arXiv subjects

Wei Lu

Publications and source records attributed to Wei Lu.

At least 397 records · Page 22Linked to original sources

arXiv2015

From Competition to Complementarity: Comparative Influence Diffusion and Maximization

Influence maximization is a well-studied problem that asks for a small set of influential users from a social network, such that by targeting them as early adopters, the expected total adoption through influence cascades over the network is maximized. However, almost all prior work focuses on cascades of a single propagating entity or purely-competitive entities. In this work, we propose the Comparative Independent Cascade (Com-IC) model that covers the full spectrum of entity interactions from competition to complementarity. In Com-IC, users' adoption decisions depend not only on edge-level information propagation, but also on a node-level automaton whose behavior is governed by a set of model parameters, enabling our model to capture not only competition, but also complementarity, to any possible degree. We study two natural optimization problems, Self Influence Maximization and Complementary Influence Maximization, in a novel setting with complementary entities. Both problems are NP-hard, and we devise efficient and effective approximation algorithms via non-trivial techniques based on reverse-reachable sets and a novel "sandwich approximation". The applicability of both techniques extends beyond our model and problems. Our experiments show that the proposed algorithms consistently outperform intuitive baselines in four real-world social networks, often by a significant margin. In addition, we learn model parameters from real user action logs.

cs.SI↗

arXiv2015

Lorentz boosted frame simulation of Laser wakefield acceleration in quasi-3D geometry

When modeling laser wakefield acceleration (LWFA) using the particle-in-cell (PIC) algorithm in a Lorentz boosted frame, the plasma is drifting relativistically at $β_b c$ towards the laser, which can lead to a computational speedup of $\sim γ_b^2=(1-β_b^2)^{-1}$. Meanwhile, when LWFA is modeled in the quasi-3D geometry in which the electromagnetic fields and current are decomposed into a limited number of azimuthal harmonics, speedups are achieved by modeling three dimensional problems with the computation load on the order of two dimensional $r-z$ simulations. Here, we describe how to combine the speed ups from the Lorentz boosted frame and quasi-3D algorithms. The key to the combination is the use of a hybrid Yee-FFT solver in the quasi-3D geometry that can be used to effectively eliminate the Numerical Cerenkov Instability (NCI) that inevitably arises in a Lorentz boosted frame due to the unphysical coupling of Langmuir modes and EM modes of the relativistically drifting plasma in these simulations. In addition, based on the space-time distribution of the LWFA data in the lab and boosted frame, we propose to use a moving window to follow the drifting plasma to further reduce the computational load. We describe the details of how the NCI is eliminated for the quasi-3D geometry, the setups for simulations which combine the Lorentz boosted frame and quasi-3D geometry, the use of a moving window, and compare the results from these simulations against their corresponding lab frame cases. Good agreement is obtained, particularly when there is no self-trapping, which demonstrates it is possible to combine the Lorentz boosted frame and the quasi-3D algorithms when modeling LWFA to achieve unprecedented speedups.

physics.plasm-ph↗

arXiv2015

Show Me the Money: Dynamic Recommendations for Revenue Maximization

Recommender Systems (RS) play a vital role in applications such as e-commerce and on-demand content streaming. Research on RS has mainly focused on the customer perspective, i.e., accurate prediction of user preferences and maximization of user utilities. As a result, most existing techniques are not explicitly built for revenue maximization, the primary business goal of enterprises. In this work, we explore and exploit a novel connection between RS and the profitability of a business. As recommendations can be seen as an information channel between a business and its customers, it is interesting and important to investigate how to make strategic dynamic recommendations leading to maximum possible revenue. To this end, we propose a novel \model that takes into account a variety of factors including prices, valuations, saturation effects, and competition amongst products. Under this model, we study the problem of finding revenue-maximizing recommendation strategies over a finite time horizon. We show that this problem is NP-hard, but approximation guarantees can be obtained for a slightly relaxed version, by establishing an elegant connection to matroid theory. Given the prohibitively high complexity of the approximation algorithm, we also design intelligent heuristics for the original problem. Finally, we conduct extensive experiments on two real and synthetic datasets and demonstrate the efficiency, scalability, and effectiveness our algorithms, and that they significantly outperform several intuitive baselines.

