arXiv subjects

Lin Lin

Publications and source records attributed to Lin Lin.

At least 271 records · Page 15Linked to original sources

arXiv2017

A structure preserving Lanczos algorithm for computing the optical absorption spectrum

We present a new structure preserving Lanczos algorithm for approximating the optical absorption spectrum in the context of solving full Bethe--Salpeter equation without Tamm--Dancoff approximation. The new algorithm is based on a structure preserving Lanczos procedure, which exploits the special block structure of Bethe--Salpeter Hamiltonian matrices. A recently developed technique of generalized averaged Gauss quadrature is incorporated to accelerate the convergence. We also establish the connection between our structure preserving Lanczos procedure with several existing Lanczos procedures developed in different contexts. Numerical examples are presented to demonstrate the effectiveness of our Lanczos algorithm.

math.NA↗

arXiv2017

Projected Commutator DIIS Method for Accelerating Hybrid Functional Electronic Structure Calculations

The commutator direct inversion of the iterative subspace (commutator DIIS or C-DIIS) method developed by Pulay is an efficient and the most widely used scheme in quantum chemistry to accelerate the convergence of self consistent field (SCF) iterations in Hartree-Fock theory and Kohn-Sham density functional theory. The C-DIIS method requires the explicit storage of the density matrix, the Fock matrix and the commutator matrix. Hence the method can only be used for systems with a relatively small basis set, such as the Gaussian basis set. We develop a new method that enables the C-DIIS method to be efficiently employed in electronic structure calculations with a large basis set such as planewaves for the first time. The key ingredient is the projection of both the density matrix and the commutator matrix to an auxiliary matrix called the gauge-fixing matrix. The resulting projected commutator-DIIS method (PC-DIIS) only operates on matrices of the same dimension as the that consists of Kohn-Sham orbitals. The cost of the method is comparable to that of standard charge mixing schemes used in large basis set calculations. The PC-DIIS method is gauge-invariant, which guarantees that its performance is invariant with respect to any unitary transformation of the Kohn-Sham orbitals. We demonstrate that the PC-DIIS method can be viewed as an extension of an iterative eigensolver for nonlinear problems. We use the PC-DIIS method for accelerating Kohn-Sham density functional theory calculations with hybrid exchange-correlation functionals, and demonstrate its superior performance compared to the commonly used nested two-level SCF iteration procedure.

physics.comp-ph↗

arXiv2017

Computing localized representations of the kohn-sham subspace via randomization and refinement

Localized representation of the Kohn-Sham subspace plays an important role in quantum chemistry and materials science. The recently developed selected columns of the density matrix (SCDM) method [J. Chem. Theory Comput. 11, 1463, 2015] is a simple and robust procedure for finding a localized representation of a set of Kohn-Sham orbitals from an insulating system. The SCDM method allows the direct construction of a well conditioned (or even orthonormal) and localized basis for the Kohn-Sham subspace. The SCDM algorithm avoids the use of an optimization procedure and does not depend on any adjustable parameters. The most computationally expensive step of the SCDM method is a column pivoted QR factorization that identifies the important columns for constructing the localized basis set. In this paper, we develop a two stage approximate column selection strategy to find the important columns at much lower computational cost. We demonstrate the effectiveness of this process using the dissociation process of a BH$_3$NH$_3$ molecule, an alkane chain and a supercell with 256 water molecules. Numerical results for the large collection of water molecules show that two stage localization procedure can be more than 30 times faster than the original SCDM algorithm and compares favorably with the popular Wannier90 package.

math.NA↗

arXiv2017

PSelInv - A Distributed Memory Parallel Algorithm for Selected Inversion: the non-symmetric Case

This paper generalizes the parallel selected inversion algorithm called PSelInv to sparse non- symmetric matrices. We assume a general sparse matrix A has been decomposed as PAQ = LU on a distributed memory parallel machine, where L, U are lower and upper triangular matrices, and P, Q are permutation matrices, respectively. The PSelInv method computes selected elements of A-1. The selection is confined by the sparsity pattern of the matrix AT . Our algorithm does not assume any symmetry properties of A, and our parallel implementation is memory efficient, in the sense that the computed elements of A-T overwrites the sparse matrix L+U in situ. PSelInv involves a large number of collective data communication activities within different processor groups of various sizes. In order to minimize idle time and improve load balancing, tree-based asynchronous communication is used to coordinate all such collective communication. Numerical results demonstrate that PSelInv can scale efficiently to 6,400 cores for a variety of matrices.

