Coarse-graining the dynamics of coupled oscillators

We present an equation-free computational approach to the study of the coarse-grained dynamics of {\it finite} assemblies of {\it non-identical} coupled oscillators at and near full synchronization. We use coarse-grained observables which account for the (rapidly developing) correlations between phase angles and oscillator natural frequencies. Exploiting short bursts of appropriately initialized detailed simulations, we circumvent the derivation of closures for the long-term dynamics of the assembly statistics.Comment: accepted for publication in Phys. Rev. Let

Fragmented and Single Condensate Ground States of Spin-1 Bose Gas

We show that the ground state of a spin-1 Bose gas with an antiferro- magnetic interaction is a fragmented condensate in uniform magnetic fields. The number fluctuations in each spin component change rapidly from being enormous (order $N$) to exceedingly small (order 1) as the magnetization of the system increases. A fragmented condensate can be turned into a single condensate state by magnetic field gradients. The conditions for existence and the method of detecting fragmented states are presented.Comment: 4 pages, no figure

Particle dynamics in a class of 2-dimensional gravity theories

We provide a method to determine the motion of a classical massive particle in a background geometry of 2-dimensional gravity theories, for which the Birkhoff theorem holds. In particular, we get the particle trajectory in a continuous class of 2-dimensional dilaton gravity theories that includes the Callan-Giddings-Harvey-Strominger (CGHS) model, the Jackiw-Teitelboim (JT) model, and the $d$-dimensional $s$-wave Einstein gravity. The explicit trajectory expressions for these theories are given along with the discussions on the results.Comment: 15 pages, LaTeX. The deletion of the repeated portion of the abstract and the proper line wrapping of the tex file. No other change

Microstructure and superconducting properties of hot isostatically pressed MgB2

Bulk samples of MgB2 have been formed by hot isostatic pressing (HIPping) of commercial powder at 100MPa and 950=B0C. The resulting material is 100% dense with a sharp superconducting transition at 37.5K. Microstructural studies have indicated the presence of small amounts of second phases within the material, namely MgO and B rich compositions, probably MgB4. Magnetisation measurements performed at 20K have revealed values of Jc=1.3 x 106A/cm2 at zero field, and 9.3 x 105A/cm2 at 1T. Magneto optical (MO) studies have shown direct evidence for the superconducting homogeneity and strong intergranular current flow in the material.Comment: 3 pages, 6 figures, text updated, new references included and discussed. Submitted to Superconductor Science and Technolog

UBVI Surface Photometry of the Spiral Galaxy NGC 300 in the Sculptor Group

We present UBVI surface photometry for 20.'5 X 20.'5 area of a late-type spiral galaxy NGC 300. In order to understand the morphological properties and luminosity distribution characteristics of NGC 300, we have derived isophotal maps, surface brightness profiles, ellipticity profiles, position angle profiles, and color profiles. By merging the I-band data of our surface brightness measurements with those of Boeker et al. (2002) based on Hubble Space Telescope observations, we have made combined I-band surface brightness profiles for the region of 0."02 < r < 500" and decomposed the profiles into three components: a nucleus, a bulge, and an exponential disk.Comment: 16 pages(cjaa209.sty), Accepted by the Chinese J. Astron. Astrophys., Fig 2 and 8 are degraded to reduce spac

Actor-Critic Sequence Training for Image Captioning.

Generating natural language descriptions of images is an important capability for a robot or other visual-intelligence driven AI agent that may need to communicate with human users about what it is seeing. Such image captioning methods are typically trained by maximising the likelihood of ground-truth annotated caption given the image. While simple and easy to implement, this approach does not directly maximise the language quality metrics we care about such as CIDEr. In this paper we investigate training image captioning methods based on actor-critic reinforcement learning in order to directly optimise non-differentiable quality metrics of interest. By formulating a per-token advantage and value computation strategy in this novel reinforcement learning based captioning model, we show that it is possible to achieve the state of the art performance on the widely used MSCOCO benchmark