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Prolonging Carrier Lifetime in P-type 4H-SiC Epilayer by Thermal Oxidation and Hydrogen Annealing
Authors:
Ruijun Zhang,
Mingkun Zhang,
Guoliang Zhang,
Yujian Chen,
Jia Liu,
Ziqian Tian,
Ye Yu,
Peng Zhao,
Shaoxiong Wu,
Yuning Zhang,
Dingqu Lin,
Xiaping Chen,
Jiafa Cai,
Rongdun Hong,
Feng Zhang
Abstract:
A minority carrier lifetime of 25.46 $μ$s in a P-type 4H-SiC epilayer has been attained through sequential thermal oxidation and hydrogen annealing. Thermal oxidation can enhance the minority carrier lifetime in the 4H-SiC epilayer by reducing carbon vacancies. However, this process also generates carbon clusters with limited diffusivity and contributes to the enlargement of surface pits on the 4H…
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A minority carrier lifetime of 25.46 $μ$s in a P-type 4H-SiC epilayer has been attained through sequential thermal oxidation and hydrogen annealing. Thermal oxidation can enhance the minority carrier lifetime in the 4H-SiC epilayer by reducing carbon vacancies. However, this process also generates carbon clusters with limited diffusivity and contributes to the enlargement of surface pits on the 4H-SiC. High-temperature hydrogen annealing effectively reduces stacking fault and dislocation density. Moreover, electron spin resonance analysis indicates a significant reduction in carbon vacancy defects after hydrogen annealing. The mechanisms of the elimination of carbon vacancies by hydrogen annealing include the decomposition of carbon clusters formed during thermal oxidation and the low-pressure selective etching by hydrogen, which increases the carbon content on the 4H-SiC surface and facilitates carbon diffusion. Consequently, the combination of thermal oxidation and hydrogen annealing eliminates carbon vacancies more effectively, substantially enhancing the minority carrier lifetime in P-type 4H-SiC. This improvement is advantageous for the application of high-voltage SiC bipolar devices.
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Submitted 15 December, 2024; v1 submitted 16 November, 2024;
originally announced November 2024.
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Entanglement scaling and criticality of infinite-size quantum many-body systems in continuous space addressed by a tensor network approach
Authors:
Rui Hong,
Hao-Wei Cui,
An-Chun Ji,
Shi-Ju Ran
Abstract:
Simulating strongly-correlated quantum systems in continuous space belongs to the most challenging and long-concerned issues in quantum physics. This work investigates the quantum entanglement and criticality of the ground-state wave-functions of infinitely-many coupled quantum oscillators (iCQOs). The essential task involves solving a set of partial differential equations (Schrödinger equations i…
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Simulating strongly-correlated quantum systems in continuous space belongs to the most challenging and long-concerned issues in quantum physics. This work investigates the quantum entanglement and criticality of the ground-state wave-functions of infinitely-many coupled quantum oscillators (iCQOs). The essential task involves solving a set of partial differential equations (Schrödinger equations in the canonical quantization picture) with infinitely-many variables, which currently lacks valid methods. By extending the imaginary-time evolution algorithm with translationally-invariant functional tensor network, we simulate the ground state of iCQOs with the presence of two- and three-body couplings. We determine the range of coupling strengths where there exists a real ground-state energy (dubbed as physical region). With two-body couplings, we reveal the logarithmic scaling law of entanglement entropy (EE) and the polynomial scaling law of correlation length against the virtual bond dimension $χ$ at the dividing point of physical and non-physical regions. These two scaling behaviors are signatures of criticality, according to the previous results in quantum lattice models, but were not reported in continuous-space quantum systems. The scaling coefficients result in a central charge $c=1$, indicating the presence of free boson conformal field theory (CFT). We further show that the presence of three-body couplings, for which there are no analytical or numerical results, breaks down the CFT description at the dividing point. Our work reveals the scaling behaviors of EE in continuous-space quantum many-body systems. These results provide strong numerical evidence supporting the efficiency of TN in representing continuous-space quantum wave-functions in the thermodynamic limit and offer an efficient approach to studying entanglement properties and criticality in continuous space.
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Submitted 13 June, 2025; v1 submitted 31 October, 2024;
originally announced October 2024.