cs.MS↗

arXiv2017

Robust Determination of the Chemical Potential in the Pole Expansion and Selected Inversion Method for Solving Kohn-Sham density functional theory

Fermi operator expansion (FOE) methods are powerful alternatives to diagonalization type methods for solving Kohn-Sham density functional theory (KSDFT). One example is the pole expansion and selected inversion (PEXSI) method, which approximates the Fermi operator by rational matrix functions and reduces the computational complexity to at most quadratic scaling for solving KSDFT. Unlike diagonalization type methods, the chemical potential often cannot be directly read off from the result of a single step of evaluation of the Fermi operator. Hence multiple evaluations are needed to be sequentially performed to compute the chemical potential to ensure the correct number of electrons within a given tolerance. This hinders the performance of FOE methods in practice. In this paper we develop an efficient and robust strategy to determine the chemical potential in the context of the PEXSI method. The main idea of the new method is not to find the exact chemical potential at each self-consistent-field (SCF) iteration iteration, but to dynamically and rigorously update the upper and lower bounds for the true chemical potential, so that the chemical potential reaches its convergence along the SCF iteration. Instead of evaluating the Fermi operator for multiple times sequentially, our method uses a two-level strategy that evaluates the Fermi operators in parallel. In the regime of full parallelization, the wall clock time of each SCF iteration is always close to the time for one single evaluation of the Fermi operator, even when the initial guess is far away from the converged solution. We demonstrate the effectiveness of the new method using examples with metallic and insulating characters, as well as results from ab initio molecular dynamics.

physics.comp-ph↗

arXiv2017

Interpolative Separable Density Fitting Decomposition for Accelerating Hybrid Density Functional Calculations With Applications to Defects in Silicon

We present a new efficient way to perform hybrid density functional theory (DFT) based electronic structure calculation. The new method uses an interpolative separable density fitting (ISDF) procedure to construct a set of numerical auxiliary basis vectors and a compact approximation of the matrix consisting of products of occupied orbitals represented in a large basis set such as the planewave basis. Such an approximation allows us to reduce the number of Poisson solves from $\Or(N_{e}^2)$ to $\Or(N_{e})$ when we apply the exchange operator to occupied orbitals in an iterative method for solving the Kohn-Sham equations, where $N_{e}$ is the number of electrons in the system to be studied. We show that the ISDF procedure can be carried out in $\Or(N_{e}^3)$ operations, with a much smaller pre-constant compared to methods used in existing approaches. When combined with the recently developed adaptively compressed exchange (ACE) operator formalism, which reduces the number of times the exchange operator needs to be updated, the resulting ACE-ISDF method significantly reduces the computational cost \REV{associated with the exchange operator} by nearly two orders of magnitude compared to existing approaches for a large silicon system with $1000$ atoms. We demonstrate that the ACE-ISDF method can produce accurate energies and forces for insulating and metallic systems, and that it is possible to obtain converged hybrid functional calculation results for a 1000-atom bulk silicon within 10 minutes on 2000 computational cores. We also show that ACE-ISDF can scale to 8192 computational cores for a 4096-atom bulk silicon system. We use the ACE-ISDF method to geometrically optimize a 1000-atom silicon system with a vacancy defect using the HSE06 functional and computes its electronic structure.

physics.comp-ph↗

arXiv2017

The peculiar filamentary HI structure of NGC 6145

In this paper, we report the peculiar HI morphology of the cluster spiral galaxy NGC 6145, which has a 150 kpc HI filament on one side that is nearly parallel to its major axis. This filament is made up of several HI clouds and the diffuse HI gas between them, with no optical counterparts. We compare its HI distribution with other one-sided HI distributions in the literature, and find that the overall HI distribution is very different from the typical tidal and ram-pressure stripped HI shape, and its morphology is inconsistent with being a pure accretion event. Only about 30% of the total HI gas is anchored on the stellar disk, while most of HI gas forms the filament in the west. At a projected distance of 122 kpc, we find a massive elliptical companion (NGC 6146) with extended radio emission, whose axis points to an HI gap in NGC 6145. The velocity of the HI filament shows an overall light-of- sight motion of 80 to 180 km/s with respect to NGC 6145. Using the long-slit spectra of NGC 6145 along its major stellar axis, we find that some outer regions show enhanced star formation, while in contrast, almost no star formation activities are found in its center (less than 2 kpc). Pure accretion, tidal or ram-pressure stripping is not likely to produce the observed HI filament. An alternative explanation is the jet-stripping from NGC 6146, although direct evidence for a jet-cold gas interaction has not been found.

