arXiv subjects

Yu Zhang

Publications and source records attributed to Yu Zhang.

At least 973 records · Page 54Linked to original sources

arXiv2023

Photometric calibration of the Stellar Abundance and Galactic Evolution Survey (SAGES): Nanshan One-meter Wide-field Telescope g, r, and i band imaging data

In this paper, a total of approximately 2.6 million dwarfs were constructed as standard stars, with an accuracy of about 0.01-0.02 mag for each band, by combining spectroscopic data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope Data Release 7, photometric data from the corrected Gaia Early Data Release 3, and photometric metallicities. Using the spectroscopy based stellar color regression method (SCR method) and the photometric-based SCR method (SCR' method), we performed the relative calibration of the Nanshan One-meter Wide-field Telescope imaging data. Based on the corrected Pan-STARRS DR1 photometry, the absolute calibration was also performed. In the photometric calibration process, we analyzed the dependence of the calibration zero points on different images (observation time), different gates of the CCD detector, and different CCD positions. We found that the stellar flat and the relative gain between different gates depend on time. The amplitude of gain variation in three channels is approximately 0.5%-0.7% relative to the other channel, with a maximum value of 4%. In addition, significant spatial variations of the stellar flat fitting residual are found and corrected. Using repeated sources in the adjacent images, we checked and discovered internal consistency of about 1-2 mmag in all the filters. Using the PS1 magnitudes synthesized by Gaia DR3 BP/RP spectra by the synthetic photometry method, we found that the photometric calibration uniformity is about 1-2 mmag for all the bands, at a spatial resolution of 1.3 degree. A detailed comparison between the spectroscopy-based SCR and photometric-based SCR method magnitude offsets was performed, and we achieved an internal consistency precision of about 2 mmag or better with resolutions of 1.3 degree for all the filters. Which is mainly from the position-dependent errors of the E(B-V) used in SCR' method.

astro-ph.SR↗

arXiv2023

A catalogue and statistical analysis for magnetic stars

Magnetic fields are significant in the structure and evolution of stars. We present a comprehensive catalogue of 1784 known magnetic stars, detailing their identifications, HD numbers, precise locations, spectral types, and averaged quadratic effective magnetic fields among other important information. The group comprises 177 O-type stars, 551 B-type stars, 520 A-type stars, 91 F-type stars, 53 G-type stars, 61 K-type stars, 31 M-type stars, and an additional 300 stars whose spectral classification remains indeterminate. Our analysis examines the statistical properties of these magnetic stars. The relative integrated distribution function and number distribution function for all magnetic stars of the same spectral type can be effectively approximated using an exponential function of the averaged quadratic effective magnetic field. The analysis further reveals that A and B-type stars possess the strongest mean magnetic fields, indicating an easier detection of their magnetic fields.

astro-ph.SR↗

arXiv2023

How wavelength affects the hydrodynamic performance of two accelerating mirror-symmetric slender swimmers

Fish schools are capable of simultaneous linear acceleration. To reveal the underlying hydrodynamic mechanism, we numerically investigate how Reynolds number $ Re = 1000 - 2000 $, Strouhal number $ St = 0.2 - 0.7 $ and wavelength $ λ= 0.5 - 2 $ affect the mean net thrust and net propulsive efficiency of two side-by-side hydrofoils undulating in anti-phase. In total, $ 550 $ cases are simulated using immersed boundary method. The thrust increases significantly with wavelength and Strouhal number, yet only slightly with the Reynolds number. We apply a symbolic regression algorithm to formulate this relationship. Furthermore, we find that mirror-symmetric schooling can achieve a \textit{net} thrust more than ten times that of a single swimmer, especially at low Reynolds numbers. The highest efficiency is obtained at $ St = 0.5 $ and $ λ= 1.2 $, where $ St $ is consistent with that observed in the linear-accelerating natural swimmers, \eg Crevalle jack. Six distinct flow structures are identified. The highest thrust corresponds to an asymmetric flow pattern, whereas the highest efficiency occurs when the flow is symmetric with converging vortex streets.

