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Gang Zhang

Publications and source records attributed to Gang Zhang.

At least 91 records · Page 5Linked to original sources

The role of flexural coupling in heat dissipation from a two-dimensional layered material to its hexagonal boron nitride substrate

Understanding the limits of phononic heat dissipation from a two-dimensional layered material (2DLM) to its hexagonal boron nitride (h-BN) substrate and how it varies with the structure of the 2DLM is important for the design and thermal management of h-BN-supported nanoelectronic devices. We formulate an elasticity-based theory to model the phonon-mediated heat dissipation between a 2DLM and its h-BN substrate. By treating the h-BN substrate as a semi-infinite stack of harmonically coupled thin plates, we obtain semi-analytical expressions for the thermal boundary conductance (TBC) and interfacial phonon transmission spectrum. We evaluate the temperature-dependent TBC of the $N$-layer 2DLM (graphene or MoS$_{2}$) on different common substrates (h-BN vs. a-SiO$_{2}$) at different values of $N$. The results suggest that h-BN is substantially more effective for heat dissipation from MoS$_{2}$ than a-SiO$_{2}$ especially at large $N$. To understand the limitations of the our stack model, we also compare its predictions in the $N=\infty$ limit to those of the more exact Atomistic Green's Function model for the graphite-BN and molybdenite-BN interfaces. Our stack model provides clear insights into the key role of the flexural modes in the TBC and how the anisotropic elastic properties of h-BN affect heat dissipation.

cond-mat.mes-hall↗

Equalization Loss v2: A New Gradient Balance Approach for Long-tailed Object Detection

Recently proposed decoupled training methods emerge as a dominant paradigm for long-tailed object detection. But they require an extra fine-tuning stage, and the disjointed optimization of representation and classifier might lead to suboptimal results. However, end-to-end training methods, like equalization loss (EQL), still perform worse than decoupled training methods. In this paper, we reveal the main issue in long-tailed object detection is the imbalanced gradients between positives and negatives, and find that EQL does not solve it well. To address the problem of imbalanced gradients, we introduce a new version of equalization loss, called equalization loss v2 (EQL v2), a novel gradient guided reweighing mechanism that re-balances the training process for each category independently and equally. Extensive experiments are performed on the challenging LVIS benchmark. EQL v2 outperforms origin EQL by about 4 points overall AP with 14-18 points improvements on the rare categories. More importantly, it also surpasses decoupled training methods. Without further tuning for the Open Images dataset, EQL v2 improves EQL by 7.3 points AP, showing strong generalization ability. Codes have been released at https://github.com/tztztztztz/eqlv2

cs.CV↗

Symmetry-enforced ideal lantern-like phonons in ternary nitride Li$_6$WN$_4$

Condensed matter systems contain both fermionic and bosonic quasiparticles. Owing to the constraint imposed by the Fermi level, ideal material candidate for the emergent particles with higher-dimensional degeneracy manifold (i.e., nodal lines and nodal surfaces) has not been found in electronic systems. This paper demonstrates that according to the first-principle calculations and symmetry analysis, realistic ternary nitride Li$_6$WN$_4$ features ideal (nearly flat) nodal-surface and nodal-line structures in its phonon spectra. These nodal degeneracies are shaped like lanterns, and their existence is guaranteed by nonsymmorphic symmetry. The corresponding topological phonon surface state covers exactly half the surface Brillouin zone (BZ) and can thereby be distinguished from those of conventional nodal-line and nodal-surface semimetals. The results of our study demonstrate the existence of ideal lantern-like phonons in realistic materials, which enriches the classification of topological quantum phases and provides a good basis for investigating the interaction between nodal-line and nodal-surface phonons in a single material.

cond-mat.mtrl-sci↗

Nonadiabatic geometric quantum gates that are insensitive to qubit-frequency drifts

Quantum manipulation based on geometric phases provides a promising way towards robust quantum gates. However, in the current implementation of nonadiabatic geometric phases, operational and/or random errors tend to destruct the conditions that induce geometric phases, thereby smearing their noise-resilient feature. In a recent experiment [Y. Xu et al., Phys. Rev. Lett. 124, 230503 (2020)], high-fidelity universal geometric quantum gates have been implemented in a superconducting circuit, which are robust to different types of errors under different configurations of the geometric evolution paths. Here, we apply the path-design strategy to explain in detail why both configurations can realize universal quantum gates in a single-loop way. Meanwhile, we purposefully induce our geometric manipulation by selecting the path configuration that is robust against the qubit-frequency-drift induced error, which is the dominant error source on realistic superconducting circuits and has not been deliberately addressed. Moreover, our proposal can further integrate with the composite scheme to enhance the gate robustness, which is verified by numerical simulations. Therefore, our scheme provides a promising way towards practical realization of high-fidelity and robust nonadiabatic geometric quantum gates.

