arXiv subjects

Feng Ding

Publications and source records attributed to Feng Ding.

At least 73 records · Page 4Linked to original sources

arXiv2023

Cloud Behaviour on Tidally Locked Rocky Planets from Global High-resolution Modeling

Determining the behaviour of convection and clouds is one of the biggest challenges in our understanding of exoplanetary climates. Given the lack of in situ observations, one of the most preferable approaches is to use cloud-resolving or cloud-permitting models (CPM). Here we present CPM simulations in a quasi-global domain with high spatial resolution (4$\times$4 km grid) and explicit convection to study the cloud regime of 1 to 1 tidally locked rocky planets orbiting around low-mass stars. We show that the substellar region is covered by deep convective clouds and cloud albedo increases with increasing stellar flux. The CPM produces relatively less cloud liquid water concentration, smaller cloud coverage, lower cloud albedo, and deeper H2O spectral features than previous general circulation model (GCM) simulations employing empirical convection and cloud parameterizations. Furthermore, cloud streets--long bands of low-level clouds oriented nearly parallel to the direction of the mean boundary-layer winds--appear in the CPM and substantially affect energy balance and surface precipitation at a local level.

astro-ph.EP↗

arXiv2023

GAN-based Image Compression with Improved RDO Process

GAN-based image compression schemes have shown remarkable progress lately due to their high perceptual quality at low bit rates. However, there are two main issues, including 1) the reconstructed image perceptual degeneration in color, texture, and structure as well as 2) the inaccurate entropy model. In this paper, we present a novel GAN-based image compression approach with improved rate-distortion optimization (RDO) process. To achieve this, we utilize the DISTS and MS-SSIM metrics to measure perceptual degeneration in color, texture, and structure. Besides, we absorb the discretized gaussian-laplacian-logistic mixture model (GLLMM) for entropy modeling to improve the accuracy in estimating the probability distributions of the latent representation. During the evaluation process, instead of evaluating the perceptual quality of the reconstructed image via IQA metrics, we directly conduct the Mean Opinion Score (MOS) experiment among different codecs, which fully reflects the actual perceptual results of humans. Experimental results demonstrate that the proposed method outperforms the existing GAN-based methods and the state-of-the-art hybrid codec (i.e., VVC).

eess.IV↗

arXiv2023

True Polar Wander of Lava Worlds

As one of the most detectable types of terrestrial planets, lava worlds are highly prioritized targets for exoplanet atmosphere characterization since their atmospheres may reveal what they are made of and how. Our work examines the possibility of true polar wander (TPW) occurring on these ultra-hot tidally-locked planets, powered by mass redistribution from atmospheric flow between the hot permanent day-side and the cold permanent night-side. We find that lava planets within a certain mass and temperature range may undergo TPW, and this likelihood increases with star mass. As a result of TPW, the magma ocean and atmospheric compositions may be less evolved (refractory-enriched) than previously thought and may be validated by exoplanet demographic surveys.

astro-ph.EP↗

arXiv2023

Dynamics of growing carbon nanotube interfaces probed by machine learning-enabled molecular simulations

Carbon nanotubes (CNTs) are currently considered a successor to silicon in future nanoelectronic devices. To realize this, controlled growth of defect-free nanotubes is required. Until now, the understanding of atomic-scale CNT growth mechanisms provided by molecular dynamics simulations has been hampered by their short timescales. Here, we develop an efficient and accurate machine learning force field, DeepCNT-22, to simulate the complete growth of defect-free single-walled CNTs (SWCNTs) on iron catalysts at near-microsecond timescales. We provide atomic-level insight into the nucleation and growth processes of SWCNTs, including the evolution of the tube-catalyst interface and the mechanisms underlying defect formation and healing. Our simulations highlight the maximization of SWCNT-edge configurational entropy during growth and how defect-free CNTs can grow ultralong if carbon supply and temperature are carefully controlled.

cond-mat.mtrl-sci↗

arXiv2023

JND-Based Perceptual Optimization For Learned Image Compression

Recently, learned image compression schemes have achieved remarkable improvements in image fidelity (e.g., PSNR and MS-SSIM) compared to conventional hybrid image coding ones due to their high-efficiency non-linear transform, end-to-end optimization frameworks, etc. However, few of them take the Just Noticeable Difference (JND) characteristic of the Human Visual System (HVS) into account and optimize learned image compression towards perceptual quality. To address this issue, a JND-based perceptual quality loss is proposed. Considering that the amounts of distortion in the compressed image at different training epochs under different Quantization Parameters (QPs) are different, we develop a distortion-aware adjustor. After combining them together, we can better assign the distortion in the compressed image with the guidance of JND to preserve the high perceptual quality. All these designs enable the proposed method to be flexibly applied to various learned image compression schemes with high scalability and plug-and-play advantages. Experimental results on the Kodak dataset demonstrate that the proposed method has led to better perceptual quality than the baseline model under the same bit rate.

