Search for Evergreens in Science: A Functional Data Analysis

Evergreens in science are papers that display a continual rise in annual citations without decline, at least within a sufficiently long time period. Aiming to better understand evergreens in particular and patterns of citation trajectory in general, this paper develops a functional data analysis method to cluster citation trajectories of a sample of 1699 research papers published in 1980 in the American Physical Society (APS) journals. We propose a functional Poisson regression model for individual papers' citation trajectories, and fit the model to the observed 30-year citations of individual papers by functional principal component analysis and maximum likelihood estimation. Based on the estimated paper-specific coefficients, we apply the K-means clustering algorithm to cluster papers into different groups, for uncovering general types of citation trajectories. The result demonstrates the existence of an evergreen cluster of papers that do not exhibit any decline in annual citations over 30 years.Comment: 40 pages, 9 figure

Minimizing Seed Set Selection with Probabilistic Coverage Guarantee in a Social Network

A topic propagating in a social network reaches its tipping point if the number of users discussing it in the network exceeds a critical threshold such that a wide cascade on the topic is likely to occur. In this paper, we consider the task of selecting initial seed users of a topic with minimum size so that with a guaranteed probability the number of users discussing the topic would reach a given threshold. We formulate the task as an optimization problem called seed minimization with probabilistic coverage guarantee (SM-PCG). This problem departs from the previous studies on social influence maximization or seed minimization because it considers influence coverage with probabilistic guarantees instead of guarantees on expected influence coverage. We show that the problem is not submodular, and thus is harder than previously studied problems based on submodular function optimization. We provide an approximation algorithm and show that it approximates the optimal solution with both a multiplicative ratio and an additive error. The multiplicative ratio is tight while the additive error would be small if influence coverage distributions of certain seed sets are well concentrated. For one-way bipartite graphs we analytically prove the concentration condition and obtain an approximation algorithm with an $O(\log n)$ multiplicative ratio and an $O(\sqrt{n})$ additive error, where $n$ is the total number of nodes in the social graph. Moreover, we empirically verify the concentration condition in real-world networks and experimentally demonstrate the effectiveness of our proposed algorithm comparing to commonly adopted benchmark algorithms.Comment: Conference version will appear in KDD 201

Unified Gas-kinetic Wave-Particle Methods III: Multiscale Photon Transport

In this paper, we extend the unified gas-kinetic wave-particle (UGKWP) method to the multiscale photon transport. In this method, the photon free streaming and scattering processes are treated in an un-splitting way. The duality descriptions, namely the simulation particle and distribution function, are utilized to describe the photon. By accurately recovering the governing equations of the unified gas-kinetic scheme (UGKS), the UGKWP preserves the multiscale dynamics of photon transport from optically thin to optically thick regime. In the optically thin regime, the UGKWP becomes a Monte Carlo type particle tracking method, while in the optically thick regime, the UGKWP becomes a diffusion equation solver. The local photon dynamics of the UGKWP, as well as the proportion of wave-described and particle-described photons are automatically adapted according to the numerical resolution and transport regime. Compared to the $S_n$ -type UGKS, the UGKWP requires less memory cost and does not suffer ray effect. Compared to the implicit Monte Carlo (IMC) method, the statistical noise of UGKWP is greatly reduced and computational efficiency is significantly improved in the optically thick regime. Several numerical examples covering all transport regimes from the optically thin to optically thick are computed to validate the accuracy and efficiency of the UGKWP method. In comparison to the $S_n$ -type UGKS and IMC method, the UGKWP method may have several-order-of-magnitude reduction in computational cost and memory requirement in solving some multsicale transport problems.Comment: 27 pages, 15 figures. arXiv admin note: text overlap with arXiv:1810.0598

Novel phase-coding method for absolute phase retrieval

This Letter presents a novel absolute phase recovery technique with phase coding. Unlike the conventional gray-coding method, the codeword is embedded into the phase and then used to determine the fringe order for absolute phase retrieval. This technique is robust because it uses phase instead of intensity to determine codewords, and it could achieve a faster measurement speed, since three additional images can represent more than 8(23) unique codewords for phase unwrapping. Experimental results will be presented to verify the performance of the proposed technique

Orbital-Energy Splitting in Anion Ordered Ruddlesden-Popper Halide Perovskites for Tunable Optoelectronic Applications

The electronic orbital characteristics at the band edges plays an important role in determining the electrical, optical and defect properties of perovskite photovoltaic materials. It is highly desirable to establish the relationship between the underlying atomic orbitals and the optoelectronic properties as a guide to maximize the photovoltaic performance. Here, using first-principles calculations and taking anion ordered Ruddlesden-Popper (RP) phase halide perovskites Cs$_{n+1}$Ge$_n$I$_{n+1}$Cl$_{2n}$ as an example, we demonstrate how to rationally optimize the optoelectronic properties (e.g., band gap, transition dipole matrix elements, carrier effective masses, band width) through a simple band structure parameter. Our results show that reducing the splitting energy $|\Delta c|$ of p orbitals of B-site atom can effectively reduce the band gap and carrier effective masses while greatly improving the optical absorption in the visible region. Thereby, the orbital-property relationship with $\Delta c$ is well established through biaxial compressive strain. Finally, it is shown that this approach can be reasonably extended to several other non-cubic halide perovskites with similar p orbitals characteristics at the conduction band edges. Therefore, we believe that our proposed orbital engineering approach provides atomic-level guidance for understanding and optimizing the device performance of layered perovskite solar cells