A self-learning particle swarm optimizer for global optimization problems

Copyright @ 2011 IEEE. All Rights Reserved. This article was made available through the Brunel Open Access Publishing Fund.Particle swarm optimization (PSO) has been shown as an effective tool for solving global optimization problems. So far, most PSO algorithms use a single learning pattern for all particles, which means that all particles in a swarm use the same strategy. This monotonic learning pattern may cause the lack of intelligence for a particular particle, which makes it unable to deal with different complex situations. This paper presents a novel algorithm, called self-learning particle swarm optimizer (SLPSO), for global optimization problems. In SLPSO, each particle has a set of four strategies to cope with different situations in the search space. The cooperation of the four strategies is implemented by an adaptive learning framework at the individual level, which can enable a particle to choose the optimal strategy according to its own local fitness landscape. The experimental study on a set of 45 test functions and two real-world problems show that SLPSO has a superior performance in comparison with several other peer algorithms.This work was supported by the Engineering and Physical Sciences Research Council of U.K. under Grants EP/E060722/1 and EP/E060722/2

Novel quantum phases of dipolar Bose gases in optical lattices

We investigate the quantum phases of polarized dipolar Bosons loaded into a two-dimensional square and three-dimensional cubic optical lattices. We show that the long-range and anisotropic nature of the dipole-dipole interaction induces a rich variety of quantum phases, including the supersolid and striped supersolid phases in 2D lattices, and the layered supersolid phase in 3D lattices.Comment: 4 pages, 4 figure

Convergence of the Lasserre Hierarchy of SDP Relaxations for Convex Polynomial Programs without Compactness

The Lasserre hierarchy of semidefinite programming (SDP) relaxations is an effective scheme for finding computationally feasible SDP approximations of polynomial optimization over compact semi-algebraic sets. In this paper, we show that, for convex polynomial optimization, the Lasserre hierarchy with a slightly extended quadratic module always converges asymptotically even in the face of non-compact semi-algebraic feasible sets. We do this by exploiting a coercivity property of convex polynomials that are bounded below. We further establish that the positive definiteness of the Hessian of the associated Lagrangian at a saddle-point (rather than the objective function at each minimizer) guarantees finite convergence of the hierarchy. We obtain finite convergence by first establishing a new sum-of-squares polynomial representation of convex polynomials over convex semi-algebraic sets under a saddle-point condition. We finally prove that the existence of a saddle-point of the Lagrangian for a convex polynomial program is also necessary for the hierarchy to have finite convergence.Comment: 17 page

QED Penguin Contributions To Isospin Splittings of Heavy-Light Quark Systems

Recent experiments show that the isospin-violating mass splitting of the B mesons is very small, but the best fits with a QCD sum rule analysis give a splitting of at least 1.0 MeV. The isospin-violating mass splittings of the charmed mesons, on the other hand, are in agreement with experiment. In this letter we show that the inclusion of 2$^{nd}$ kind QED penguin diagrams can account for this discrepancy within the errors in the QCD sum rule method.Comment: 9 pages, latex, 2 figure

Macroscopic Black Holes, Microscopic Black Holes and Noncommutative Membrane

We study the stretched membrane of a black hole as consisting of a perfect fluid. We find that the pressure of this fluid is negative and the specific heat is negative too. A surprising result is that if we are to assume the fluid be composed of some quanta, then the dispersion relation of the fundamental quantum is $E=m^2/k$, with $m$ at the scale of the Planck mass. There are two possible interpretation of this dispersion relation, one is the noncommutative spacetime on the stretched membrane, another is that the fundamental quantum is microscopic black holes.Comment: 10 pages, harvmac; v2: refs. adde

Double-layer Perfect Metamaterial Absorber and Its Application for RCS Reduction of Antenna

To reduce the radar cross section (RCS) of a circularly polarized (CP) tilted beam antenna, a double-layer perfect metamaterial absorber (DLPMA) in the microwave frequency is proposed. The DLPMA exhibits a wider band by reducing the distance between the three absorption peaks. Absorbing characteristics are analyzed and the experimental results demonstrate that the proposed absorber works well from 5.95 GHz to 6.86 GHz (relative bandwidth 14.1%) with the thickness of 0.5 mm. Then, the main part of perfect electric conductor ground plane of the CP tilted beam antenna is covered by the DLPMA. Simu¬lated and experimental results reveal that the novel antenna performs well from 5.5 GHz to 7 GHz, and its monostatic RCS is reduced significantly from 5.8 GHz to 7 GHz. The agreement between measured and simulated data validates the present design