arXiv subjects

Fan Zhang

Publications and source records attributed to Fan Zhang.

At least 613 records · Page 34Linked to original sources

arXiv2023

Discovery of the linear energy-dependence of the spectral lag of X-ray bursts from SGR J1935+2154

Spectral lag of the low-energy photons with respect to the high-energy ones is a common astrophysical phenomenon (such as Gamma-ray bursts and the Crab pulsar) and may serve as a key probe to the underlying radiation mechanism. However, spectral lag in keV range of the magnetar bursts has not been systematically studied yet. In this work, we perform a detailed spectral lag analysis with the Li-CCF method for SGR J1935+2154 bursts observed by {\it Insight}-HXMT, GECAM and Fermi/GBM from July 2014 to Jan 2022. We discover that the spectral lags of about 61\% (non-zero significance >1$σ$) bursts from SGR J1935+2154 are linearly dependent on the photon energy ($E$) with $t_{\rm lag}(E)=α(E/{\rm keV})+C$, which may be explained by a linear change of the temperature of the blackbody-emitting plasma with time. The distribution of the slope ($α$) approximately follows a Gaussian function with mean and standard deviation of 0.02 ms/keV (i.e. high-energy photons arrive earlier) and 0.02 ms/keV, respectively. We also find that the distribution can be well fitted with three Gaussians with mean values of $\sim$ -0.009, 0.013 and 0.039 ms/keV, which may correspond to different origins of the bursts. These spectral lag features may have important implications on the magnetar bursts.

astro-ph.HE↗

arXiv2023

Extraordinary surface critical behavior induced by symmetry-protected topological state of a two-dimensional quantum magnet

Using Quantum Monte Carlo simulations, we study spin-1/2 diagonal ladders coupled by ferromagnetic Heisenberg interactions. The model can also be viewed as usual ladders with ferromagnetic rung couplings coupled by antiferromagnetic diagonal couplings. We find that the model hosts a striped magnetic ordered phase and two topological nontrivial Haldane phases, separated by two quantum critical points. We show that the two quantum critical points are all in the three-dimensional O(3) universality class irrelevant to the topological properties of the Haldane phases. The properties of the surface formed by ladder ends in the two Haldane phases are studied. We find that the surface states are both gapless due to the symmetry-protected topological bulk states. We further demonstrate that extraordinary surface critical behaviors are realized at both critical points on such gapless surfaces without enhancing the surface coupling. Notably, the surface is not expected to be ordered in the three-dimensional classical O(3) critical point, suggesting that the topological properties of the Haldane phases are responsible for such surface critical behavior.

cond-mat.str-el↗

arXiv2023

Assessing inner boundary conditions for global coronal modeling of solar maxima

Computational Fluid Dynamics (CFD)-based global solar coronal simulations are slowly making their way into the space weather modeling toolchains to replace the semi-empirical methods such as the Wang-Sheeley-Arge (WSA) model. However, since they are based on CFD, if the assumptions in them are too strong, these codes might experience issues with convergence and unphysical solutions. Particularly the magnetograms corresponding to solar maxima can pose problems as they contain active regions with strong magnetic fields, resulting in large gradients. Combined with the approximate way in which the inner boundary is often treated, this can lead to non-physical features or even a complete divergence of the simulation in these cases. Here, we show some of the possible approaches to handle this inner boundary in our global coronal model COolfluid COrona uNstrUcTured (COCONUT) in a way that improves both convergence and accuracy. Since we know that prescribing the photospheric magnetic field for a region that represents the lower corona is not entirely physical, first, we look at the ways in which we can adjust the input magnetograms to remove the highest magnitudes and gradients. Secondly, since in the default setup we also assume a constant density, here we experiment with changing these values locally and globally to see the effect on the results. We conclude, through comparison with observations and convergence analysis, that modifying the density locally in active regions is the best way to improve the performance both in terms of convergence and physical accuracy from the tested approaches.