quant-ph↗

Coexistience of phononic six-fold, four-fold and three-fold excitations in ternary antimonide Zr3Ni3Sb4

Three-, four-, and six-fold excitations have significantly extended the subjects of condensed matter physics. There is an urgent need for a realistic material that can have coexisting 3-, 4-, and 6-fold excitations. However, these materials are uncommon because these excitations in electronic systems are usually broken by spin-orbit coupling (SOC) and normally far from the Fermi level. Unlike the case in electronic systems, the phonon systems with negligible SOC effect, not constrained by the Pauli exclusion principle, provide a feasible platform to realize these excitations in a wide frequency range. Hence, in this work, we demonstrate by first-principle calculations and symmetry analysis that perfect 3-, 4-, 6-fold excitations appear in the phonon dispersion rather than the band structures of Zr3Ni3Sb4, which is a well-known indirect-gap semiconductor with an Y3Au3Sb4-type structure. This material features 3-fold quadratic contact triple-point phonon, 4-fold Dirac point phonon, and 6-fold point phonon. Moreover, these nodal-point phonons are very robust to uniform strain. Two obvious phonon surface arcs of the [001] plane are extended in the whole Brillouin zone, which will facilitate their detection in future experimental studies. The current work provides an ideal model to investigate the rich excitations in a single material.

cond-mat.mtrl-sci↗

Quantum operation of fermionic systems and process tomography using Majorana fermion gates

Quantum tomography is an important tool for the characterisation of quantum operations. In this paper, we present a framework of quantum tomography in fermionic systems. Compared with qubit systems, fermions obey the superselection rule, which sets constraints on states, processes and measurements in a fermionic system. As a result, we can only partly reconstruct an operation that acts on a subset of fermion modes, and the full reconstruction always requires at least one ancillary fermion mode in addition to the subset. We also report a protocol for the full reconstruction based on gates in Majorana fermion quantum computer, including a set of circuits for realising the informationally-complete state preparation and measurement.

quant-ph↗

Real Image Super Resolution Via Heterogeneous Model Ensemble using GP-NAS

With advancement in deep neural network (DNN), recent state-of-the-art (SOTA) image superresolution (SR) methods have achieved impressive performance using deep residual network with dense skip connections. While these models perform well on benchmark dataset where low-resolution (LR) images are constructed from high-resolution (HR) references with known blur kernel, real image SR is more challenging when both images in the LR-HR pair are collected from real cameras. Based on existing dense residual networks, a Gaussian process based neural architecture search (GP-NAS) scheme is utilized to find candidate network architectures using a large search space by varying the number of dense residual blocks, the block size and the number of features. A suite of heterogeneous models with diverse network structure and hyperparameter are selected for model-ensemble to achieve outstanding performance in real image SR. The proposed method won the first place in all three tracks of the AIM 2020 Real Image Super-Resolution Challenge.

eess.IV↗

Theoretical analysis of thermal boundary conductance of MoS2-SiO2 and WS2-SiO2 interface

Understanding the physical processes involved in interfacial heat transfer is critical for the interpretation of thermometric measurements and the optimization of heat dissipation in nanoelectronic devices that are based on transition metal dichalcogenide (TMD) semiconductors. We model the phononic and electronic contributions to the thermal boundary conductance (TBC) variability for the MoS$_{2}$-SiO$_{2}$ and WS$_{2}$-SiO$_{2}$ interface. A phenomenological theory to model diffuse phonon transport at disordered interfaces is introduced and yields $G$=13.5 and 12.4 MW/K/m$^{2}$ at 300 K for the MoS$_{2}$-SiO$_{2}$ and WS$_{2}$-SiO$_{2} $ interface, respectively. We compare its predictions to those of the coherent phonon model and find that the former fits the MoS$_{2}$-SiO$_{2}$ data from experiments and simulations significantly better. Our analysis suggests that heat dissipation at the TMD-SiO$_{2}$ interface is dominated by phonons scattered diffusely by the rough interface although the electronic TBC contribution can be significant even at low electron densities ($n\leq10^{12}$ cm$^{-2}$) and may explain some of the variation in the experimental TBC data from the literature. The physical insights from our study can be useful for the development of thermally aware designs in TMD-based nanoelectronics.

