Quantum entangled ground states of two spinor Bose-Einstein condensates

We revisit in detail the non-mean-field ground-state phase diagram for a binary mixture of spin-1 Bose-Einstein condensates including quantum fluctuations. The non-commuting terms in the spin-dependent Hamiltonian under single spatial mode approximation make it difficult to obtain exact eigenstates. Utilizing the spin z-component conservation and the total spin angular momentum conservation, we numerically derive the information of the building blocks and evaluate von Neumann entropy to quantify the ground states. The mean-field phase boundaries are found to remain largely intact, yet the ground states show fragmented and entangled behaviors within large parameter spaces of interspecies spin-exchange and singlet-pairing interactions.Comment: 7 pages, 5 figure

Intersecting M-branes and bound states

In this paper, we construct multi-scalar, multi-center $p$-brane solutions in toroidally compactified M-theory. We use these solutions to show that all supersymmetric $p$-branes can be viewed as bound states of certain basic building blocks, namely $p$-branes that preserve $1/2$ of the supersymmetry. We also explore the M-theory interpretation of $p$-branes in lower dimensions. We show that all the supersymmetric $p$-branes can be viewed as intersections of M-branes or boosted M-branes in $D=11$.Comment: Latex, 14 pages, no figures. References adde

On defining partition entropy by inequalities

Partition entropy is the numerical metric of uncertainty within a partition of a finite set, while conditional entropy measures the degree of difficulty in predicting a decision partition when a condition partition is provided. Since two direct methods exist for defining conditional entropy based on its partition entropy, the inequality postulates of monotonicity, which conditional entropy satisfies, are actually additional constraints on its entropy. Thus, in this paper partition entropy is defined as a function of probability distribution, satisfying all the inequalities of not only partition entropy itself but also its conditional counterpart. These inequality postulates formalize the intuitive understandings of uncertainty contained in partitions of finite sets.We study the relationships between these inequalities, and reduce the redundancies among them. According to two different definitions of conditional entropy from its partition entropy, the convenient and unified checking conditions for any partition entropy are presented, respectively. These properties generalize and illuminate the common nature of all partition entropies

Annihilation Type Radiative Decays of BB Meson in Perturbative QCD Approach

With the perturbative QCD approach based on $k_T$ factorization, we study the pure annihilation type radiative decays $B^0 \to \phi\gamma$ and $B^0\to J/\psi \gamma$. We find that the branching ratio of $B^0 \to \phi\gamma$ is $(2.7^{+0.3+1.2}_{-0.6-0.6})\times10^{-11}$, which is too small to be measured in the current $B$ factories of BaBar and Belle. The branching ratio of $B^0\to J/\psi \gamma$ is $({4.5^{+0.6+0.7}_{-0.5-0.6}})\times10^{-7}$, which is just at the corner of being observable in the $B$ factories. A larger branching ratio $BR(B_s^0 \to J/\psi \gamma) \simeq 5 \times 10^{-6}$ is also predicted. These decay modes will help us testing the standard model and searching for new physics signals.Comment: 4 pages, revtex, with 1 eps figur

Adaptive neighborhood search for nurse rostering

This paper presents an adaptive neighborhood search method (ANS) for solving the nurse rostering problem proposed for the First International Nurse Rostering Competition (INRC-2010). ANS uses jointly two distinct neighborhood moves and adaptively switches among three intensification and diversification search strategies according to the search history. Computational results assessed on the three sets of 60 competition instances show that ANS improves the best known results for 12 instances while matching the best bounds for 39 other instances. An analysis of some key elements of ANS sheds light on the understanding of the behavior of the proposed algorithm

Adaptive Tabu Search for course timetabling

This paper presents an Adaptive Tabu Search algorithm (denoted by ATS) for solving a problem of curriculum-based course timetabling. The proposed algorithm follows a general framework composed of three phases: initialization, intensification and diversification. The initialization phase constructs a feasible initial timetable using a fast greedy heuristic. Then an adaptively combined intensification and diversification phase is used to reduce the number of soft constraint violations while maintaining the satisfaction of hard constraints. The proposed ATS algorithm integrates several distinguished features such as an original double Kempe chains neighborhood structure, a penalty-guided perturbation operator and an adaptive search mechanism. Computational results show the high effectiveness of the proposed ATS algorithm, compared with five reference algorithms as well as the current best known results. This paper also shows an analysis to explain which are the essential ingredients of the ATS algorithm