arXiv subjects

Yao Chen

Publications and source records attributed to Yao Chen.

At least 127 records · Page 7Linked to original sources

arXiv2022

Nuclear spin self compensation system for moving MEG sensing with optical pumped atomic spin co-magnetometer

Recording the moving MEGs of a person in which a person's head could move freely as we record the brain's magnetic field is a hot topic in recent years. Traditionally, atomic magnetometers are utilized for moving MEGs recording and a large compensation coil system is utilized for background magnetic field compensation. Here we described a new potential candidate: an optically pumped atomic co-magnetometer(OPACM) for moving MEGs recording. In the OPACM, hyper-polarized nuclear spins could produce a magnetic field which will shield the background fluctuation low frequency magnetic field noise while the the fast changing MEGs signal could be recorded. The nuclear spins look like an automatic magnetic field shields and dynamically compensate the fluctuated background magnetic field noise. In this article, the magnetic field compensation is studied theoretically and we find that the compensation is closely related to several parameters such as the electron spin magnetic field, the nuclear spin magnetic field and the holding magnetic field. Based on the model, the magnetic field compensation could be optimized. We also experimentally studied the magnetic field compensation and the responses of the OPACM to different frequencies of magnetic field are measured. We show that the OPACM owns a clear suppression of low frequency magnetic field under 1Hz and response to magnetic field's frequencies around the band of the MEGs. Magnetic field sensitivity of $3fT/Hz^{1/2}$ has been achieved. Finally, we do a simulation for the OPACM as it is utilized for moving MEGs recording. For comparison, the traditional compensation system for moving MEGs recording is based on a coil which is around 2m in dimension while our compensation system is only 2mm in dimension. Moreover, our compensation system could work in situ and will not affect each other.

physics.app-ph↗

arXiv2022

Random diffusivity processes in an external force field

Brownian yet non-Gaussian processes have recently been observed in numerous biological systems and the corresponding theories have been built based on random diffusivity models. Considering the particularity of random diffusivity, this paper studies the effect of an external force acting on two kinds of random diffusivity models whose difference is embodied in whether the fluctuation-dissipation theorem is valid. Based on the two random diffusivity models, we derive the Fokker-Planck equations with an arbitrary external force, and analyse various observables in the case with a constant force, including the Einstein relation, the moments, the kurtosis, and the asymptotic behaviors of the probability density function of particle's displacement at different time scales. Both the theoretical results and numerical simulations of these observables show significant difference between the two kinds of random diffusivity models, which implies the important role of the fluctuation-dissipation theorem in random diffusivity systems.

cond-mat.stat-mech↗

arXiv2022

Birth places of extreme ultraviolet waves driven by impingement of solar jets upon coronal loops

Solar extreme ultraviolet (EUV) waves are large-scale propagating disturbances in the corona. It is generally believed that the vital key for the formation of EUV waves is the rapid expansion of the loops that overlie erupting cores in solar eruptions, such as coronal mass ejections (CMEs) and solar jets. However, the details of the interaction between the erupting cores and overlying loops are not clear, because that the overlying loops are always instantly opened after the energetic eruptions. Here, we present three typical jet-driven EUV waves without CME to study the interaction between the jets and the overlying loops that remained closed during the events. All three jets emanated from magnetic flux cancelation sites in source regions. Interestingly, after the interactions between jets and overlying loops, three EUV waves respectively formed ahead of the top, the near end (close to the jet source), and the far (another) end of the overlying loops. According to the magnetic field distribution of the loops extrapolated from Potential Field Source Surface method, it is confirmed that the birth places of three jet-driven EUV waves were around the weakest magnetic field strength part of the overlying loops. We suggest that the jet-driven EUV waves preferentially occur at the weakest part of the overlying loops, and the location can be subject to the magnetic field intensity around the ends of the loops.

