Quark Orbital Angular Momentum in the Baryon

Analytical and numerical results, for the orbital and spin content carried by different quark flavors in the baryons, are given in the chiral quark model with symmetry breaking. The reduction of the quark spin, due to the spin dilution in the chiral splitting processes, is transferred into the orbital motion of quarks and antiquarks. The orbital angular momentum for each quark flavor in the proton as a function of the partition factor $\kappa$ and the chiral splitting probability $a$ is shown. The cancellation between the spin and orbital contributions in the spin sum rule and in the baryon magnetic moments is discussed.Comment: 26 pages, 3 figures, revised version with minor eq. no and ref. no. corrections. Discussion on the $\Lambda$ spin and a new ref. are adde

Deep Discrete Hashing with Self-supervised Pairwise Labels

Hashing methods have been widely used for applications of large-scale image retrieval and classification. Non-deep hashing methods using handcrafted features have been significantly outperformed by deep hashing methods due to their better feature representation and end-to-end learning framework. However, the most striking successes in deep hashing have mostly involved discriminative models, which require labels. In this paper, we propose a novel unsupervised deep hashing method, named Deep Discrete Hashing (DDH), for large-scale image retrieval and classification. In the proposed framework, we address two main problems: 1) how to directly learn discrete binary codes? 2) how to equip the binary representation with the ability of accurate image retrieval and classification in an unsupervised way? We resolve these problems by introducing an intermediate variable and a loss function steering the learning process, which is based on the neighborhood structure in the original space. Experimental results on standard datasets (CIFAR-10, NUS-WIDE, and Oxford-17) demonstrate that our DDH significantly outperforms existing hashing methods by large margin in terms of~mAP for image retrieval and object recognition. Code is available at \url{https://github.com/htconquer/ddh}

A covariant entropy conjecture on cosmological dynamical horizon

We here propose a covariant entropy conjecture on cosmological dynamical horizon. After the formulation of our conjecture, we test its validity in adiabatically expanding universes with open, flat and closed spatial geometry, where our conjecture can also be viewed as a cosmological version of the generalized second law of thermodynamics in some sense.Comment: JHEP style, 9 pages, 1 figure, typos corrected, accepted for publication in JHE

First-principles calculations of the self-trapped exciton in crystalline NaCl

The atomic and electronic structure of the lowest triplet state of the off-center (C2v symmetry) self-trapped exciton (STE) in crystalline NaCl is calculated using the local-spin-density (LSDA) approximation. In addition, the Franck-Condon broadening of the luminescence peak and the a1g -> b3u absorption peak are calculated and compared to experiment. LSDA accurately predicts transition energies if the initial and final states are both localized or delocalized, but 1 eV discrepancies with experiment occur if one state is localized and the other is delocalized.Comment: 4 pages with 4 embeddded figure

Estimating Depth from RGB and Sparse Sensing

We present a deep model that can accurately produce dense depth maps given an RGB image with known depth at a very sparse set of pixels. The model works simultaneously for both indoor/outdoor scenes and produces state-of-the-art dense depth maps at nearly real-time speeds on both the NYUv2 and KITTI datasets. We surpass the state-of-the-art for monocular depth estimation even with depth values for only 1 out of every ~10000 image pixels, and we outperform other sparse-to-dense depth methods at all sparsity levels. With depth values for 1/256 of the image pixels, we achieve a mean absolute error of less than 1% of actual depth on indoor scenes, comparable to the performance of consumer-grade depth sensor hardware. Our experiments demonstrate that it would indeed be possible to efficiently transform sparse depth measurements obtained using e.g. lower-power depth sensors or SLAM systems into high-quality dense depth maps.Comment: European Conference on Computer Vision (ECCV) 2018. Updated to camera-ready version with additional experiment

Covariant entropy conjecture and concordance cosmological models

Recently a covariant entropy conjecture has been proposed for dynamical horizons. We apply this conjecture to concordance cosmological models, namely, those cosmological models filled with perfect fluids, in the presence of a positive cosmological constant. As a result, we find this conjecture has a severe constraint power. Not only does this conjecture rule out those cosmological models disfavored by the anthropic principle, but also it imposes an upper bound $10^{-60}$ on the cosmological constant for our own universe, which thus provides an alternative macroscopic perspective for understanding the long-standing cosmological constant problem.Comment: 10 pages, 1 figure, JHEP style, references added, published versio

Properties of vector mesons at finite temperature -effective lagrangian approach-

The properties of $\rho$-mesons at finite temperature ($T$) are examined with an effective chiral lagrangian in which vector and axial-vector mesons are included as massive Yang-Mills fields of the chiral symmetry. It is shown that, at $T^2$ order, the effective mass is not changed but only the mixing effect in vector and axial-vector correlator appears.Comment: 13 pages (REVTeX), two figures

The Far-Infrared Background Correlation with CMB Lensing

The intervening large--scale structure distorts cosmic microwave background (CMB) anisotropies via gravitational lensing. The same large--scale structure, traced by dusty star--forming galaxies, also induces anisotropies in the far--infrared background (FIRB). We investigate the resulting inter--dependence of the FIRB and CMB with a halo model for the FIRB. In particular, we calculate the cross--correlation between the lensing potential and the FIRB. The lensing potential can be quadratically estimated from CMB temperature and/or polarization maps. We show that the cross--correlation can be measured with high signal--to--noise with data from the Planck Surveyor. We discuss how such a measurement can be used to understand the nature of FIRB sources and their relation to the distribution of dark matter.Comment: 9 pages, 5 figures, submitted to Ap

An analysis of the acoustic cavitation noise spectrum: The role of periodic shock waves

Research on applications of acoustic cavitation is often reported in terms of the features within the spectrum of the emissions gathered during cavitation occurrence. There is, however, limited understanding as to the contribution of specific bubble activity to spectral features, beyond a binary interpretation of stable versus inertial cavitation. In this work, laser-nucleation is used to initiate cavitation within a few millimeters of the tip of a needle hydrophone, calibrated for magnitude and phase from 125 kHz to 20 MHz. The bubble activity, acoustically driven at f0 = 692 kHz, is resolved with high-speed shadowgraphic imaging at 5 × 106 frames per second. A synthetic spectrum is constructed from component signals based on the hydrophone data, deconvolved within the calibration bandwidth, in the time domain. Cross correlation coefficients between the experimental and synthetic spectra of 0.97 for the f 0/2 and f 0/3 regimes indicate that periodic shock waves and scattered driving field predominantly account for all spectral features, including the sub-harmonics and their over-harmonics, and harmonics of f 0