physics.flu-dyn↗

arXiv2023

Engineering mobility in quasiperiodic lattices with exact mobility edges

We investigate the effect of an additional modulation parameter $δ$ on the mobility properties of quasiperiodic lattices described by a generalized Ganeshan-Pixley-Das Sarma model with two on site modulation parameters. For the case with bounded quasiperiodic potential, we unveil the existence of self-duality relation, independent of $δ$. By applying Avila's global theory, we analytically derive Lyapunov exponents in the whole parameter space, which enables us to determine mobility edges or anomalous mobility edges exactly. Our analytical results indicate that the mobility edge equation is described by two curves and their intersection with the spectrum gives the true mobility edge. Tuning the strength parameter $δ$ can change the spectrum of the quasiperiodic lattice, and thus engineers the mobility of quasi-periodic systems, giving rise to completely extended, partially localized, and completely localized regions. For the case with unbounded quasiperiodic potential, we also obtain the analytical expression of the anomalous mobility edge, which separates localized states from critical states. By increasing the strength parameter $δ$, we find that the critical states can be destroyed gradually and finally vanishes.

cond-mat.dis-nn↗

arXiv2023

Real-World Evaluation of Full-Duplex Millimeter Wave Communication Systems

Noteworthy strides continue to be made in the development of full-duplex millimeter wave (mmWave) communication systems, but most of this progress has been built on theoretical models and validated through simulation. In this work, we conduct a long overdue real-world evaluation of full-duplex mmWave systems using off-the-shelf 60 GHz phased arrays. Using an experimental full-duplex base station, we collect over 200,000 measurements of self-interference by electronically sweeping its transmit and receive beams across a dense spatial profile, shedding light on the effects of the environment, array positioning, and beam steering direction. We then call attention to five key challenges faced by practical full-duplex mmWave systems and, with these in mind, propose a general framework for beamforming-based full-duplex solutions. Guided by this framework, we introduce a novel solution called STEER+, a more robust version of recent work called STEER, and experimentally evaluate both in a real-world setting with actual downlink and uplink users. Rather than purely minimize self-interference as with STEER, STEER+ makes use of additional measurements to maximize spectral efficiency, which proves to make it much less sensitive to one's choice of design parameters. We experimentally show that STEER+ can reliably reduce self-interference to near or below the noise floor while maintaining high SNR on the downlink and uplink, thus enabling full-duplex operation purely via beamforming.

eess.SP↗

arXiv2023

Cohomologies of modified $λ$-differential Lie triple systems and applications

In this paper, we introduce the concept and representation of modified $λ$-differential Lie triple systems. Next, we define the cohomology of modified $λ$-differential Lie triple systems with coefficients in a suitable representation. As applications of the proposed cohomology theory, we study 1-parameter formal deformations and abelian extensions of modified $λ$-differential Lie triple systems.

math.RA↗

arXiv2023

Thermal fluctuation, deflection angle and greybody factor of a high-dimensional Schwarzschild black hole in STVG

In this work, we study the thermal fluctuation, deflection angle and greybody factor of the high-dimensional Schwarzschild black hole in scalar-tensor-vector gravity (STVG). Based on the correction of black hole entropy due to thermal fluctuation, we calculate some thermodynamic quantities associated with the correction of black hole entropy. The influence of the first-order and second-order corrections, spacetime dimensionality and STVG parameters on these thermodynamics quantities are discussed in detail. Additionally, by utilizing the Gauss-Bonnet theorem, the deflection angle is obtained in the weak field limit and the effect of two parameters on the results is visualized. Finally, we calculate the bounds on greybody factors of a massless scalar field.

