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Bo Wang

Publications and source records attributed to Bo Wang.

At least 685 records · Page 38Linked to original sources
arXiv2019

Second-order cosmological perturbations. I. Produced by scalar-scalar coupling in synchronous gauge

We present a systematic study of the 2nd order scalar, vector and tensor metric perturbations in the Einstein-de Sitter Universe in synchronous coordinates. For the scalar-scalar coupling between 1st order perturbations, we decompose the 2nd order perturbed Einstein equation into the respective field equations of 2nd order scalar, vector, and tensor perturbations, and obtain their solutions with general initial conditions. In particular, the decaying modes of solution are included, the 2nd order vector is generated even the 1st order vector is absent, and the solution of 2nd order tensor corrects that in literature. We perform general synchronous-to-synchronous gauge transformations up to 2nd order generated by a 1st order vector field $ξ^{(1)μ}$ and a 2nd order $ξ^{(2)μ}$. All the residual gauge modes of 2nd order metric perturbations and density contrast are found, and their number is substantially reduced when the transformed 3-velocity of dust is set be zero. Moreover, we show that only $ξ^{(2)μ}$ is effective in carrying out 2nd order transformations that we consider, because $ξ^{(1)μ}$ has been used in obtaining the 1st order perturbations. Holding the 1st order perturbations fixed, the transformations by $ξ^{(2)μ}$ on the 2nd order perturbations have the same structure as those by $ξ^{(1)μ}$ on the 1st order perturbations.

gr-qc↗
arXiv2019

Second-order cosmological perturbations. III. Produced by scalar-scalar coupling during radiation-dominated stage

We study the 2nd-order scalar, vector and tensor metric perturbations in Robertson-Walker (RW) spacetime in synchronous coordinates during the radiation dominated (RD) stage. The dominant radiation is modeled by a relativistic fluid described by a stress tensor $T_{μν}=(ρ+p)U_μU_ν+g_{μν}p$ with $p= c^2_s ρ$, and the 1st-order velocity is assumed to be curlless. We analyze the solutions of 1st-order perturbations, upon which the solutions of 2nd-order perturbation are based. We show that the 1st-order tensor modes propagate at the speed of light and are truly radiative, but the scalar and vector modes do not. The 2nd-order perturbed Einstein equation contains various couplings of 1st-order metric perturbations, and the scalar-scalar coupling is considered in this paper. We decompose the 2nd-order Einstein equation into the evolution equations of 2nd-order scalar, vector, and tensor perturbations, and the energy and momentum constraints. The coupling terms and the stress tensor of the fluid together serve as the effective source for the 2nd-order metric perturbations. The equation of covariant conservation of stress tensor is also needed to determine $ρ$ and $U^μ$. By solving this set of equations up to 2nd order analytically, we obtain the 2nd-order integral solutions of all the metric perturbations, density contrast and velocity. To use these solutions in applications, one needs to carry out seven types of the numerical integrals. We perform the residual gauge transformations between synchronous coordinates up to 2nd order, and identify the gauge-invariant modes of 2nd-order solutions.

gr-qc↗
arXiv2019

Optimization of high performance spintronic terahertz sources

To achieve high efficiency and good performance of spintronic terahertz sources, we propose and corroborate a remnant magnetization method to radiate continuously and stably terahertz pulses from W/CoFeB/Pt magnetic nanofilms without carrying magnets on the transmitters driven by femtosecond laser pulses. We systematically investigate the influences of the pumping central wavelength and find out the optimal wavelength for a fixed sample thickness. We also optimize the incidence angle of the pumping laser and find the emission efficiency is enhanced under oblique incidence. Combing the aforementioned optimizations, we finally obtain comparable radiation efficiency and broadband spectra in W/CoFeB/Pt heterostructures compared with that from 1 mm thick ZnTe nonlinear crystals via optical rectification under the same pumping conditions of 100 fs pulse duration from a Ti:sapphire laser oscillator, which was not previously demonstrated under such pulse duration. We believe our observations not only benefit for a deep insight into the physics of femtosecond spin dynamics, but also help develop novel and cost-effective ultrabroadband spintronic terahertz emitters.