eess.IV↗

arXiv2022

CAMEMBERT: A Mini-Neptunes GCM Intercomparison, Protocol Version 1.0. A CUISINES Model Intercomparison Project

With an increased focus on the observing and modelling of mini-Neptunes, there comes a need to better understand the tools we use to model their atmospheres. In this paper, we present the protocol for the CAMEMBERT (Comparing Atmospheric Models of Extrasolar Mini-neptunes Building and Envisioning Retrievals and Transits) project, an intercomparison of general circulation models (GCMs) used by the exoplanetary science community to simulate the atmospheres of mini-Neptunes. We focus on two targets well studied both observationally and theoretically with planned JWST Cycle 1 observations: the warm GJ~1214b and the cooler K2-18b. For each target, we consider a temperature-forced case, a clear sky dual-grey radiative transfer case, and a clear sky multi band radiative transfer case, covering a range of complexities and configurations where we know differences exist between GCMs in the literature. This paper presents all the details necessary to participate in the intercomparison, with the intention of presenting the results in future papers. Currently, there are eight GCMs participating (ExoCAM, Exo-FMS, FMS PCM, Generic PCM, MITgcm, RM-GCM, THOR, and the UM), and membership in the project remains open. Those interested in participating are invited to contact the authors.

astro-ph.EP↗

arXiv2022

Atomically Sharp, Closed Bilayer Phosphorene Edges by Self-Passivation

Two-dimensional (2D) crystals' edge structures not only influence their overall properties but also dictate their formation due to edge-mediated synthesis and etching processes. Edges must be carefully examined because they often display complex, unexpected features at the atomic scale, such as reconstruction, functionalization, and uncontrolled contamination. Here, we examine atomic-scale edge structures and uncover reconstruction behavior in bilayer phosphorene. We use in situ transmission electron microscopy (TEM) of phosphorene/graphene specimens at elevated temperatures to minimize surface contamination and reduce e-beam damage, allowing us to observe intrinsic edge configurations. Bilayer zigzag (ZZ) edge was found the most stable edge configuration under e-beam irradiation. Through first-principles calculations and TEM image analysis under various tilting and defocus conditions, we find that bilayer ZZ edges undergo edge reconstruction and so acquire closed, self-passivated edge configurations. The extremely low formation energy of the closed bilayer ZZ edge and its high stability against e-beam irradiation are confirmed by first-principles calculations. Moreover, we fabricate bilayer phosphorene nanoribbons with atomically-sharp closed ZZ edges. The identified bilayer ZZ edges will aid in the fundamental understanding of the synthesis, degradation, reconstruction, and applications of phosphorene and related structures.

cond-mat.mes-hall↗

arXiv2022

Catalytic growth of ultralong graphene nanoribbons on insulating substrates

Graphene nanoribbons (GNRs) with widths of a few nanometres are promising candidates for future nano-electronic applications due to their structurally tunable bandgaps, ultrahigh carrier mobilities, and exceptional stability. However, the direct growth of micrometre-long GNRs on insulating substrates, which is essential for the fabrication of nano-electronic devices, remains an immense challenge. Here, we report the epitaxial growth of GNRs on an insulating hexagonal boron nitride (h-BN) substrate through nanoparticle-catalysed chemical vapor deposition (CVD). Ultra-narrow GNRs with lengths of up to 10 μm are synthesized. Remarkably, the as-grown GNRs are crystallographically aligned with the h-BN substrate, forming one-dimensional (1D) moiré superlattices. Scanning tunnelling microscopy reveals an average width of 2 nm and a typical bandgap of ~1 eV for similar GNRs grown on conducting graphite substrates. Fully atomistic computational simulations support the experimental results and reveal a competition between the formation of GNRs and carbon nanotubes (CNTs) during the nucleation stage, and van der Waals sliding of the GNRs on the h-BN substrate throughout the growth stage. Our study provides a scalable, single-step method for growing micrometre-long narrow GNRs on insulating substrates, thus opening a route to explore the performance of high-quality GNR devices and the fundamental physics of 1D moiré superlattices.

cond-mat.mes-hall↗

arXiv2022

Prospects for water vapor detection in the atmospheres of temperate and arid rocky exoplanets around M-dwarf stars

