arXiv subjects

Xi Zhang

Publications and source records attributed to Xi Zhang.

At least 289 records · Page 16Linked to original sources

arXiv2020

Into the UV: The Atmosphere of the Hot Jupiter HAT-P-41b Revealed

For solar-system objects, ultraviolet spectroscopy has been critical in identifying sources for stratospheric heating and measuring the abundances of a variety of hydrocarbon and sulfur-bearing species, produced via photochemical mechanisms, as well as oxygen and ozone. To date, less than 20 exoplanets have been probed in this critical wavelength range (0.2-0.4 um). Here we use data from Hubble's newly implemented WFC3 UVIS G280 grism to probe the atmosphere of the hot Jupiter HAT-P-41b in the ultraviolet through optical in combination with observations at infrared wavelengths. We analyze and interpret HAT-P-41b's 0.2-5.0 um transmission spectrum using a broad range of methodologies including multiple treatments of data systematics as well as comparisons with atmospheric forward, cloud microphysical, and multiple atmospheric retrieval models. Although some analysis and interpretation methods favor the presence of clouds or potentially a combination of Na, VO, AlO, and CrH to explain the ultraviolet through optical portions of HAT-P-41b's transmission spectrum, we find that the presence of a significant H- opacity provides the most robust explanation. We obtain a constraint for the abundance of H-, log(H-) = -8.65 +/- 0.62 in HAT-P-41b's atmosphere, which is several orders of magnitude larger than predictions from equilibrium chemistry for a 1700 - 1950 K hot Jupiter. We show that a combination of photochemical and collisional processes on hot hydrogen-dominated exoplanets can readily supply the necessary amount of H- and suggest that such processes are at work in HAT-P-41b and many other hot Jupiter atmospheres.

astro-ph.EP↗

arXiv2020

Demarcating circulation regimes of synchronously rotating terrestrial planets within the habitable zone

We investigate the atmospheric dynamics of terrestrial planets in synchronous rotation within the habitable zone of low-mass stars using the Community Atmosphere Model (CAM). The surface temperature contrast between day and night hemispheres decreases with an increase in incident stellar flux, which is opposite the trend seen on gas giants. We define three dynamical regimes in terms of the equatorial Rossby deformation radius and the Rhines length. The slow rotation regime has a mean zonal circulation that spans from day to night side, with both the Rossby deformation radius and the Rhines length exceeding planetary radius, which occurs for planets around stars with effective temperatures of 3300 K to 4500 K (rotation period > 20 days). Rapid rotators have a mean zonal circulation that partially spans a hemisphere and with banded cloud formation beneath the substellar point, with the Rossby deformation radius is less than planetary radius, which occurs for planets orbiting stars with effective temperatures of less than 3000 K (rotation period < 5 days). In between is the Rhines rotation regime, which retains a thermally-direct circulation from day to night side but also features midlatitude turbulence-driven zonal jets. Rhines rotators occur for planets around stars in the range of 3000 K to 3300 K (rotation period ~ 5 to 20 days), where the Rhines length is greater than planetary radius but the Rossby deformation radius is less than planetary radius. The dynamical state can be observationally inferred from comparing the morphology of the thermal emission phase curves of synchronously rotating planets.

astro-ph.EP↗

arXiv2020

QSAN: A Quantum-probability based Signed Attention Network for Explainable False Information Detection

False information detection on social media is challenging as it commonly requires tedious evidence-collecting but lacks available comparative information. Clues mined from user comments, as the wisdom of crowds, could be of considerable benefit to this task. However, it is non-trivial to capture the complex semantics from the contents and comments in consideration of their implicit correlations. Although deep neural networks have good expressive power, one major drawback is the lack of explainability. In this paper, we focus on how to learn from the post contents and related comments in social media to understand and detect the false information more effectively, with explainability. We thus propose a Quantum-probability based Signed Attention Network (QSAN) that integrates the quantum-driven text encoding and a novel signed attention mechanism in a unified framework. QSAN is not only able to distinguish important comments from the others, but also can exploit the conflicting social viewpoints in the comments to facilitate the detection. Moreover, QSAN is advantageous with its explainability in terms of transparency due to quantum physics meanings and the attention weights. Extensive experiments on real-world datasets show that our approach outperforms state-of-the-art baselines and can provide different kinds of user comments to explain why a piece of information is detected as false.