cs.DB↗

arXiv2015

Viral Marketing Meets Social Advertising: Ad Allocation with Minimum Regret

In this paper, we study the problem of allocating ads to users through the viral-marketing lens. Advertisers approach the host with a budget in return for the marketing campaign service provided by the host. We show that allocation that takes into account the propensity of ads for viral propagation can achieve significantly better performance. However, uncontrolled virality could be undesirable for the host as it creates room for exploitation by the advertisers: hoping to tap uncontrolled virality, an advertiser might declare a lower budget for its marketing campaign, aiming at the same large outcome with a smaller cost. This creates a challenging trade-off: on the one hand, the host aims at leveraging virality and the network effect to improve advertising efficacy, while on the other hand the host wants to avoid giving away free service due to uncontrolled virality. We formalize this as the problem of ad allocation with minimum regret, which we show is NP-hard and inapproximable w.r.t. any factor. However, we devise an algorithm that provides approximation guarantees w.r.t. the total budget of all advertisers. We develop a scalable version of our approximation algorithm, which we extensively test on four real-world data sets, confirming that our algorithm delivers high quality solutions, is scalable, and significantly outperforms several natural baselines.

cs.SI↗

arXiv2015

Ultrasensitive and broadband MoS2 photodetector driven by ferroelectrics

Photodetectors based on two dimensional materials have attracted growing interest. However, the sensitivity is still unsatisfactory even under high gate voltage. Here we demonstrate a MoS2 photodetector with a poly(vinylidene fluoride-trifluoroethylene) ferroelectric layer in place of the oxide layer in a traditional field effect transistor. The dark current of the photodetector is strongly suppressed by ferroelectric polarization. A high detectivity 2.21012 Jones) and photoresponsitivity (2570 A W) detector has been achieved under ZERO gate bias at a wavelength of 635 nm. Most strikingly, the band gap of few-layer MoS2 can be tuned by the ultra-high electrostatic field from the ferroelectric polarization. With this characteristic, photoresponse wavelengths of the photodetector are extended into the near infrared (0.85-1.55m). A ferroelectrics optoelectronics hybrid structure is an effective way to achieve high performance 2D electronic optoelectronic devices.

cond-mat.mes-hall↗

arXiv2015

Time-Critical Influence Maximization in Social Networks with Time-Delayed Diffusion Process

Influence maximization is a problem of finding a small set of highly influential users, also known as seeds, in a social network such that the spread of influence under certain propagation models is maximized. In this paper, we consider time-critical influence maximization, in which one wants to maximize influence spread within a given deadline. Since timing is considered in the optimization, we also extend the Independent Cascade (IC) model and the Linear Threshold (LT) model to incorporate the time delay aspect of influence diffusion among individuals in social networks. We show that time-critical influence maximization under the time-delayed IC and LT models maintains desired properties such as submodularity, which allows a greedy approximation algorithm to achieve an approximation ratio of $1-1/e$. To overcome the inefficiency of the greedy algorithm, we design two heuristic algorithms: the first one is based on a dynamic programming procedure that computes exact influence in tree structures and directed acyclic subgraphs, while the second one converts the problem to one in the original models and then applies existing fast heuristic algorithms to it. Our simulation results demonstrate that our algorithms achieve the same level of influence spread as the greedy algorithm while running a few orders of magnitude faster, and they also outperform existing fast heuristics that disregard the deadline constraint and delays in diffusion.

cs.SI↗

arXiv2015

Stochastic Geometry Modeling of Cellular Networks: Analysis, Simulation and Experimental Validation

Due to the increasing heterogeneity and deployment density of emerging cellular networks, new flexible and scalable approaches for their modeling, simulation, analysis and optimization are needed. Recently, a new approach has been proposed: it is based on the theory of point processes and it leverages tools from stochastic geometry for tractable system-level modeling, performance evaluation and optimization. In this paper, we investigate the accuracy of this emerging abstraction for modeling cellular networks, by explicitly taking realistic base station locations, building footprints, spatial blockages and antenna radiation patterns into account. More specifically, the base station locations and the building footprints are taken from two publicly available databases from the United Kingdom. Our study confirms that the abstraction model based on stochastic geometry is capable of accurately modeling the communication performance of cellular networks in dense urban environments.