Detection of water vapor in the atmosphere of temperate rocky exoplanets would be a major milestone on the path towards characterization of exoplanet habitability. Past modeling work has shown that cloud formation may prevent the detection of water vapor on Earth-like planets with surface oceans using the James Webb Space Telescope (JWST). Here we analyze the potential for atmospheric detection of H2O on a different class of targets: arid planets. Using transit spectrum simulations, we show that atmospheric H2O may be easier to be detected on arid planets with cold-trapped ice deposits on the surface, because such planets will not possess thick H2O cloud decks that limit the transit depth of spectral features. However, additional factors such as band overlap with CO2 and other gases, extinction by mineral dust, overlap of stellar and planetary H2O lines, and the ultimate noise floor obtainable by JWST still pose important challenges. For this reason, combination of space- and ground-based spectroscopic observations will be essential for reliable detection of H2O on rocky exoplanets in the future.

astro-ph.EP↗

arXiv2022

Distributed simultaneous state and parameter estimation of nonlinear systems

In this paper, we consider distributed simultaneous state and parameter estimation for a class of nonlinear systems, for which the augmented model comprising both the states and the parameters is only partially observable. Specifically, we first illustrate how the sensitivity analysis (SA) can select variables for simultaneous state and parameter estimation. Then, a community structure detection (CSD) based process decomposition method is proposed for dividing the entire system into interconnected subsystems as the basis of distributed estimation. Next, we develop local moving horizon estimators based on the configured subsystem models, and the local estimators communicate with each other to exchange their estimates. Finally, an SA and CSD based distributed moving horizon estimation (DMHE) mechanism is proposed. The effectiveness of the proposed approach is illustrated using a chemical process consisting of four connected reactors.

eess.SY↗

arXiv2022

Bottom-up Growth of Graphene Nanospears and Nanoribbons

Graphene nanoribbons (GNRs) are considered one of the most promising materials for next generation electronics, however a reliable and controllable synthesis method is still lacking. Here, we report the CVD growth of GNRs on a copper surface and the corresponding mechanisms of growth. One-dimensional GNR growth is enabled by a vapor-liquid-solid (VLS) graphene growth guided by on-surface propagation of a liquid catalyst particle. Controlling the suppression of vapor-solid-solid (VSS) graphene growth along the width direction of the GNR by tuning the flow of H2 during growth gives rise to a spear head-shaped graphene that we term graphene nanospears (GNSs). The real-time visual and spatially resolved observations confirm the VSS growth of graphene can be fully suppressed and lead to GNR formation on Cu surface. These findings reveal key insight into the growth mechanism of graphene and open a door for achieving a facile and scalable method of synthesizing free standing GNRs.

cond-mat.mes-hall↗

arXiv2021

Self-Supervised Pre-Training for Transformer-Based Person Re-Identification

Transformer-based supervised pre-training achieves great performance in person re-identification (ReID). However, due to the domain gap between ImageNet and ReID datasets, it usually needs a larger pre-training dataset (e.g. ImageNet-21K) to boost the performance because of the strong data fitting ability of the transformer. To address this challenge, this work targets to mitigate the gap between the pre-training and ReID datasets from the perspective of data and model structure, respectively. We first investigate self-supervised learning (SSL) methods with Vision Transformer (ViT) pretrained on unlabelled person images (the LUPerson dataset), and empirically find it significantly surpasses ImageNet supervised pre-training models on ReID tasks. To further reduce the domain gap and accelerate the pre-training, the Catastrophic Forgetting Score (CFS) is proposed to evaluate the gap between pre-training and fine-tuning data. Based on CFS, a subset is selected via sampling relevant data close to the down-stream ReID data and filtering irrelevant data from the pre-training dataset. For the model structure, a ReID-specific module named IBN-based convolution stem (ICS) is proposed to bridge the domain gap by learning more invariant features. Extensive experiments have been conducted to fine-tune the pre-training models under supervised learning, unsupervised domain adaptation (UDA), and unsupervised learning (USL) settings. We successfully downscale the LUPerson dataset to 50% with no performance degradation. Finally, we achieve state-of-the-art performance on Market-1501 and MSMT17. For example, our ViT-S/16 achieves 91.3%/89.9%/89.6% mAP accuracy on Market1501 for supervised/UDA/USL ReID. Codes and models will be released to https://github.com/michuanhaohao/TransReID-SSL.

cs.CV↗

arXiv2021

Multiple moist climate equilibrium states on arid rocky M-dwarf planets: A last-saturation tracer analysis

