For a nonempty set S of vertices of a connected graph G, the Steiner distance d(S) of S is the minimum size among all connected subgraphs whose vertex set contains S. For an ordered set W = {Wl, W2,"', Wk} of vertices in a connected graph G and a vertex v of G, the Steiner representation s(vIW) of v with respect to W is the (2k I)-vector where d i1 ,i2, ... ,ij(V) is the Steiner distance d({V,W...

We investigate the energy of arrangements of N points on a rectifiable d-dimensional manifold A ⊂ Rd′ that interact through the power law (Riesz) potential V = 1/r, where s > 0 and r is Euclidean distance in R ′ . With Es(A, N) denoting the minimal energy for such N -point configurations, we determine the asymptotic behavior (as N → ∞) of Es(A, N) for each fixed s ≥ d. Moreover, if A has positi...

Consider two (n−1)-dimensional manifolds, S and S in R. We say that they are normalcompatible when the closest projection of each one onto the other is a homeomorphism. We give a tight condition under which S and S are normal-compatible. It involves the minimum feature size of S and of S and the Hausdorff distance between them. Furthermore, when S and S are normal-compatible, their Frechet dist...

Besides their appearance at short distances >∼ 1/MW , local dimension-eight operators also contribute to kaon matrix elements at long distances of order ∼ 1/μope, where μope is the scale controlling the Operator Product Expansion in pure QCD, without weak interactions. This comes about in the matching condition between the effective quark Lagrangian and the Chiral Lagrangian of mesons. Working ...

Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data analysis and bioinformatics. The focus of this paper is on developing algorithms for reducing the computational complexity of manifold learning algorithms, in particular, we consider the case when the number of features...

Let S ⊂ R be contained in the unit ball. Let ∆(S) = {||a− b|| : a, b ∈ S}, the Euclidean distance set of S. Falconer conjectured that the ∆(S) has positive Lebesque measure if the Hausdorff dimension of S is greater than d 2 . He also produced an example, based on the integer lattice, showing that the exponent d 2 cannot be improved. In this paper we prove the Falconer distance conjecture for t...

Distance measurements to Type Ia supernovae (SNe Ia) at cosmological distances indicate that the Universe is accelerating and that a large fraction of the critical energy density exists in a component with negative pressure. Various hypotheses on the nature of this “dark energy” can be tested via their prediction for the equation of state of this component. If the dark energy is due to a scalar...

Let K be a 2-dimensional finite flag complex. We study the CAT(0) dimension of the ‘Bestvina-Brady group’, or ‘Artin kernel’, ΓK . We show that ΓK has CAT(0) dimension 3 unless K admits a piecewise Euclidean metric of non-positive curvature. We give an example to show that this implication cannot be reversed. Different choices of K lead to examples where the CAT(0) dimension is 3, and either (i...

We propose a method for learning skills by learning kinesthetic skills via trajectory optimization. We recreate demonstrations by optimizing the trajectory to be near the demonstration. We use the trajectory optimizer, TrajOpt to turn distance metrics, the Frechet and Hausdorff distances, into cost functions that penalize a trajectory from deviating from the demonstration. Using a few technique...

The problem of efficiently computing and visualizing the structural resemblance between a pair of protein backbones in 3D has led Bereg et al. [BJW08] to pose the Chain Pair Simplification problem (CPS). In this problem, given two polygonal chains A and B of lengths m and n, respectively, one needs to simplify them simultaneously, such that each of the resulting simplified chains, A′ and B′, is...