Synthetic horizontal branch morphology for different metallicities and ages under tidally enhanced stellar wind

It is believed that, except for metallicity, some other parameters are needed to explain the horizontal branch (HB) morphology of globular clusters (GCs). Furthermore, these parameters are considered to be correlated with the mass loss of the red giant branch (RGB) stars. In our previous work, we proposed that tidally enhanced stellar wind during binary evolution may affect the HB morphology by enhancing the mass loss of the red giant primary. As a further study, we now investigate the effects of metallicity and age on HB morphology by considering tidally enhanced stellar winds during binary evolution. We incorporated the tidally enhanced-stellar-wind model into Eggleton's stellar evolution code to study the binary evolution. To study the effects of metallicity and age on our final results, we conducted two sets of model calculations: (i) for a fixed age, we used three metallicities, namely Z=0.0001, 0.001, and 0.02. (ii) For a fixed metallicity, Z=0.001, we used five ages in our model calculations: 14, 13, 12, 10, and 7 Gyr. We found that HB morphology of GCs becomes bluer with decreasing metallicity, and old GCs present bluer HB morphology than young ones. These results are consistent with previous work. Although the envelope-mass distributions of zero-age HB stars produced by tidally enhanced stellar wind are similar for different metallicities, the synthetic HB under tidally enhanced stellar wind for Z=0.02 presented a distinct gap between red and blue HB. However, this feature was not seen clearly in the synthetic HB for Z=0.001 and 0.0001. We also found that higher binary fractions may make HB morphology become bluer, and we discussed the results with recent observations.Comment: 16 pages, 6 figures, 3 tables, accepted for publication in Astronomy & Astrophysic

On a refinement of Wilf-equivalence for permutations

Recently, Dokos et al. conjectured that for all $k, m\geq 1$, the patterns $12\ldots k(k+m+1)\ldots (k+2)(k+1)$ and $(m+1)(m+2)\ldots (k+m+1)m\ldots 21$ are $maj$-Wilf-equivalent. In this paper, we confirm this conjecture for all $k\geq 1$ and $m=1$. In fact, we construct a descent set preserving bijection between $12\ldots k (k-1)$-avoiding permutations and $23\ldots k1$-avoiding permutations for all $k\geq 3$. As a corollary, our bijection enables us to settle a conjecture of Gowravaram and Jagadeesan concerning the Wilf-equivalence for permutations with given descent sets

[Colored solutions of Yang-Baxter equation from representations of U_{q}gl(2)]

We study the Hopf algebra structure and the highest weight representation of a multiparameter version of $U_{q}gl(2)$. The commutation relations as well as other Hopf algebra maps are explicitly given. We show that the multiparameter universal ${\cal R}$ matrix can be constructed directly as a quantum double intertwiner, without using Reshetikhin's transformation. An interesting feature automatically appears in the representation theory: it can be divided into two types, one for generic $q$, the other for $q$ being a root of unity. When applying the representation theory to the multiparameter universal ${\cal R}$ matrix, the so called standard and nonstandard colored solutions $R(\mu,\nu; {\mu}', {\nu}')$ of the Yang-Baxter equation is obtained.Comment: [14]pages, latex, no figure

First High Contrast Imaging Using a Gaussian Aperture Pupil Mask

Placing a pupil mask with a gaussian aperture into the optical train of current telescopes represents a way to attain high contrast imaging that potentially improves contrast by orders of magnitude compared to current techniques. We present here the first observations ever using a gaussian aperture pupil mask (GAPM) on the Penn State near-IR Imager and Spectrograph (PIRIS) at the Mt. Wilson 100$^{\prime\prime}$ telescope. Two nearby stars were observed, $\epsilon$ Eridani and $\mu$ Her A. A faint companion was detected around $\mu$ Her A, confirming it as a proper motion companion. Furthermore, the observed H and K magnitudes of the companion were used to constrain its nature. No companions or faint structure were observed for $\epsilon$ Eridani. We found that our observations with the GAPM achieved contrast levels similar to our coronographic images, without blocking light from the central star. The mask's performance also nearly reached sensitivities reported for other ground based adaptive optics coronographs and deep HST images, but did not reach theoretically predicted contrast levels. We outline ways that could improve the performance of the GAPM by an order of magnitude or more.Comment: 8 pages, 4 figures, accepted by ApJ letter

Shear viscosity, instability and the upper bound of the Gauss-Bonnet coupling constant

We compute the dimensionality dependence of $\eta/s$ for charged black branes with Gauss-Bonnet correction. We find that both causality and stability constrain the value of Gauss-Bonnet coupling constant to be bounded by 1/4 in the infinite dimensionality limit. We further show that higher dimensionality stabilize the gravitational perturbation. The stabilization of the perturbation in higher dimensional space-time is a straightforward consequence of the Gauss-Bonnet coupling constant bound.Comment: 16 pages,3 figures+3 tables,typos corrected, published versio

Algebraic Bethe Ansatz for Integrable Extended Hubbard Models Arising from Supersymmetric Group Solutions

Integrable extended Hubbard models arising from symmetric group solutions are examined in the framework of the graded Quantum Inverse Scattering Method. The Bethe ansatz equations for all these models are derived by using the algebraic Bethe ansatz method.Comment: 15 pages, RevTex, No figures, to be published in J. Phys.

Stochastic Physics, Complex Systems and Biology

In complex systems, the interplay between nonlinear and stochastic dynamics, e.g., J. Monod's necessity and chance, gives rise to an evolutionary process in Darwinian sense, in terms of discrete jumps among attractors, with punctuated equilibrium, spontaneous random "mutations" and "adaptations". On an evlutionary time scale it produces sustainable diversity among individuals in a homogeneous population rather than convergence as usually predicted by a deterministic dynamics. The emergent discrete states in such a system, i.e., attractors, have natural robustness against both internal and external perturbations. Phenotypic states of a biological cell, a mesoscopic nonlinear stochastic open biochemical system, could be understood through such a perspective.Comment: 10 page

Joint interaction with context operation for collaborative filtering

In recommender systems, the classical matrix factorization model for collaborative filtering only considers joint interactions between users and items. In contrast, context-aware recommender systems (CARS) use contexts to improve recommendation performance. Some early CARS models treat user, item and context equally, unable to capture contextual impact accurately. More recent models perform context operations on users and items separately, leading to “double-counting” of contextual information. This paper proposes a new model, Joint Interaction with Context Operation (JICO), to integrate the joint interaction model with the context operation model, via two layers. The joint interaction layer models interactions between users and items via an interaction tensor. The context operation layer captures contextual information via a contextual operating tensor. We evaluate JICO on four datasets and conduct novel studies, including varying contextual influence and time split recommendation. JICO consistently outperforms competing methods, while providing many useful insights to assist further analysis

Pose-Normalized Image Generation for Person Re-identification

Person Re-identification (re-id) faces two major challenges: the lack of cross-view paired training data and learning discriminative identity-sensitive and view-invariant features in the presence of large pose variations. In this work, we address both problems by proposing a novel deep person image generation model for synthesizing realistic person images conditional on the pose. The model is based on a generative adversarial network (GAN) designed specifically for pose normalization in re-id, thus termed pose-normalization GAN (PN-GAN). With the synthesized images, we can learn a new type of deep re-id feature free of the influence of pose variations. We show that this feature is strong on its own and complementary to features learned with the original images. Importantly, under the transfer learning setting, we show that our model generalizes well to any new re-id dataset without the need for collecting any training data for model fine-tuning. The model thus has the potential to make re-id model truly scalable.Comment: 10 pages, 5 figure