Electromagnetic multipoles have been broadly adopted as a fundamental language throughout photonics, of which general features such as radiation patterns and polarization distributions are ...generically known, while their singularities and topological properties have mostly been left unattended. Here we map all the singularities of multipolar radiations of different orders, identify their indices, and show explicitly that the index sum over the entire momentum sphere is always 2, consistent with the Poincaré-Hopf theorem. Upon those revealed properties, we attribute the formation of bound states in the continuum to the overlapping of multipolar singularities with open radiation channels. This insight unveils a subtle equivalence between indices of multipolar singularities and topological charges of those bound states. Our work has fused two fundamental and sweeping concepts of multipoles and topologies, which can potentially bring unforeseen opportunities for many multipole-related fields within and beyond photonics.
Full text
Available for:
CMK, CTK, FMFMET, NUK, UL
To supplement missing logging information without increasing economic cost, a machine learning method to generate synthetic well logs from the existing log data was presented, and the experimental ...verification and application effect analysis were carried out. Since the traditional Fully Connected Neural Network (FCNN) is incapable of preserving spatial dependency, the Long Short-Term Memory (LSTM) network, which is a kind of Recurrent Neural Network (RNN), was utilized to establish a method for log reconstruction. By this method, synthetic logs can be generated from series of input log data with consideration of variation trend and context information with depth. Besides, a cascaded LSTM was proposed by combining the standard LSTM with a cascade system. Testing through real well log data shows that: the results from the LSTM are of higher accuracy than the traditional FCNN; the cascaded LSTM is more suitable for the problem with multiple series data; the machine learning method proposed provides an accurate and cost effective way for synthetic well log generation.
In this study, we propose an ensemble long short‐term memory (EnLSTM) network, which can be trained on a small data set and process sequential data. The EnLSTM is built by combining the ensemble ...neural network and the cascaded LSTM network to leverage their complementary strengths. Two perturbation methods are applied to resolve the issues of overconvergence and disturbance compensation. The EnLSTM is compared with commonly used models on a published data set and proven to be the state‐of‐the‐art model in generating well logs. In the case study, 12 well logs that cannot be measured while drilling are generated based on the logs available in the drilling process. The EnLSTM is capable of reducing cost and saving time in practice.
Plain Language Summary
A novel neural network, called EnLSTM, is proposed by combining the ensemble neural network, which has good performance on small‐data problems, and the cascaded long short‐term memory network, which is effective at processing sequential data. The EnLSTM's capability of processing sequential data based on a small data set is especially suitable for generating synthetic well logs. In addition, two perturbation methods are used to ensure that the EnLSTM can be fully trained in practice. In the experiments, the EnLSTM achieved the current best results on a published well log data set, and its application value is verified in a case study.
Key Points
We proposed an ensemble long short‐term memory (EnLSTM) network to process sequential data based on a small dataset
The EnLSTM solved a well log generation problem with higher prediction accuracy than the previously best model on a published dataset
The EnLSTM accurately generated 12 hard‐to‐measure well logs based on LWD logs, resulting in a reduction of cost and time in practice
Core concepts in singular optics, especially the polarization singularities, have rapidly penetrated the surging fields of topological and non-Hermitian photonics. For open photonic structures with ...non-Hermitian degeneracies in particular, polarization singularities would inevitably encounter another sweeping concept of Berry phase. Several investigations have discussed, in an inexplicit way, connections between both concepts, hinting at that nonzero topological charges for far-field polarizations on a loop are inextricably linked to its nontrivial Berry phase when degeneracies are enclosed. In this work, we reexamine the seminal photonic crystal slab that supports the fundamental two-level non-Hermitian degeneracies. Regardless of the invariance of nontrivial Berry phase (concerning near-field Bloch modes defined on the momentum torus) for different loops enclosing both degeneracies, we demonstrate that the associated far polarization fields (defined on the momentum sphere) exhibit topologically inequivalent patterns that are characterized by variant topological charges, including even the trivial scenario of zero charge. Moreover, the charge carried by the Fermi arc actually is not well defined, which could be different on opposite bands. It is further revealed that for both bands, the seemingly complex evolutions of polarizations are bounded by the global charge conservation, with extra points of circular polarizations playing indispensable roles. This indicates that although not directly associated with any local charges, the invariant Berry phase is directly linked to the globally conserved charge, physical principles underlying which have all been further clarified by a two-level Hamiltonian with an extra chirality term. Our work can potentially trigger extra explorations beyond photonics connecting Berry phase and singularities.
Many novel properties of non-Hermitian systems are found at or near the exceptional points-branch points of complex energy surfaces at which eigenvalues and eigenvectors coalesce. In particular, ...higher-order exceptional points can result in optical structures that are ultrasensitive to external perturbations. Here we show that an arbitrary order exceptional point can be achieved in a simple system consisting of identical resonators placed near a waveguide. Unidirectional coupling between any two chiral dipolar states of the resonators mediated by the waveguide mode leads to the exceptional point, which is protected by the transverse spin-momentum locking of the guided wave and is independent of the positions of the resonators. Various analytic response functions of the resonators at the exceptional points are experimentally manifested in the microwave regime. The enhancement of sensitivity to external perturbations near the exceptional point is also numerically and analytically demonstrated.
