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Alfv\'en waves, considered one of the primary candidates for heating and accelerating the fast solar wind, are ubiquitous in spacecraft observations, yet their origin remains elusive. In this study, we analyze data from the first 19 encounters of the Parker Solar Probe (PSP) and report dominance of 2-minute oscillations near the Alfv\'en surface. The frequency-rectified trace magnetic power spectral density (PSD) of these oscillations indicates that the fluctuation energy is concentrated around 2 minutes for the ``youngest'' solar wind. Further analysis using wavelet spectrograms reveals that these oscillations primarily consist of outward-propagating, spherically polarized Alfv\'en wave bursts. Through Doppler analysis, we show that the wave frequency observed in the spacecraft frame can be mapped directly to the launch frequency at the base of the corona, where previous studies have identified a distinct peak around 2 minutes ($\sim 8$ mHz) in the spectrum of swaying motions of coronal structures observed by SDO AIA. These findings strongly suggest that the Alfv\'en waves originate from the solar atmosphere. Furthermore, statistical analysis of the PSD deformation beyond the Alfv\'en surface supports the idea of dynamic formation of the otherwise absent $1/f$ range in the solar wind turbulence spectrum.

Dark photon dark matter emerges as a compelling candidate for ultralight bosonic dark matter, detectable through resonant conversion into photons within a plasma environment. This study employs in-situ measurements from the Parker Solar Probe (PSP), the first spacecraft to venture into the solar corona, to probe for DPDM signatures. The PSP in-situ measurements go beyond the traditional radio window, spanning frequencies between about 10 kHz and 20 MHz, a challenging range inaccessible to Earth-based radio astronomy. Additionally, the proximity of PSP to the resonant conversion location enhances the signal flux, providing a distinct advantage over ground-based observations. As a result, the PSP data establishes the most stringent constraints on the kinetic mixing parameter $\epsilon$ for DPDM frequencies between 70 kHz and 20 MHz, with values of $\epsilon \lesssim 10^{-14}-10^{-13}$. Investigating the data from STEREO satellites resulted in weaker constraints compared to those obtained from PSP. By utilizing state-of-the-art solar observations from space, we have surpassed the cosmic microwave background limits established in the early universe., Comment: 13 pages, 6 figures

The rapid development of large machine learning (ML) models requires a massive amount of training data, resulting in booming demands of data sharing and trading through data markets. Traditional centralized data markets suffer from low level of security, and emerging decentralized platforms are faced with efficiency and privacy challenges. In this paper, we propose OmniLytics+, the first decentralized data market, built upon blockchain and smart contract technologies, to simultaneously achieve 1) data (resp., model) privacy for the data (resp. model) owner; 2) robustness against malicious data owners; 3) efficient data validation and aggregation. Specifically, adopting the zero-knowledge (ZK) rollup paradigm, OmniLytics+ proposes to secret share encrypted local gradients, computed from the encrypted global model, with a set of untrusted off-chain servers, who collaboratively generate a ZK proof on the validity of the gradient. In this way, the storage and processing overheads are securely offloaded from blockchain verifiers, significantly improving the privacy, efficiency, and affordability over existing rollup solutions. We implement the proposed OmniLytics+ data market as an Ethereum smart contract [41]. Extensive experiments demonstrate the effectiveness of OmniLytics+ in training large ML models in presence of malicious data owner, and the substantial advantages of OmniLytics+ in gas cost and execution time over baselines.

Improving the efficiency of current neural networks and modeling them in biological neural systems have become popular research directions in recent years. Pulse-coupled neural network (PCNN) is a well applicated model for imitating the computation characteristics of the human brain in computer vision and neural network fields. However, differences between the PCNN and biological neural systems remain: limited neural connection, high computational cost, and lack of stochastic property. In this study, random-coupled neural network (RCNN) is proposed. It overcomes these difficulties in PCNN's neuromorphic computing via a random inactivation process. This process randomly closes some neural connections in the RCNN model, realized by the random inactivation weight matrix of link input. This releases the computational burden of PCNN, making it affordable to achieve vast neural connections. Furthermore, the image and video processing mechanisms of RCNN are researched. It encodes constant stimuli as periodic spike trains and periodic stimuli as chaotic spike trains, the same as biological neural information encoding characteristics. Finally, the RCNN is applicated to image segmentation, fusion, and pulse shape discrimination subtasks. It is demonstrated to be robust, efficient, and highly anti-noised, with outstanding performance in all applications mentioned above.