gr-qc↗

arXiv2023

Weak gravitational lensing by an ESTGB black hole in the presence of a plasma

This paper is devoted to studying the weak-field gravitational lensing properties of a 4D ESTGB black hole, which is surrounded by the plasma medium. The effects of the magnetic charges and the three plasma distribution models in the deflection of light around a 4D ESTGB black hole are investigated in detail. We find that the uniform plasma leads to a larger deflection of light rays in comparison with the singular isothermal sphere (SIS), the non-singular isothermal sphere (NSIS) models. Moreover, the deflection angle increases slightly as the absolute value of the magnetic charge decreases. Finally, we analyze the total magnification of image due to weak gravitational lensing around the black hole. The result shows that the presence of a uniform plasma medium remarkably enhances the total magnification whereas the non-uniform plasma reduces the total magnification.

gr-qc↗

arXiv2023

Gray-body factor and absorption of the Dirac field in ESTGB gravity

The gray-body factor and the absorption cross section of the 4D ESTGB gravity with a mode of nonlinear electrodynamics for the massless Dirac field are studied in this paper. The magnetic charge value varies between $-2^{(\frac{5}{3})}/3$ and $0$ as well as the ADM mass is set to $1$, which corresponds to a non-extreme black hole. The gray-body factor is obtained using the semi-analytic WKB method after solving the massless Dirac equation. When the absolute value of magnetic charge is increasing, the gray-body factor $γ(ω)$ is decreasing. In addition, the partial absorption cross section and the total absorption cross section are calculated by using the partial wave method. We find that the maximum value of partial absorption cross section decreases as $κ$ increases. And the existence of magnetic charge causes the diminishing of the total absorption cross section. Finally, we find that the absorption cross section of the Dirac field is more sensitive to electric charge than magnetic charge by comparing the absorption cross section of the Reissner-Nordstr$\rm\ddot{o}$m and ESTGB-NLED black holes.

gr-qc↗

arXiv2023

Shadow, absorption and Hawking radiation of a Schwarzschild black hole surrounded by a cloud of strings in Rastall gravity

This paper studies the black hole shadow, absorption cross section, and Hawking radiation of a massless scalar field in the background of a static spherically symmetric black hole spacetime that is surrounded by a cloud of strings in Rastall gravity. Specifically, the effects of the parameters $a$ and $β$ on the photon sphere and shadow radii are investigated. The results show that as the negative parameter $β$ decreases, the photon sphere and shadow radii change in an N-shape. In addition, the absorption cross section obtained after solving the massless Klein-Gordon equation is calculated using the sinc approximation and the partial waves method. We compare the absorption cross section obtained by the sinc approximation and the partial waves method, and find it to be exceptionally consistent in the mid-to-high frequency region. Furthermore, the effects of parameters $a$ and $β$ on absorption are examined in detail. Finally, we study in detail the effects of the parameters $a$, $β$ and $l$ on the Hawking radiation power emission spectrum of the considered black hole. It turns out that the string parameter $a$ always suppresses the power emission spectrum, indicating that such black holes live longer when the string parameter $a$ is increased while other parameters are fixed.

gr-qc↗

arXiv2023

Testing Neutrino Dipole Portal by Long-lived Particle Detectors at the LHC

We discuss the potential of using detectors aimed for searching long-lived particles~(LLP) at the high-luminosity LHC run, to probe the neutrino dipole models. This is achieved by taking the heavy neutral leptons~(HNL) of the models as candidates of the LLPs. Taking into account the dipole couplings to the weak bosons, $d_{W,Z}$, which control the production of the HNLs at the LHC, we discuss the reach on the electromagnetic dipole couplings, $d_γ$, by searching for a single high-energy photon at LLP detectors. Four typical scenarios are considered in this paper, scenario A, B with $d_{W}=0$ or $d_{Z}=0$, and scenario C, D with $d_{W,Z}\gg d_γ$. We show the sensitivity on $d_γ$, can be fairly different depending on the relations between the $d_{W,Z}$ and $d_γ$. And the LLP detectors can potentially extend the sensitivity on dipole couplings during the High-luminosity runs of the LHC in certain scenarios.

hep-ph↗

arXiv2023

Reinforcement Learning for Robot Navigation with Adaptive Forward Simulation Time (AFST) in a Semi-Markov Model

