arXiv subjects

Fan Li

Publications and source records attributed to Fan Li.

320 records · Page 18Linked to original sources

arXiv2015

Magnetoelectric coupling induced by interfacial orbital reconstruction

The magnetoelectric coupling effect with profound physics and enormous potential applications has provoked a great number of research activities in materials science. Here, we report that the reversible orbital reconstruction driven by ferroelectric polarization modulates the magnetic performance of ferroelectric ferromagnetic heterostructure. Mn in plane orbital occupancy and related interfacial exotic magnetic state are enhanced and weakened by the negative and positive electric field, respectively. Our findings thus not only present a broad opportunity to fill the missing member, orbital in the mechanism of magnetoelectric coupling, but also make the orbital degree of freedom straight forward to the application in microelectronic device.

cond-mat.str-el↗

arXiv2015

Evaluating the Causal Effect of University Grants on Student Dropout: Evidence from a Regression Discontinuity Design Using Principal Stratification

Regression discontinuity (RD) designs are often interpreted as local randomized experiments: a RD design can be considered as a randomized experiment for units with a realized value of a so-called forcing variable falling around a pre-fixed threshold. Motivated by the evaluation of Italian university grants, we consider a fuzzy RD design where the receipt of the treatment is based on both eligibility criteria and a voluntary application status. Resting on the fact that grant application and grant receipt statuses are post-assignment (post-eligibility) intermediate variables, we use the principal stratification framework to define causal estimands within the Rubin Causal Model. We propose a probabilistic formulation of the assignment mechanism underlying RD designs, by re-formulating the Stable Unit Treatment Value Assumption (SUTVA) and making an explicit local overlap assumption for a subpopulation around the threshold. A local randomization assumption is invoked instead of more standard continuity assumptions. We also develop a model-based Bayesian approach to select the target subpopulation(s) with adjustment for multiple comparisons, and to draw inference for the target causal estimands in this framework. Applying the method to the data from two Italian universities, we find evidence that university grants are effective in preventing students from low-income families from dropping out of higher education.

stat.AP↗

arXiv2015

Do debit cards decrease cash demand? Evidence from a causal analysis using Principal Stratification

It has been argued that innovation in transaction technology may modify the cash holding behaviour of agents, as debit card holders may either withdraw cash from ATMs or purchase items using POS devices at retailers. In this paper, within the Rubin Causal Model, we investigate the causal effects of the use of debit cards on the cash inventories held by households using data from the Italy Survey of Household Income and Wealth (SHIW). We adopt the principal stratification approach to incorporate the share of debit card holders who do not use this payment instrument. We use a regression model with the propensity score as the single predictor to adjust for the imbalance in observed covariates. We further develop a sensitivity analysis approach to assess the sensitivity of the proposed model to violation to the key unconfoundedness assumption. Our empirical results suggest statistically significant negative effects of debit cards on the household cash level in Italy.

stat.AP↗

arXiv2015

Do debit cards increase household spending? Evidence from a semiparametric causal analysis of a survey

Motivated by recent findings in the field of consumer science, this paper evaluates the causal effect of debit cards on household consumption using population-based data from the Italy Survey on Household Income and Wealth (SHIW). Within the Rubin Causal Model, we focus on the estimand of population average treatment effect for the treated (PATT). We consider three existing estimators, based on regression, mixed matching and regression, propensity score weighting, and propose a new doubly-robust estimator. Semiparametric specification based on power series for the potential outcomes and the propensity score is adopted. Cross-validation is used to select the order of the power series. We conduct a simulation study to compare the performance of the estimators. The key assumptions, overlap and unconfoundedness, are systematically assessed and validated in the application. Our empirical results suggest statistically significant positive effects of debit cards on the monthly household spending in Italy.

stat.AP↗

arXiv2014

Electrical manipulation of orbital occupancy and magnetic anisotropy in manganites

Electrical manipulation of lattice, charge, and spin has been realized respectively by the piezoelectric effect, field-effect transistor, and electric field control of ferromagnetism, bringing about dramatic promotions both in fundamental research and industrial production. However, it is generally accepted that the orbital of materials are impossible to be altered once they have been made. Here we use electric-field to dynamically tune the electronic phase transition in (La,Sr)MnO3 films with different Mn^4+/(Mn^3+ + Mn^4+) ratios. The orbital occupancy and corresponding magnetic anisotropy of these thin films are manipulated by gate voltage in a reversible and quantitative manner. Positive gate voltage increases the proportion of occupancy of the orbital and magnetic anisotropy that were initially favored by strain (irrespective of tensile and compressive), while negative gate voltage reduces the concomitant preferential orbital occupancy and magnetic anisotropy. Besides its fundamental significance in orbital physics, our findings might advance the process towards practical oxide-electronics based on orbital.

