21,904 research outputs found
Weak Gravitational Flexion
Flexion is the significant third-order weak gravitational lensing effect
responsible for the weakly skewed and arc-like appearance of lensed galaxies.
Here we demonstrate how flexion measurements can be used to measure galaxy halo
density profiles and large-scale structure on non-linear scales, via
galaxy-galaxy lensing, dark matter mapping and cosmic flexion correlation
functions. We describe the origin of gravitational flexion, and discuss its
four components, two of which are first described here. We also introduce an
efficient complex formalism for all orders of lensing distortion. We proceed to
examine the flexion predictions for galaxy-galaxy lensing, examining isothermal
sphere and Navarro, Frenk & White (NFW) profiles and both circularly symmetric
and elliptical cases. We show that in combination with shear we can precisely
measure galaxy masses and NFW halo concentrations. We also show how flexion
measurements can be used to reconstruct mass maps in 2-D projection on the sky,
and in 3-D in combination with redshift data. Finally, we examine the
predictions for cosmic flexion, including convergence-flexion
cross-correlations, and find that the signal is an effective probe of structure
on non-linear scales.Comment: 17 pages, including 12 figures, submitted to MNRA
Learning Convex Partitions and Computing Game-theoretic Equilibria from Best Response Queries
Suppose that an -simplex is partitioned into convex regions having
disjoint interiors and distinct labels, and we may learn the label of any point
by querying it. The learning objective is to know, for any point in the
simplex, a label that occurs within some distance from that point.
We present two algorithms for this task: Constant-Dimension Generalised Binary
Search (CD-GBS), which for constant uses queries, and Constant-Region Generalised Binary
Search (CR-GBS), which uses CD-GBS as a subroutine and for constant uses
queries.
We show via Kakutani's fixed-point theorem that these algorithms provide
bounds on the best-response query complexity of computing approximate
well-supported equilibria of bimatrix games in which one of the players has a
constant number of pure strategies. We also partially extend our results to
games with multiple players, establishing further query complexity bounds for
computing approximate well-supported equilibria in this setting.Comment: 38 pages, 7 figures, second version strengthens lower bound in
Theorem 6, adds footnotes with additional comments and fixes typo
Spatial Mixing of Coloring Random Graphs
We study the strong spatial mixing (decay of correlation) property of proper
-colorings of random graph with a fixed . The strong spatial
mixing of coloring and related models have been extensively studied on graphs
with bounded maximum degree. However, for typical classes of graphs with
bounded average degree, such as , an easy counterexample shows that
colorings do not exhibit strong spatial mixing with high probability.
Nevertheless, we show that for with and
sufficiently large , with high probability proper -colorings of
random graph exhibit strong spatial mixing with respect to an
arbitrarily fixed vertex. This is the first strong spatial mixing result for
colorings of graphs with unbounded maximum degree. Our analysis of strong
spatial mixing establishes a block-wise correlation decay instead of the
standard point-wise decay, which may be of interest by itself, especially for
graphs with unbounded degree
Quantum Monte Carlo diagonalization for many-fermion systems
In this study we present an optimization method based on the quantum Monte
Carlo diagonalization for many-fermion systems. Using the Hubbard-Stratonovich
transformation, employed to decompose the interactions in terms of auxiliary
fields, we expand the true ground-state wave function. The ground-state wave
function is written as a linear combination of the basis wave functions. The
Hamiltonian is diagonalized to obtain the lowest energy state, using the
variational principle within the selected subspace of the basis functions. This
method is free from the difficulty known as the negative sign problem. We can
optimize a wave function using two procedures. The first procedure is to
increase the number of basis functions. The second improves each basis function
through the operators, , using the Hubbard-Stratonovich
decomposition. We present an algorithm for the Quantum Monte Carlo
diagonalization method using a genetic algorithm and the renormalization
method. We compute the ground-state energy and correlation functions of small
clusters to compare with available data
A controlled migration genetic algorithm operator for hardware-in-the-loop experimentation
In this paper, we describe the development of an extended migration operator, which combats the negative effects of noise on the effective search capabilities of genetic algorithms. The research is motivated by the need to minimize the num- ber of evaluations during hardware-in-the-loop experimentation, which can carry a significant cost penalty in terms of time or financial expense. The authors build on previous research, where convergence for search methods such as Simulated Annealing and Variable Neighbourhood search was accelerated by the implementation of an adaptive decision support operator. This methodology was found to be effective in searching noisy data surfaces. Providing that noise is not too significant, Genetic Al- gorithms can prove even more effective guiding experimentation. It will be shown that with the introduction of a Controlled Migration operator into the GA heuristic, data, which repre- sents a significant signal-to-noise ratio, can be searched with significant beneficial effects on the efficiency of hardware-in-the- loop experimentation, without a priori parameter tuning. The method is tested on an engine-in-the-loop experimental example, and shown to bring significant performance benefits
Evolution of constrained layer damping using a cellular automaton algorithm
Constrained layer damping (CLD) is a highly effective passive vibration control strategy if optimized adequately. Factors controlling CLD performance are well documented for the flexural modes of beams but not for more complicated mode shapes or structures. The current paper introduces an approach that is suitable for locating CLD on any type of structure. It follows the cellular automaton (CA) principle and relies on the use of finite element models to describe the vibration properties of the structure. The ability of the algorithm to reach the best solution is demonstrated by applying it to the bending and torsion modes of a plate. Configurations that give the most weight-efficient coverage for each type of mode are first obtained by adapting the existing 'optimum length' principle used for treated beams. Next, a CA algorithm is developed, which grows CLD patches one at a time on the surface of the plate according to a simple set of rules. The effectiveness of the algorithm is then assessed by comparing the generated configurations with the known optimum ones
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