cs.SI↗

arXiv2020

The Science Case for a Titan Flagship-class Orbiter with Probes

We outline a flagship-class mission concept focused on studying Titan as a global system, with particular emphasis on the polar regions. Investigating Titan from the unique standpoint of a polar orbit would enable comprehensive global maps to uncover the physics and chemistry of the atmosphere, and the topography and geophysical environment of the surface and subsurface. The mission includes two key elements: (1) an orbiter spacecraft, which also acts as a data relay, and (2) one or more small probes to directly investigate Titan's seas and make the first direct measurements of their liquid composition and physical environment. The orbiter would carry a sophisticated remote sensing payload, including a novel topographic lidar, a long-wavelength surface-penetrating radar, a sub-millimeter sounder for winds and for mesospheric/thermospheric composition, and a camera and near-infrared spectrometer. An instrument suite to analyze particles and fields would include a mass spectrometer to focus on the interactions between Titan's escaping upper atmosphere and the solar wind and Saturnian magnetosphere. The orbiter would enter a stable polar orbit around 1500 to 1800 km, from which vantage point it would make global maps of the atmosphere and surface. One or more probes, released from the orbiter, would investigate Titan's seas in situ, including possible differences in composition between higher and lower latitude seas, as well as the atmosphere during the parachute descent. The number of probes, as well as the instrument complement on the orbiter and probe, remain to be finalized during a mission study that we recommend to NASA as part of the NRC Decadal Survey for Planetary Science now underway, with the goal of an overall mission cost in the "small flagship" category of ~$2 bn. International partnerships, similar to Cassini-Huygens, may also be included for consideration.

astro-ph.IM↗

arXiv2020

Projectively flat bundles and semi-stable Higgs bundles

The Corlette-Donaldson-Hitchin-Simpson's correspondence states that, on a compact Kähler manifold $(X, ω)$, there is a one-to-one correspondence between the moduli space of semisimple flat complex vector bundles and the moduli space of poly-stable Higgs bundles with vanishing Chern numbers. In this paper, we extend this correspondence to the projectively flat bundles case. We prove that there is an equivalence of categories between the category of $ω$-semi-stable (poly-stable) Higgs bundles $(E, \overline{\partial}_{E}, ϕ)$ with $(2rc_{2}(E)-(r-1)c_{1}^{2}(E))\cdot [ω]^{n-2}=0 $ and the category of (semi-simple) projectively flat bundles $(E, D)$ with $\sqrt{-1}F_{D}=α\otimes \mbox{Id}_{E}$ for some real (1,1)-form $α$. Furthermore, we also establish the above correspondence on some compact non-Kähler manifolds. As its application, we obtain a vanishing theorem of characteristic classes of projectively flat bundles.

math.DG↗

arXiv2020

Deep Multi-modality Soft-decoding of Very Low Bit-rate Face Videos

We propose a novel deep multi-modality neural network for restoring very low bit rate videos of talking heads. Such video contents are very common in social media, teleconferencing, distance education, tele-medicine, etc., and often need to be transmitted with limited bandwidth. The proposed CNN method exploits the correlations among three modalities, video, audio and emotion state of the speaker, to remove the video compression artifacts caused by spatial down sampling and quantization. The deep learning approach turns out to be ideally suited for the video restoration task, as the complex non-linear cross-modality correlations are very difficult to model analytically and explicitly. The new method is a video post processor that can significantly boost the perceptual quality of aggressively compressed talking head videos, while being fully compatible with all existing video compression standards.

cs.CV↗

arXiv2020

Image polaritons in boron nitride for extreme polariton confinement with low losses

Polaritons in two-dimensional materials provide extreme light confinement that is difficult to achieve with metal plasmonics. However, such tight confinement inevitably increases optical losses through various damping channels. Here we demonstrate that hyperbolic phonon polaritons in hexagonal boron nitride can overcome this fundamental trade-off. Among two observed polariton modes, featuring a symmetric and antisymmetric charge distribution, the latter exhibits lower optical losses and tighter polariton confinement. Far-field excitation and detection of this high-momenta mode becomes possible with our resonator design that can boost the coupling efficiency via virtual polariton modes with image charges that we dub image polaritons. Using these image polaritons, we experimentally observe a record-high effective index of up to 132 and quality factors as high as 501. Further, our phenomenological theory suggests an important role of hyperbolic surface scattering in the damping process of hyperbolic phonon polaritons.