astro-ph.SR↗

arXiv2022

Twin extreme ultraviolet waves in the solar corona

Solar extreme ultraviolet (EUV) waves are spectacular propagating disturbances with EUV enhancements in annular shapes in the solar corona. These EUV waves carry critical information about the coronal magnetised plasma that can shed light on the elusive physical parameters (e.g. the magnetic field strength) by global solar coronal magneto-seismology. EUV waves are closely associated with a wide range of solar atmospheric eruptions, from violent flares and coronal mass ejections (CMEs) to less energetic plasma jets or mini-filament eruptions. However, the physical nature and driving mechanism of EUV waves is still controversial. Here, we report the unique discovery of twin EUV waves (TEWs) that were formed in a single eruption with observations from two different perspectives. In all earlier studies, a single eruption was associated at most with a single EUV wave. The newly found TEWs urge to re-visit our theoretical understanding about the underlying formation mechanism(s) of coronal EUV waves. Two distinct scenarios of TEWs were found. In the first scenario, the two waves were separately associated with a filament eruption and a precursor jet, while in another scenario the two waves were successively associated with a filament eruption. Hence, we label these distinguished scenarios as "fraternal TEWs" and "identical TEWs", respectively. Further, we also suggest that impulsive lateral expansions of two distinct groups of coronal loops are critical to the formation of TEWs in a single eruption.

astro-ph.SR↗

arXiv2022

ReGraph: Scaling Graph Processing on HBM-enabled FPGAs with Heterogeneous Pipelines

The use of FPGAs for efficient graph processing has attracted significant interest. Recent memory subsystem upgrades including the introduction of HBM in FPGAs promise to further alleviate memory bottlenecks. However, modern multi-channel HBM requires much more processing pipelines to fully utilize its bandwidth potential. Existing designs do not scale well, resulting in underutilization of the HBM facilities even when all other resources are fully consumed. In this paper, we re-examined the graph processing workloads and found much diversity in processing. We also found that the diverse workloads can be easily classified into two types, namely dense and sparse partitions. This motivates us to propose a resource-efficient heterogeneous pipeline architecture. Our heterogeneous architecture comprises of two types of pipelines: Little pipelines to process dense partitions with good locality and Big pipelines to process sparse partitions with the extremely poor locality. Unlike traditional monolithic pipeline designs, the heterogeneous pipelines are tailored for more specific memory access patterns, and hence are more lightweight, allowing the architecture to scale up to more effectively with limited resources. In addition, we propose a model-guided task scheduling method that schedules partitions to the right pipeline types, generates the most efficient pipeline combination and balances workloads. Furthermore, we develop an automated open-source framework, called ReGraph, which automates the entire development process. ReGraph outperforms state-of-the-art FPGA accelerators by up to 5.9 times in terms of performance and 12times in terms of resource efficiency.

cs.AR↗

arXiv2022

Machine learning-enabled high-entropy alloy discovery

High-entropy alloys are solid solutions of multiple principal elements, capable of reaching composition and feature regimes inaccessible for dilute materials. Discovering those with valuable properties, however, relies on serendipity, as thermodynamic alloy design rules alone often fail in high-dimensional composition spaces. Here, we propose an active-learning strategy to accelerate the design of novel high-entropy Invar alloys in a practically infinite compositional space, based on very sparse data. Our approach works as a closed-loop, integrating machine learning with density-functional theory, thermodynamic calculations, and experiments. After processing and characterizing 17 new alloys (out of millions of possible compositions), we identified 2 high-entropy Invar alloys with extremely low thermal expansion coefficients around 2*10-6 K-1 at 300 K. Our study thus opens a new pathway for the fast and automated discovery of high-entropy alloys with optimal thermal, magnetic and electrical properties.

cond-mat.mtrl-sci↗

arXiv2022

Double-power-law feature of energetic particles accelerated at coronal shocks

Recent observations have shown that in many large solar energetic particle (SEP) events the event-integrated differential spectra resemble double power laws. We perform numerical modeling of particle acceleration at coronal shocks propagating through a streamer-like magnetic field by solving the Parker transport equation, including protons and heavier ions. We find that for all ion species the energy spectra integrated over the simulation domain can be described by a double power law, and the break energy depends on the ion charge-to-mass ratio as $E_B \sim (Q/A)^α$, with $α$ varying from 0.16 to 1.2 by considering different turbulence spectral indices. We suggest that the double power law distribution may emerge as a result of the superposition of energetic particles from different source regions where the acceleration rates differ significantly due to particle diffusion. The diffusion and mixing of energetic particles could also provide an explanation for the increase of Fe/O at high energies as observed in some SEP events. Although further mixing processes may occur, our simulations indicate that either power-law break or rollover can occur near the Sun and predict that the spectral forms vary significantly along the shock front, which may be examined by upcoming near-Sun SEP measurements from Parker Solar Probe and Solar Orbiter.