Deep reinforcement learning (DRL) algorithms have proven effective in robot navigation, especially in unknown environments, by directly mapping perception inputs into robot control commands. However, most existing methods ignore the local minimum problem in navigation and thereby cannot handle complex unknown environments. In this paper, we propose the first DRL-based navigation method modeled by a semi-Markov decision process (SMDP) with continuous action space, named Adaptive Forward Simulation Time (AFST), to overcome this problem. Specifically, we reduce the dimensions of the action space and improve the distributed proximal policy optimization (DPPO) algorithm for the specified SMDP problem by modifying its GAE to better estimate the policy gradient in SMDPs. Experiments in various unknown environments demonstrate the effectiveness of AFST.

cs.RO↗

arXiv2023

Mu$^{2}$SLAM: Multitask, Multilingual Speech and Language Models

We present Mu$^{2}$SLAM, a multilingual sequence-to-sequence model pre-trained jointly on unlabeled speech, unlabeled text and supervised data spanning Automatic Speech Recognition (ASR), Automatic Speech Translation (AST) and Machine Translation (MT), in over 100 languages. By leveraging a quantized representation of speech as a target, Mu$^{2}$SLAM trains the speech-text models with a sequence-to-sequence masked denoising objective similar to T5 on the decoder and a masked language modeling (MLM) objective on the encoder, for both unlabeled speech and text, while utilizing the supervised tasks to improve cross-lingual and cross-modal representation alignment within the model. On CoVoST AST, Mu$^{2}$SLAM establishes a new state-of-the-art for models trained on public datasets, improving on xx-en translation over the previous best by 1.9 BLEU points and on en-xx translation by 1.1 BLEU points. On Voxpopuli ASR, our model matches the performance of an mSLAM model fine-tuned with an RNN-T decoder, despite using a relatively weaker sequence-to-sequence architecture. On text understanding tasks, our model improves by more than 6\% over mSLAM on XNLI, getting closer to the performance of mT5 models of comparable capacity on XNLI and TydiQA, paving the way towards a single model for all speech and text understanding tasks.

cs.CL↗

arXiv2023

Capturing Conversion Rate Fluctuation during Sales Promotions: A Novel Historical Data Reuse Approach

Conversion rate (CVR) prediction is one of the core components in online recommender systems, and various approaches have been proposed to obtain accurate and well-calibrated CVR estimation. However, we observe that a well-trained CVR prediction model often performs sub-optimally during sales promotions. This can be largely ascribed to the problem of the data distribution shift, in which the conventional methods no longer work. To this end, we seek to develop alternative modeling techniques for CVR prediction. Observing similar purchase patterns across different promotions, we propose reusing the historical promotion data to capture the promotional conversion patterns. Herein, we propose a novel \textbf{H}istorical \textbf{D}ata \textbf{R}euse (\textbf{HDR}) approach that first retrieves historically similar promotion data and then fine-tunes the CVR prediction model with the acquired data for better adaptation to the promotion mode. HDR consists of three components: an automated data retrieval module that seeks similar data from historical promotions, a distribution shift correction module that re-weights the retrieved data for better aligning with the target promotion, and a TransBlock module that quickly fine-tunes the original model for better adaptation to the promotion mode. Experiments conducted with real-world data demonstrate the effectiveness of HDR, as it improves both ranking and calibration metrics to a large extent. HDR has also been deployed on the display advertising system in Alibaba, bringing a lift of $9\%$ RPM and $16\%$ CVR during Double 11 Sales in 2022.

cs.IR↗

arXiv2023

Cell-inspired, massive electromodulation of interfacial energy dissipation

Transient electric fields across cell bilayer membranes can lead to electroporation, as well as to cell fusion, and have been extensively studied. We find that transmembrane electric fields similar to those in cells can lead to a massive, reversible modulation--by up to 200-fold--of the interfacial energy dissipation between surfaces sliding across the lipid bilayer membranes. Atomistic simulations reveal that this arises from (fully reversible) electroporation of the interfacially-confined bilayers, and formation of bilayer bridges analogous to stalks preceding intermembrane fusion. These cell-membrane-mimicking effects topologically-force the slip to partially-revert from the low-dissipation, hydrated lipid-headgroups plane to the intra-bilayer, high-dissipation acyl tail interface. Our results demonstrate that lipid bilayers under transmembrane electric fields can have striking materials-modification properties, and shed new light on membrane hemifusion.