cond-mat.mes-hall↗

AutoPruning for Deep Neural Network with Dynamic Channel Masking

Modern deep neural network models are large and computationally intensive. One typical solution to this issue is model pruning. However, most current pruning algorithms depend on hand crafted rules or domain expertise. To overcome this problem, we propose a learning based auto pruning algorithm for deep neural network, which is inspired by recent automatic machine learning(AutoML). A two objectives' problem that aims for the the weights and the best channels for each layer is first formulated. An alternative optimization approach is then proposed to derive the optimal channel numbers and weights simultaneously. In the process of pruning, we utilize a searchable hyperparameter, remaining ratio, to denote the number of channels in each convolution layer, and then a dynamic masking process is proposed to describe the corresponding channel evolution. To control the trade-off between the accuracy of a model and the pruning ratio of floating point operations, a novel loss function is further introduced. Preliminary experimental results on benchmark datasets demonstrate that our scheme achieves competitive results for neural network pruning.

cs.CV↗

Computable steering criterion for bipartite quantum systems

Quantum steering describes the ability of one observer to nonlocally affect the other observer's state through local measurements, which represents a new form of quantum nonlocal correlation and has potential applications in quantum information and quantum communication. In this paper, we propose a computable steering criterion that is applicable to bipartite quantum systems of arbitrary dimensions. The criterion can be used to verify a wide range of steerable states directly from a given density matrix without constructing measurement settings. Compared with the existing steering criteria, it is readily computable and testable in experiment, which can also be used to verify entanglement as all steerable quantum states are entangled.

quant-ph↗

Nonlinear steering criteria for arbitrary two-qubit quantum systems

By employing Pauli measurements, we present some nonlinear steering criteria applicable for arbitrary two-qubit quantum systems and optimized ones for symmetric quantum states. These criteria provide sufficient conditions to witness steering, which can recover the previous elegant results for some well-known states. Compared with the existing linear steering criterion and entropic criterion, ours can certify more steerable states without selecting measurement settings or correlation weights, which can also be used to verify entanglement as all steerable quantum states are entangled.

quant-ph↗

AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results

This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020. This challenge involves three tracks to super-resolve an input image for $\times$2, $\times$3 and $\times$4 scaling factors, respectively. The goal is to attract more attention to realistic image degradation for the SR task, which is much more complicated and challenging, and contributes to real-world image super-resolution applications. 452 participants were registered for three tracks in total, and 24 teams submitted their results. They gauge the state-of-the-art approaches for real image SR in terms of PSNR and SSIM.

cs.CV↗

Gate-tunable cross-plane heat dissipation in single-layer transition metal dichalcogenides

Efficient heat dissipation to the substrate is crucial for optimal device performance in nanoelectronics. We develop a theory of electronic thermal boundary conductance (TBC) mediated by remote phonon scattering for the single-layer transition metal dichalcogenide (TMD) semiconductors MoS$_{2}$ and WS$_{2}$, and model their electronic TBC with different dielectric substrates (SiO$_{2}$, HfO$_{2}$ and Al$_{2}$O$_{3}$). Our results indicate that the electronic TBC is strongly dependent on the electron density, suggesting that it can be modulated by the gate electrode in field-effect transistors, and this effect is most pronounced with Al$_{2}$O$_{3}$. Our work paves the way for the design of novel thermal devices with gate-tunable cross-plane heat-dissipative properties.

cond-mat.mes-hall↗

Magnon-magnon interaction and magnon relaxation time in ferromagnetic Cr2Ge2Te6 monolayer

Despite the intense amount of attention and huge potential of two-dimensional (2D) magnets for applications in novel magnetic, magneto-optical, magneto-thermal and magneto-electronic devices, there has yet to be a robust strategy developed to systematically understand magnon-magnon (MMI) interactions at finite temperature. In this paper, we present a first-principles theoretical method to introduce the finite temperature magnon-magnon interaction into Heisenberg Hamiltonian through a nonlinear correction energy. The Wick theorem is used to decouple the four-magnon operators to two-magnon order. We demonstrate the capabilities of this method by studying the strength of MMI in Cr2Ge2Te6 (CGT) monolayer. The spin wave spectrum at finite temperature and the time-dependent spin autocorrelation function are explored. It is found that the magnon relaxation time due to magnon-magnon scattering increases with temperature because of the reduction in magnon energy, while decreases with wavevector and external magnetic field. Our results provide a new insight to understand the magnon damping and energy dissipation in two-dimensional ferromagnetic materials.