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Functional Tensor Network Solving Many-body Schrödinger Equation
Authors:
Rui Hong,
Ya-Xuan Xiao,
Jie Hu,
An-Chun Ji,
Shi-Ju Ran
Abstract:
Schrödinger equation belongs to the most fundamental differential equations in quantum physics. However, the exact solutions are extremely rare, and many analytical methods are applicable only to the cases with small perturbations or weak correlations. Solving the many-body Schrödinger equation in the continuous spaces with the presence of strong correlations is an extremely important and challeng…
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Schrödinger equation belongs to the most fundamental differential equations in quantum physics. However, the exact solutions are extremely rare, and many analytical methods are applicable only to the cases with small perturbations or weak correlations. Solving the many-body Schrödinger equation in the continuous spaces with the presence of strong correlations is an extremely important and challenging issue. In this work, we propose the functional tensor network (FTN) approach to solve the many-body Schrödinger equation. Provided the orthonormal functional bases, we represent the coefficients of the many-body wave-function as tensor network. The observables, such as energy, can be calculated simply by tensor contractions. Simulating the ground state becomes solving a minimization problem defined by the tensor network. An efficient gradient-decent algorithm based on the automatically differentiable tensors is proposed. We here take matrix product state (MPS) as an example, whose complexity scales only linearly with the system size. We apply our approach to solve the ground state of coupled harmonic oscillators, and achieve high accuracy by comparing with the exact solutions. Reliable results are also given with the presence of three-body interactions, where the system cannot be decoupled to isolated oscillators. Our approach is simple and with well-controlled error, superior to the highly-nonlinear neural-network solvers. Our work extends the applications of tensor network from quantum lattice models to the systems in the continuous space. FTN can be used as a general solver of the differential equations with many variables. The MPS exemplified here can be generalized to, e.g., the fermionic tensor networks, to solve the electronic Schrödinger equation.
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Submitted 30 January, 2022;
originally announced January 2022.
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Predicting Quantum Potentials by Deep Neural Network and Metropolis Sampling
Authors:
Rui Hong,
Peng-Fei Zhou,
Bin Xi,
Jie Hu,
An-Chun Ji,
Shi-Ju Ran
Abstract:
The hybridizations of machine learning and quantum physics have caused essential impacts to the methodology in both fields. Inspired by quantum potential neural network, we here propose to solve the potential in the Schrodinger equation provided the eigenstate, by combining Metropolis sampling with deep neural network, which we dub as Metropolis potential neural network (MPNN). A loss function is…
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The hybridizations of machine learning and quantum physics have caused essential impacts to the methodology in both fields. Inspired by quantum potential neural network, we here propose to solve the potential in the Schrodinger equation provided the eigenstate, by combining Metropolis sampling with deep neural network, which we dub as Metropolis potential neural network (MPNN). A loss function is proposed to explicitly involve the energy in the optimization for its accurate evaluation. Benchmarking on the harmonic oscillator and hydrogen atom, MPNN shows excellent accuracy and stability on predicting not just the potential to satisfy the Schrodinger equation, but also the eigen-energy. Our proposal could be potentially applied to the ab-initio simulations, and to inversely solving other partial differential equations in physics and beyond.
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Submitted 8 August, 2021; v1 submitted 6 June, 2021;
originally announced June 2021.
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Automatically Differentiable Quantum Circuit for Many-qubit State Preparation
Authors:
Peng-Fei Zhou,
Rui Hong,
Shi-Ju Ran
Abstract:
Constructing quantum circuits for efficient state preparation belongs to the central topics in the field of quantum information and computation. As the number of qubits grows fast, methods to derive large-scale quantum circuits are strongly desired. In this work, we propose the automatically differentiable quantum circuit (ADQC) approach to efficiently prepare arbitrary quantum many-qubit states.…
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Constructing quantum circuits for efficient state preparation belongs to the central topics in the field of quantum information and computation. As the number of qubits grows fast, methods to derive large-scale quantum circuits are strongly desired. In this work, we propose the automatically differentiable quantum circuit (ADQC) approach to efficiently prepare arbitrary quantum many-qubit states. A key ingredient is to introduce the latent gates whose decompositions give the unitary gates that form the quantum circuit. The circuit is optimized by updating the latent gates using back propagation to minimize the distance between the evolved and target states. Taking the ground states of quantum lattice models and random matrix product states as examples, with the number of qubits where processing the full coefficients is unlikely, ADQC obtains high fidelities with small numbers of layers $N_L \sim O(1)$. Superior accuracy is reached compared with the existing state-preparation approach based on the matrix product disentangler. The parameter complexity of MPS can be significantly reduced by ADQC with the compression ratio $r \sim O(10^{-3})$. Our work sheds light on the "intelligent construction" of quantum circuits for many-qubit systems by combining with the machine learning methods.