astro-ph.SR↗

arXiv2023

Phased Progressive Learning with Coupling-Regulation-Imbalance Loss for Imbalanced Data Classification

Deep convolutional neural networks often perform poorly when faced with datasets that suffer from quantity imbalances and classification difficulties. Despite advances in the field, existing two-stage approaches still exhibit dataset bias or domain shift. To counter this, a phased progressive learning schedule has been proposed that gradually shifts the emphasis from representation learning to training the upper classifier. This approach is particularly beneficial for datasets with larger imbalances or fewer samples. Another new method a coupling-regulation-imbalance loss function is proposed, which combines three parts: a correction term, Focal loss, and LDAM loss. This loss is effective in addressing quantity imbalances and outliers, while regulating the focus of attention on samples with varying classification difficulties. These approaches have yielded satisfactory results on several benchmark datasets, including Imbalanced CIFAR10, Imbalanced CIFAR100, ImageNet-LT, and iNaturalist 2018, and can be easily generalized to other imbalanced classification models.

cs.LG↗

arXiv2023

Efficient Self-supervised Continual Learning with Progressive Task-correlated Layer Freezing

Inspired by the success of Self-supervised learning (SSL) in learning visual representations from unlabeled data, a few recent works have studied SSL in the context of continual learning (CL), where multiple tasks are learned sequentially, giving rise to a new paradigm, namely self-supervised continual learning (SSCL). It has been shown that the SSCL outperforms supervised continual learning (SCL) as the learned representations are more informative and robust to catastrophic forgetting. However, if not designed intelligently, the training complexity of SSCL may be prohibitively high due to the inherent training cost of SSL. In this work, by investigating the task correlations in SSCL setup first, we discover an interesting phenomenon that, with the SSL-learned background model, the intermediate features are highly correlated between tasks. Based on this new finding, we propose a new SSCL method with layer-wise freezing which progressively freezes partial layers with the highest correlation ratios for each task to improve training computation efficiency and memory efficiency. Extensive experiments across multiple datasets are performed, where our proposed method shows superior performance against the SoTA SSCL methods under various SSL frameworks. For example, compared to LUMP, our method achieves 12\%/14\%/12\% GPU training time reduction, 23\%/26\%/24\% memory reduction, 35\%/34\%/33\% backward FLOPs reduction, and 1.31\%/1.98\%/1.21\% forgetting reduction without accuracy degradation on three datasets, respectively.

cs.CV↗

arXiv2023

Inverse Orbital Hall Effect Discovered from Light-Induced Terahertz Emission

Recent progress in orbitronics reveals the possibility of using orbit current as an information carrier. The interconversion between orbit currents and charge currents is crucial for orbit information processing. Although orbit currents can be created from charge currents via the orbital Hall effect, the conversion from orbit currents into charge currents has been observed only in very few systems due to the lack of a reliable orbit current source and the disturbance of the omnipresent inverse spin Hall effect. In this study, we show that ultrafast pulses of orbit current can be generated in Ni layers by femtosecond laser pulses. We demonstrate that, by injecting such orbit current pulses into nonmagnetic metals, a transient charge current is induced and emits terahertz electromagnetic pulses. The nonmagnetic metal layer acts as a converter of the orbit current into the charge current. The discovery of the generation and conversion of light-induced orbit current opens a new route for developing future orbitronic devices.

cond-mat.mes-hall↗

arXiv2023

The Impact of Coherence Diversity on MIMO Relays

This paper studies MIMO relays with non-identical link coherence times, a frequently occurring condition when, e.g., the nodes in the relay channel do not all have the same mobility, or the scatterers around some nodes have different mobility compared with those around other nodes. Despite its practical relevance, this condition, known as coherence diversity, has not been studied in the relay channel. This paper studies the performance of MIMO relays and proposes efficient transmission strategies under coherence diversity. Since coherence times have a prominent impact on channel training, we do not assume channel state is available to the decoder for free; all channel training resources are accounted for in the calculations. A product superposition technique is employed at the source, which allows a more efficient usage of degrees of freedom when the relay and the destination have different training requirements. Varying configurations of coherence times are studied. The interesting case where the different link coherence intervals are not a multiple of each other, and therefore the coherence intervals do not align, is studied. Relay scheduling is combined with the product superposition to obtain further gains in degrees of freedom. The impact of coherence diversity is further studied in the presence of multiple parallel relays.