astro-ph.GA↗

arXiv2017

The Properties of Massive Star-forming galaxies with Outside-in Assembly Mode

Previous findings show that massive ($> 10^{10} M_{sun}$) star-forming (SF) galaxies usually have an inside-out stellar mass assembly mode. In this paper, we have for the first time selected a sample of 77 massive SF galaxies with an outside-in assembly mode (called targeted sample) from the Mapping Nearby Galaxies at the Apache Point Observatory (MaNGA) survey. For comparison, two control samples are constructed from MaNGA sample matched in stellar mass: a sample of 154 normal SF galaxies and a sample of 62 quiescent galaxies. In contrast to normal SF galaxies, the targeted galaxies appear to be more smooth-like and bulge-dominated, and have smaller size, higher concentration, higher star formation rate and higher gas-phase metallicity as a whole. However, they have larger size and lower concentration than quiescent galaxies. Unlike normal SF sample, the targeted sample exhibits a slightly positive gradient of 4000 Å break and a pronounced negative gradient of H$α$ equivalent width. Further more, their median surface mass density profile is between that of normal SF sample and quiescent sample, indicating that the gas accretion of quiescent galaxies is not likely to be the main approach for the outside-in assembly mode. Our results suggest that the targeted galaxies are likely in the transitional phase from normal SF galaxies to quiescent galaxies, with rapid on-going central stellar mass assembly (or bulge growth). We discuss several possible formation mechanisms for the outside-in mass assembly mode.

astro-ph.GA↗

arXiv2017

ELSI: A Unified Software Interface for Kohn-Sham Electronic Structure Solvers

Solving the electronic structure from a generalized or standard eigenproblem is often the bottleneck in large scale calculations based on Kohn-Sham density-functional theory. This problem must be addressed by essentially all current electronic structure codes, based on similar matrix expressions, and by high-performance computation. We here present a unified software interface, ELSI, to access different strategies that address the Kohn-Sham eigenvalue problem. Currently supported algorithms include the dense generalized eigensolver library ELPA, the orbital minimization method implemented in libOMM, and the pole expansion and selected inversion (PEXSI) approach with lower computational complexity for semilocal density functionals. The ELSI interface aims to simplify the implementation and optimal use of the different strategies, by offering (a) a unified software framework designed for the electronic structure solvers in Kohn-Sham density-functional theory; (b) reasonable default parameters for a chosen solver; (c) automatic conversion between input and internal working matrix formats, and in the future (d) recommendation of the optimal solver depending on the specific problem. Comparative benchmarks are shown for system sizes up to 11,520 atoms (172,800 basis functions) on distributed memory supercomputing architectures.

physics.comp-ph↗

arXiv2017

Towards Interrogating Discriminative Machine Learning Models

It is oftentimes impossible to understand how machine learning models reach a decision. While recent research has proposed various technical approaches to provide some clues as to how a learning model makes individual decisions, they cannot provide users with ability to inspect a learning model as a complete entity. In this work, we propose a new technical approach that augments a Bayesian regression mixture model with multiple elastic nets. Using the enhanced mixture model, we extract explanations for a target model through global approximation. To demonstrate the utility of our approach, we evaluate it on different learning models covering the tasks of text mining and image recognition. Our results indicate that the proposed approach not only outperforms the state-of-the-art technique in explaining individual decisions but also provides users with an ability to discover the vulnerabilities of a learning model.

cs.LG↗

arXiv2017

From Physical to Cyber: Escalating Protection for Personalized Auto Insurance

Nowadays, auto insurance companies set personalized insurance rate based on data gathered directly from their customers' cars. In this paper, we show such a personalized insurance mechanism -- wildly adopted by many auto insurance companies -- is vulnerable to exploit. In particular, we demonstrate that an adversary can leverage off-the-shelf hardware to manipulate the data to the device that collects drivers' habits for insurance rate customization and obtain a fraudulent insurance discount. In response to this type of attack, we also propose a defense mechanism that escalates the protection for insurers' data collection. The main idea of this mechanism is to augment the insurer's data collection device with the ability to gather unforgeable data acquired from the physical world, and then leverage these data to identify manipulated data points. Our defense mechanism leveraged a statistical model built on unmanipulated data and is robust to manipulation methods that are not foreseen previously. We have implemented this defense mechanism as a proof-of-concept prototype and tested its effectiveness in the real world. Our evaluation shows that our defense mechanism exhibits a false positive rate of 0.032 and a false negative rate of 0.013.

