7145981
High performance first principles method for complex magnetic properties
The understanding of metallic magnetism is of fundamental importance for a wide range of technological applications ranging from thin film disc drive read heads to bulk magnets used in motors and power generation. In this submission for the Gordon Bell Prize we use the power of massively parallel processing (MPP) computers to perform first principles calculations of large system models of non-equilibrium magnetic states in metallic magnets. The calculations are based on a new constrained local moment (CLM) model that places the recently proposed Spin-Dynamics of Antropov et al. [1] on firm theoretical foundations. The equations of constrained local spin density approximation (constrained LSDA) are solved using the massively parallel locally self-consistent multiple scattering (LSMS) method[3] extended to treat general non-collinear arrangements of the magnetic moments [4]. A general algorithm has been developed for self-consistently finding the constraining fields which are introduced into LSDA in order to maintain a prescribed magnetic moment orientation configuration. The existence of CLM states is demonstrated for 1024 atom per unit cell models of Iron above its Curie temperature. The constrained LSMS method we have developed exploits the locality in the physics of the problem to produce an algorithm that has only local and limited communications on parallel computers leading to very good scale-up to large processor counts and linear scaling of the number of operations with the number of atoms in the system. The computationally intensive step of inversion of a dense complex matrix is largely reduced to matrix-matrix multiplies which are implemented in BLAS. Throughout the code attention is paid to minimizing both the total operation count and total execution time, with primacy given to the latter. Full 64-bit arithmetic is used throughout. The code shows near linear scale-up to 1024-processing elements (PE) and attains a performance of 657 Gflops on a Cray T3E1200 LC1024 at a US Government site. Performance figures of 276 Gflops and 329 Gflops have also been obtained on T3E900 and T3E1200 LC512 machines at the National Energy Research Scientific Computing Center (NERSC), and Cray Research respectively. All performance figures include necessary I/O.
45169888
Multi-teraflops spin dynamics studies of the magnetic structure of FeMn/Co interfaces
8929565
Integrating the QMR Method with First Principles Material Science Application Code
First principles methods are used to aid the material designers and metallurgists in the investigation and design of new materials. These methods suffer from a divergent O(N{sup 3}) scaling which restricts the problem sizes that can be addressed. It will be demonstrated that the O(N{sup 3}) scaling problem can be overcome by employing real-space multiple scattering techniques to calculate the scattering properties, combined with the QMR algorithm. By incorporating the QMR method into our real-space multiple scattering code, we observed O(N) scaling for the large problem sizes of interest. This advancement will provide researchers with the necessary tools to treat large systems.
18355899
A microscopic view on community detection in complex networks
The community structure is a basic characteristic of complex networks. A strong community structure has high modularity. It has been proven an NP-Complete problem to identify the community structure with the highest modularity. Many approximate algorithms have been proposed to alleviate the problem. However, they suffer from inefficiency or low quality. In this paper, we propose a two-step method. The first step of our method analyze the vertex similarity of the network, which is a microscopic view. If a pair of vertices are similar enough, they will be put into the same community. The second step of our method focuses on the increment of modularity of the similarity-based communities generated by the first step. If the number of edges between two communities is greater than the expected number based on random choice, the two communities will be merged. The second step is implemented by the CNM algorithm or its improvement CNM+HE'. The similarity-based community remedies the defect on microscope introduced by CNM or CNM+HE'. Our method runs efficiently and finds meaningful communities effectively. We tested the method on more than twenty datasets. The modularity of community structure found by the method is higher than the state-of-the-art algorithm.
9251959
Visual Zen art: aesthetic cognitive dissonance in Japanese dry stone garden measured in visual PageRank
One of the most famous Japanese landscape of dry stone Zen gardens in Ryoan temple established AC 1450 at Kyoto by the deputy Shogun Katsumoto Hosokawa, a UNESCO World Heritage Site, has the small 248 m2 empty rectangle where white sand was laid in between, in the abstract, placements of 15 rocks with mosses that seem to be scattered in seemingly haphazard. The landscape attracts many visitors, including Queen Elizabeth II, 1975, to hundreds of thousands for long years. The stone placements designed by the ancient anonymous landscape designer look random at a glance, however, the placement structure is hidden in white sand of the garden space in sophisticated manner, and that we are in perfect harmony with the temple buildings and landscapes. The stone structure looks puzzling at glance. However, the general stone placement structure can immediately be revealed by understanding the ancient garden design rule texts described in, for example, “Sakuteiki” (“Landscape Design” in Japanese, published around AC 1200). According to this instruction text, the stones are placed recursively and in fractal as an obtuse inequilateral triangle in different three level scales. The three stones are placed as vertices entitled “真 (very formal)” at the obtuse angle, “副(formal)” at the vertex closest to “very formal”, and “対(Casual)” at the remaining vertex. These three stones form a cluster and three clusters form a different obtuse inequilateral triangle, recursively, as shown in Image (lower). If we plot the size and the rank of the three level obtuse triangles in log scale, we obtain the perfect Zipf’s law[Gabaix 1999] or 1/f pink noise[Voss 1985]. This means that the stones are placed in a perfect fractal manner, and this fractal stone placement is completely understood by the garden viewers unconsciously in our eyetracking measurements shown in Image (upper). Eye tracking experiments are performed and the visual “PageRank”[Page et al. 1998] of eye movement are measured. We measured 10 testers’ eye movement while they were watching the landscape garden. All