cs.IT↗

arXiv2023

The performance of SiPM-based gamma-ray detector (GRD) of GECAM-C

As a new member of GECAM mission, the GECAM-C (also called High Energy Burst Searcher, HEBS) is a gamma-ray all-sky monitor onboard SATech-01 satellite, which was launched on July 27th, 2022 to detect gamma-ray transients from 6 keV to 6 MeV, such as Gamma-Ray Bursts (GRBs), high energy counterpart of Gravitational Waves (GWs) and Fast Radio Bursts (FRBs), and Soft Gamma-ray Repeaters (SGRs). Together with GECAM-A and GECAM-B launched in December 2020, GECAM-C will greatly improve the monitoring coverage, localization, as well as temporal and spectral measurements of gamma-ray transients. GECAM-C employs 12 SiPM-based Gamma-Ray Detectors (GRDs) to detect gamma-ray transients . In this paper, we firstly give a brief description of the design of GECAM-C GRDs, and then focus on the on-ground tests and in-flight performance of GRDs. We also did the comparison study of the SiPM in-flight performance between GECAM-C and GECAM-B. The results show GECAM-C GRD works as expected and is ready to make scientific observations.

astro-ph.IM↗

arXiv2023

Correlating Chemical Reaction and Mass Transport in Hydrogen-based Direct Reduction of Iron Oxide

Steelmaking contributes 8% to the total CO2 emissions globally, primarily due to coal-based iron ore reduction. Clean hydrogen-based ironmaking has variable performance because the dominant gas-solid reduction mechanism is set by the defects and pores inside the mm-nm sized oxide particles that change significantly as the reaction progresses. While these governing dynamics are essential to establish continuous flow of iron and its ores through reactors, the direct link between agglomeration and chemistry is still contested due to missing measurements. In this work, we directly measure the connection between chemistry and agglomeration in the smallest iron oxides relevant to magnetite ores. Using synthesized spherical 10-nm magnetite particles reacting in H2, we resolve the formation and consumption of wüstite (FeO) - the step most commonly attributed to agglomeration. Using X-ray scattering and microscopy, we resolve crystallographic anisotropy in the rate of the initial reaction, which becomes isotropic as the material sinters. Complementing with imaging, we demonstrate how the particles self-assemble, subsequently react and sinter into ~100x oblong grains. Our insights into how morphologically uniform iron oxide particles react and agglomerate H2 reduction enable future size-dependent models to effectively describe the multiscale iron ore reduction.

cond-mat.mtrl-sci↗

arXiv2023

Force-Directed Graph Layouts Revisited: A New Force Based on the T-Distribution

In this paper, we propose the t-FDP model, a force-directed placement method based on a novel bounded short-range force (t-force) defined by Student's t-distribution. Our formulation is flexible, exerts limited repulsive forces for nearby nodes and can be adapted separately in its short- and long-range effects. Using such forces in force-directed graph layouts yields better neighborhood preservation than current methods, while maintaining low stress errors. Our efficient implementation using a Fast Fourier Transform is one order of magnitude faster than state-of-the-art methods and two orders faster on the GPU, enabling us to perform parameter tuning by globally and locally adjusting the t-force in real-time for complex graphs. We demonstrate the quality of our approach by numerical evaluation against state-of-the-art approaches and extensions for interactive exploration.

