Cosmological Constraints on Variable Warm Dark Matter

Although $\Lambda$CDM model is very successful in many aspects, it has been seriously challenged. Recently, warm dark matter (WDM) remarkably rose as an alternative of cold dark matter (CDM). In the literature, many attempts have been made to determine the equation-of-state parameter (EoS) of WDM. However, in most of the previous works, it is usually assumed that the EoS of dark matter (DM) is constant (and usually the EoS of dark energy is also constant). Obviously, this assumption is fairly restrictive. It is more natural to assume a variable EoS for WDM (and dark energy). In the present work, we try to constrain the EoS of variable WDM with the current cosmological observations. We find that the best fits indicate WDM, while CDM is still consistent with the current observational data. However, $\Lambda$CDM is still better than WDM models from the viewpoint of goodness-of-fit. So, in order to distinguish WDM and CDM, the further observations on the small/galactic scale are required. On the other hand, in this work we also consider WDM whose EoS is constant, while the role of dark energy is played by various models. We find that the cosmological constraint on the constant EoS of WDM is fairly robust.Comment: 11 pages, 6 figures, 1 table, revtex4; v2: discussions added, Phys. Lett. B in press; v3: published versio

Dense CNN Learning with Equivalent Mappings

Large receptive field and dense prediction are both important for achieving high accuracy in pixel labeling tasks such as semantic segmentation. These two properties, however, contradict with each other. A pooling layer (with stride 2) quadruples the receptive field size but reduces the number of predictions to 25\%. Some existing methods lead to dense predictions using computations that are not equivalent to the original model. In this paper, we propose the equivalent convolution (eConv) and equivalent pooling (ePool) layers, leading to predictions that are both dense and equivalent to the baseline CNN model. Dense prediction models learned using eConv and ePool can transfer the baseline CNN's parameters as a starting point, and can inverse transfer the learned parameters in a dense model back to the original one, which has both fast testing speed and high accuracy. The proposed eConv and ePool layers have achieved higher accuracy than baseline CNN in various tasks, including semantic segmentation, object localization, image categorization and apparent age estimation, not only in those tasks requiring dense pixel labeling.Comment: submitted to NIPS 201

Martingale Hardy spaces with variable exponents

In this paper, we introduce Hardy spaces with variable exponents defined on a probability space and develop the martingale theory of variable Hardy spaces. We prove the weak type and strong type inequalities on Doob's maximal operator and get a $(1,p(\cdot),\infty)$-atomic decomposition for Hardy martingale spaces associated with conditional square functions. As applications, we obtain a dual theorem and the John-Nirenberg inequalities in the frame of variable exponents. The key ingredient is that we find a condition with probabilistic characterization of $p(\cdot)$ to replace the so-called log-H\"{o}lder continuity condition in $\mathbb {R}^n.$Comment: Banach Journal of Mathematical Analysis, to appea

Content-Centric Multicast Beamforming in Cache-Enabled Cloud Radio Access Networks

Multicast transmission and wireless caching are effective ways of reducing air and backhaul traffic load in wireless networks. This paper proposes to incorporate these two key ideas for content-centric multicast transmission in a cloud radio access network (RAN) where multiple base stations (BSs) are connected to a central processor (CP) via finite-capacity backhaul links. Each BS has a cache with finite storage size and is equipped with multiple antennas. The BSs cooperatively transmit contents, which are either stored in the local cache or fetched from the CP, to multiple users in the network. Users requesting a same content form a multicast group and are served by a same cluster of BSs cooperatively using multicast beamforming. Assuming fixed cache placement, this paper investigates the joint design of multicast beamforming and content-centric BS clustering by formulating an optimization problem of minimizing the total network cost under the quality-of-service (QoS) constraints for each multicast group. The network cost involves both the transmission power and the backhaul cost. We model the backhaul cost using the mixed $\ell_0/\ell_2$-norm of beamforming vectors. To solve this non-convex problem, we first approximate it using the semidefinite relaxation (SDR) method and concave smooth functions. We then propose a difference of convex functions (DC) programming algorithm to obtain suboptimal solutions and show the connection of three smooth functions. Simulation results validate the advantage of multicasting and show the effects of different cache size and caching policies in cloud RAN.Comment: IEEE Globecom 201

Content-Centric Sparse Multicast Beamforming for Cache-Enabled Cloud RAN

This paper presents a content-centric transmission design in a cloud radio access network (cloud RAN) by incorporating multicasting and caching. Users requesting a same content form a multicast group and are served by a same cluster of base stations (BSs) cooperatively. Each BS has a local cache and it acquires the requested contents either from its local cache or from the central processor (CP) via backhaul links. We investigate the dynamic content-centric BS clustering and multicast beamforming with respect to both channel condition and caching status. We first formulate a mixed-integer nonlinear programming problem of minimizing the weighted sum of backhaul cost and transmit power under the quality-of-service constraint for each multicast group. Theoretical analysis reveals that all the BSs caching a requested content can be included in the BS cluster of this content, regardless of the channel conditions. Then we reformulate an equivalent sparse multicast beamforming (SBF) problem. By adopting smoothed $\ell_0$-norm approximation and other techniques, the SBF problem is transformed into the difference of convex (DC) programs and effectively solved using the convex-concave procedure algorithms. Simulation results demonstrate significant advantage of the proposed content-centric transmission. The effects of three heuristic caching strategies are also evaluated.Comment: To appear in IEEE Trans. on Wireless Communication