testers spend more than 90% of their time to watch the stone objects, and move their eyes from a stone vertex to another, following the triangles, recursively. Image (upper) shows a typical eye movement trajectory in 20 seconds, and the trajectory follows the three level of fractal triangle structure displayed in Image (lower). Five human figures 1 to 5 in different colors represent different viewing positions corresponding to different eye movement trajectories in their colors. We assume that the eye movement from one stone or one cluster to another is a forward “link”. Using the same technique as “PageRank”, the eye movement from one stone to another is taken as a directed graph. First, we generate an adjacency matrix of this graph structure with weighted sum of the number of eye visits. Next, we obtain the largest absolute eigenvalue of this matrix and its eigenvector. Third, the normalized component values of the eigenvector are the visual “PageRanks”, and now we rank the stones or the cluster in order. The visual “PageRank” in the Japanese dry stone Zen garden reveals the amazing hidden structure in this old landscape garden, which cannot be discovered by a simple hot spot diagram that only represents the length of fixation time. Figure 1 indicates that the “PageRanks” in two “真 (very formal)” stones (number 2-2 and 3-2) are significantly higher than the others, where the general fractal placement manner is somehow violated. At these stones circled in red in Image, the eye trajectories are strongly disturbed and some psychological tension caused by a disparity between what one expects to see and what one actually sees is observed. This is a well-known phenomenon in social psychology today called “cognitive dissonance” or “visual dissonance” although totally not known in 560 years ago when the temple was build. The cognitive dissonance happens when we perceive a discrepancy between our attitudes and our behaviors. Our eye sees the world of art with a thousand of expectations based on our personalities and our cognitive structure or knowledge system. Sometimes those expectations are fulfilled, sometimes not. In the case of unfulfilled expectations, the viewer is required to resolve his or her tension, or simply abandon the piece and consider another. An important part of human motivation is found in “dissonance reduction”, in that people do not normally choose to live in a state of psychological tension. In psychological terms, it is better to be avoided or resolved such an aversive state. The technique to produce unexpected visual forms is widely practiced by modern artists who seek to gain our attentions. However, the most striking feature here is that this cognitive dissonance was implemented in a very naive way and viewer observe this only unconsciously, not like many visual dissonance in modern arts. When people view this garden people feels deep serenity and perfect harmony with very small “disharmony” i. e. “dissonance” like in much beautiful music.
5756583
Face Relighting from a Single Image under Arbitrary Unknown Lighting Conditions
In this paper, we present a new method to modify the appearance of a face image by manipulating the illumination condition, when the face geometry and albedo information is unknown. This problem is particularly difficult when there is only a single image of the subject available. Recent research demonstrates that the set of images of a convex Lambertian object obtained under a wide variety of lighting conditions can be approximated accurately by a low-dimensional linear subspace using a spherical harmonic representation. Moreover, morphable models are statistical ensembles of facial properties such as shape and texture. In this paper, we integrate spherical harmonics into the morphable model framework by proposing a 3D spherical harmonic basis morphable model (SHBMM). The proposed method can represent a face under arbitrary unknown lighting and pose simply by three low-dimensional vectors, i.e., shape parameters, spherical harmonic basis parameters, and illumination coefficients, which are called the SHBMM parameters. However, when the image was taken under an extreme lighting condition, the approximation error can be large, thus making it difficult to recover albedo information. In order to address this problem, we propose a subregion-based framework that uses a Markov random field to model the statistical distribution and spatial coherence of face texture, which makes our approach not only robust to extreme lighting conditions, but also insensitive to partial occlusions. The performance of our framework is demonstrated through various experimental results, including the improved rates for face recognition under extreme lighting conditions.
122096563
Ricci Flow for 3D Shape Analysis
Ricci flow is a powerful curvature flow method in geometric analysis. This work is the first application of surface Ricci flow in computer vision. We show that previous methods based on conformal geometries, such as harmonic maps and least-square conformal maps, which can only handle 3D shapes with simple topology are subsumed by our Ricci flow based method which can handle surfaces with arbitrary topology. Because the Ricci flow method is intrinsic and depends on the surface metric only, it is invariant to rigid motion, scaling, and isometric and conformal deformations. The solution to Ricci flow is unique and its computation is robust to noise. Our Ricci flow based method can convert all 3D problems into 2D domains and offers a general framework for 3D surface analysis. Large non-rigid deformations can be registered with feature constraints, hence we introduce a method that constrains Ricci flow computation using feature points and feature curves. Finally, we demonstrate the applicability of this intrinsic shape representation through standard shape analysis problems, such as 3D shape matching and registration.
5597681
An Ensemble Approach to Learning to Rank
In recent years, 'learning to rank' is a focused approach for information retrieval, which can learn the ranking order given by experts and construct a uniform model to rank for new query. But in practice user queries vary in large diversity, it makes a single learned ranker not representative. Therefore, we propose an ensemble approach to 'learning to rank,' in which a lower generalization error can be gotten by generating a set of rankers and leveraging these rankers for the final prediction. Moreover, two strategies of creating multiple base rankers are proposed to make the ensemble more effective for information retrieval. The experiment results on two real world datasets indicate that the proposed approach can outperform the original 'learning to rank' methods significantly.