cs.GR↗

arXiv2023

GeoLab: Geometry-based Tractography Parcellation of Superficial White Matter

Superficial white matter (SWM) has been less studied than long-range connections despite being of interest to clinical research, andfew tractography parcellation methods have been adapted to SWM. Here, we propose an efficient geometry-based parcellation method (GeoLab) that allows high-performance segmentation of hundreds of short white matter bundles from a subject. This method has been designed for the SWM atlas of EBRAINS European infrastructure, which is composed of 657 bundles. The atlas projection relies on the precomputed statistics of six bundle-specific geometrical properties of atlas streamlines. In the spirit of RecoBundles, a global and local streamline-based registration (SBR) is used to align the subject to the atlas space. Then, the streamlines are labeled taking into account the six geometrical parameters describing the similarity to the streamlines in the model bundle. Compared to other state-of-the-art methods, GeoLab allows the extraction of more bundles with a higher number of streamlines.

eess.IV↗

arXiv2023

Few-shots Portrait Generation with Style Enhancement and Identity Preservation

Nowadays, the wide application of virtual digital human promotes the comprehensive prosperity and development of digital culture supported by digital economy. The personalized portrait automatically generated by AI technology needs both the natural artistic style and human sentiment. In this paper, we propose a novel StyleIdentityGAN model, which can ensure the identity and artistry of the generated portrait at the same time. Specifically, the style-enhanced module focuses on artistic style features decoupling and transferring to improve the artistry of generated virtual face images. Meanwhile, the identity-enhanced module preserves the significant features extracted from the input photo. Furthermore, the proposed method requires a small number of reference style data. Experiments demonstrate the superiority of StyleIdentityGAN over state-of-art methods in artistry and identity effects, with comparisons done qualitatively, quantitatively and through a perceptual user study. Code has been released on Github3.

cs.CV↗

arXiv2023

Cross calibration of gamma-ray detectors (GRD) of GECAM-C

The gamma-ray detectors (GRDs) of GECAM-C onborad SATech-01 satellite is designed to monitor gamma-ray transients all over the sky from 6 keV to 6 MeV. The energy response matrix is the key to do spectral measurements of bursts, which is usually generated from GEANT4 simulation and partially verified by the ground calibration. In this work, energy response matrix of GECAM-C GRD is cross-calibrated with Fermi/GBM and Swift/BAT using a sample of Gamma-Ray Bursts (GRBs) and Soft Gamma-Ray Repeaters (SGRs). The calibration results show there is a good agreement between GECAM-C and other reasonably well calibrated instrument (i.e. Fermi/GBM and Swift/BAT). We also find that different GRD detectors of GECAM-C also show consistency with each other. All these results indicate that GECAM-C GRD can provide reliable spectral measurements.

astro-ph.IM↗

arXiv2023

Minimizing the Influence of Misinformation via Vertex Blocking

Information cascade in online social networks can be rather negative, e.g., the spread of rumors may trigger panic. To limit the influence of misinformation in an effective and efficient manner, the influence minimization (IMIN) problem is studied in the literature: given a graph G and a seed set S, blocking at most b vertices such that the influence spread of the seed set is minimized. In this paper, we are the first to prove the IMIN problem is NP-hard and hard to approximate. Due to the hardness of the problem, existing works resort to greedy solutions and use Monte-Carlo Simulations to solve the problem. However, they are cost-prohibitive on large graphs since they have to enumerate all the candidate blockers and compute the decrease of expected spread when blocking each of them. To improve the efficiency, we propose the AdvancedGreedy algorithm (AG) based on a new graph sampling technique that applies the dominator tree structure, which can compute the decrease of the expected spread of all candidate blockers at once. Besides, we further propose the GreedyReplace algorithm (GR) by considering the relationships among candidate blockers. Extensive experiments on 8 real-life graphs demonstrate that our AG and GR algorithms are significantly faster than the state-of-the-art by up to 6 orders of magnitude, and GR can achieve better effectiveness with its time cost close to AG.