physics.optics↗
arXiv2019

New insights on Multi-Solution Distribution of the P3P Problem

Traditionally, the P3P problem is solved by firstly transforming its 3 quadratic equations into a quartic one, then by locating the roots of the resulting quartic equation and verifying whether a root does really correspond to a true solution of the P3P problem itself. However, a root of the quartic equation does not always correspond to a solution of the P3P problem. In this work, we show that when the optical center is outside of all the 6 toroids defined by the control point triangle, each positive root of the Grunert's quartic equation must correspond to a true solution of the P3P problem, and the corresponding P3P problem cannot have a unique solution, it must have either 2 positive solutions or 4 positive solutions. In addition, we show that when the optical center passes through any one of the 3 toroids among these 6 toroids ( except possibly for two concentric circles) , the number of the solutions of the corresponding P3P problem always changes by 1, either increased by 1 or decreased by 1.Furthermore we show that such changed solutions always locate in a small neighborhood of control points, hence the 3 toroids are critical surfaces of the P3P problem and the 3 control points are 3 singular points of solutions. A notable example is that when the optical center passes through the outer surface of the union of the 6 toroids from the outside to inside, the number of the solutions must always decrease by 1. Our results are the first to give an explicit and geometrically intuitive relationship between the P3P solutions and the roots of its quartic equation. It could act as some theoretical guidance for P3P practitioners to properly arrange their control points to avoid undesirable solutions.

cs.CV↗
arXiv2019

$\bar{B}^{(\ast)} \bar{B}^{(\ast)}$ interactions in chiral effective field theory

In this work, the intermeson interactions of double-beauty $\bar{B}\bar{B}$, $\bar{B}\bar{B}^\ast$, and $\bar{B}^\ast\bar{B}^\ast$ systems have been studied with heavy meson chiral effective field theory. The effective potentials are calculated with Weinberg's scheme up to one-loop level. At the leading order, four body contact interactions and one pion exchange contributions are considered. In addition to two pion exchange diagrams, we include the one-loop chiral corrections to contact terms and one pion exchange diagrams at the next-to-leading order. The behaviours of effective potentials both in momentum space and coordinate space are investigated and discussed extensively. We notice the contact terms play important roles in determining the characteristics of the total potentials. Only the potentials in $I(J^P)=0(1^+)$ $\bar{B}\bar{B}^\ast$ and $\bar{B}^\ast\bar{B}^\ast$ systems are attractive, and the corresponding binding energies in these two channels are solved to be $ΔE_{\bar{B}\bar{B}^\ast}\simeq -12.6^{+9.2}_{-12.9}$ MeV and $ΔE_{\bar{B}^\ast\bar{B}^\ast}\simeq -23.8^{+16.3}_{-21.5}$ MeV, respectively. The masses of $0(1^+)$ $\bar{B}\bar{B}^\ast$ and $\bar{B}^\ast\bar{B}^\ast$ states lie above the threshold of their electromagnetic decay modes $\bar{B}\bar{B}γ$ and $\bar{B}\bar{B}γγ$, and thus they can be reconstructable via electromagnetic interactions. Our calculation not only provides some useful information to explore exotic doubly-bottomed molecular states for future experiments, but also is helpful for the extrapolations of Lattice QCD simulations.

hep-ph↗
arXiv2019

Towards a Liouville theorem for continuous viscosity solutions to fully nonlinear elliptic equations in conformal geometry

We study entire continuous viscosity solutions to fully nonlinear elliptic equations involving the conformal Hessian. We prove the strong comparison principle and Hopf Lemma for (non-uniformly) elliptic equations when one of the competitors is $C^{1,1}$. We obtain as a consequence a Liouville theorem for entire solutions which are approximable by $C^{1,1}$ solutions on larger and larger compact domains, and, in particular, for entire $C^{1,1}_{\rm loc}$ solutions: they are either constants or standard bubbles.

math.AP↗
arXiv2019

Multivariate Gaussian and Student$-t$ Process Regression for Multi-output Prediction

