arXiv subjects

Xi Zhang

Publications and source records attributed to Xi Zhang.

At least 253 records · Page 14Linked to original sources

arXiv2022

Unsupervised Scene Sketch to Photo Synthesis

Sketches make an intuitive and powerful visual expression as they are fast executed freehand drawings. We present a method for synthesizing realistic photos from scene sketches. Without the need for sketch and photo pairs, our framework directly learns from readily available large-scale photo datasets in an unsupervised manner. To this end, we introduce a standardization module that provides pseudo sketch-photo pairs during training by converting photos and sketches to a standardized domain, i.e. the edge map. The reduced domain gap between sketch and photo also allows us to disentangle them into two components: holistic scene structures and low-level visual styles such as color and texture. Taking this advantage, we synthesize a photo-realistic image by combining the structure of a sketch and the visual style of a reference photo. Extensive experimental results on perceptual similarity metrics and human perceptual studies show the proposed method could generate realistic photos with high fidelity from scene sketches and outperform state-of-the-art photo synthesis baselines. We also demonstrate that our framework facilitates a controllable manipulation of photo synthesis by editing strokes of corresponding sketches, delivering more fine-grained details than previous approaches that rely on region-level editing.

cs.CV↗

arXiv2022

Depletion of gaseous CO in protoplanetary disks by surface-energy-regulated ice formation

Empirical constraints of fundamental properties of protoplanetary disks are essential for understanding planet formation and planetary properties (1,2). Carbon monoxide (CO) gas is often used to constrain disk properties (3). However, estimates show that the CO gas abundance in disks is depleted relative to expected values (4,5,6,7), and models of various disk processes impacting the CO abundance could not explain this depletion on observed 1Myr timescales (8,9,10,11,12,13,14). Here we demonstrate that surface energy effects on particles in disks, such as the Kelvin effect, that arise when ice heterogeneously nucleates onto an existing particle can efficiently trap CO in its ice phase. In previous ice formation models, CO gas was released when small ice-coated particles were lofted to warmed disk layers. Our model can reproduce the observed abundance, distribution and time evolution of gaseous CO in the four most studied protoplanetary disks (7). We constrain the solid and gaseous CO inventory at the midplane and disk diffusivities and resolve inconsistencies in estimates of the disk mass -- three crucial parameters that control planetary formation.

astro-ph.EP↗

arXiv2022

Strain tunability of perpendicular magnetic anisotropy in van der Waals ferromagnets VI3

Layered ferromagnets with high coercivity have special applications in nanoscale memory elements in electronic circuits, such as data storage. Therefore, searching for new hard ferromagnets and effectively tuning or enhancing the coercivity are the hottest topics in layered magnets today. Here, we report a strain tunability of perpendicular magnetic anisotropy in van der Waals (vdW) ferromagnets VI3 using magnetic circular dichroism measurements. For an unstrained flake, the M-H curve shows a rectangular-shaped hysteresis loop with perpendicular magnetic anisotropy and a large coercivity (up to 1.775 T at 10 K). Furthermore, the coercivity can be enhanced to a maximum of 2.6 T at 10 K under a 2.9% in-plane tensile strain. Our DFT calculations show that the magnetic anisotropy energy (MAE) can be dramatically increased after applying an in-plain tensile strain, which contributes to the enhancement of coercivity in the VI3 flake. Meanwhile, the strain tunability on the coercivity of CrI3, with a similar crystal structure, is limited. The main reason is the strong spin-orbital coupling in V3+ in VI6 octahedra in comparison with that in Cr3+. The strain tunability of coercivity in VI3 flakes highlights its potential for integration into vdW heterostructures, paving the way toward nanoscale spintronic devices and applications in the future.

cond-mat.mtrl-sci↗

arXiv2022

Structured Graph Variational Autoencoders for Indoor Furniture layout Generation

We present a structured graph variational autoencoder for generating the layout of indoor 3D scenes. Given the room type (e.g., living room or library) and the room layout (e.g., room elements such as floor and walls), our architecture generates a collection of objects (e.g., furniture items such as sofa, table and chairs) that is consistent with the room type and layout. This is a challenging problem because the generated scene should satisfy multiple constrains, e.g., each object must lie inside the room and two objects cannot occupy the same volume. To address these challenges, we propose a deep generative model that encodes these relationships as soft constraints on an attributed graph (e.g., the nodes capture attributes of room and furniture elements, such as class, pose and size, and the edges capture geometric relationships such as relative orientation). The architecture consists of a graph encoder that maps the input graph to a structured latent space, and a graph decoder that generates a furniture graph, given a latent code and the room graph. The latent space is modeled with auto-regressive priors, which facilitates the generation of highly structured scenes. We also propose an efficient training procedure that combines matching and constrained learning. Experiments on the 3D-FRONT dataset show that our method produces scenes that are diverse and are adapted to the room layout.

