Mixing of gravitational wave echoes

Gravitational wave (GW) echoes, if they exist, would be a probe to the near-horizon quantum structure of black hole (BH), which has motivated the searching for the echo signals in GW data. We point out that the echo phenomenology related with the potential structure might be not so simple as expected. In particular, if the near-horizon regime of BH is modelled as a multiple-barriers filter, the late-time GW ringdown waveform will exhibit the mixing of echoes, even the superpositions. As a result, the amplitudes of successive echoes might not drop sequentially.Comment: 18 pages, 10 figure

On dRGT massive gravity with degenerate reference metrics

In dRGT massive gravity, to get the equations of motion, the square root tensor is assumed to be invertible in the variation of the action. However, this condition can not be fulfilled when the reference metric is degenerate. This implies that the resulting equations of motion might be different from the case where the reference metric has full rank. In this paper, by generalizing the Moore-Penrose inverse to the symmetric tensor on Lorentz manifolds, we get the equations of motion of the theory with degenerate reference metric. It is found that the equations of motion are a little bit different from those in the non-degenerate cases. Based on the result of the equations of motion, for the $(2+n)$-dimensional solutions with the symmetry of $n$-dimensional maximally symmetric space, we prove a generalized Birkhoff theorem in the case where the degenerate reference metric has rank $n$, i.e., we show that the solutions must be Schwarzschild-type or Nariai-Bertotti-Robinson-type under the assumptions.Comment: v1, Latex, 29 pages, no figures; v2, references added, typos corrected, 30 page

CA-EHN: Commonsense Analogy from E-HowNet

Embedding commonsense knowledge is crucial for end-to-end models to generalize inference beyond training corpora. However, existing word analogy datasets have tended to be handcrafted, involving permutations of hundreds of words with only dozens of pre-defined relations, mostly morphological relations and named entities. In this work, we model commonsense knowledge down to word-level analogical reasoning by leveraging E-HowNet, an ontology that annotates 88K Chinese words with their structured sense definitions and English translations. We present CA-EHN, the first commonsense word analogy dataset containing 90,505 analogies covering 5,656 words and 763 relations. Experiments show that CA-EHN stands out as a great indicator of how well word representations embed commonsense knowledge. The dataset is publicly available at https://github.com/ckiplab/CA-EHN.Comment: In proceedings of LREC 202

Lowering the Characteristic Mass of Cluster Stars by Magnetic Fields and Outflow Feedback

Magnetic fields are generally expected to increase the characteristic mass of stars formed in stellar clusters, because they tend to increase the effective Jeans mass. We test this expectation using adaptive mesh refinement (AMR) magnetohydrodynamic simulations of cluster formation in turbulent magnetized clumps of molecular clouds, treating stars as accreting sink particles. We find that, contrary to the common expectation, a magnetic field of strength in the observed range decreases, rather than increases, the characteristic stellar mass. It (1) reduces the number of intermediate-mass stars that are formed through direct turbulent compression, because sub-regions of the clump with masses comparable to those of stars are typically magnetically subcritical and cannot be compressed directly into collapse, and (2) increases the number of low-mass stars that are produced from the fragmentation of dense filaments. The filaments result from mass accumulation along the field lines. In order to become magnetically supercritical and fragment, the filament must accumulate a large enough column density (proportional to the field strength), which yields a high volume density (and thus a small thermal Jeans mass) that is conducive to forming low-mass stars. We find, in addition, that the characteristic stellar mass is reduced further by outflow feedback. The conclusion is that both magnetic fields and outflow feedback are important in shaping the stellar initial mass function (IMF).Comment: Accepted to ApJ

Development of an Autonomous Sanding Robot with Structured-Light Technology

Large demand for robotics and automation has been reflected in the sanding works, as current manual operations are labor-intensive, without consistent quality, and also subject to safety and health issues. While several machines have been developed to automate one or two steps in the sanding works, the autonomous capability of existing solutions is relatively low, and the human assistance or supervision is still heavily required in the calibration of target objects or the planning of robot motion and tasks. This paper presents the development of an autonomous sanding robot, which is able to perform the sanding works on an unknown object automatically, without any prior calibration or human intervention. The developed robot works as follows. First, the target object is scanned then modeled with the structured-light camera. Second, the robot motion is planned to cover all the surfaces of the object with an optimized transition sequence. Third, the robot is controlled to perform the sanding on the object under the desired impedance model. A prototype of the sanding robot is fabricated and its performance is validated in the task of sanding a batch of wooden boxes. With sufficient degrees of freedom (DOFs) and the module design for the end effector, the developed robot is able to provide a general solution to the autonomous sanding on many other different objects.Comment: 7 pages, 11 figures, IEEE/RSJ International Conference on Intelligent Robots and Systems 201