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Submitted 30 April, 2021;
originally announced April 2021.
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Effect of Interfacial Dipole on Heterogeneous Ice Nucleation
Authors:
Hao Lu,
Quanming Xu,
Jianyang Wu,
Rongdun Hong,
Zhisen Zhang
Abstract:
In this letter, we performed molecular dynamics simulations of ice nucleation on a rigid surface model of cubic zinc blende structure with different surface dipole strength and orientation. It follows that, despite the excellent lattice match between cubic ice and substrates, the ice nucleation happened only when the interfacial water molecules (IWs) have the same or similar orientations as that o…
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In this letter, we performed molecular dynamics simulations of ice nucleation on a rigid surface model of cubic zinc blende structure with different surface dipole strength and orientation. It follows that, despite the excellent lattice match between cubic ice and substrates, the ice nucleation happened only when the interfacial water molecules (IWs) have the same or similar orientations as that of the water molecules in cubic ice. The free energy landscapes revealed that, for substrates with improper dipole strength/orientation, large free energy barriers arose to prevent the dipole of IWs rotating to the right orientation to trigger ice formation. Our results suggest that the traditional concept of lattice match, the similarity of lattice length between a substrate and the new-formed crystalline, should be extended to a broader match include the similarity between the molecular orientations of the interfacial component and the component in the specific new-formed crystalline face.
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Submitted 15 April, 2021;
originally announced April 2021.
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Influence of geometric structure, convection, and eddy on sound propagation in acoustic metamaterial with turbulent flow
Authors:
Myong Chol Pak,
Kwang-Il Kim,
Hak Chol Pak,
Kwon Ryong Hong
Abstract:
The problem of reducing noise in the transportation is an important research field to prevent accidents and to provide a civilized environment for people. A material that has recently attracted attention in research to reduce noise is acoustic metamaterial, and most of the research projects so far have been limited to the case of static media without flow. We have studied the sound transmission pr…
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The problem of reducing noise in the transportation is an important research field to prevent accidents and to provide a civilized environment for people. A material that has recently attracted attention in research to reduce noise is acoustic metamaterial, and most of the research projects so far have been limited to the case of static media without flow. We have studied the sound transmission properties of acoustic metamaterial with turbulent flow to develop acoustic metamaterial that be used in transportation. In this paper, the effect of geometrical structure, the convective effect, and the eddy effect on sound propagation in acoustic metamaterial with turbulent flow are investigated, and the relationships between them are analyzed. The convective effect and the eddy effect both reduce the resonant strength of sound transmission loss resulting from the unique geometry of the acoustic crystal, but shift the resonant frequencies in opposite directions. In addition, when the convective effect and the eddy effect of the airflow, as well as the intrinsic interaction effect generated from the unique geometrical structure of the acoustic metamaterial cannot be ignored, they exhibit competition phenomena with each other, resulting in a widening of the resonance peak. As a result, these three effects cause the shift of the resonance frequency of the sound transmission loss and the widening of the resonance peak. The results of this study show that even in the case of turbulent flow, acoustic metamaterial can be used for transportation by properly controlling the geometric size and shape of the acoustic metamaterial.
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Submitted 22 December, 2020;
originally announced December 2020.
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The Effect of Dipole from $γ$-AgI Substrates on Heterogeneous Ice Nucleation
Authors:
Hao Lu,
Quanming Xu,
Chaohong Wang,
Jianyang Wu,
Rongdun Hong,
Xiang-Yang Liu,
Zhisen Zhang
Abstract:
Heterogeneous ice nucleation is one of the most common and important process in the physical environment. AgI has been proved to be an effective ice nucleating agent in the process of ice nucleation. However, the microscopic mechanism of AgI in heterogeneous ice nucleation has not been fully understood. Molecular dynamics simulations are applied to investigate the ability of which kinds of $γ$-AgI…
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Heterogeneous ice nucleation is one of the most common and important process in the physical environment. AgI has been proved to be an effective ice nucleating agent in the process of ice nucleation. However, the microscopic mechanism of AgI in heterogeneous ice nucleation has not been fully understood. Molecular dynamics simulations are applied to investigate the ability of which kinds of $γ$-AgI substrate can promote ice nucleation by changing the dipole of $γ$-AgI on the substrate, we conclude that the dipole of $γ$-AgI on the substrate can affect the conformation of ice nucleation. The surface ions with positive charge on the substrate may promote ice nucleation, while there is no ice nucleation founded on the surface ions with negative charge. $γ$-AgI substrates affect ice nucleation through adjust the orientations of water molecules near the surfaces.