Gaussian process model for vector-valued function has been shown to be useful for multi-output prediction. The existing method for this model is to re-formulate the matrix-variate Gaussian distribution as a multivariate normal distribution. Although it is effective in many cases, re-formulation is not always workable and is difficult to apply to other distributions because not all matrix-variate distributions can be transformed to respective multivariate distributions, such as the case for matrix-variate Student$-t$ distribution. In this paper, we propose a unified framework which is used not only to introduce a novel multivariate Student$-t$ process regression model (MV-TPR) for multi-output prediction, but also to reformulate the multivariate Gaussian process regression (MV-GPR) that overcomes some limitations of the existing methods. Both MV-GPR and MV-TPR have closed-form expressions for the marginal likelihoods and predictive distributions under this unified framework and thus can adopt the same optimization approaches as used in the conventional GPR. The usefulness of the proposed methods is illustrated through several simulated and real data examples. In particular, we verify empirically that MV-TPR has superiority for the datasets considered, including air quality prediction and bike rent prediction. At last, the proposed methods are shown to produce profitable investment strategies in the stock markets.

stat.ML↗
arXiv2018

Femtosecond control of terahertz spin-charge conversion in ferromagnetic heterostructures

Employing electron spin instead of charge to develop spintronic devices holds the merits of low-power consumption in information technologies. Meanwhile, the demand for increasing speed in spintronics beyond current CMOS technology has further triggered intensive researches for ultrafast control of spins even up to unprecedent terahertz regime. The femtosecond laser has been emerging as a potential technique to generate an ultrafast spin-current burst for magnetization manipulation. However, there is a great challenge to establish all-optical control and monitor of the femtosecond transient spin current. Deep insights into the physics and mechanism are extremely essential for the technique. Here, we demonstrate coherently nonthermal excitation of femtosecond spin-charge current conversion parallel to the magnetization in W/CoFeB/Pt heterostructures driven by linearly polarized femtosecond laser pulses. Through systematical investigation we observe the terahertz emission polarization depends on both the magnetization direction and structural asymmetry. We attribute this phenomenon of the terahertz generation parallel to the magnetization induced by linearly polarized femtosecond laser pulses probably to inverse spin-orbit torque effect. Our work not only is beneficial to the deep understanding of spin-charge conversion and spin transportation, but also helps develop novel on-chip terahertz opto-spintronic devices.

physics.optics↗
arXiv2018

Robust Face Detection via Learning Small Faces on Hard Images

Recent anchor-based deep face detectors have achieved promising performance, but they are still struggling to detect hard faces, such as small, blurred and partially occluded faces. A reason is that they treat all images and faces equally, without putting more effort on hard ones; however, many training images only contain easy faces, which are less helpful to achieve better performance on hard images. In this paper, we propose that the robustness of a face detector against hard faces can be improved by learning small faces on hard images. Our intuitions are (1) hard images are the images which contain at least one hard face, thus they facilitate training robust face detectors; (2) most hard faces are small faces and other types of hard faces can be easily converted to small faces by shrinking. We build an anchor-based deep face detector, which only output a single feature map with small anchors, to specifically learn small faces and train it by a novel hard image mining strategy. Extensive experiments have been conducted on WIDER FACE, FDDB, Pascal Faces, and AFW datasets to show the effectiveness of our method. Our method achieves APs of 95.7, 94.9 and 89.7 on easy, medium and hard WIDER FACE val dataset respectively, which surpass the previous state-of-the-arts, especially on the hard subset. Code and model are available at https://github.com/bairdzhang/smallhardface.

cs.CV↗
arXiv2018

Past and future of the central double-degenerate core of Henize 2-428

It has been suggested that SNe Ia could be produced in the condition of the violent merger scenario of the double-degenerate model, in which a thermonuclear explosion could be produced when the merging of double carbon-oxygen white dwarfs (CO WDs) is still ongoing. It has been recently found that the nucleus of the bipolar planetary nebula Henize 2-428 consists of double CO WDs that have a total mass of ~1.76Msun, a mass ratio of ~1 and an orbital period of ~4.2 hours, which is the first and only discovered progenitor candidate of SNe Ia predicted by the violent merger scenario. In this work, we aim to reproduce the evolutionary history of the central double CO WDs of Henize 2-428. We find that the planetary nebula Henize 2-428 may originate from a primordial binary that have a ~5.4Msun primary and a ~2.7Msun secondary with an initial orbital period of ~15.9 days. The double CO WDs are formed after the primordial binary experiencing two Roche-lobe overflows and two common-envelope ejection processes. According to our calculations, it takes about ~840 Myr for the double CO WDs to merge and form an SN Ia driven by the gravitational wave radiation after their birth. To produce the current status of Henize 2-428, a large common-envelope parameter is needed. We also estimate that the rate of SNe Ia from the violent merger scenario is at most 2.9*10-4 yr-1, and that the delay time is in the range of ~90 Myr to the Hubble time.