cs.DB↗

arXiv2023

WPC: Whole-picture Workload Characterization

This article raises an important and challenging workload characterization issue: can we uncover each critical component across the stacks contributing what percentages to any specific bottleneck? The typical critical components include languages, programming frameworks, runtime environments, instruction set architectures (ISA), operating systems (OS), and microarchitecture. Tackling this issue could help propose a systematic methodology to guide the software and hardware co-design and critical component optimizations. We propose a whole-picture workload characterization (WPC) methodology to answer the above issue. In essence, WPC is an iterative ORFE loop consisting of four steps: Observation, Reference, Fusion, and Exploration. WPC observes different level data (observation), fuses and normalizes the performance data (fusion) with respect to the well-designed standard reference workloads suite (reference), and explores the software and hardware co-design space (exploration) to investigate the impacts of critical components across the stacks. We build and open-source the WPC tool. Our evaluations confirm WPC can quantitatively reveal the contributions of the language, framework, runtime environment, ISA, OS, and microarchitecture to the primary pipeline efficiency.

cs.PF↗

arXiv2023

Text-Guided Mask-free Local Image Retouching

In the realm of multi-modality, text-guided image retouching techniques emerged with the advent of deep learning. Most currently available text-guided methods, however, rely on object-level supervision to constrain the region that may be modified. This not only makes it more challenging to develop these algorithms, but it also limits how widely deep learning can be used for image retouching. In this paper, we offer a text-guided mask-free image retouching approach that yields consistent results to address this concern. In order to perform image retouching without mask supervision, our technique can construct plausible and edge-sharp masks based on the text for each object in the image. Extensive experiments have shown that our method can produce high-quality, accurate images based on spoken language. The source code will be released soon.

cs.CV↗

arXiv2023

ST-MFNet Mini: Knowledge Distillation-Driven Frame Interpolation

Currently, one of the major challenges in deep learning-based video frame interpolation (VFI) is the large model sizes and high computational complexity associated with many high performance VFI approaches. In this paper, we present a distillation-based two-stage workflow for obtaining compressed VFI models which perform competitively to the state of the arts, at a greatly reduced model size and complexity. Specifically, an optimisation-based network pruning method is first applied to a recently proposed frame interpolation model, ST-MFNet, which outperforms many other VFI methods but suffers from large model size. The resulting new network architecture achieves a 91% reduction in parameters and 35% increase in speed. Secondly, the performance of the new network is further enhanced through a teacher-student knowledge distillation training process using a Laplacian distillation loss. The final low complexity model, ST-MFNet Mini, achieves a comparable performance to most existing high-complex VFI methods, only outperformed by the original ST-MFNet. Our source code is available at https://github.com/crispianm/ST-MFNet-Mini

eess.IV↗

arXiv2023

Burst search method based on likelihood ratio in Poisson Statistics

Searching for X-ray and gamma-ray bursts, including Gamma-ray bursts (GRBs), Soft Gamma-ray Repeaters (SGRs) and high energy transients associated with Gravitational wave (GW) events or Fast radio bursts (FRBs), is of great importance in the multi-messenger and multi-wavelength era. Although a coherent search based on the likelihood ratio and Gaussian statistics has been established and utilized in many studies, this Gaussian-based method could be problematic for weak and short bursts which usually have very few counts. To deal with all bursts including weak ones, here we propose the coherent search in Poisson statistics. We studied the difference between Poisson-based and Gaussian-based search methods by Monte Carlo simulations, and find that the Poisson-based search method has advantages compared to the Gaussian case especially for weak bursts. Our results show that, for very weak bursts with very low number of counts, the Poisson-based search can provide higher significance than the Gaussian-based search, and its likelihood ratio (for background fluctuation) still generally follows the chi2 distribution, making the significance estimation of searched bursts very convenient. Thus, we suggest that the coherent search based on Poisson likelihood ratio is more appropriate in the search for generic transients including very weak ones.

astro-ph.HE↗