astro-ph.SR↗

arXiv2022

Plasma Emission Induced By Electron Beam in Weakly Magnetized Plasmas

Previous studies on the beam-driven plasma emission process were done mainly for unmagnetized plasmas. Here we present fully-kinetic electromagnetic particle-in-cell simulations to investigate such process in weakly-magnetized plasmas of the solar corona conditions. The primary mode excited is the beam-Langmuir (BL) mode via the classical bump-on-tail instability. Other modes include the whistler (W) mode excited by the electron cyclotron resonance instability, the generalized Langmuir (GL) waves that include a superluminal Z-mode component with smaller wave number $k$ and a thermal Langmuir component with larger $k$, and the fundamental (F) and harmonic (H) branches of plasma emission. Further simulations of different mass and temperature ratios of electrons and protons indicate that the GL mode and the two escaping modes (F and H) correlate positively with the BL mode in intensity, supporting that they are excited through nonlinear wave-wave coupling processes involving the BL mode. We suggest that the dominant process is the decay of the primary BL mode. This is consistent with the standard theory of plasma emission. Yet, the other possibility of the Z+W$\rightarrow$O--F coalescing process for the F emission cannot be ruled out completely.

physics.plasm-ph↗

arXiv2021

HiKonv: High Throughput Quantized Convolution With Novel Bit-wise Management and Computation

Quantization for Convolutional Neural Network (CNN) has shown significant progress with the intention of reducing the cost of computation and storage with low-bitwidth data inputs. There are, however, no systematic studies on how an existing full-bitwidth processing unit, such as CPUs and DSPs, can be better utilized to carry out significantly higher computation throughput for convolution under various quantized bitwidths. In this study, we propose HiKonv, a unified solution that maximizes the compute throughput of a given underlying processing unit to process low-bitwidth quantized data inputs through novel bit-wise parallel computation. We establish theoretical performance bounds using a full-bitwidth multiplier for highly parallelized low-bitwidth convolution, and demonstrate new breakthroughs for high-performance computing in this critical domain. For example, a single 32-bit processing unit can deliver 128 binarized convolution operations (multiplications and additions) under one CPU instruction, and a single 27x18 DSP core can deliver eight convolution operations with 4-bit inputs in one cycle. We demonstrate the effectiveness of HiKonv on CPU and FPGA for both convolutional layers or a complete DNN model. For a convolutional layer quantized to 4-bit, HiKonv achieves a 3.17x latency improvement over the baseline implementation using C++ on CPU. Compared to the DAC-SDC 2020 champion model for FPGA, HiKonv achieves a 2.37x throughput improvement and 2.61x DSP efficiency improvement, respectively.

cs.DC↗

arXiv2021

Comparison of Helium Abundance between ICMEs and Solar Wind near 1 AU

The Helium abundance, defined as $A_{He}=n_{He}/n_{H}\times 100$, is $\sim$8.5 in the photosphere and seldom exceeds 5 in fast solar wind. Previous statistics have demonstrated that $A_{He}$ in slow solar wind correlates tightly with sunspot number. However, less attention is paid to the solar cycle dependence of $A_{He}$ within interplanetary coronal mass ejections (ICMEs) and comparing the $A_{He}$ characteristics of ICMEs and solar wind. In this paper we conduct a statistical comparison of Helium abundance between ICMEs and solar wind near 1 AU with observations of \textit{Advanced Composition Explorer} from 1998 to 2019, and find that the ICME $A_{He}$ also exhibits the obvious solar cycle dependence. Meanwhile, we find that the $A_{He}$ is obviously higher within ICMEs compared to solar wind, and the means within 37\% and 12\% of ICMEs exceed 5 and 8.5, respectively. It is interesting to answer where and how the high Helium abundance originates. Our statistics demonstrate that 21\% (3\%) of ICME (slow wind) $A_{He}$ data points exceed 8.5 around solar maximum, which decreases dramatically near minimum, while no such high $A_{He}$ values appear in the fast wind throughout the whole solar cycle. This indicates that the high $A_{He}$ (e.g., $>$8.5) emanates from active regions as more ICMEs and slow wind originates from active regions around maximum, and supports that both active regions and quiet-Sun regions are the sources of slow wind. We suggest that the high $A_{He}$ from active regions could be explained by means of the magnetic loop confinement model and/or photoionization effect.

astro-ph.SR↗

arXiv2021

Quadrupolar interaction induced frequency shift of 131Xe nuclear spins on the surface of silicon