physics.optics↗

arXiv2020

Atmospheric Regimes and Trends on Exoplanets and Brown Dwarfs

A planetary atmosphere is the outer gas layer of a planet. Besides its scientific significance among the first and most accessible planetary layers observed from space, it is closely connected with planetary formation and evolution, surface and interior processes, and habitability of planets. Current theories of the planetary atmosphere were primarily obtained through the studies of eight large planets, Pluto and three large moons (Io, Titan, and Triton) in the Solar System. Outside the Solar System, more than four thousand extra-solar planets (exoplanets) and two thousand brown dwarfs have been confirmed in our galaxy, and their population is rapidly growing. The rich information from these exotic bodies offers a database to test, in a statistical sense, the fundamental theories of planetary climates. Here we review the current knowledge of atmospheres of exoplanets and brown dwarfs from recent observations and theories. This review highlights important regimes and statistical trends in an ensemble of atmospheres as an initial step towards fully characterizing diverse substellar atmospheres, that illustrates the underlying principles and critical problems. Insights are obtained through analysis of the dependence of atmospheric characteristics on basic planetary parameters. Dominant processes that influence atmospheric stability, energy transport, temperature, composition, and flow pattern are discussed and elaborated with simple scaling laws. We dedicate this review to Dr. Adam P. Showman (1968-2020) in recognition of his fundamental contribution to the understanding of atmospheric dynamics on giant planets, exoplanets, and brown dwarfs.

astro-ph.EP↗

arXiv2020

Eightfold Fermionic Excitation in a Charge Density Wave Compound

Unconventional quasiparticle excitations in condensed matter systems have become one of the most important research frontiers. Beyond two- and fourfold degenerate Weyl and Dirac fermions, three-, six- and eightfold symmetry protected degeneracies have been predicted however remain challenging to realize in solid state materials. Here, charge density wave compound TaTe4 is proposed to hold eightfold fermionic excitation and Dirac point in energy bands. High quality TaTe4 single crystals are prepared, where the charge density wave is revealed by directly imaging the atomic structure and a pseudogap of about 45 meV on the surface. Shubnikov de-Haas oscillations of TaTe4 are consistent with band structure calculation. Scanning tunneling microscopy reveals atomic step edge states on the surface of TaTe4. This work uncovers that charge density wave is able to induce new topological phases and sheds new light on the novel excitations in condensed matter materials.

cond-mat.mtrl-sci↗

arXiv2020

Local Causal Structure Learning and its Discovery Between Type 2 Diabetes and Bone Mineral Density

Type 2 diabetes (T2DM), one of the most prevalent chronic diseases, affects the glucose metabolism of the human body, which decreases the quantity of life and brings a heavy burden on social medical care. Patients with T2DM are more likely to suffer bone fragility fracture as diabetes affects bone mineral density (BMD). However, the discovery of the determinant factors of BMD in a medical way is expensive and time-consuming. In this paper, we propose a novel algorithm, Prior-Knowledge-driven local Causal structure Learning (PKCL), to discover the underlying causal mechanism between BMD and its factors from the clinical data. Since there exist limited data but redundant prior knowledge for medicine, PKCL adequately utilize the prior knowledge to mine the local causal structure for the target relationship. Combining the medical prior knowledge with the discovered causal relationships, PKCL can achieve more reliable results without long-standing medical statistical experiments. Extensive experiments are conducted on a newly provided clinical data set. The experimental study of PKCL on the data is proved to highly corresponding with existing medical knowledge, which demonstrates the superiority and effectiveness of PKCL. To illustrate the importance of prior knowledge, the result of the algorithm without prior knowledge is also investigated.

q-bio.QM↗

arXiv2020

A Global Non-Hydrostatic Atmospheric Model with a Mass and Energy Conserving Vertically-Implicit-Correction (VIC) Scheme

Global non-hydrostatic atmospheric models are becoming increasingly important for studying the climates of planets and exoplanets. However, such models suffer from computational difficulties due to the large aspect ratio between the horizontal and vertical directions. To overcome this problem, we developed a global model using a vertically-implicit-correction (VIC) scheme in which the integration time step is no longer limited by the propagation of acoustic waves in the vertical. We proved that our model, based on the $\rm Athena^{++}$ framework and its extension for planetary atmospheres - SNAP (Simulating Non-hydrostatic Atmosphere on Planets), rigorously conserves mass and energy in finite volume simulations. We found that traditional numerical stabilizers such as hyper-viscosity and divergence damping are not needed when using the VIC scheme, which greatly simplifies the numerical implementation and improves stability. We present simulation results ranging from 1D linear waves to 3D global circulations with and without the VIC scheme. These tests demonstrate that our formulation correctly tracks local turbulent motions, produces Kelvin-Helmholtz instability, and generates a super-rotating jet on hot Jupiters. Employing this VIC scheme improves the computational efficiency of global simulations by more than two orders of magnitude compared to an explicit model and facilitates the capability of simulating a wide range of planetary atmospheres both regionally and globally.