cond-mat.mes-hall↗

Material Platforms for Defect Qubits and Single Photon Emitters

Quantum technology has grown out of quantum information theory and now provides a valuable tool that researchers from numerous fields can add to their toolbox of research methods. To date, various systems have been exploited to promote the application of quantum information processing. The systems that can be used for quantum technology include superconducting circuits, ultra-cold atoms, trapped ions, semiconductor quantum dots, and solid-state spins and emitters. In this review, we will discuss the state of the art on material platforms for spin-based quantum technology, with a focus on the progress in solid-state spins and emitters in several leading host materials, including diamond, silicon carbide, boron nitride, silicon, two-dimensional semiconductors, and other materials. We will highlight how first-principles calculations can serve as an exceptionally robust tool for finding the novel defect qubits and single photon emitters in solids, through detailed predictions of the electronic, magnetic and optical properties.

cond-mat.mtrl-sci↗

1st Place Solution of LVIS Challenge 2020: A Good Box is not a Guarantee of a Good Mask

This article introduces the solutions of the team lvisTraveler for LVIS Challenge 2020. In this work, two characteristics of LVIS dataset are mainly considered: the long-tailed distribution and high quality instance segmentation mask. We adopt a two-stage training pipeline. In the first stage, we incorporate EQL and self-training to learn generalized representation. In the second stage, we utilize Balanced GroupSoftmax to promote the classifier, and propose a novel proposal assignment strategy and a new balanced mask loss for mask head to get more precise mask predictions. Finally, we achieve 41.5 and 41.2 AP on LVIS v1.0 val and test-dev splits respectively, outperforming the baseline based on X101-FPN-MaskRCNN by a large margin.

cs.CV↗

NTIRE 2020 Challenge on Real Image Denoising: Dataset, Methods and Results

This paper reviews the NTIRE 2020 challenge on real image denoising with focus on the newly introduced dataset, the proposed methods and their results. The challenge is a new version of the previous NTIRE 2019 challenge on real image denoising that was based on the SIDD benchmark. This challenge is based on a newly collected validation and testing image datasets, and hence, named SIDD+. This challenge has two tracks for quantitatively evaluating image denoising performance in (1) the Bayer-pattern rawRGB and (2) the standard RGB (sRGB) color spaces. Each track ~250 registered participants. A total of 22 teams, proposing 24 methods, competed in the final phase of the challenge. The proposed methods by the participating teams represent the current state-of-the-art performance in image denoising targeting real noisy images. The newly collected SIDD+ datasets are publicly available at: https://bit.ly/siddplus_data.

cs.CV↗

Detecting and Studying High-Energy Collider Neutrinos with FASER at the LHC

Neutrinos are copiously produced at particle colliders, but no collider neutrino has ever been detected. Colliders, and particularly hadron colliders, produce both neutrinos and anti-neutrinos of all flavors at very high energies, and they are therefore highly complementary to those from other sources. FASER, the recently approved Forward Search Experiment at the Large Hadron Collider, is ideally located to provide the first detection and study of collider neutrinos. We investigate the prospects for neutrino studies of a proposed component of FASER, FASER$ν$, a 25cm x 25cm x 1.35m emulsion detector to be placed directly in front of the FASER spectrometer in tunnel TI12. FASER$ν$ consists of 1000 layers of emulsion films interleaved with 1-mm-thick tungsten plates, with a total tungsten target mass of 1.2 tons. We estimate the neutrino fluxes and interaction rates at FASER$ν$, describe the FASER$ν$ detector, and analyze the characteristics of the signals and primary backgrounds. For an integrated luminosity of 150 fb$^{-1}$ to be collected during Run 3 of the 14 TeV Large Hadron Collider from 2021-23, and assuming standard model cross sections, approximately 1300 electron neutrinos, 20,000 muon neutrinos, and 20 tau neutrinos will interact in FASER$ν$, with mean energies of 600 GeV to 1 TeV, depending on the flavor. With such rates and energies, FASER will measure neutrino cross sections at energies where they are currently unconstrained, will bound models of forward particle production, and could open a new window on physics beyond the standard model.

hep-ex↗