cs.CR↗

arXiv2017

A General Model for Robust Tensor Factorization with Unknown Noise

Because of the limitations of matrix factorization, such as losing spatial structure information, the concept of low-rank tensor factorization (LRTF) has been applied for the recovery of a low dimensional subspace from high dimensional visual data. The low-rank tensor recovery is generally achieved by minimizing the loss function between the observed data and the factorization representation. The loss function is designed in various forms under different noise distribution assumptions, like $L_1$ norm for Laplacian distribution and $L_2$ norm for Gaussian distribution. However, they often fail to tackle the real data which are corrupted by the noise with unknown distribution. In this paper, we propose a generalized weighted low-rank tensor factorization method (GWLRTF) integrated with the idea of noise modelling. This procedure treats the target data as high-order tensor directly and models the noise by a Mixture of Gaussians, which is called MoG GWLRTF. The parameters in the model are estimated under the EM framework and through a new developed algorithm of weighted low-rank tensor factorization. We provide two versions of the algorithm with different tensor factorization operations, i.e., CP factorization and Tucker factorization. Extensive experiments indicate the respective advantages of this two versions in different applications and also demonstrate the effectiveness of MoG GWLRTF compared with other competing methods.

cs.CV↗

arXiv2017

Spectroscopic Observation and Analysis of HII regions in M33 with MMT: Temperatures and Oxygen Abundances

The spectra of 413 star-forming (or HII) regions in M33 (NGC 598) were observed by using the multifiber spectrograph of Hectospec at the 6.5-m Multiple Mirror Telescope (MMT). By using this homogeneous spectra sample, we measured the intensities of emission lines and some physical parameters, such as electron temperatures, electron densities, and metallicities. Oxygen abundances were derived via the direct method (when available) and two empirical strong-line methods, namely, O3N2 and N2. In the high-metallicity end, oxygen abundances derived from O3N2 calibration were higher than those derived from N2 index, indicating an inconsistency between O3N2 and N2 calibrations. We presented a detailed analysis of the spatial distribution of gas-phase oxygen abundances in M33 and confirmed the existence of the axisymmetric global metallicity distribution widely assumed in literature. Local variations were also observed and subsequently associated with spiral structures to provide evidence of radial migration driven by arms. Our O/H gradient fitted out to 1.1 $R_{25}$ resulted in slopes of $-0.17\pm0.03$, $-0.19\pm0.01$, and $-0.16\pm0.17$ dex $R_{25}^{-1}$ utilizing abundances from O3N2, N2 diagnostics, and direct method, respectively.

astro-ph.GA↗

arXiv2017

Bar-induced central star formation as revealed by integral field spectroscopy from CALIFA

We investigate the recent star formation history (SFH) in the inner region of 57 nearly face-on spiral galaxies selected from the Calar Alto Legacy Integral Field Area (CALIFA) survey. For each galaxy we use the integral field spectroscopy from CALIFA to obtain two-dimensional maps and radial profiles of three parameters that are sensitive indicators of the recent SFH: the 4000Å break (D$_n$(4000)), and the equivalent width of H$δ$ absorption (EW(H$δ_A$)) and H$α$ emission (EW(H$α$)). We have also performed photometric decomposition of bulge/bar/disk components based on SDSS optical image. We identify a class of 17 "turnover" galaxies whose central region present significant drop in D$_n$(4000), and most of them correspondingly show a central upturn in EW(H$δ_A$) and EW(H$α$). This indicates that the central region of the turnover galaxies has experienced star formation in the past 1-2 Gyr, which makes the bulge younger and more star-forming than surrounding regions. We find almost all (15/17) the turnover galaxies are barred, while only half of the barred galaxies in our sample (15/32) are classified as a turnover galaxy. This finding provides strong evidence in support of the theoretical expectation that the bar may drive gas from the disc inward to trigger star formation in galaxy center, an important channel for the growth/rejuvenation of pseudobulges in disc galaxies.

astro-ph.GA↗

arXiv2017

X-ray and radio observations of the magnetar SGR J1935+2154 during its 2014, 2015, and 2016 outbursts