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Submitted 23 August, 2020;
originally announced August 2020.
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Spontaneous emission of a quantum emitter near a Chern insulator: interplay of time reversal symmetry breaking and van Hove singularity
Authors:
Bing-Sui Lu,
Khatee Zathul Arifa,
Xing Ru Hong
Abstract:
We consider the generic problem of a two-level quantum emitter near a two-dimensional Chern insulator in the dipole approximation, and study how the frequency-dependent response and electronic density of states of the insulator modifies the transition rate of the emitter between the ground and excited levels. To this end, we obtain the full real-frequency behavior of the conductivity tensor by per…
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We consider the generic problem of a two-level quantum emitter near a two-dimensional Chern insulator in the dipole approximation, and study how the frequency-dependent response and electronic density of states of the insulator modifies the transition rate of the emitter between the ground and excited levels. To this end, we obtain the full real-frequency behavior of the conductivity tensor by performing a tight-binding calculation based on the Qi-Wu-Zhang model and using a Kubo formula, and derive the full electromagnetic Green tensor of the system, which breaks Onsager reciprocity. This enables us to find that for frequencies smaller than the maximum band gap, the system is sensitive to time reversal symmetry-breaking, whereas for much larger frequencies the system becomes insensitive, with implications for the discrimination of the state of a circularly polarised dipole emitter. We also study the impact of a van Hove singularity on the surface-induced correction to the transition rate, finding that it can enhance its amplitude by a few orders of magnitude compared to the case where the conductivity is set to its static value. By considering configurations in which the dipole is circularly polarised or parallel with the surface of the Chern insulator, we find that the surface correction to the transition rate can exhibit a novel decay with sine integral-like oscillations.
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Submitted 11 May, 2020; v1 submitted 10 March, 2020;
originally announced March 2020.
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Classification and prediction of wave chaotic systems with machine learning techniques
Authors:
Shukai Ma,
Bo Xiao,
Ron Hong,
Bisrat Addissie,
Zachary Drikas,
Thomas Antonsen,
Edward Ott,
Steven Anlage
Abstract:
The wave properties of complex scattering systems that are large compared to the wavelength, and show chaos in the classical limit, are extremely sensitive to system details. A solution to the wave equation for a specific configuration can change substantially under small perturbations. Due to this extreme sensitivity, it is difficult to discern basic information about a complex system simply from…
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The wave properties of complex scattering systems that are large compared to the wavelength, and show chaos in the classical limit, are extremely sensitive to system details. A solution to the wave equation for a specific configuration can change substantially under small perturbations. Due to this extreme sensitivity, it is difficult to discern basic information about a complex system simply from scattering data as a function of energy or frequency, at least by eye. In this work, we employ supervised machine learning algorithms to reveal and classify hidden information about the complex scattering system presented in the data. As an example we are able to distinguish the total number of connected cavities in a linear chain of weakly coupled lossy enclosures from measured reflection data. A predictive machine learning algorithm for the future states of a perturbed complex scattering system is also trained with a recurrent neural network. Given a finite training data series, the reflection/transmission properties can be forecast by the proposed algorithm.
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Submitted 13 August, 2019;
originally announced August 2019.
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Avalanche dynamics driven by adaptive rewirings in complex networks
Authors:
K. Rho,
S. R. Hong,
B. Kahng
Abstract:
We introduce a toy model displaying the avalanche dynamics of failure in scale-free networks. In the model, the network growth is based on the Barabási and Albert model and each node is assigned a capacity or tolerance, which is constant irrespective of node index. The degree of each node increases over time. When the degree of a node exceeds its capacity, it fails and each link connected to it…
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We introduce a toy model displaying the avalanche dynamics of failure in scale-free networks. In the model, the network growth is based on the Barabási and Albert model and each node is assigned a capacity or tolerance, which is constant irrespective of node index. The degree of each node increases over time. When the degree of a node exceeds its capacity, it fails and each link connected to it is is rewired to other unconnected nodes by following the preferential attachment rule. Such a rewiring edge may trigger another failure. This dynamic process can occur successively, and it exhibits a self-organized critical behavior in which the avalanche size distribution follows a power law. The associated exponent is $τ\approx 2.6(1)$. The entire system breaks down when any rewired edges cannot locate target nodes: the time at which this occurs is referred to as the breaking time. We obtain the breaking time as a function of the capacity. Moreover, using extreme value statistics, we determine the distribution function of the breaking time.
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Submitted 1 September, 2005; v1 submitted 29 August, 2005;
originally announced August 2005.