•Constructed TgDLF to deal with short-term load forecasting by combining domain knowledge and machine learning algorithms.•Proposed a load ratio decomposition method to obtain dimensionless trend and ...local fluctuation.•Increased the model's robustness to inaccurate weather forecast data by adding synthetic disturbances.•Discovered that the prediction error of TgDLF is 23% lower than the long short-term memory, and the TgDLF with enhanced robustness can extract effective information from the weather forecast data with up to 40% noise.
Electricity constitutes an indispensable source of secondary energy in modern society. Accurate and robust short-term electrical load forecasting is essential for more effective scheduling of load generation, minimizing the gap between generation and demand, and reducing electricity losses. This study proposes theory-guided deep-learning load forecasting (TgDLF), which is a gradient-free model that fully combines domain knowledge and machine learning algorithms. TgDLF predicts the future load through load ratio decomposition, in which dimensionless trends are obtained based on domain knowledge, and the local fluctuations are estimated via data-driven models. TgDLF simplifies the problem with the assistance of expertise, and utilizes the strong expressive power of neural networks to obtain accurate predictions. The historical load, weather forecast and calendar effect are considered in the model, and the model's robustness to inaccurate weather forecast data is improved by adding synthetic disturbance during the training process. Cross-validation experiments demonstrate that TgDLF is 23% more accurate than long short-term memory, and the TgDLF with enhanced robustness can effectively extract information from weather forecast data with up to 40% noise.
Display omitted
Epidemiology of urolithiasis in Asia Liu, Yu; Chen, Yuntian; Liao, Banghua ...
Asian Journal of Urology,
10/2018, Volume:
5, Issue:
4
Journal Article
Peer reviewed
Open access
In Asia, about 1%–19.1% of the population suffer from urolithiasis. However, due to variations in socio-economic status and geographic locations, the prevalence and incidence have changed in ...different countries or regions over the years. The research for risk factors of urinary tract stones is of predominant importance. In this review, we find the prevalence of urolithiasis is 5%–19.1% in West Asia, Southeast Asia, South Asia, as well as some developed countries (South Korea and Japan), whereas, it is only 1%–8% in most part of East Asia and North Asia. The recurrence rate ranges from 21% to 53% after 3–5 years. Calcium oxalate (75%–90%) is the most frequent component of calculi, followed by uric acid (5%−20%), calcium phosphate (6%−13%), struvite (2%−15%), apatite (1%) and cystine (0.5%−1%). The incidence of urolithiasis reaches its peak in population aged over 30 years. Males are more likely to suffer from urinary calculi. Because of different dietary habits or genetic background, differences of prevalence among races or nationalities also exist. Genetic mutation of specific locus may contribute to the formation of different kinds of calculi. Dietary habits (westernized dietary habits and less fluid intake), as well as climatic factors (hot temperature and many hours of exposure to sunshine) play a crucial role in the development of stones. Other diseases, especially metabolic syndrome, may also contribute to urinary tract stones.
Partial differential equations (PDEs) are concise and understandable representations of domain knowledge, which are essential for deepening our understanding of physical processes and predicting ...future responses. However, the PDEs of many real-world problems are uncertain, which calls for PDE discovery. We propose the symbolic genetic algorithm to discover open-form PDEs (SGA-PDE) directly from data without prior knowledge about the equation structure. SGA-PDE focuses on the representation and optimization of PDEs. Firstly, SGA-PDE uses symbolic mathematics to realize the flexible representation of any given PDE, transforms a PDE into a forest, and converts each function term into a binary tree. Secondly, SGA-PDE adopts a specially designed genetic algorithm to efficiently optimize the binary trees by iteratively updating the tree topology and node attributes. The SGA-PDE is gradient free, which is a desirable characteristic in PDE discovery since it is difficult to obtain the gradient between the PDE loss and the PDE structure. In the experiment, SGA-PDE not only successfully discovered the nonlinear Burgers’ equation, the Korteweg–de Vries equation, and the Chafee-Infante equation but also handled PDEs with fractional structure and compound functions that cannot be solved by conventional PDE discovery methods.
Full text
Available for:
CMK, CTK, FMFMET, NUK, UL
The concept of gauge field is a cornerstone of modern physics and the synthetic gauge field has emerged as a new way to manipulate particles in many disciplines. In optics, several schemes of Abelian ...synthetic gauge fields have been proposed. Here, we introduce a new platform for realizing synthetic SU(2) non-Abelian gauge fields acting on two-dimensional optical waves in a wide class of anisotropic materials and discover novel phenomena. We show that a virtual non-Abelian Lorentz force arising from material anisotropy can induce light beams to travel along Zitterbewegung trajectories even in homogeneous media. We further design an optical non-Abelian Aharonov-Bohm system which results in the exotic spin density interference effect. We can extract the Wilson loop of an arbitrary closed optical path from a series of gauge fixed points in the interference fringes. Our scheme offers a new route to study SU(2) gauge field related physics using optics.
PDF