astro-ph.SR↗
arXiv2018

The outcomes of carbon-oxygen white dwarfs accreting CO-rich material

The double-degenerate model, involving the merger of double carbon-oxygen white dwarfs (CO WDs), is one of the two classic models for the progenitors of type Ia supernovae (SNe Ia). Previous studies suggested that off-centre carbon burning would occur if the mass-accretion rate (Macc) is relatively high during the merging process, leading to the formation of oxygen-neon (ONe) cores that may collapse into neutron stars. However, the off-centre carbon burning is still incompletely understood, especially when the inwardly propagating burning wave reaches the centre. In this paper, we aim to investigate the propagating characteristics of burning waves and the subsequently evolutionary outcomes of these CO cores. We simulated the long-term evolution of CO WDs that accrete CO-rich material by employing the stellar evolution code MESA on the basis of the thick-disc assumption. We found that the final outcomes of CO WDs strongly depend on Macc (Msun/yr) based on the thick-disc assumption, which can be divided into four regions: (1) explosive carbon ignition in the centre, then SNe Ia (Macc < 2.45*10^-6); (2) OSi cores, then neutron stars (2.45*10^-6 < Macc < 4.5*10^-6); (3) ONe cores, then e-capture SNe (4.5*10^-6 < Macc < 1.05*10^-5); (4) off-centre oxygen and neon ignition, then off-centre explosion or Si-Fe cores (Macc > 1.05*10^-5). Our results indicate that the final fates of double CO WD mergers are strongly dependent on the merging processes (e.g. slow merger, fast merger, composite merger, violent merger, etc.).

astro-ph.SR↗
arXiv2018

Machine Learning for Integrating Data in Biology and Medicine: Principles, Practice, and Opportunities

New technologies have enabled the investigation of biology and human health at an unprecedented scale and in multiple dimensions. These dimensions include a myriad of properties describing genome, epigenome, transcriptome, microbiome, phenotype, and lifestyle. No single data type, however, can capture the complexity of all the factors relevant to understanding a phenomenon such as a disease. Integrative methods that combine data from multiple technologies have thus emerged as critical statistical and computational approaches. The key challenge in developing such approaches is the identification of effective models to provide a comprehensive and relevant systems view. An ideal method can answer a biological or medical question, identifying important features and predicting outcomes, by harnessing heterogeneous data across several dimensions of biological variation. In this Review, we describe the principles of data integration and discuss current methods and available implementations. We provide examples of successful data integration in biology and medicine. Finally, we discuss current challenges in biomedical integrative methods and our perspective on the future development of the field.

q-bio.QM↗
arXiv2018

Broadband Magnetic-Manipulated Spintronic Terahertz Emitter with Arbitrarily Tunable Polarizations

Flexible manipulation of terahertz-wave polarization during the generation process is very important for terahertz applications, especially for the next-generation on-chip functional terahertz sources. However, current terahertz emitters could not satisfy such demand, hence calling for new mechanism and conceptually new terahertz source. Here we demonstrate a magnetic-field-controlled, highly-efficient, cost-effective, and broadband terahertz source with flexible switch of terahertz polarization states in ferromagnetic heterostructures driven by femtosecond laser pulses. We verify that the chirality, azimuthal angle, and ellipticity of the generated elliptical terahertz waves can be independently manipulated by delicately engineering of the external applied magnetic fields via effectively manipulating the photo-induced spin currents. Such an ultrafast photomagnetic interaction-based, magnetic-field-controlled, and broadband tunable solid-state terahertz source integrated with terahertz polarization tunability function not only has the capability to reveal physical mechanisms of femtosecond spin dynamics, but also demonstrates the feasibility to realize novel on-chip terahertz functional devices, boosting the potential applications for controlling elementary molecular rotations, phonon vibrations, spin precessions, high-speed terahertz communication, and accelerating the development of ultrafast terahertz opto-spintronics.

