mitigates the bias by making the network focus on similar facial regions. In addition, we also use masks to erase the Top-N sensitive facial regions, forcing the network to allocate its attention to a larger facial region. This method expands the sensitive region of darker-skinned people and further reduces the gap between GAM of darker-skinned people and GAM of Caucasians. Extensive experiments show that GABN successfully mitigates racial bias in face recognition and learns more balanced performance for people of different races.

cs.CV↗

arXiv2023

A holistically 3D-printed flexible millimeter-wave Doppler radar: Towards fully printed high-frequency multilayer flexible hybrid electronics systems

Flexible hybrid electronics (FHE) is an emerging technology enabled through the integration of advanced semiconductor devices and 3D printing technology. It unlocks tremendous market potential by realizing low-cost flexible circuits and systems that can be conformally integrated into various applications. However, the operating frequencies of most reported FHE systems are relatively low. It is also worth to note that reported FHE systems have been limited to relatively simple design concept (since complex systems will impose challenges in aspects such as multilayer interconnections, printing materials, and bonding layers). Here, we report a fully 3D-printed flexible four-layer millimeter-wave Doppler radar (i.e., a millimeter-wave FHE system). The sensing performance and flexibility of the 3D-printed radar are characterized and validated by general field tests and bending tests, respectively. Our results demonstrate the feasibility of developing fully 3D-printed high-frequency multilayer FHE, which can be conformally integrated into irregular surfaces (e.g., vehicle bumpers) for applications such as vehicle radars and wearable electronics.

eess.SY↗

arXiv2023

Dive into the Resolution Augmentations and Metrics in Low Resolution Face Recognition: A Plain yet Effective New Baseline

Although deep learning has significantly improved Face Recognition (FR), dramatic performance deterioration may occur when processing Low Resolution (LR) faces. To alleviate this, approaches based on unified feature space are proposed with the sacrifice under High Resolution (HR) circumstances. To deal with the huge domain gap between HR and LR domains and achieve the best on both domains, we first took a closer look at the impacts of several resolution augmentations and then analyzed the difficulty of LR samples from the perspective of the model gradient produced by different resolution samples. Besides, we also find that the introduction of some resolutions could help the learning of lower resolutions. Based on these, we divide the LR samples into three difficulties according to the resolution and propose a more effective Multi-Resolution Augmentation. Then, due to the rapidly increasing domain gap as the resolution decreases, we carefully design a novel and effective metric loss based on a LogExp distance function that provides decent gradients to prevent oscillation near the convergence point or tolerance to small distance errors; it could also dynamically adjust the penalty for errors in different dimensions, allowing for more optimization of dimensions with large errors. Combining these two insights, our model could learn more general knowledge in a wide resolution range of images and balanced results can be achieved by our extremely simple framework. Moreover, the augmentations and metrics are the cornerstones of LRFR, so our method could be considered a new baseline for the LRFR task. Experiments on the LRFR datasets: SCface, XQLFW, and large-scale LRFR dataset: TinyFace demonstrate the effectiveness of our methods, while the degradation on HRFR datasets is significantly reduced.

cs.CV↗

arXiv2020

Observation of spin-momentum-layer locking in centrosymmetric BiOI

Spin polarization effects in nonmagnetic materials are generally believed as an outcome of spin-orbit coupling provided that the global inversion symmetry is lacking, also known as 'spin-momentum locking'. The recently discovered hidden spin polarization indicates that specific atomic site asymmetry could also induce measurable spin polarization, leading to a paradigm shift to centrosymmetric crystals for potential spintronic applications. Here, combining spin- and angle-resolved photoemission spectroscopy and theoretical calculations, we report distinct spin-layer locking phenomena surrounding different high-symmetry momenta in a centrosymmetric, layered material BiOI. The measured spin is highly polarized along the Brillouin zone boundary, while is almost vanishing around the zone center due to its nonsymmorphic crystal structure. Our work not only demonstrates the existence of hidden spin polarization, but also uncovers the microscopic mechanism of the way spin, momentum and layer locking to each other, shedding lights on the design metrics for future spintronic devices.