An evolving network model with modular growth

In this paper, we propose an evolving network model growing fast in units of module, based on the analysis of the evolution characteristics in real complex networks. Each module is a small-world network containing several interconnected nodes, and the nodes between the modules are linked by preferential attachment on degree of nodes. We study the modularity measure of the proposed model, which can be adjusted by changing ratio of the number of inner-module edges and the number of inter-module edges. Based on the mean field theory, we develop an analytical function of the degree distribution, which is verified by a numerical example and indicates that the degree distribution shows characteristics of the small-world network and the scale-free network distinctly at different segments. The clustering coefficient and the average path length of the network are simulated numerically, indicating that the network shows the small-world property and is affected little by the randomness of the new module.Comment: 14 pages, 7 figure

Tell Me Where to Look: Guided Attention Inference Network

Weakly supervised learning with only coarse labels can obtain visual explanations of deep neural network such as attention maps by back-propagating gradients. These attention maps are then available as priors for tasks such as object localization and semantic segmentation. In one common framework we address three shortcomings of previous approaches in modeling such attention maps: We (1) first time make attention maps an explicit and natural component of the end-to-end training, (2) provide self-guidance directly on these maps by exploring supervision form the network itself to improve them, and (3) seamlessly bridge the gap between using weak and extra supervision if available. Despite its simplicity, experiments on the semantic segmentation task demonstrate the effectiveness of our methods. We clearly surpass the state-of-the-art on Pascal VOC 2012 val. and test set. Besides, the proposed framework provides a way not only explaining the focus of the learner but also feeding back with direct guidance towards specific tasks. Under mild assumptions our method can also be understood as a plug-in to existing weakly supervised learners to improve their generalization performance.Comment: Accepted in CVPR201

Specific Absorbed Fractions of Electrons and Photons for Rad-HUMAN Phantom Using Monte Carlo Method

The specific absorbed fractions (SAF) for self- and cross-irradiation are effective tools for the internal dose estimation of inhalation and ingestion intakes of radionuclides. A set of SAFs of photon and electron were calculated using the Rad-HUMAN phantom, a computational voxel phantom of Chinese adult female and created using the color photographic image of the Chinese Visible Human (CVH) data set. The model can represent most of Chinese adult female anatomical characteristics and can be taken as an individual phantom to investigate the difference of internal dose with Caucasians. In this study, the emission of mono-energetic photons and electrons of 10keV to 4MeV energy were calculated using the Monte Carlo particle transport calculation code MCNP. Results were compared with the values from ICRP reference and ORNL models. The results showed that SAF from Rad-HUMAN have the similar trends but larger than those from the other two models. The differences were due to the racial and anatomical differences in organ mass and inter-organ distance. The SAFs based on the Rad-HUMAN phantom provide an accurate and reliable data for internal radiation dose calculations for Chinese female.Comment: 9 pages,8 figures,Submitted to Chinese Physics

Tunneling Field-Effect Junctions with WS2_2 barrier

Transition metal dichalcogenides (TMDCs), with their two-dimensional structures and sizable bandgaps, are good candidates for barrier materials in tunneling field-effect transistor (TFET) formed from atomic precision vertical stacks of graphene and insulating crystals of a few atomic layers in thickness. We report first-principles study of the electronic properties of the Graphene/WS$_2$/Graphene sandwich structure revealing strong interface effects on dielectric properties and predicting a high ON/OFF ratio with an appropriate WS$_2$ thickness and a suitable range of the gate voltage. Both the band spin-orbit coupling splitting and the dielectric constant of the WS$_2$ layer depend on its thickness when in contact with the graphene electrodes, indicating strong influence from graphene across the interfaces. The dielectric constant is significantly reduced from the bulk WS$_2$ value. The effective barrier height varies with WS$_2$ thickness and can be tuned by a gate voltage. These results are critical for future nanoelectronic device designs.Comment: 18 pages, 5 figure

Constraints on the ultracompact minihalos using neutrino signals from the gravitino dark matter decay

Ultracompact dark matter minihalos (UCMHs) would be formed during the earlier universe if there were large density perturbations. If the dark matter can decay into the standard model particles, such as neutrinos, these objects would become the potential astrophysical sources and could be detected by the related instruments, such as IceCube. In this paper, we investigate the neutrino signals from the nearby UCMHs due to the gravitino dark matter decay and compare these signals with the background neutrino flux which is mainly from the atmosphere to get the constraints on the abundance of UCMHs.Comment: 7 pages, 3 figures, Accepted by RAA (Research in Astronomy and Astrophysics). Comments welcome!