cs.CV↗

arXiv2022

A Simple Condensation Model for the H2SO4-H2O Gas-cloud System on Venus

The current Venus climate is largely regulated by globally-covered concentrated sulfuric acid clouds from binary condensation of sulfuric acid (H2SO4) and water (H2O). To understand this complicated H2SO4-H2O gas-cloud system, previous theoretical studies either adopted complicated microphysical calculations or assumed that both H2SO4 and H2O vapor follow their saturation vapor pressure. In this study, we developed a simple one-dimensional cloud condensation model including condensation, diffusion and sedimentation of H2SO4 and H2O but without detailed microphysics. Our model is able to explain the observed vertical structure of cloud and upper haze mass loading, cloud acidity, H2SO4, and H2O vapor, and the mode-2 particle size on Venus. We found that most H2SO4 is stored in the condensed phase above 48 km, while the partitioning of H2O between the vapor and clouds is complicated. The cloud cycle is mostly driven by evaporation and condensation of H2SO4 rather than H2O and is about seven times stronger than the H2SO4 photochemical cycle. Most of the condensed H2O in the upper clouds is evaporated before the falling particles reach the middle clouds. The cloud acidity is affected by the temperature and the condensation-evaporation cycles of both H2SO4 and H2O. Because of the large chemical production of H2SO4 vapor and relatively inefficient cloud condensation, the simulated H2SO4 vapor above 60 km is largely supersaturated by more than two orders of magnitude, which could be tested by future observations.

astro-ph.EP↗

arXiv2022

A Fast, Semi-analytical Model for the Venusian Binary Cloud System

The Venusian clouds originate from the binary condensation of H$_{2}$SO$_{4}$ and H$_{2}$O. The two components strongly interact with each other via chemistry and cloud formation. Previous works adopted sophisticated microphysical approaches to understand the clouds. Here we show that the observed vapor and cloud distributions on Venus can be well explained by a semi-analytical model. Our model assumes local thermodynamical equilibrium for water vapor but not for sulfuric acid vapor, and includes the feedback of cloud condensation and acidity to vapor distributions. The model predicts strong supersaturation of the H$_{2}$SO$_{4}$ vapor above 60 km, consistent with our recent cloud condensation model. The semi-analytical model is 100 times faster than the condensation model and 1000 times faster than the microphysical models. This allows us to quickly explore a large parameter space of the sulfuric acid gas-cloud system. We found that the cloud mass loading in the upper clouds has an opposite response of that in the lower clouds to the vapor mixing ratios in the lower atmosphere. The transport of water vapor influences the cloud acidity in all cloud layers while the transport of sulfuric acid vapor only dominates in the lower clouds. This cloud model is fast enough to be coupled with the climate models and chemistry models to understand the cloudy atmospheres of Venus and Venus-like extra-solar planets.

astro-ph.EP↗

arXiv2022

LAMOST meets Gaia: The Galactic Open Clusters

Open Clusters are born and evolve along the Milky Way plane, on them is imprinted the history of the Galactic disc, including the chemical and dynamical evolution. Chemical and dynamical properties of open clusters can be derived from photometric, spectroscopic, and astrometric data of their member stars. Based on the photometric and astrometric data from the Gaia mission, the membership of stars in more than 2000 Galactic clusters has been identified in the literature. The chemical and kinematical properties, however, are still poorly known for many of these clusters. In synergy with the large spectroscopic survey LAMOST (data release 8) and Gaia (data release 2), we report a new comprehensive catalogue of 386 open clusters. This catalogue has homogeneous parameter determinations of radial velocity, metallicity, and dynamical properties, such as orbit, eccentricity, angular momenta, total energy, and 3D Galactic velocity. These parameters allow the first radial velocity determination and the first spectroscopic [Fe/H] determination for 44 and 137 clusters, respectively. The metallicity distribution of majority clusters shows falling trends in the parameter space of the Galactocentric radius, the total energy, and the Z component of angular momentum -- except for two old groups that show flat tails in their own parameter planes. Cluster populations of ages younger and older than 500 Myrs distribute diversely on the disc. The latter has a spatial consistency with the Galactic disc flare. The 3-D spatial comparison between very young clusters (< 100 Myr) and nearby molecular clouds revealed a wide range of metallicity distribution along the Radcliffe gas cloud wave, indicating a possible inhomogeneous mixing or fast star formation along the wave. This catalogue would serve the community as a useful tool to trace the chemical and dynamical evolution of the Milky Way.

