Authentication email has already been sent, please check your email box: and activate it as soon as possible.
You can login to My Profile and manage your email alerts.
If you haven’t received the email, please:
|
|
There are 911 papers published in subject: since this site started. |
Select Subject |
Select/Unselect all | For Selected Papers |
Saved Papers
Please enter a name for this paper to be shown in your personalized Saved Papers list
|
1. Quantum Transport Simulations of α-In2Se3 Antiferroelectric Tunnel Junctions | |||
Zhang Lingxue,Zhang Jiaxin,Sun Yuxuan,Li Wei,Quhe Ruge | |||
Physics 08 March 2024 | |||
Show/Hide Abstract | Cite this paper︱Full-text: PDF (0 B) | |||
Abstract:Due to semiconductor characteristics and non-volatile ferroelectricity, two-dimensional (2D) In2Se3 are considered as potential candidates for next-generation storage and computing devices. Based on first principles calculations, we designed antiferroelectric tunnel junctions (AFTJs) using α-In2Se3 as channels. The tunneling barrier height is controlled by the antiferroelectric to ferroelectric (AFE-FE) phase transition of the channel. A maximum current ratio up to 426 is predicted between the AFE and FE phases, enabling the two distinct memory states. By constructing two AFTJs into a calculation unit, the total current can either be fully turned on/off or function as XNOR logic with bias as inputs. Our research provides a new approach to implementing integrated storage and computing devices, making it possible for efficient data centric applications in the era of big data. | |||
TO cite this article:Zhang Lingxue,Zhang Jiaxin,Sun Yuxuan, et al. Quantum Transport Simulations of α-In2Se3 Antiferroelectric Tunnel Junctions[OL].[ 8 March 2024] http://en.paper.edu.cn/en_releasepaper/content/4762525 |
2. Resistance switching characteristic of Ag/Fe2O3/MoS2/Ag with very low switching voltage | |||
SHU Haiyan,HE Chaotao,ZHANG Xingwen,LI Shichang,CHEN Peng | |||
Physics 28 November 2023 | |||
Show/Hide Abstract | Cite this paper︱Full-text: PDF (0 B) | |||
Abstract:In this paper,the resistive switching characteristics of Ag/Fe2O3/MoS2/Ag multilayer film deposited on ITO by magnetron sputtering are investigated.The Ag/Fe2O3/MoS2/Ag device exhibits superior resistive switching behavior compared to the device without Fe2O3 layer due to the positive effect of oxygen vacancies in Fe2O3 on the formation of conducting filaments. The resistive switching ratio of the device is close to 7.0 × 105. The current value of the device drops sharply at 0.12 V when the voltage is swept forward, and the device switches from HRS back to LRS at -0.28 V when a voltage of opposite polarity is applied.The I-V curves of the device are fitted in double logarithmic coordinates, and it is found that the device is controlled by an ohmic conduction model in the low resistance state and two conduction models in the high resistance state: in the low bias region, which exhibits ohmic conduction, and at higher voltages, which is controlled by the SCLC conduction model. Such a resistive switching characteristic with very low switching voltage and high resistance ratio is of particular importance in the application of resistive stochastic storage. | |||
TO cite this article:SHU Haiyan,HE Chaotao,ZHANG Xingwen, et al. Resistance switching characteristic of Ag/Fe2O3/MoS2/Ag with very low switching voltage[OL].[28 November 2023] http://en.paper.edu.cn/en_releasepaper/content/4761573 |
3. Physics-informed Neural Network method for predicting soliton dynamics supported by complex PT-symmetric potentials | |||
LIU Ximeng,ZHANG Zhiyang,LIU Wenjun | |||
Physics 06 May 2023 | |||
Show/Hide Abstract | Cite this paper︱Full-text: PDF (0 B) | |||
Abstract:We examine the deep learning technique referred to as the physics-informed neural network method for approximating nonlinear Schr?dinger equation under considered parity time symmetric potentials and obtaining multifarious soliton solutions. For the first time, neural networks founded principally physical information are adopted to figure out the solution the examined nonlinear partial differential equation and generate six different types of soliton solutions, which are basic, dipole, tripole, quadruple, pentapole and sextupole solitons we consider. We make comparisons between the predicted and actual soliton solutions to see whether deep learning is capable of seeking the solution the partial differential equation described before. We may assess whether physics-informed neural network is capable of effectively providing approximate soliton solutions through the evaluation of squared error between the predicted and numerical results. Besides, we also scrutinize how different activation mechanisms and network architectures impact the capability of selected deep learning technique works.Through the findings we can prove that the neural networks model we established can be utilized to accurately and effectively approximate nonlinear Schr?dinger equation under consideration and predict the dynamics of soliton solution. | |||
TO cite this article:LIU Ximeng,ZHANG Zhiyang,LIU Wenjun. Physics-informed Neural Network method for predicting soliton dynamics supported by complex PT-symmetric potentials[OL].[ 6 May 2023] http://en.paper.edu.cn/en_releasepaper/content/4760642 |