astro-ph.EP↗

arXiv2020

Revisiting the Sulfur-Water Chemical System in the Middle Atmosphere of Venus

Sulfur-water chemistry plays an important role in the middle atmosphere of Venus. Ground based observations have found that simultaneously observed SO2 and H2O at ~64 km vary with time and are temporally anti-correlated. To understand these observations, we explore the sulfur-water chemical system using a one-dimensional chemistry-diffusion model. We find that SO2 and H2O mixing ratios above the clouds are highly dependent on mixing ratios of the two species at the middle cloud top (58 km). The behavior of sulfur-water chemical system can be classified into three regimes but there is no abrupt transition among these regimes. In particular, there is no bifurcation behavior as previously claimed. We also find that the SO2 self-shielding effect causes H2O above the clouds to respond to the middle cloud top in a non-monotonic fashion. Through comparison with observations, we find that mixing ratio variations at the middle cloud top can explain the observed variability of SO2 and H2O. The sulfur-water chemistry in the middle atmosphere is responsible for the H2O-SO2 anti-correlation at 64 km. Eddy transport change alone cannot explain the variations of both species. These results imply that variations of species abundance in the middle atmosphere are significantly influenced by the lower atmospheric processes. Continued ground-based measurements of the co-evolution of SO2 and H2O above the clouds and new spacecraft missions will be crucial for uncover the complicated processes underlying the interaction among the lower atmosphere, the clouds and the middle atmosphere of Venus.

astro-ph.EP↗

arXiv2020

Aerosol Composition of Hot Giant Exoplanets Dominated by Silicates and Hydrocarbon Hazes

Aerosols are common in the atmospheres of exoplanets across a wide swath of temperatures, masses, and ages. These aerosols strongly impact observations of transmitted, reflected, and emitted light from exoplanets, obfuscating our understanding of exoplanet thermal structure and composition. Knowing the dominant aerosol composition would facilitate interpretations of exoplanet observations and theoretical understanding of their atmospheres. A variety of compositions have been proposed, including metal oxides and sulphides, iron, chromium, sulphur, and hydrocarbons. However, the relative contributions of these species to exoplanet aerosol opacity is unknown. Here we show that the aerosol composition of giant exoplanets observed in transmission is dominated by silicates and hydrocarbons. By constraining an aerosol microphysics model with trends in giant exoplanet transmission spectra, we find that silicates dominate aerosol opacity above planetary equilibrium temperatures of 950 K due to low nucleation energy barriers and high elemental abundances, while hydrocarbon aerosols dominate below 950 K due to an increase in methane abundance. Our results are robust to variations in planet gravity and atmospheric metallicity within the range of most giant transiting exoplanets. We predict that spectral signatures of condensed silicates in the mid-infrared are most prominent for hot (>1600 K), low-gravity (<10 m s$^{-2}$) objects.

astro-ph.EP↗

arXiv2020

Challenge of Spatial Cognition for Deep Learning

Given the success of the deep convolutional neural networks (DCNNs) in applications of visual recognition and classification, it would be tantalizing to test if DCNNs can also learn spatial concepts, such as straightness, convexity, left/right, front/back, relative size, aspect ratio, polygons, etc., from varied visual examples of these concepts that are simple and yet vital for spatial reasoning. Much to our dismay, extensive experiments of the type of cognitive psychology demonstrate that the data-driven deep learning (DL) cannot see through superficial variations in visual representations and grasp the spatial concept in abstraction. The root cause of failure turns out to be the learning methodology, not the computational model of the neural network itself. By incorporating task-specific convolutional kernels, we are able to construct DCNNs for spatial cognition tasks that can generalize to input images not drawn from the same distribution of the training set. This work raises a precaution that without manually-incorporated priors or features DCCNs may fail spatial cognitive tasks at rudimentary level.

cs.CV↗

arXiv2020

Rigorous Explanation of Inference on Probabilistic Graphical Models

Probabilistic graphical models, such as Markov random fields (MRF), exploit dependencies among random variables to model a rich family of joint probability distributions. Sophisticated inference algorithms, such as belief propagation (BP), can effectively compute the marginal posteriors. Nonetheless, it is still difficult to interpret the inference outcomes for important human decision making. There is no existing method to rigorously attribute the inference outcomes to the contributing factors of the graphical models. Shapley values provide an axiomatic framework, but naively computing or even approximating the values on general graphical models is challenging and less studied. We propose GraphShapley to integrate the decomposability of Shapley values, the structure of MRFs, and the iterative nature of BP inference in a principled way for fast Shapley value computation, that 1) systematically enumerates the important contributions to the Shapley values of the explaining variables without duplicate; 2) incrementally compute the contributions without starting from scratches. We theoretically characterize GraphShapley regarding independence, equal contribution, and additivity. On nine graphs, we demonstrate that GraphShapley provides sensible and practical explanations.