astro-ph.GA↗

arXiv2022

Cleaning our Hazy Lens: Exploring Trends in Transmission Spectra of Warm Exoplanets

Relatively little is understood about the atmospheric composition of temperate to warm exoplanets (equilibrium temperature $T_{\rm eq}<$ 1000 K), as many of them are found to have uncharacteristically flat transmission spectra. Their flattened spectra are likely due to atmospheric opacity sources such as planet-wide photochemical hazes and condensation clouds. We compile the transmission spectra of 25 warm exoplanets previously observed by the Hubble Space Telescope and quantify the haziness of each exoplanet using a normalized amplitude of the water absorption feature ($A_{\rm H}$). By examining the relationships between $A_{\rm H}$ and various planetary and stellar forcing parameters, we endeavor to find correlations of haziness associated with planetary properties. We adopt new statistical correlation tests that are more suitable for the small, non-normally distributed warm exoplanet sample. Our analysis shows that none of the parameters hold statistically significant correlation with $A_{\rm H}$ ($p \le 0.01$) with the addition of new exoplanet data, including the previously identified linear trends between $A_{\rm H}$ and $T_{\rm{eq}}$ or hydrogen-helium envelope mass fraction (f$_{\rm{HHe}}$). This suggests that haziness in warm exoplanets is not simply controlled by any single planetary/stellar parameter. Among all the parameters we investigated, planet gravity ($g_{\rm p}$), atmospheric scale height ($H$), planet density ($ρ_{\rm p}$), orbital eccentricity ($e$), and age of the star ($t_{\rm age}$) hold tentative correlations with $A_{\rm H}$. Specifically, lower $H$, higher $g_{\rm p}$, $ρ_{\rm p}$, $e$, or $t_{\rm age}$ may lead to clearer atmospheres. We still need more observations and laboratory experiments to fully understand the complex physics and chemistry involved in creating hazy warm exoplanets.

astro-ph.EP↗

arXiv2022

ABO: Dataset and Benchmarks for Real-World 3D Object Understanding

We introduce Amazon Berkeley Objects (ABO), a new large-scale dataset designed to help bridge the gap between real and virtual 3D worlds. ABO contains product catalog images, metadata, and artist-created 3D models with complex geometries and physically-based materials that correspond to real, household objects. We derive challenging benchmarks that exploit the unique properties of ABO and measure the current limits of the state-of-the-art on three open problems for real-world 3D object understanding: single-view 3D reconstruction, material estimation, and cross-domain multi-view object retrieval.

cs.CV↗

arXiv2022

Tunable linearity of high-performance vertical dual-gate vdW phototransistor

Layered two-dimensional (2D) semiconductors have been widely exploited in photodetectors due to their excellent electronic and optoelectronic properties. To improve their performance, photogating, photoconductive, photovoltaic, photothermoelectric, and other effects have been used in phototransistors and photodiodes made with 2D semiconductors or hybrid structures. However, it is difficult to achieve the desired high responsivity and linear photoresponse simultaneously in a monopolar conduction channel or a p-n junction. Here we present dual-channel conduction with ambipolar multilayer WSe2 by employing the device concept of dual-gate phototransistor, where p-type and n-type channels are produced in the same semiconductor using opposite dual-gating. It is possible to tune the photoconductive gain using a vertical electric field, so that the gain is constant with respect to the light intensity-a linear photoresponse, with a high responsivity of ~2.5*10^4 A/W. Additionally, the 1/f noise of the device is kept at a low level under the opposite dual-gating due to the reduction of current and carrier fluctuation, resulting in a high detectivity of ~2*10^13 Jones in the linear photoresponse regime. The linear photoresponse and high performance of our dual-gate WSe2 phototransistor offer the possibility of achieving high-resolution and quantitative light detection with layered 2D semiconductors.