cs.IT↗

arXiv2015

Mitigation of numerical Cerenkov radiation and instability using a hybrid finite difference-FFT Maxwell solver and a local charge conserving current deposit

A hybrid Maxwell solver for fully relativistic and electromagnetic (EM) particle-in-cell (PIC) codes is described. In this solver, the EM fields are solved in $k$ space by performing an FFT in one direction, while using finite difference operators in the other direction(s). This solver eliminates the numerical Cerenkov radiation for particles moving in the preferred direction. Moreover, the numerical Cerenkov instability (NCI) induced by the relativistically drifting plasma and beam can be eliminated using this hybrid solver by applying strategies that are similar to those recently developed for pure FFT solvers. A current correction is applied for the charge conserving current deposit to correctly account for the EM calculation in hybrid Yee-FFT solver. A theoretical analysis of the dispersion properties in vacuum and in a drifting plasma for the hybrid solver is presented, and compared with PIC simulations with good agreement obtained. This hybrid solver is applied to both 2D and 3D Cartesian and quasi-3D (in which the fields and current are decomposed into azimuthal harmonics) geometries. Illustrative results for laser wakefield accelerator simulation in a Lorentz boosted frame using the hybrid solver in the 2D Cartesian geometry are presented, and compared against results from 2D UPIC-EMMA simulation which uses a pure spectral Maxwell solver, and from OSIRIS 2D lab frame simulation using the standard Yee solver. Very good agreement is obtained which demonstrates the feasibility of using the hybrid solver for high fidelity simulation of relativistically drifting plasma with no evidence of the numerical Cerenkov instability.

physics.comp-ph↗

arXiv2015

Elimination of the numerical Cerenkov instability for spectral EM-PIC codes

When using an electromagnetic particle-in-cell (EM-PIC) code to simulate a relativistically drifting plasma, a violent numerical instability known as the numerical Cerenkov instability (NCI) occurs. The NCI is due to the unphysical coupling of electromagnetic waves on a grid to wave-particle resonances, including aliased resonances, i.e., $ω+ 2πμ/Δt=(k_1+ 2πν_1/Δx_1)v_0$, where $μ$ and $ν_1$ refer to the time and space aliases and the plasma is drifting relativistically at velocity $v_0$ in the $\hat{1}$-direction. Recent studies have shown that an EM-PIC code which uses a spectral field solver and a low pass filter can eliminate the fastest growing modes of the NCI. Based on these studies a new spectral PIC code for studying laser wakefield acceleration (LWFA) in the Lorentz boosted frame was developed. However, we show that for parameters of relevance for LWFA simulations in the boosted frame, a relativistically drifting plasma is susceptible to a host of additional unstable modes with lower growth rates, and that these modes appear when the fastest growing unstable modes are filtered out. We show that these modes are most easily identified as the coupling between modes which are purely transverse (EM) and purely longitudinal (Langmuir) in the rest frame of the plasma for specific time and space aliases. We rewrite the dispersion relation of the drifting plasma for a general field solver and obtain analytic expressions for the location and growth rate for each unstable mode, i.e, for each time and space aliased resonances. We show for the spectral solver that when the fastest growing mode is eliminated a new mode at the fundamental resonance ($μ=ν_1=0$) can be seen. (Please check the whole abstract in the paper).

physics.plasm-ph↗

arXiv2014

Effects of Data Resolution and Human Behavior on Large Scale Evacuation Simulations