4. Noise Resistance of Next Generation Reservoir Computing: A Comparative Study with High-Order Correlation Computation | |||
LIU Sheng-Yu,XIAO Jing-Hua,YAN Zi-Xiang,GAO Jian | |||
Physics 01 April 2023 | |||
Show/Hide Abstract | Cite this paper︱Full-text: PDF (0 B) | |||
Abstract:Reservoir computing (RC) methods have received more and more attention and applications in chaotic time series prediction with their simple structure and training method. Recently, the next generation reservoir computing (NG-RC) method (Nature Communications,12,5564) has been proposed with less training cost and better time-series predictions. Nevertheless, in practice, available data on dynamic systems are contaminated with noise. Though NG-RC is shown highly efficient in learning and predicting, its noise resistance captivity is not clear yet, limiting its use in practical problems. In this paper, we study the noise resistance of the NG-RC method, taking the well-known denoising method, the high-order correlation computation (HOCC) method, as a reference. Both methods have similar procedures in respect of function bases and regression processes. With the simple ridge regression method, the NG-RC method has a strong noise resistance for white noise, even better than the HOCC method. Besides, the NG-RC method also shows a good prediction ability for small color noise, while it does not provide correct reconstruct dynamics. In this paper, other than reconstruction parameters, four numerical indicators are used to check the noise resistance comprehensively, such as the training error, prediction error, prediction time, and auto-correlation prediction error, for both the short-time series and long climate predictions. Our results provide a systematic estimation of NG-RC's noise resistance capacity, which is helpful for its applications in practical problems. | |||
TO cite this article:LIU Sheng-Yu,XIAO Jing-Hua,YAN Zi-Xiang, et al. Noise Resistance of Next Generation Reservoir Computing: A Comparative Study with High-Order Correlation Computation[OL].[ 1 April 2023] http://en.paper.edu.cn/en_releasepaper/content/4759954 |
5. Quantum Transport Simulations of a Proposed Logic In-Memory Device Based on Bipolar Magnetic Semiconductor | |||
Ke Yunzhe,Yin Guoxue,Zhang Lingxue,Li Wei,Quhe Ruge | |||
Physics 20 March 2023 | |||
Show/Hide Abstract | Cite this paper︱Full-text: PDF (0 B) | |||
Abstract:To overcome the memory wall based on the von Neumann architecture, in-memory computing has been intensively studied as a potential solution. Recently, a new type of spintronic material, namely bipolar magnetic semiconductors (BMSs), draw much attention because of its opposite spin-polarized valence and conduction bands and thus facilitates electrically tunable spin transport. Here, we propose a novel logic-in-memory device with a traditional field effect transistor (FET) configuration by making use of the ferromagnetic and semiconducting features of BMSs simultaneously. Two represented BMSs (2H-VS2 and semihydrogenated graphene) are selected as the channel of FETs and the transport properties of these devices have been investigated by using ab initio quantum transport simulations. The spin polarization of the current reaches up to 98%, enabling the device to provide an ideal spin polarization signal. The distinct electronic structures under the two magnetic states and the electrically tunable spin polarization allow the devices to perform logic operations directly in situ. Two-input NAND and OR logic and non-volatile NOR logic gates can be realized with one and two BMS FETs, respectively, efficiently decreasing the integration density of logical circuits. This work provides a new route to realize fused storage and computing functions in a single transistor. | |||
TO cite this article:Ke Yunzhe,Yin Guoxue,Zhang Lingxue, et al. Quantum Transport Simulations of a Proposed Logic In-Memory Device Based on Bipolar Magnetic Semiconductor[OL].[20 March 2023] http://en.paper.edu.cn/en_releasepaper/content/4759823 |
6. Dynamical Analysis of Reservoir Computing: From Single to Few Nodes | |||
LAN Xiu-Wen, CHEN Wei, GAO Jian, YAN Zi-Xiang, XIAO Jing-Hua, XIAO Jing-Hua | |||
Physics 18 March 2023 | |||
Show/Hide Abstract | Cite this paper︱Full-text: PDF (0 B) | |||
Abstract:Reservoir computing (RC) has been widely used for learning and predicting dynamical behaviors. However, the success and power of RC lack systematic research and explanation. RC's learning process is analyzed as a nonlinear dynamic procedure to study the influence of parameters on the RC learning effect. The simplest RCs, from single to few nodes, are considered for learning various states of logistic maps. Even the simple single-node RC shows rich dynamical features in the learning process. The relationship between input training states and output predicted states is quite complicated. The phase diagram of the correspondence between input and output states is analyzed through the nonlinear stability analysis. Specifically, the appropriate parameters for learning and predicting the correct states are obtained analytically, and consistent well with numerical simulations. With the increased RC size, the region of appropriate parameters for correct states increases rapidly. For logistic maps and randomly selected RC, 30 nodes are sufficient to ensure a 90 percent success rate for predicting the correct states. The dynamical analysis of reservoir computing provides the basis for its success in learning and predicting various dynamical behaviors. | |||