cond-mat.mtrl-sci↗

arXiv2022

THP: Topological Hawkes Processes for Learning Causal Structure on Event Sequences

Learning causal structure among event types on multi-type event sequences is an important but challenging task. Existing methods, such as the Multivariate Hawkes processes, mostly assumed that each sequence is independent and identically distributed. However, in many real-world applications, it is commonplace to encounter a topological network behind the event sequences such that an event is excited or inhibited not only by its history but also by its topological neighbors. Consequently, the failure in describing the topological dependency among the event sequences leads to the error detection of the causal structure. By considering the Hawkes processes from the view of temporal convolution, we propose a Topological Hawkes process (THP) to draw a connection between the graph convolution in the topology domain and the temporal convolution in time domains. We further propose a causal structure learning method on THP in a likelihood framework. The proposed method is featured with the graph convolution-based likelihood function of THP and a sparse optimization scheme with an Expectation-Maximization of the likelihood function. Theoretical analysis and experiments on both synthetic and real-world data demonstrate the effectiveness of the proposed method

cs.LG↗

arXiv2022

Mechanism-based Tuning of Room-temperature Ferromagnetism in Mn-doped \b{eta}-Ga2O3 by Annealing Atmospher

Mn-doped \b{eta}-Ga2O3 (GMO) films with room-temperature ferromagnetism (RTFM) are synthesized by polymer-assisted deposition and the effects of annealing atmosphere (air or pure O2 gas) on their structures and physical properties are investigated. The characterizations show that the concentrations of vacancy defects and Mn dopants in various valence states and lattice constants of the samples are all modulated by the annealing atmosphere. Notably, the samples annealed in air (GMO-air) exhibit a saturation magnetization as strong as 170% times that of the samples annealed in pure O2 gas (GMO-O2), which can be quantitatively explained by oxygen vacancy (VO) controlled ferromagnetism due to bound magnetic polarons established between delocalized hydrogenic electrons of VOs and local magnetic moments of Mn2+, Mn3+, and Mn4+ ions in the samples. Our results provide insights into mechanism-based tuning of RTFM in Ga2O3 and may be useful for design, fabrication, and application of related spintronic materials.

cond-mat.mtrl-sci↗

arXiv2022

Heterogeneous Information Network based Default Analysis on Banking Micro and Small Enterprise Users

Risk assessment is a substantial problem for financial institutions that has been extensively studied both for its methodological richness and its various practical applications. With the expansion of inclusive finance, recent attentions are paid to micro and small-sized enterprises (MSEs). Compared with large companies, MSEs present a higher exposure rate to default owing to their insecure financial stability. Conventional efforts learn classifiers from historical data with elaborate feature engineering. However, the main obstacle for MSEs involves severe deficiency in credit-related information, which may degrade the performance of prediction. Besides, financial activities have diverse explicit and implicit relations, which have not been fully exploited for risk judgement in commercial banks. In particular, the observations on real data show that various relationships between company users have additional power in financial risk analysis. In this paper, we consider a graph of banking data, and propose a novel HIDAM model for the purpose. Specifically, we attempt to incorporate heterogeneous information network with rich attributes on multi-typed nodes and links for modeling the scenario of business banking service. To enhance feature representation of MSEs, we extract interactive information through meta-paths and fully exploit path information. Furthermore, we devise a hierarchical attention mechanism respectively to learn the importance of contents inside each meta-path and the importance of different metapahs. Experimental results verify that HIDAM outperforms state-of-the-art competitors on real-world banking data.

q-fin.RM↗

arXiv2022

Values of Coordinated Residential Space Heating in Demand Response Provision

Demand-side response from space heating in residential buildings can potentially provide a huge amount of flexibility for the power system, particularly with deep electrification of the heat sector. In this context, this paper presents a novel distributed control strategy to coordinate space heating across numerous residential households with diversified thermal parameters. By employing an iterative algorithm under the game-theoretical framework, each household adjusts its own heating schedule through demand shift and thermal comfort compensation with the purpose of achieving individual cost savings, whereas the aggregate peak demand is effectively shaved on the system level. Additionally, an innovative thermal comfort model which considers both the temporal and spatial differences in customised thermal comfort requirements is proposed. Through a series of case studies, it is demonstrated that the proposed space heating coordination strategy can facilitate effective energy arbitrage for individual buildings, driving a 13.96% reduction in system operational cost and 28.22% peak shaving. Moreover, the superiority of the proposed approach in thermal comfort maintenance is numerically analysed based on the proposed thermal comfort quantification model.