Traffic Analysis Zones (TAZ) based macroscopic simulation studies are mostly applied in evacuation planning and operation areas. The large size in TAZ and aggregated information of macroscopic simulation underestimate the real evacuation performance. To take advantage of the high resolution demographic data LandScan USA (the zone size is much smaller than TAZ) and agent-based microscopic traffic simulation models, many new problems appeared and novel solutions are needed. A series of studies are conducted using LandScan USA Population Cells (LPC) data for evacuation assignments with different network configurations, travel demand models, and travelers compliance behavior. First, a new Multiple Source Nearest Destination Shortest Path (MSNDSP) problem is defined for generating Origin Destination matrix in evacuation assignments when using LandScan dataset. Second, a new agent-based traffic assignment framework using LandScan and TRANSIMS modules is proposed for evacuation planning and operation study. Impact analysis on traffic analysis area resolutions (TAZ vs LPC), evacuation start times (daytime vs nighttime), and departure time choice models (normal S shape model vs location based model) are studied. Third, based on the proposed framework, multi-scale network configurations (two levels of road networks and two scales of zone sizes) and three routing schemes (shortest network distance, highway biased, and shortest straight-line distance routes) are implemented for the evacuation performance comparison studies. Fourth, to study the impact of human behavior under evacuation operations, travelers compliance behavior with compliance levels from total complied to total non-complied are analyzed.

physics.soc-ph↗

arXiv2014

Contactless Probing of the Intrinsic Carrier Transport in Single-Walled Carbon Nanotubes

Intrinsic carrier transport properties of single-walled carbon nanotubes are probed by two parallel methods on the same individual tubes: the contactless dielectric force microscopy (DFM) technique and the conventional field-effect transistor (FET) method. The dielectric responses of SWNTs are strongly correlated with electronic transport of the corresponding FETs. The DC bias voltage in DFM plays a role analogous to the gate voltage in FET. A microscopic model based on the general continuity equation and numerical simulation is built to reveal the link between intrinsic properties such as carrier concentration and mobility and the macroscopic observable, i.e. dielectric responses, in DFM experiments. Local transport barriers in nanotubes, which influence the device transport behaviors, are also detected with nanometer scale resolution.

cond-mat.mes-hall↗

arXiv2014

Modified Einstein-Cartan Gravity and its Implications for Cosmology

We propose a modification of Einstein-Cartan gravity equations. The modified cosmology departs from the standard model of cosmology for small Hubble parameter. A characteristic Hubble scale h0, which is intrinsically related to cosmological constant, marks the boundary between the validity domains of the standard model of cosmology and modified cosmology. For large Hubble parameter, the standard model of cosmology is restored. In the opposite limit of small Hubble parameter, which is the case for present epoch, Lorentz-violating effects would manifest themselves. One of the implications is that there may be no need to invoke dark matter to account for cosmological mass discrepancies.

gr-qc↗

arXiv2014

Replicating Kernels with a Short Stride Allows Sparse Reconstructions with Fewer Independent Kernels

In sparse coding it is common to tile an image into nonoverlapping patches, and then use a dictionary to create a sparse representation of each tile independently. In this situation, the overcompleteness of the dictionary is the number of dictionary elements divided by the patch size. In deconvolutional neural networks (DCNs), dictionaries learned on nonoverlapping tiles are replaced by a family of convolution kernels. Hence adjacent points in the feature maps (V1 layers) have receptive fields in the image that are translations of each other. The translational distance is determined by the dimensions of V1 in comparison to the dimensions of the image space. We refer to this translational distance as the stride. We implement a type of DCN using a modified Locally Competitive Algorithm (LCA) to investigate the relationship between the number of kernels, the stride, the receptive field size, and the quality of reconstruction. We find, for example, that for 16x16-pixel receptive fields, using eight kernels and a stride of 2 leads to sparse reconstructions of comparable quality as using 512 kernels and a stride of 16 (the nonoverlapping case). We also find that for a given stride and number of kernels, the patch size does not significantly affect reconstruction quality. Instead, the learned convolution kernels have a natural support radius independent of the patch size.

q-bio.QM↗

arXiv2014

3D Vertical Dual-Layer Oxide Memristive Devices for Neuromorphic Computing

Dual-layer resistive switching devices with horizontal W electrodes, vertical Pd electrodes and WOx switching layer formed at the sidewall of the horizontal electrodes have been fabricated and characterized. The devices exhibit well-characterized analog switching characteristics and small mismatch in electrical characteristics for devices formed at the two layers. The three-dimensional (3D) vertical device structure allows higher storage density and larger connectivity for neuromorphic computing applications. We show the vertical devices exhibit potentiation and depression characteristics similar to planar devices, and can be programmed independently with no crosstalk between the layers.