cond-mat.mtrl-sci↗

arXiv2023

FlowFace++: Explicit Semantic Flow-supervised End-to-End Face Swapping

This work proposes a novel face-swapping framework FlowFace++, utilizing explicit semantic flow supervision and end-to-end architecture to facilitate shape-aware face-swapping. Specifically, our work pretrains a facial shape discriminator to supervise the face swapping network. The discriminator is shape-aware and relies on a semantic flow-guided operation to explicitly calculate the shape discrepancies between the target and source faces, thus optimizing the face swapping network to generate highly realistic results. The face swapping network is a stack of a pre-trained face-masked autoencoder (MAE), a cross-attention fusion module, and a convolutional decoder. The MAE provides a fine-grained facial image representation space, which is unified for the target and source faces and thus facilitates final realistic results. The cross-attention fusion module carries out the source-to-target face swapping in a fine-grained latent space while preserving other attributes of the target image (e.g. expression, head pose, hair, background, illumination, etc). Lastly, the convolutional decoder further synthesizes the swapping results according to the face-swapping latent embedding from the cross-attention fusion module. Extensive quantitative and qualitative experiments on in-the-wild faces demonstrate that our FlowFace++ outperforms the state-of-the-art significantly, particularly while the source face is obstructed by uneven lighting or angle offset.

cs.CV↗

arXiv2023

Weakly Supervised Multi-Label Classification of Full-Text Scientific Papers

Instead of relying on human-annotated training samples to build a classifier, weakly supervised scientific paper classification aims to classify papers only using category descriptions (e.g., category names, category-indicative keywords). Existing studies on weakly supervised paper classification are less concerned with two challenges: (1) Papers should be classified into not only coarse-grained research topics but also fine-grained themes, and potentially into multiple themes, given a large and fine-grained label space; and (2) full text should be utilized to complement the paper title and abstract for classification. Moreover, instead of viewing the entire paper as a long linear sequence, one should exploit the structural information such as citation links across papers and the hierarchy of sections and paragraphs in each paper. To tackle these challenges, in this study, we propose FUTEX, a framework that uses the cross-paper network structure and the in-paper hierarchy structure to classify full-text scientific papers under weak supervision. A network-aware contrastive fine-tuning module and a hierarchy-aware aggregation module are designed to leverage the two types of structural signals, respectively. Experiments on two benchmark datasets demonstrate that FUTEX significantly outperforms competitive baselines and is on par with fully supervised classifiers that use 1,000 to 60,000 ground-truth training samples.

cs.CL↗

arXiv2023

AudioPaLM: A Large Language Model That Can Speak and Listen

We introduce AudioPaLM, a large language model for speech understanding and generation. AudioPaLM fuses text-based and speech-based language models, PaLM-2 [Anil et al., 2023] and AudioLM [Borsos et al., 2022], into a unified multimodal architecture that can process and generate text and speech with applications including speech recognition and speech-to-speech translation. AudioPaLM inherits the capability to preserve paralinguistic information such as speaker identity and intonation from AudioLM and the linguistic knowledge present only in text large language models such as PaLM-2. We demonstrate that initializing AudioPaLM with the weights of a text-only large language model improves speech processing, successfully leveraging the larger quantity of text training data used in pretraining to assist with the speech tasks. The resulting model significantly outperforms existing systems for speech translation tasks and has the ability to perform zero-shot speech-to-text translation for many languages for which input/target language combinations were not seen in training. AudioPaLM also demonstrates features of audio language models, such as transferring a voice across languages based on a short spoken prompt. We release examples of our method at https://google-research.github.io/seanet/audiopalm/examples

cs.CL↗