eess.SY↗

arXiv2022

New Open Cluster candidates Found in Galactic Disk Using Gaia DR2/EDR3 Data

We report 541 new open cluster candidates in Gaia EDR3 through revisiting the cluster results from an earlier analysis of the Gaia DR2, which revealed nearly a thousand open cluster candidates in the solar neighborhood (mostly d < 3 kpc) resideing at Galactic latitudes |b| < 20 degrees. A subsequent comparison with lists of known clusters shows a large increases of the cluster samples within 2 kpc from the Sun. We assign membership probabilities to the stars through the open source pyUPMASK algorithm, and also estimate the physical parameters through isochrone fitting for each candidate. Most of the new candidates show small total proper motion dispersions and clear features in the color-magnitude diagrams. Besides, the metallicity gradient of the new candidates is consistent with those found in the literature. The cluster parameters and member stars are available at CDS via anonymous ftp to cdsarc.u-strasbg.fr(130.79.128.5) or via https://cdsarc.unistra.fr/viz-bin/cat/J/ApJS. The discovery of these new objects shows that the open cluster samples in Gaia data is still not complete, and more discoveries are expected in the future researches.

astro-ph.GA↗

arXiv2022

Multi-modality Deep Restoration of Extremely Compressed Face Videos

Arguably the most common and salient object in daily video communications is the talking head, as encountered in social media, virtual classrooms, teleconferences, news broadcasting, talk shows, etc. When communication bandwidth is limited by network congestions or cost effectiveness, compression artifacts in talking head videos are inevitable. The resulting video quality degradation is highly visible and objectionable due to high acuity of human visual system to faces. To solve this problem, we develop a multi-modality deep convolutional neural network method for restoring face videos that are aggressively compressed. The main innovation is a new DCNN architecture that incorporates known priors of multiple modalities: the video-synchronized speech signal and semantic elements of the compression code stream, including motion vectors, code partition map and quantization parameters. These priors strongly correlate with the latent video and hence they are able to enhance the capability of deep learning to remove compression artifacts. Ample empirical evidences are presented to validate the superior performance of the proposed DCNN method on face videos over the existing state-of-the-art methods.

cs.CV↗

arXiv2022

Deep Decoding of $\ell_\infty$-coded Light Field Images

To enrich the functionalities of traditional cameras, light field cameras record both the intensity and direction of light rays, so that images can be rendered with user-defined camera parameters via computations. The added capability and flexibility are gained at the cost of gathering typically more than $100\times$ greater amount of information than conventional images. To cope with this issue, several light field compression schemes have been introduced. However, their ways of exploiting correlations of multidimensional light field data are complex and are hence not suited for inexpensive light field cameras. In this work, we propose a novel $\ell_\infty$-constrained light-field image compression system that has a very low-complexity DPCM encoder and a CNN-based deep decoder. Targeting high-fidelity reconstruction, the CNN decoder capitalizes on the $\ell_\infty$-constraint and light field properties to remove the compression artifacts and achieves significantly better performance than existing state-of-the-art $\ell_2$-based light field compression methods.

eess.IV↗

arXiv2022

A bimodal distribution of haze in Pluto's atmosphere

Pluto, Titan, and Triton make up a unique class of solar system bodies, with icy surfaces and chemically reducing atmospheres rich in organic photochemistry and haze formation. Hazes play important roles in these atmospheres, with physical and chemical processes highly dependent on particle sizes, but the haze size distribution in reducing atmospheres is currently poorly understood. Here we report observational evidence that Pluto's haze particles are bimodally distributed, which successfully reproduces the full phase scattering observations from New Horizons. Combined with previous simulations of Titan's haze, this result suggests that haze particles in reducing atmospheres undergo rapid shape change near pressure levels ~0.5Pa and favors a photochemical rather than a dynamical origin for the formation of Titan's detached haze. It also demonstrates that both oxidizing and reducing atmospheres can produce multi-modal hazes, and encourages reanalysis of observations of hazes on Titan and Triton.

astro-ph.EP↗