cond-mat.mtrl-sci↗

arXiv2014

Improving Inference of Gaussian Mixtures Using Auxiliary Variables

Expanding a lower-dimensional problem to a higher-dimensional space and then projecting back is often beneficial. This article rigorously investigates this perspective in the context of finite mixture models, namely how to improve inference for mixture models by using auxiliary variables. Despite the large literature in mixture models and several empirical examples, there is no previous work that gives general theoretical justification for including auxiliary variables in mixture models, even for special cases. We provide a theoretical basis for comparing inference for mixture multivariate models with the corresponding inference for marginal univariate mixture models. Analytical results for several special cases are established. We show that the probability of correctly allocating mixture memberships and the information number for the means of the primary outcome in a bivariate model with two Gaussian mixtures are generally larger than those in each univariate model. Simulations under a range of scenarios, including misspecified models, are conducted to examine the improvement. The method is illustrated by two real applications in ecology and causal inference.

stat.ME↗

arXiv2014

A Conversation with Donald B. Rubin

Donald Bruce Rubin is John L. Loeb Professor of Statistics at Harvard University. He has made fundamental contributions to statistical methods for missing data, causal inference, survey sampling, Bayesian inference, computing and applications to a wide range of disciplines, including psychology, education, policy, law, economics, epidemiology, public health and other social and biomedical sciences.

stat.OT↗

arXiv2014

Exploiting multiple outcomes in Bayesian principal stratification analysis with application to the evaluation of a job training program

The causal effect of a randomized job training program, the JOBS II study, on trainees' depression is evaluated. Principal stratification is used to deal with noncompliance to the assigned treatment. Due to the latent nature of the principal strata, strong structural assumptions are often invoked to identify principal causal effects. Alternatively, distributional assumptions may be invoked using a model-based approach. These often lead to weakly identified models with substantial regions of flatness in the posterior distribution of the causal effects. Information on multiple outcomes is routinely collected in practice, but is rarely used to improve inference. This article develops a Bayesian approach to exploit multivariate outcomes to sharpen inferences in weakly identified principal stratification models. We show that inference for the causal effect on depression is significantly improved by using the re-employment status as a secondary outcome in the JOBS II study. Simulation studies are also performed to illustrate the potential gains in the estimation of principal causal effects from jointly modeling more than one outcome. This approach can also be used to assess plausibility of structural assumptions and sensitivity to deviations from these structural assumptions. Two model checking procedures via posterior predictive checks are also discussed.

stat.AP↗

arXiv2013

Almost Optimal Channel Access in Multi-Hop Networks With Unknown Channel Variables

We consider distributed channel access in multi-hop cognitive radio networks. Previous works on opportunistic channel access using multi-armed bandits (MAB) mainly focus on single-hop networks that assume complete conflicts among all secondary users. In the multi-hop multi-channel network settings studied here, there is more general competition among different communication pairs. We formulate the problem as a linearly combinatorial MAB problem that involves a maximum weighted independent set (MWIS) problem with unknown weights which need to learn. Existing methods for MAB where each of $N$ nodes chooses from $M$ channels have exponential time and space complexity $O(M^N)$, and poor theoretical guarantee on throughput performance. We propose a distributed channel access algorithm that can achieve $1/ρ$ of the optimum averaged throughput where each node has communication complexity $O(r^2+D)$ and space complexity $O(m)$ in the learning process, and time complexity $O(D m^{ρ^r})$ in strategy decision process for an arbitrary wireless network. Here $ρ=1+ε$ is the approximation ratio to MWIS for a local $r$-hop network with $m<N$ nodes,and $D$ is the number of mini-rounds inside each round of strategy decision. For randomly located networks with an average degree $d$, the time complexity is $O(d^{ρ^r})$.

cs.NI↗

arXiv2013

A New TCP/AQM System Analysis

The MGT fluid model has been used extensively to guide designs of AQM schemes aiming to alleviate adverse effects of Internet congestion. In this paper, we provide a new analysis of a TCP/AQM system that aims to improve the accuracy of the MGT fluid model especially in heavy traffic conditions. The analysis is based on the consideration of two extreme congestion scenarios that leads to the derivation of upper and lower bounds for the queue length and marking probability dynamics and showing that they approach each other in steady state. Both discrete and continuous time models are provided. Simulation results demonstrate that the new model achieves a significantly higher level of accuracy than a simplified version of the MGT fluid model.