cond-mat.mtrl-sci↗

arXiv2020

Experimental Detection of the Quantum Phases of a Three-Dimensional Topological Insulator on a Spin Quantum Simulator

The detection of topological phases of matter becomes a central issue in recent years. Conventionally, the realization of a specific topological phase in condensed matter physics relies on probing the underlying surface band dispersion or quantum transport signature of a real material, which may be imperfect or even absent. On the other hand, quantum simulation offers an alternative approach to directly measure the topological invariant on a universal quantum computer. However, experimentally demonstrating high-dimensional topological phases remains a challenge due to the technical limitations of current experimental platforms. Here, we investigate the three-dimensional topological insulators in the AIII (chiral unitary) symmetry class which yet lack experimental realization. Using the nuclear magnetic resonance system, we experimentally demonstrate their topological properties, where a dynamical quenching approach is adopted and the dynamical bulk-boundary correspondence in the momentum space is observed. As a result, the topological invariants are measured with high precision on the band-inversion surface, exhibiting robustness to the decoherence effect. Our work paves the way towards the quantum simulation of topological phases of matter in higher dimensions and more complex systems through controllable quantum phases transitions.

quant-ph↗

arXiv2019

Rational design principles of quantum anomalous Hall effect from superlattice-like magnetic topological insulators

As one of paradigmatic phenomena in condensed matter physics, the quantum anomalous Hall effect (QAHE) in stoichiometric Chern insulators has drawn great interest for years. By using model Hamiltonian analysis and first-principle calculations, we establish a topological phase diagram and map on it with different two-dimensional configurations, which is taken from the recently-grown magnetic topological insulators MnBi4Te7 and MnBi6Te10 with superlattice-like stacking patterns. These configurations manifest various topological phases, including quantum spin Hall effect with and without time-reversal symmetry, as well as QAHE. We then provide design principles to trigger QAHE by tuning experimentally accessible knobs, such as slab thickness and magnetization. Our work reveals that superlattice-like magnetic topological insulators with tunable exchange interaction serve as an ideal platform to realize the long-sought QAHE in pristine compounds, paving a new avenue within the area of topological materials.

cond-mat.mes-hall↗

arXiv2019

Symmetry-assisted protection and compensation of hidden spin polarization in centrosymmetric systems

It is recently noted that in certain centrosymmetric compounds, spin-orbit interaction couples each local sector that lacks inversion symmetry and thus leads to visible spin polarization effects in the real space, dubbed as 'hidden spin polarization (HSP)'. However, observable spin polarization of a given local sector suffers interference by its inversion partner, impeding material realization and potential applications of HSP. Starting from a single-orbital tight-binding model, we propose a nontrivial way to protect strong sector-projected spin texture through minimizing the interaction between inversion partners by nonsymmorphic symmetry. The HSP effect is generally compensated by inversion partners near the Γ point but immune from interaction around the boundary of the Brillouin zone. We further summarize 17 layer groups that support such symmetry-assisted HSP and identify by first-principle calculations hundreds of quasi-2D materials from the existing databases, among which a group of rare-earth compounds LnOI (Ln = Pr, Nd, Ho, Tm and Lu) serves as great candidates showing strong Rashba- and Dresselhaus-type HSP. Our finding also provides an ideal platform to control HSP for emergent physical effects, such as opening a hybridization gap by tensile strain to realize the time-reversal-invariant topological superconductivity.