Terrestrial-type exoplanets orbiting nearby red dwarf stars (M dwarfs) are the first potentially habitable exoplanets suitable for atmospheric characterization in the near future. Understanding the stability of water in cold-trap regions on such planets is critical because it directly impacts transmission spectroscopy observations, the global energy budget, and long-term surface water evolution. Here we diagnose the humidity distribution in idealized general circulation model (GCM) simulations of terrestrial-type exoplanets. We use the `tracer of last saturation' technique to study the saturation statistics of air parcels. We find that on synchronously rotating planets, the water vapor abundance in the nightside upper troposphere depends weakly on planetary rotation, while more water vapor builds up in the nightside lower troposphere on fast-rotating planets. We then discuss how last-saturation statistics can elucidate the multiple moist climate equilibrium states on synchronously and asynchronously rotating arid planets. We show that the multiple moist climate states arise from the cold-trapping competition between the substellar upper atmosphere and cold surface regions. We find that fast synchronously rotating planets tend to trap surface water on the nightside as a result of their weak atmospheric and strong surface cold traps compared to the slow rotating case. These results elucidate the nature of the water cycle on arid rocky exoplanets and will aid interpretation of atmospheric observations in the future.

astro-ph.EP↗

arXiv2021

Amplifying asymmetry with correlated catalysts

We investigate the basic constraint on amplifying the asymmetry in quantum states with correlated catalysts. Here a correlated catalyst is a finite-dimensional auxiliary, which exactly preserves its reduced state while allowed to become correlated to the quantum system. Interestingly, we prove that under translationally invariant operations, catalysts in pure states are useless in any state transformation, while with a correlated catalyst in a mixed state, one can enlarge the set of accessible states from an initially asymmetric state. Moreover, we show that the power of a catalyst increases with its dimension, and further, with a large enough catalyst, a qubit state with arbitrarily small amount of asymmetry can be converted to any mixed qubit state. In doing so, we build a bridge between two important results concerning the restrictions on coherence conversion, the no-broadcasting theorem and the catalytic coherence. Our results may also apply to the constraints on coherence evolution in quantum thermodynamics, and to the distribution of timing information between quantum clocks.

quant-ph↗

arXiv2021

Exploring the gap between thermal operations and enhanced thermal operations

The gap between thermal operations (TO) and enhanced thermal operations (EnTO) is an open problem raised in [Phys. Rev. Lett. 115, 210403 (2015)]. It originates from the limitations on coherence evolutions. Here we solve this problem by analytically proving that, a state transition induced by EnTO cannot be approximately realized by TO. It confirms that TO and EnTO lead to different laws of state conversions. Our results can also contribute to the study of the restrictions on coherence dynamics in quantum thermodynamics.

quant-ph↗

arXiv2021

Angstrom-wide conductive channels in black phosphorus by Cu intercalation

Intercalation is an effective method to improve and modulate properties of two-dimensional materials. Even so, spatially controlled intercalation at atomic scale, which is important to introduce and modulated properties, has not been successful due to difficulties in controlling the diffusion of intercalants. Here, we show formation of angstrom-wide conductive channels (~4.3 A) in black phosphorus by Cu intercalation. The atomic structure, resultant microstructural effects, intercalation mechanism, and local variations of electronic properties modulated in black phosphorus by Cu intercalation were investigated extensively by transmission electron microscopy including in situ observation, DFT calculation, and conductive atomic force microscopy.

cond-mat.mtrl-sci↗

arXiv2020

Crystallographic Reconstruction Driven Modified Mechanical Properties in Anisotropic Rhenium Disulfides

Atomic-scale investigation on mechanical behaviors is highly necessary to fully understand the fracture mechanics especially of brittle materials, which are determined by atomic-scale phenomena (e.g., lattice trapping). Here, exfoliated anisotropic rhenium disulfide (ReS2) flakes are used to investigate atomic-scale crack propagation depending on the propagation directions. While the conventional strain-stress curves exhibit a strong anisotropy depending on the cleavage direction of ReS2, but our experimental results show a reduced cleavage anisotropy due to the lattice reconstruction in [100] cracking with high resistance to fracture. In other words, [010] and [110] cracks with low barriers to cleavage exhibit the ultimate sharpness of the crack tip without plastic deformation, whereas [100] cracks drive lattice rotation on one side of the crack, leading to a non-flat grain boundary formation. Finally, crystallographic reconstruction associated with the high lattice randomness of two-dimensional materials drives to a modified cleavage tendency, further indicating the importance of atomic-scale studies for a complete understanding of the mechanics.

cond-mat.mtrl-sci↗

arXiv2020

Masking Quantum Information on Hyperdisks

Masking information is a protocol that encodes quantum information into a bipartite entangled state while the information is completely unknown to local systems. This paper explicitly studies the structure of the set of maskable states and its relation to hyperdisks. We prove that although the qubit states which can be masked must locate on a single hyperdisk, the set of maskable states can consist of two or more hyperdisks for high-dimensional cases. Our results may shed light on several research fields of quantum information theory, such as the structure of entangled states and the local discrimination of bipartite states.

quant-ph↗