TO cite this article:LAN Xiu-Wen, CHEN Wei, GAO Jian, et al. Dynamical Analysis of Reservoir Computing: From Single to Few Nodes[OL].[18 March 2023] http://en.paper.edu.cn/en_releasepaper/content/4759779 |
7. From heterogeneous network to homogeneous network: the influence of structure on synergistic epidemic spreading | |||
LIN Chang, YAN Zi-Xiang, GAO Jian, XIAO Jing-Hua, XIAO Jing-Hua | |||
Physics 18 March 2023 | |||
Show/Hide Abstract | Cite this paper︱Full-text: PDF (0 B) | |||
Abstract:Synergistic epidemic-like spreading phenomena in networked system occur in various forms in nature and human society. The networks’ structure characterized by its structural heterogeneity affects the synergistic spreading process dramatically. It was believed that the synergistic epidemic spreading follows a continuous transition on heterogeneous networks, but an explosive one on homogeneous networks. In this work, we adopt the model that interpolates between homogeneous and heterogeneous networks to generate a series of studied networks. By continuously changing the ratio of homogeneous structure α of the network, we numerically show that the interplay between the spreading transition and the structural heterogeneity of network is much more complicated. Although the explosive epidemic transition is likely to be hindered by structural heterogeneity, it could occur on completely heterogeneous network as long as the synergistic strength is sufficiently strong. The predictions of heterogeneous mean-field analysis agree with the numerical results, thus helping to understand the role of structural heterogeneity in affecting synergistic epidemic spreading. | |||
TO cite this article:LIN Chang, YAN Zi-Xiang, GAO Jian, et al. From heterogeneous network to homogeneous network: the influence of structure on synergistic epidemic spreading[OL].[18 March 2023] http://en.paper.edu.cn/en_releasepaper/content/4759760 |
8. Direct tuning of soliton microcombs in ultrahigh-Q MgF2 crystalline microresonator | |||
WANG Heng,WANG Chuan | |||
Physics 09 March 2023 | |||
Show/Hide Abstract | Cite this paper︱Full-text: PDF (0 B) | |||
Abstract:The dissipative Kerr soliton combs based on microresonators have attracted wide attention due to their high coherence and on-chip integration. Soliton microcombs have been proven to have broad application prospects in the fields of coherent communication, on-chip low-noise microwave generation, optical clock, etc. However, most applications for tuning the bandwidth of soliton microcombs use a thermoelectric cooler (TEC), which increases the complexity of the system. Here, we have fabricated a magnesium fluoride microresonator with an ultrahigh-quality factor of about 927 million. Use \'power-kicking\' technology to actively capture and stabilize solitons. Then, the bandwidth and recoil of the solitons are tuned directly by the acousto-optic modulator of the system. We have demonstrated that this technique provides more direct and concise feedback and reduces the complexity and cost of the system. | |||
TO cite this article:WANG Heng,WANG Chuan. Direct tuning of soliton microcombs in ultrahigh-Q MgF2 crystalline microresonator[OL].[ 9 March 2023] http://en.paper.edu.cn/en_releasepaper/content/4759504 |
9. Vorticity and the first class of eigenvalue system associated with SU(2) group | |||
Zheng Ran | |||
Physics 16 November 2022 | |||
Show/Hide Abstract | Cite this paper︱Full-text: PDF (0 B) | |||
Abstract:The concept of vorticity is central to many aspects of fluid dynamics. It is shown that the problem of defining a vortex in a real fluid could be discussed based on the associated quaternions. In this context and in the treatment of vortices in general, the concept of the associated SU(2) group plays such an essential role, meanwhile, in this letter, we construct the first class of eigenvalue system based on the SU(2) group associated with the vorticity in fluid dynamics. | |||
TO cite this article:Zheng Ran. Vorticity and the first class of eigenvalue system associated with SU(2) group[OL].[16 November 2022] http://en.paper.edu.cn/en_releasepaper/content/4758348 |
10. Vorticity and the Associated Quaternions | |||
Zheng Ran | |||
Physics 28 October 2022 | |||
Show/Hide Abstract | Cite this paper︱Full-text: PDF (0 B) | |||
Abstract:In this letter we provide a quaternion expression of the most primary derived field in fluid motion, describing the local spatial variation of a velocity field, to measure the isotropic expansion and the rotation of fluid particles from a new point of view. | |||
TO cite this article:Zheng Ran. Vorticity and the Associated Quaternions[OL].[28 October 2022] http://en.paper.edu.cn/en_releasepaper/content/4758285 |
Select/Unselect all | For Selected Papers |
Saved Papers
Please enter a name for this paper to be shown in your personalized Saved Papers list
|
|
About Sciencepaper Online | Privacy Policy | Terms & Conditions | Contact Us
© 2003-2012 Sciencepaper Online. unless otherwise stated