cond-mat.mes-hall↗

arXiv2018

Boundary Evolution Algorithm for SAT-NP

A boundary evolution Algorithm (BEA) is proposed by simultaneously taking into account the bottom and the high-level crossover and mutation, ie., the boundary of the hierarchical genetic algorithm. Operators and optimal individuals based on optional annealing are designed. Based on the numerous versions of genetic algorithm, the boundary evolution approach with crossover and mutation has been tested on the SAT problem and compared with two competing methods: a traditional genetic algorithm and another traditional hierarchical genetic algorithm, and among some others. The results of the comparative experiments in solving SAT problem have proved that the new hierarchical genetic algorithm based on simulated annealing and optimal individuals (BEA) can improve the success rate and convergence speed considerably for SAT problem due to its avoidance of both divergence and loss of optimal individuals, and by coronary, conducive to NP problem. Though more extensive comparisons are to be made on more algorithms, the consideration of the boundary elasticity of hierarchical genetic algorithm is an implication of evolutionary algorithm.

cs.NE↗

arXiv2018

Electronic transport in a two-dimensional superlattice engineered via self-assembled nanostructures

Nanoscience offers a unique opportunity to design modern materials from the bottom up, via low-cost, solution processed assembly of nanoscale building blocks. These systems promise electronic band structure engineering using not only the nanoscale structural modulation, but also the mesoscale spatial patterning, although experimental realization of the latter has been challenging. Here we design and fabricate a new type of artificial solid by stacking graphene on a self-assembled, nearly periodic array of nanospheres, and experimentally observe superlattice miniband effects. We find conductance dips at commensurate fillings of charge carriers per superlattice unit cell, which are key features of minibands that are induced by the quasi-periodic deformation of the graphene lattice. These dips become stronger when the lattice strain is larger. Using a tight-binding model, we simulate the effect of lattice deformation as a parameter affecting the inter-atomic hopping integral, and confirm the superlattice transport behavior. This 2D material-nanoparticle heterostructure enables facile band structure engineering via self-assembly, promising for large area electronics and optoelectronics applications.

cond-mat.mes-hall↗

arXiv2018

Strain Modulation of Graphene by Nanoscale Substrate Curvatures: A Molecular View

Spatially nonuniform strain is important for engineering the pseudomagnetic field and band structure of graphene. Despite the wide interest in strain engineering, there is still a lack of control on device-compatible strain patterns due to the limited understanding of the structure-strain relationship. Here, we study the effect of substrate corrugation and curvature on the strain profiles of graphene via combined experimental and theoretical studies of a model system: graphene on closely packed SiO2 nanospheres with different diameters (20-200 nm). Experimentally, via quantitative Raman analysis, we observe partial adhesion and wrinkle features and find that smaller nanospheres induce larger tensile strain in graphene, theoretically, molecular dynamics simulations confirm the same microscopic structure and size dependence of strain and reveal that a larger strain is caused by a stronger, inhomogeneous interaction force between smaller nanospheres and graphene. This molecular-level understanding of the strain mechanism is important for strain engineering of graphene and other two-dimensional materials.

cond-mat.mes-hall↗

arXiv2013

Quantum speed limit for arbitrary initial states

We investigate the generic bound on the minimal evolution time of the open dynamical quantum system. This quantum speed limit time is applicable to both mixed and pure initial states. We then apply this result to the damped Jaynes-Cummings model and the Ohimc-like dephasing model starting from a general time-evolution state. The bound of this time-dependent state at any point in time can be found. For the damped Jaynes-Cummings model, the corresponding bound first decreases and then increases in the Markovian dynamics. While in the non-Markovian regime, the speed limit time shows an interesting periodic oscillatory behavior. For the case of Ohimc-like dephasing model, this bound would be gradually trapped to a fixed value. In addition, the roles of the relativistic effects on the speed limit time for the observer in non-inertial frames are discussed.

quant-ph↗

arXiv2011

Coherent control of two nuclear spins using the anisotropic hyperfine interaction

We demonstrate coherent control of two nuclear spins mediated by the magnetic resonance of a hyperfine-coupled electron spin. This control is used to create a double nuclear coherence in one of the two electron spin manifolds, starting from an initial thermal state, in direct analogy to the creation of an entangled (Bell) state from an initially pure unentangled state. We identify challenges and potential solutions to obtaining experimental gate fidelities useful for quantum information processing in this type of system.

quant-ph↗