The combination of micro-machined technology with the Atomic Spin Gyroscope(ASG) devices could fabricated Chip Scale Atomic Spin Gyroscope(CASG). The core of the gyroscope is a micro-machined vapor cell which contains alkali metal and isotope enriched noble gases such as 129Xe and 131Xe. The quadrupolar frequency shift of 131Xe is key parameters which could affect the drift of the ASG and is related to the material of the cell in which they are contained. In micro machined technology, the typical utilized material is silicon. In this article, we studied the electric quadrupolar frequency shift of 131Xe atoms with the silicon wall of the micro-machined vapor cell. A cylinder micro-machined vapor cell is utilized in the experiment and a large part of the inner cell surface is composed of silicon material. We studied the temperature dependence of the 129Xe spin relaxation and 131Xe frequency shifts to evaluate the interaction of the nuclear spin with container wall and the alkali metal atoms. The results show that the average twisted angle of the 131Xe nuclear spins as they collide with the silicon wall is measured to be 29 *10^-6 rad. The desorption energy for the 131Xe nuclear spin to escape from the silicon surface is Esi = 0.009eV . This study could help to improve the bias stability of the CASG which is a key parameter for the gyroscope as well as may developes a method to study the surface property of various material.

physics.ins-det↗

arXiv2021

Compound eruptions of twin flux ropes in a solar active region

Compound eruptions represent that multiple closely spaced magnetic structures erupt consecutively within a short interval, and then lead to a single flare and a single CME. However, it is still subtle for the links between multiple eruptions and the associated single flare or/and single CME. In this Letter, we report the compound eruptions of twin close flux ropes (FR1 and FR2) within a few minutes that resulted in a flare with a single soft X-ray peak and a CME with two cores. The successive groups of expanding loops and double peaks of intensity flux in AIA cool wavelengths indicate two episodes of internal magnetic reconnections during the compound eruptions. Following the eruption of FR2, the erupting FR1 was accelerated, and then the expanding loops overlying FR2 were deflected. Moreover, the eruption of FR2 likely involved the external magnetic reconnection between the bottom of the overlying stretching field lines and the rebounding loops that were previously pushed by the eruption of FR1, which was evidenced by a pair of groups of newly-formed loops. All results suggest that the compound eruptions involved both internal and external magnetic reconnections, and two erupting structures of twin FRs interacted at the initial stage. We propose that two episodes of internal magnetic reconnections were likely united within a few minutes to form the continuous impulsive phase of the single peaked flare, and two separated cores of the CME was possibly because that the latter core was too slow to merge with the former one.

astro-ph.SR↗

arXiv2021

Harmonic maser emissions from electrons with loss-cone distribution in solar active regions

Electron cyclotron maser emission (ECME) is regarded as a plausible source for the coherent radio radiations from solar active regions (e.g., solar radio spikes). In this Letter, we present a 2D3V fully kinetic electromagnetic particle-in-cell (PIC) simulation to investigate the wave excitations and subsequent nonlinear processes induced by the energetic electrons in the loss-cone distribution. The ratio of the plasma frequency to the electron gyrofrequency $ω_{pe}/Ω_{ce}$ is set to 0.25, adequate for solar active region conditions. As a main result, we obtain strong emissions at the second-harmonic X mode (X2). While the fundamental X mode (X1) and the Z mode are amplified directly via the electron cyclotron maser instability, the X2 emissions can be produced by the nonlinear coalescence between two Z modes and between Z and X1 modes. This represents a novel generation mechanism for the harmonic emissions in plasmas with a low value of $ω_{pe}/Ω_{ce}$, which may resolve the escaping difficulty of explaining solar radio emissions with the ECME mechanism.

astro-ph.SR↗

arXiv2021

YOLO-ReT: Towards High Accuracy Real-time Object Detection on Edge GPUs

Performance of object detection models has been growing rapidly on two major fronts, model accuracy and efficiency. However, in order to map deep neural network (DNN) based object detection models to edge devices, one typically needs to compress such models significantly, thus compromising the model accuracy. In this paper, we propose a novel edge GPU friendly module for multi-scale feature interaction by exploiting missing combinatorial connections between various feature scales in existing state-of-the-art methods. Additionally, we propose a novel transfer learning backbone adoption inspired by the changing translational information flow across various tasks, designed to complement our feature interaction module and together improve both accuracy as well as execution speed on various edge GPU devices available in the market. For instance, YOLO-ReT with MobileNetV2x0.75 backbone runs real-time on Jetson Nano, and achieves 68.75 mAP on Pascal VOC and 34.91 mAP on COCO, beating its peers by 3.05 mAP and 0.91 mAP respectively, while executing faster by 3.05 FPS. Furthermore, introducing our multi-scale feature interaction module in YOLOv4-tiny and YOLOv4-tiny (3l) improves their performance to 41.5 and 48.1 mAP respectively on COCO, outperforming the original versions by 1.3 and 0.9 mAP.