cs.SI↗

arXiv2020

High Curie Temperature Ferromagnetism and High Hole Mobility in Tensile Strained Mn-doped SiGe Thin Films

Diluted magnetic semiconductors (DMSs) based on group-IV materials are desirable for spintronic devices compatible with current silicon technology. In this work, amorphous Mn-doped SiGe thin films were first fabricated on Ge substrates by radio frequency magnetron sputtering and then crystallized by rapid thermal annealing (RTA). After the RTA, the samples became ferromagnetic (FM) semiconductors, in which the Curie temperature increased with increasing Mn doping concentration and reached 280 K with 5% Mn concentration. The data suggest that the ferromagnetism came from the hole-mediated process and was enhanced by the tensile strain in the SiGe crystals. Meanwhile, the Hall effect measurement up to 33 T to eliminate the influence of anomalous Hall effect (AHE) reveals that the hole mobility of the annealed samples was greatly enhanced and the maximal value was ~1000 cm2/Vs, owing to the tensile strain-induced band structure modulation. The Mn-doped SiGe thin films with high Curie temperature ferromagnetism and high hole mobility may provide a promising platform for semiconductor spintronics.

cond-mat.mtrl-sci↗

arXiv2020

Unexpected two-fold symmetric superconductivity in few-layer NbSe$_2$

Two-dimensional transition metal dichalcogenides (TMDs) have been attracting significant interest due to a range of properties, such as layer-dependent inversion symmetry, valley-contrasted Berry curvatures, and strong spin-orbit coupling (SOC). Of particular interest is niobium diselenide (NbSe2), whose superconducting state in few-layer samples is profoundly affected by an unusual type of SOC called Ising SOC. Combined with the reduced dimensionality, the latter stabilizes the superconducting state against magnetic fields up to ~35 T and could lead to other exotic properties such as nodal and crystalline topological superconductivity. Here, we report transport measurements of few-layer NbSe$_2$ under in-plane external magnetic fields, revealing an unexpected two-fold rotational symmetry of the superconducting state. In contrast to the three-fold symmetry of the lattice, we observe that the magnetoresistance and critical field exhibit a two-fold oscillation with respect to an applied in-plane magnetic field. We find similar two-fold oscillations deep inside the superconducting state in differential conductance measurements on NbSe$_2$/CrBr$_3$ superconductor-magnet junctions. In both cases, the anisotropy vanishes in the normal state, demonstrating that it is an intrinsic property of the superconducting phase. We attribute the behavior to the mixing between two closely competing pairing instabilities, namely, the conventional s-wave instability typical of bulk NbSe$_2$ and an unconventional d- or p-wave channel that emerges in few-layer NbSe2. Our results thus demonstrate the unconventional character of the pairing interaction in a few-layer TMD, opening a new avenue to search for exotic superconductivity in this family of 2D materials.

cond-mat.supr-con↗

arXiv2020

Two-Dimensional Si-Ge Monolayers: Stabilities, Structures and Electronic Properties

Si-Ge monolayers (SiGeM) with different elementary proportion x (0<x<1) were systematically studied for the first-time using ab initio calculations in this work. The structural stabilities of the Si1-xGexM with different symmetries were investigated using phonon spectra, and an infinite miscibility between Si and Ge elements were revealed in the 2D honeycomb structures. The simulated scanning tunneling microscope images and Raman and infrared active modes of the Si1-xGexM were then obtained for structural characterizations. Interestingly, the study of electronic properties revealed not previously reported oscillatory nonlinear dependence of band gap values on the elementary proportion x in the Si1-xGexM, which suggests an alternative way for tuning the band gaps of 2D materials. Additionally, low effective masses (0.008m0 ~ 0.021m0) of the carriers in the semiconducting Si1-xGexM were found, which has potentials for high-speed applications. Considering the advantage of their compatibility with current Si-based technology and the trend of miniature of electronic devices, the Si1-xGexM with stable structures and excellent properties would be important for 2D applications based on group IV materials.

cond-mat.mtrl-sci↗