We analyzed broad-band X-ray and radio data of the magnetar SGR J1935+2154 taken in the aftermath of its 2014, 2015, and 2016 outbursts. The source soft X-ray spectrum <10 keV is well described with a BB+PL or 2BB model during all three outbursts. NuSTAR observations revealed a hard X-ray tail, $Γ=0.9$, extending up to 79 keV, with flux larger than the one detected <10 keV. Imaging analysis of Chandra data did not reveal small-scale extended emission around the source. Following the outbursts, the total 0.5-10 keV flux from SGR J1935+2154 increased in concordance to its bursting activity, with the flux at activation onset increasing by a factor of $\sim7$ following its strongest June 2016 outburst. A Swift/XRT observation taken 1.5 days prior to the onset of this outburst showed a flux level consistent with quiescence. We show that the flux increase is due to the PL or hot BB component, which increased by a factor of $25$ compared to quiescence, while the cold BB component $kT=0.47$ keV remained more or less constant. The 2014 and 2015 outbursts decayed quasi-exponentially with time-scales of $\sim40$ days, while the stronger May and June 2016 outbursts showed a quick short-term decay with time-scales of $\sim4$ days. Our Arecibo radio observations set the deepest limits on the radio emission from a magnetar, with a maximum flux density limit of 14 $μ$Jy for the 4.6 GHz observations and 7 $μ$Jy for the 1.4 GHz observations. We discuss these results in the framework of the current magnetar theoretical models.

astro-ph.HE↗

arXiv2016

Using Non-invertible Data Transformations to Build Adversarial-Robust Neural Networks

Deep neural networks have proven to be quite effective in a wide variety of machine learning tasks, ranging from improved speech recognition systems to advancing the development of autonomous vehicles. However, despite their superior performance in many applications, these models have been recently shown to be susceptible to a particular type of attack possible through the generation of particular synthetic examples referred to as adversarial samples. These samples are constructed by manipulating real examples from the training data distribution in order to "fool" the original neural model, resulting in misclassification (with high confidence) of previously correctly classified samples. Addressing this weakness is of utmost importance if deep neural architectures are to be applied to critical applications, such as those in the domain of cybersecurity. In this paper, we present an analysis of this fundamental flaw lurking in all neural architectures to uncover limitations of previously proposed defense mechanisms. More importantly, we present a unifying framework for protecting deep neural models using a non-invertible data transformation--developing two adversary-resilient architectures utilizing both linear and nonlinear dimensionality reduction. Empirical results indicate that our framework provides better robustness compared to state-of-art solutions while having negligible degradation in accuracy.

cs.LG↗

arXiv2016

Burst and Outburst Characteristics of Magnetar 4U 0142+61

We have compiled the most comprehensive burst sample from magnetar 4U 0142+61, comprising 27 bursts from its three burst-active episodes in 2011, 2012 and the latest one in 2015 observed with Swift/BAT and Fermi/GBM. Bursts from 4U 0142+61 morphologically resemble typical short bursts from other magnetars. However, 4U 0142+61 bursts are less energetic compared to the bulk of magnetar bursts. We uncovered an extended tail emission following a burst on 2015 February 28, with a thermal nature, cooling over a time-scale of several minutes. During this tail emission, we also uncovered pulse peak phase aligned X-ray bursts , which could originate from the same underlying mechanism as that of the extended burst tail, or an associated and spatially coincident but different mechanism.

astro-ph.HE↗

arXiv2016

PEXSI-$Σ$: A Green's function embedding method for Kohn-Sham density functional theory

In this paper, we propose a new Green's function embedding method called PEXSI-$Σ$ for describing complex systems within the Kohn-Sham density functional theory (KSDFT) framework, after revisiting the physics literature of Green's function embedding methods from a numerical linear algebra perspective. The PEXSI-$Σ$ method approximates the density matrix using a set of nearly optimally chosen Green's functions evaluated at complex frequencies. For each Green's function, the complex boundary conditions are described by a self energy matrix $Σ$ constructed from a physical reference Green's function, which can be computed relatively easily. In the linear regime, such treatment of the boundary condition can be numerically exact. The support of the $Σ$ matrix is restricted to degrees of freedom near the boundary of computational domain, and can be interpreted as a frequency dependent surface potential. This makes it possible to perform KSDFT calculations with $\mathcal{O}(N^2)$ computational complexity, where $N$ is the number of atoms within the computational domain. Green's function embedding methods are also naturally compatible with atomistic Green's function methods for relaxing the atomic configuration outside the computational domain. As a proof of concept, we demonstrate the accuracy of the PEXSI-$Σ$ method for graphene with divacancy and dislocation dipole type of defects using the DFTB+ software package.

physics.comp-ph↗