31,471 research outputs found
Minimum-Cost Coverage of Point Sets by Disks
We consider a class of geometric facility location problems in which the goal
is to determine a set X of disks given by their centers (t_j) and radii (r_j)
that cover a given set of demand points Y in the plane at the smallest possible
cost. We consider cost functions of the form sum_j f(r_j), where f(r)=r^alpha
is the cost of transmission to radius r. Special cases arise for alpha=1 (sum
of radii) and alpha=2 (total area); power consumption models in wireless
network design often use an exponent alpha>2. Different scenarios arise
according to possible restrictions on the transmission centers t_j, which may
be constrained to belong to a given discrete set or to lie on a line, etc. We
obtain several new results, including (a) exact and approximation algorithms
for selecting transmission points t_j on a given line in order to cover demand
points Y in the plane; (b) approximation algorithms (and an algebraic
intractability result) for selecting an optimal line on which to place
transmission points to cover Y; (c) a proof of NP-hardness for a discrete set
of transmission points in the plane and any fixed alpha>1; and (d) a
polynomial-time approximation scheme for the problem of computing a minimum
cost covering tour (MCCT), in which the total cost is a linear combination of
the transmission cost for the set of disks and the length of a tour/path that
connects the centers of the disks.Comment: 10 pages, 4 figures, Latex, to appear in ACM Symposium on
Computational Geometry 200
Criticality for the Gehring link problem
In 1974, Gehring posed the problem of minimizing the length of two linked
curves separated by unit distance. This constraint can be viewed as a measure
of thickness for links, and the ratio of length over thickness as the
ropelength. In this paper we refine Gehring's problem to deal with links in a
fixed link-homotopy class: we prove ropelength minimizers exist and introduce a
theory of ropelength criticality.
Our balance criterion is a set of necessary and sufficient conditions for
criticality, based on a strengthened, infinite-dimensional version of the
Kuhn--Tucker theorem. We use this to prove that every critical link is C^1 with
finite total curvature. The balance criterion also allows us to explicitly
describe critical configurations (and presumed minimizers) for many links
including the Borromean rings. We also exhibit a surprising critical
configuration for two clasped ropes: near their tips the curvature is unbounded
and a small gap appears between the two components. These examples reveal the
depth and richness hidden in Gehring's problem and our natural extension.Comment: This is the version published by Geometry & Topology on 14 November
200
Classification and Geometry of General Perceptual Manifolds
Perceptual manifolds arise when a neural population responds to an ensemble
of sensory signals associated with different physical features (e.g.,
orientation, pose, scale, location, and intensity) of the same perceptual
object. Object recognition and discrimination requires classifying the
manifolds in a manner that is insensitive to variability within a manifold. How
neuronal systems give rise to invariant object classification and recognition
is a fundamental problem in brain theory as well as in machine learning. Here
we study the ability of a readout network to classify objects from their
perceptual manifold representations. We develop a statistical mechanical theory
for the linear classification of manifolds with arbitrary geometry revealing a
remarkable relation to the mathematics of conic decomposition. Novel
geometrical measures of manifold radius and manifold dimension are introduced
which can explain the classification capacity for manifolds of various
geometries. The general theory is demonstrated on a number of representative
manifolds, including L2 ellipsoids prototypical of strictly convex manifolds,
L1 balls representing polytopes consisting of finite sample points, and
orientation manifolds which arise from neurons tuned to respond to a continuous
angle variable, such as object orientation. The effects of label sparsity on
the classification capacity of manifolds are elucidated, revealing a scaling
relation between label sparsity and manifold radius. Theoretical predictions
are corroborated by numerical simulations using recently developed algorithms
to compute maximum margin solutions for manifold dichotomies. Our theory and
its extensions provide a powerful and rich framework for applying statistical
mechanics of linear classification to data arising from neuronal responses to
object stimuli, as well as to artificial deep networks trained for object
recognition tasks.Comment: 24 pages, 12 figures, Supplementary Material
A moving control volume approach to computing hydrodynamic forces and torques on immersed bodies
We present a moving control volume (CV) approach to computing hydrodynamic
forces and torques on complex geometries. The method requires surface and
volumetric integrals over a simple and regular Cartesian box that moves with an
arbitrary velocity to enclose the body at all times. The moving box is aligned
with Cartesian grid faces, which makes the integral evaluation straightforward
in an immersed boundary (IB) framework. Discontinuous and noisy derivatives of
velocity and pressure at the fluid-structure interface are avoided and
far-field (smooth) velocity and pressure information is used. We re-visit the
approach to compute hydrodynamic forces and torques through force/torque
balance equation in a Lagrangian frame that some of us took in a prior work
(Bhalla et al., J Comp Phys, 2013). We prove the equivalence of the two
approaches for IB methods, thanks to the use of Peskin's delta functions. Both
approaches are able to suppress spurious force oscillations and are in
excellent agreement, as expected theoretically. Test cases ranging from Stokes
to high Reynolds number regimes are considered. We discuss regridding issues
for the moving CV method in an adaptive mesh refinement (AMR) context. The
proposed moving CV method is not limited to a specific IB method and can also
be used, for example, with embedded boundary methods
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