cond-mat.other↗

arXiv2013

Exchange-dominated Standing Spin Wave Excitations under microwave irradiation in Ni80Fe20 Thin Films

We investigated the microwave-assisted DC voltages of ferromagnetic resonances and exchangedominated standing spin wave excitations in two different in-plane magnetized permalloy thin films via homodyne detection. The line shapes of ferromagnetic resonance spectra and the dispersion curves of ferromagnetic resonance and standing spin wave are in agreement of previous studies, while further investigations of DC voltage spectra for these two excitations reveal that 1. unlike ferromagnetic resonance signals, the anti-symmetrical line shapes of standing spin wave excitations are not depend on the electromagnetic relative phase of assisted microwave, and 2. linewidths of their DC voltage spectra are distinct. The complicated spin dynamics of standing spin wave is consequently discussed by applying Landau-Lifshitz-Gilbert equation in term of exchange interaction.

cond-mat.mtrl-sci↗

arXiv2013

Magnetization Characteristic of Ferromagnetic Thin Strip by Measuring Anisotropic Magnetoresistance and Ferromagnetic Resonance

The magnetization characteristic in a permalloy thin strip is investigated by electrically measuring the anisotropic magnetoresistance and ferromagnetic resonance in in-plane and out-of-plane configurations. Our results indicate that the magnetization vector can rotate in the film plane as well as out of the film plane by changing the intensity of external magnetic field of certain direction. The magnetization characteristic can be explained by considering demagnetization and magnetic anisotropy. Our method can be used to obtain the demagnetization factor, saturated magnetic moment and the magnetic anisotropy.

cond-mat.mtrl-sci↗

arXiv2013

Modeling of Laser wakefield acceleration in Lorentz boosted frame using EM-PIC code with spectral solver

Simulating laser wakefield acceleration (LWFA) in a Lorentz boosted frame in which the plasma drifts towards the laser with $v_b$ can speedup the simulation by factors of $γ^2_b=(1-v^2_b/c^2)^{-1}$. In these simulations the relativistic drifting plasma inevitably induces a high frequency numerical instability that contaminates the interested physics. Various approaches have been proposed to mitigate this instability. One approach is to solve Maxwell equations in Fourier space (a spectral solver) as this has been shown to suppress the fastest growing modes of this instability in simple test problems using a simple low pass, ring (in two dimensions), or shell (in three dimensions) filter in Fourier space. We describe the development of a fully parallelized, multi-dimensional, particle-in-cell code that uses a spectral solver to solve Maxwell's equations and that includes the ability to launch a laser using a moving antenna. This new EM-PIC code is called UPIC-EMMA and it is based on the components of the UCLA PIC framework (UPIC). We show that by using UPIC-EMMA, LWFA simulations in the boosted frames with arbitrary $γ_b$ can be conducted without the presence of the numerical instability. We also compare the results of a few LWFA cases for several values of $γ_b$, including lab frame simulations using OSIRIS, a EM-PIC code with a finite difference time domain (FDTD) Maxwell solver. These comparisons include cases in both linear, and nonlinear regimes. We also investigate some issues associated with numerical dispersion in lab and boosted frame simulations and between FDTD and spectral solvers.

physics.comp-ph↗

arXiv2013

Half-Semiconductor antiferromagnets and Spin-Gapless-Semiconductor antiferromagnets

We propose a concept of half-semiconductor antiferromagnets in which both spin-polarized valence and conduction bands belong to the same spin channel with completely compensated spontaneous magnetization. Using density functional theory plus Hubbard U (DFT+U) methods, we find a viable approach to achieve the half-semiconductor antiferromagnets through the transition metal (TM) Fe and Cr codoped boron nitride(BN) sheet. Moreover, spin gapless semiconductor antiferromagnets with zero magnetic moment are also achieved in such systems.

cond-mat.mtrl-sci↗