physics.optics↗
arXiv2018

Image Captioning based on Deep Reinforcement Learning

Recently it has shown that the policy-gradient methods for reinforcement learning have been utilized to train deep end-to-end systems on natural language processing tasks. What's more, with the complexity of understanding image content and diverse ways of describing image content in natural language, image captioning has been a challenging problem to deal with. To the best of our knowledge, most state-of-the-art methods follow a pattern of sequential model, such as recurrent neural networks (RNN). However, in this paper, we propose a novel architecture for image captioning with deep reinforcement learning to optimize image captioning tasks. We utilize two networks called "policy network" and "value network" to collaboratively generate the captions of images. The experiments are conducted on Microsoft COCO dataset, and the experimental results have verified the effectiveness of the proposed method.

cs.CV↗
arXiv2018

Stellar and AGN feedback in isolated early-type galaxies: the role in regulating star formation and ISM properties

Understanding how galaxies maintain the inefficiency of star formation with physically self-consistent models is a central problem for galaxy evolution. Although numerous theoretical models have been proposed in recent decades, the debate still exists. By means of high-resolution two-dimensional hydrodynamical simulations, we study the three feedback effects (the stellar wind heating, SNe feedback, and AGN feedback) in suppressing star formation activities on the evolution of early-type galaxies with different stellar masses. AGN feedback models are updated based on \citet{Yuan2018}. The gas sources comes exclusively from the mass losses of dying low-mass stars for most of our models. We find that SNe feedback can keep star formation at a significantly low level for low mass elliptical galaxies for a cosmological evolution time. For the high mass galaxies, AGN feedback can efficiently offset the radiative cooling and thus regulate the star formation activities. Such a suppression of star formation is extremely efficient in the inner region of the galaxies. AGB heating cannot account for this suppression for low and high mass galaxies. The X-ray temperature $T_{\rm X}$ and luminosity $L_{\rm X}$ of hot plasma can be in agreement with the observed data with the inclusion of effective feedback processes. These results thus suggest that we can use $T_{\rm X}$ and $L_{\rm X}$ to probe the role of different feedback processes. The inclusion of additional gas sources can make the mass scale between SNe and AGN feedback dominating in suppressing star formation decrease to an observationally inferred value of a few $10^{10}~M_{\odot}$.

astro-ph.HE↗
arXiv2018

The single-degenerate model for the progenitors of accretion-induced collapse events

It has been suggested that the accretion-induced collapse (AIC) of an oxygen-neon white dwarf (ONe WD) to a neutron star is a theoretically predicted outcome in stellar evolution, likely relating to the formation of some neutron star systems. However, the progenitor models of AIC events are still not well studied, and recent studies indicated that CO WD+He star systems may also contribute to the formation of neutron star systems through AIC process when off-centre carbon ignition happens on the surface of the CO WD. In this work, I studied the single-degenerate (SD) model of AIC events in a systematic way, including the contribution of the CO WD+He star channel and the ONe WD+MS/RG/He star channels. Firstly, I gave the initial parameter space of these SD channels for producing AIC events in the orbital period--secondary mass plane based on detailed binary evolution computations. Then, according to a binary population synthesis approach, I gave the rates and delay times of AIC events for these SD channels based on their initial parameter space. I found that the rates of AIC events in our galaxy are in the range of $\sim0.3-0.9\times10^{-3}$\,yr$^{-1}$,and that their delay times are $>$30\,Myr. I also found that the ONe WD+He star channel is the main way to produce AIC events, and that the CO WD+He star channel cannot be ignored when studying the progenitors of AIC events.

astro-ph.SR↗
arXiv2018

Short-term load forecasting using optimized LSTM networks based on EMD

Short-term load forecasting is one of the crucial sections in smart grid. Precise forecasting enables system operators to make reliable unit commitment and power dispatching decisions. With the advent of big data, a number of artificial intelligence techniques such as back propagation, support vector machine have been used to predict the load of the next day. Nevertheless, due to the noise of raw data and the randomness of power load, forecasting errors of existing approaches are relatively large. In this study, a short-term load forecasting method is proposed on the basis of empirical mode decomposition and long short-term memory networks, the parameters of which are optimized by a particle swarm optimization algorithm. Essentially, empirical mode decomposition can decompose the original time series of historical data into relatively stationary components and long short-term memory network is able to emphasize as well as model the timing of data, the joint use of which is expected to effectively apply the characteristics of data itself, so as to improve the predictive accuracy. The effectiveness of this research is exemplified on a realistic data set, the experimental results of which show that the proposed method has higher forecasting accuracy and applicability, as compared with existing methods.

eess.SP↗