cs.CV↗

arXiv2021

Novel anomalous diffusion phenomena of underdamped Langevin equation with random parameters

The diffusion behavior of particles moving in complex heterogeneous environment is a very topical issue. We characterize particle's trajectory via an underdamped Langevin system driven by a Gaussian white noise with a time dependent diffusivity of velocity, together with a random relaxation timescale $τ$ to parameterize the effect of complex medium. We mainly concern how the random parameter $τ$ influences the diffusion behavior and ergodic property of this Langevin system. Besides, the comparison between the fixed and random initial velocity $v_0$ is conducted to show the effect of different initial ensembles. The heavy-tailed distribution of $τ$ with finite mean is found to suppress the decay rate of the velocity correlation function and promote the diffusion behavior, playing a competition role to the time dependent diffusivity. More interestingly, a random $v_0$ with a specific distribution depending on random $τ$ also enhances the diffusion. Both the random parameters $τ$ and $v_0$ influence the dynamics of the Langevin system in an non-obvious way, which cannot be ignored even they has finite moments.

cond-mat.stat-mech↗

arXiv2021

Paramagnetic spin Hall magnetoresistance

Spin Hall magnetoresistance (SMR) refers to a resistance change in a metallic film reflecting the magnetization direction of a magnet attached to the film. The mechanism of this phenomenon is spin exchange between conduction-electron spins and magnetization at the interface. SMR has been used to read out information written in a small magnet and to detect magnetization dynamics, but it has been limited to magnets; magnetic ordered phases or instability of magnetic phase transition has been believed to be indispensable. Here, we report the observation of SMR in a paramagnetic insulator Gd$_{3}$Ga$_{5}$O$_{12}$ (GGG) without spontaneous magnetization combined with a Pt film. The paramagnetic SMR can be attributed to spin-transfer torque acting on localized spins in GGG. We determine the efficiencies of spin torque and spin-flip scattering at the Pt/GGG interface, and demonstrate these quantities can be tuned with external magnetic fields. The results clarify the mechanism of spin-transport at a metal/paramagnetic insulator interface, which gives new insight into the spintronic manipulation of spin states in paramagnetic systems.

cond-mat.mtrl-sci↗

arXiv2021

Free Lunch for Co-Saliency Detection: Context Adjustment

We unveil a long-standing problem in the prevailing co-saliency detection systems: there is indeed inconsistency between training and testing. Constructing a high-quality co-saliency detection dataset involves time-consuming and labor-intensive pixel-level labeling, which has forced most recent works to rely instead on semantic segmentation or saliency detection datasets for training. However, the lack of proper co-saliency and the absence of multiple foreground objects in these datasets can lead to spurious variations and inherent biases learned by models. To tackle this, we introduce the idea of counterfactual training through context adjustment and propose a "cost-free" group-cut-paste (GCP) procedure to leverage off-the-shelf images and synthesize new samples. Following GCP, we collect a novel dataset called Context Adjustment Training (CAT). CAT consists of 33,500 images, which is four times larger than the current co-saliency detection datasets. All samples are automatically annotated with high-quality mask annotations, object categories, and edge maps. Extensive experiments on recent benchmarks are conducted, show that CAT can improve various state-of-the-art models by a large margin (5% ~ 25%). We hope that the scale, diversity, and quality of our dataset can benefit researchers in this area and beyond. Our dataset will be publicly accessible through our project page.

cs.CV↗

arXiv2021

Ergodic property of random diffusivity system with trapping events

Brownian yet non-Gaussian phenomenon has recently been observed in many biological and active matter systems. The main idea of explaining this phenomenon is to introduce a random diffusivity for particles moving in inhomogeneous environment. This paper considers a Langevin system containing a random diffusivity and an $α$-stable subordinator with $α<1$. This model describes the particle's motion in complex media where both the long trapping events and random diffusivity exist. We derive the general expressions of ensemble- and time-averaged mean-squared displacements which only contain the values of the inverse subordinator and diffusivity. Further taking specific time-dependent diffusivity, we obtain the analytic expressions of ergodicity breaking parameter and probability density function of the time-averaged mean-squared displacement. The results imply the nonergodicity of the random diffusivity model for any kind of diffusivity, including the critical case where the model presenting normal diffusion.

cond-mat.stat-mech↗