Improving Wireless Physical Layer Security via D2D Communication

This paper investigates the physical layer security issue of a device-to-device (D2D) underlaid cellular system with a multi-antenna base station (BS) and a multi-antenna eavesdropper. To investigate the potential of D2D communication in improving network security, the conventional network without D2D users (DUs) is first considered. It is shown that the problem of maximizing the sum secrecy rate (SR) of cellular users (CUs) for this special case can be transformed to an assignment problem and optimally solved. Then, a D2D underlaid network is considered. Since the joint optimization of resource block (RB) allocation, CU-DU matching and power control is a mixed integer programming, the problem is difficult to handle. Hence, the RB assignment process is first conducted by ignoring D2D communication, and an iterative algorithm is then proposed to solve the remaining problem. Simulation results show that the sum SR of CUs can be greatly increased by D2D communication, and compared with the existing schemes, a better secrecy performance can be obtained by the proposed algorithms.Comment: 7 pages, 4 figures, accepted for presentation at the 2018 Global Communications Conference (IEEE GLOBECOM

Detection of the Prodromal Phase of Bipolar Disorder from Psychological and Phonological Aspects in Social Media

Seven out of ten people with bipolar disorder are initially misdiagnosed and thirty percent of individuals with bipolar disorder will commit suicide. Identifying the early phases of the disorder is one of the key components for reducing the full development of the disorder. In this study, we aim at leveraging the data from social media to design predictive models, which utilize the psychological and phonological features, to determine the onset period of bipolar disorder and provide insights on its prodrome. This study makes these discoveries possible by employing a novel data collection process, coined as Time-specific Subconscious Crowdsourcing, which helps collect a reliable dataset that supplements diagnosis information from people suffering from bipolar disorder. Our experimental results demonstrate that the proposed models could greatly contribute to the regular assessments of people with bipolar disorder, which is important in the primary care setting

f(T)f(T) non-linear massive gravity and the cosmic acceleration

Inspired by the $f(R)$ non-linear massive gravity, we propose a new kind of modified gravity model, namely $f(T)$ non-linear massive gravity, by adding the dRGT mass term reformulated in the vierbein formalism, to the $f(T)$ theory. We then investigate the cosmological evolution of $f(T)$ massive gravity, and constrain it by using the latest observational data. We find that it slightly favors a crossing of the phantom divide line from the quintessence-like phase ($w_{de} > -1$) to the phantom-like one ($w_{de} < -1$) as redshift decreases.Comment: 12 pages, 4 figures, revtex4, Commun. Theor. Phys. in press; v2: published versio

ALMA Submillimeter Continuum Imaging of the Host Galaxies of GRB021004 and GRB080607

We report 345 GHz continuum observations of the host galaxies of gamma-ray bursts (GRBs) 021004 and 080607 at z>2 using the Atacama Large Millimeter/Submillimeter Array (ALMA) in Cycle 0. Of the two bursts, GRB021004 is one of the few GRBs that originates in a Lyman limit host, while GRB080607 is classified as a "dark burst" and its host galaxy is a candidate of dusty star forming galaxy at z~3. With an order of magnitude improvement in the sensitivities of the new imaging searches, we detect the host galaxy of GRB080607 with a flux of S_{345} = 0.31+/-0.09 mJy and a corresponding infrared luminosity of L_{IR}=(2.4-4.5)x10^{11} L_sun. However, the host galaxy of GRB021004 remains undetected and the ALMA observations allow us to place a 3-sigma upper limit of L_{IR}<3.1x10^{11} L_sun for the host galaxy. The continuum imaging observations show that the two galaxies are not ultraluminous infrared galaxies but are at the faintest end of the dusty galaxy population that gives rise to the submillimeter extragalactic background light. The derived star formation rates of the two GRB host galaxies are less than 100 M_sun yr^{-1}, which are broadly consistent with optical measurements. The result suggests that the large extinction (A_V~3) in the afterglow of GRB080607 is confined along its particularly dusty sightline, and not representative of the global properties of the host galaxy.Comment: 5 pages, 3 figures; accepted for publication in ApJ Letter

Topological and Geometric Universal Thermodynamics in Conformal Field Theory

Universal thermal data in conformal field theory (CFT) offer a valuable means for characterizing and classifying criticality. With improved tensor network techniques, we investigate the universal thermodynamics on a nonorientable minimal surface, the crosscapped disk (or real projective plane, $\mathbb{RP}^2$). Through a cut-and-sew process, $\mathbb{RP}^2$ is topologically equivalent to a cylinder with rainbow and crosscap boundaries. We uncover that the crosscap contributes a fractional topological term $\frac{1}{2} \ln{k}$ related to nonorientable genus, with $k$ a universal constant in two-dimensional CFT, while the rainbow boundary gives rise to a geometric term $\frac{c}{4} \ln{\beta}$, with $\beta$ the manifold size and $c$ the central charge. We have also obtained analytically the logarithmic rainbow term by CFT calculations, and discuss its connection to the renowned Cardy-Peschel conical singularity.Comment: 4 pages + references, 7 figures, 2 tables, supplementary material; published versio