cs.NI↗

arXiv2012

Bayesian inference on dependence in multivariate longitudinal data

In many applications, it is of interest to assess the dependence structure in multivariate longitudinal data. Discovering such dependence is challenging due to the dimensionality involved. By concatenating the random effects from component models for each response, dependence within and across longitudinal responses can be characterized through a large random effects covariance matrix. Motivated by the common problems in estimating this matrix, especially the off-diagonal elements, we propose a Bayesian approach that relies on shrinkage priors for parameters in a modified Cholesky decomposition. Without adjustment, such priors and previous related approaches are order-dependent and tend to shrink strongly toward an ARtype structure. We propose moment-matching (MM) priors to mitigate such problems. Efficient Gibbs samplers are developed for posterior computation. The methods are illustrated through simulated examples and are applied to a longitudinal epidemiologic study of hormones and oxidative stress.

stat.AP↗

arXiv2011

BL Lacertae Objects and the Extragalactic Gamma-Ray Background

A tight correlation between gamma-ray and radio emission is found for a sample of BL Lacertae (BL Lac) objects detected by Fermi Gamma-ray Space Telescope (Fermi) and the Energetic Gamma-Ray Experiment Telescope (EGRET). The gamma-ray emission of BL Lac objects exhibits strong variability, and the detection rate of gamma-ray BL Lac objects is low, which may be related to the gamma-ray duty cycle of BL Lac objects. We estimate the gamma-ray duty cycle ~ 0.11, for BL Lac objects detected by EGRET and Fermi. Using the empirical relation of gamma-ray emission with radio emission and the estimated gamma-ray duty cycle, we derive the gamma-ray luminosity function (LF) of BL Lac objects from their radio LF. Our derived gamma-ray LF of BL Lac objects can almost reproduce that calculated with the recently released Fermi bright active galactic nuclei (AGN) sample. We find that about 45% of the extragalactic diffuse gamma-ray background (EGRB) is contributed by BL Lac objects. Combining the estimate of the quasar contribution to the EGRB in the previous work, we find that about 77% of the EGRB is contributed by BL Lac objects and radio quasars.

astro-ph.HE↗

arXiv2010

A better tester for bipartiteness?

Alon and Krivelevich (SIAM J. Discrete Math. 15(2): 211-227 (2002)) show that if a graph is ε-far from bipartite, then the subgraph induced by a random subset of O(1/ε) vertices is bipartite with high probability. We conjecture that the induced subgraph is Ω~(ε)-far from bipartite with high probability. Gonen and Ron (RANDOM 2007) proved this conjecture in the case when the degrees of all vertices are at most O(εn). We give a more general proof that works for any d-regular (or almost d-regular) graph for arbitrary degree d. Assuming this conjecture, we prove that bipartiteness is testable with one-sided error in time O(1/ε^c), where c is a constant strictly smaller than two, improving upon the tester of Alon and Krivelevich. As it is known that non-adaptive testers for bipartiteness require Ω(1/ε^2) queries (Bogdanov and Trevisan, CCC 2004), our result shows, assuming the conjecture, that adaptivity helps in testing bipartiteness.

cs.DS↗

arXiv2008

Rapidly spinning massive black holes in active galactic nuclei: evidence from the black hole mass function

The comparison of the black hole mass function (BHMF) of active galactic nuclei (AGN) relics with the measured mass function of the massive black holes in galaxies provides strong evidence for the growth of massive black holes being dominated by mass accretion. We derive the Eddington ratio distributions as functions of black hole mass and redshift from a large AGN sample with measured Eddington ratios given by Kollmeier et al. We find that, even at the low mass end, most black holes are accreting at Eddington ratio ~0.2, which implies that the objects accreting at extremely high rates should be rare or such phases are very short. Using the derived Eddington ratios, we explore the cosmological evolution of massive black holes with an AGN bolometric luminosity function (LF). It is found that the resulted BHMF of AGN relics is unable to match the measured local BHMF of galaxies for any value of (constant) radiative efficiency. Motivated by Volonteri, Sikora & Lasota's study on the spin evolution of massive black holes, we assume the radiative efficiency to be dependent of black hole mass, i.e., it is low for M<10^8 solar masses and it increases with black hole mass for black holes with >10^8 solar masses. We find that the BHMF of AGN relics can roughly reproduce the local BHMF of galaxies if the radiative efficiency ~0.08 for the black holes with <10^8 solar masses and it increases to ~0.18 for black holes with >10^9 solar masses, which implies that most massive black holes (>10^9 solar masses) are spinning very rapidly.

astro-ph↗