We report on the first direct in situ measurements of a fast coronal mass ejection (CME) and shock in the corona, which occurred on 2022 September 5. In situ measurements from the Parker Solar Probe (PSP) spacecraft near perihelion suggest two shocks with the second one decayed, which is consistent with more than one eruptions in coronagraph images. Despite a flank crossing, the measurements indicate unique features of the young ejecta: a plasma much hotter than the ambient medium suggestive of a hot solar source, and a large plasma $\beta$ implying a highly non-force-free state and the importance of thermal pressure gradient for CME acceleration and expansion. Reconstruction of the global coronal magnetic fields shows a long-duration change in the heliospheric current sheet (HCS), and the observed field polarity reversals agree with a more warped HCS configuration. Reconnection signatures are observed inside an HCS crossing as deep as the sonic critical point. As the reconnection occurs in the sub-Alfv\'enic wind, the reconnected flux sunward of the reconnection site can close back to the Sun, which helps balance magnetic flux in the heliosphere. The nature of the sub-Alfv\'enic wind after the HCS crossing as a low Mach-number boundary layer (LMBL) leads to in situ measurements of the near subsonic plasma at a surprisingly large distance. Specifically, an LMBL may provide favorable conditions for the crossings of the sonic critical point in addition to the Alfv\'en surface., Comment: Accepted for publication in the The Astrophysical Journal

The CGI (CGI) has the potential of low cost, low dose, and high resolution, which is very attractive for the development of radiation imaging field. However, many sub-coding plates must be used in the modulation process, which greatly affects the development of CGI technology. In order to reduce the coding plates, we refer to the rotation method of computed tomography (CT), then propose a novel CGI method based on rotational modulation method of a single-column striped coding plate. This method utilizes the spatial variation of a single sub-coding plate (rotation) to realize multiple modulation of the ray field and improves the utilization rate of a single sub-coding plate. However, for this rotation scheme of CGI, the traditional binary modulation matrix is no longer applicable. To obtain the system matrix of the rotated striped coding plate, an area model based on beam boundaries is established. Subsequently, numerical and Monte Carlo simulations were conducted. The results reveal that our scheme enables high-quality imaging of N*N resolution objects using only N sub-coding plates, under both full-sampling and under-sampling scenarios. Moreover, our scheme demonstrates superiority over the Hadamard scheme in both imaging quality and the number of required sub-coding plates, whether in scenarios of full-sampling or under-sampling. Finally, an {\alpha} ray imaging platform was established to further demonstrate the feasibility of the rotational modulation method. By employing our scheme, a mere 8 sub-coding plates were employed to achieve CGI of the radiation source intensity distribution, achieving a resolution of 8*8. Therefore, the novel ray CGI based on rotational modulation method can achieve high-quality imaging effect with fewer sub-coding plates, which has important practical value and research significance for promoting single-pixel radiation imaging technology.

Parker Solar Probe (PSP) observes unexpectedly prevalent switchbacks, which are rapid magnetic field reversals that last from seconds to hours, in the inner heliosphere, posing new challenges to understanding their nature, origin, and evolution. In this work, we investigate the thermal states, electron pitch angle distributions, and pressure signatures of both inside and outside switchbacks, separating a switchback into spike, transition region (TR), and quiet period (QP). Based on our analysis, we find that the proton temperature anisotropies in TRs seem to show an intermediate state between spike and QP plasmas. The proton temperatures are more enhanced in spike than in TR and QP, but the alpha temperatures and alpha-to-proton temperature ratios show the opposite trends, implying that the preferential heating mechanisms of protons and alphas are competing in different regions of switchbacks. Moreover, our results suggest that the electron integrated intensities are almost the same across the switchbacks but the electron pitch angle distributions are more isotropic inside than outside switchbacks, implying switchbacks are intact structures but strong scattering of electrons happens inside switchbacks. In addition, the examination of pressures reveals that the total pressures are comparable through an individual switchback, confirming switchbacks are pressure-balanced structures. These characteristics could further our understanding of ion heating, electron scattering, and the structure of switchbacks., Comment: published in ApJ

The publicly accessible dataset includes neutron and gamma-ray pulse signals for conducting pulse shape discrimination experiments. Several traditional and recently proposed pulse shape discrimination algorithms are utilized to evaluate the performance of pulse shape discrimination under raw pulse signals and noise-enhanced datasets. These algorithms comprise zero-crossing (ZC), charge comparison (CC), falling edge percentage slope (FEPS), frequency gradient analysis (FGA), pulse-coupled neural network (PCNN), ladder gradient (LG), and het-erogeneous quasi-continuous spiking cortical model (HQC-SCM). In addition to the pulse signals, this dataset includes the source code for all the aforementioned pulse shape discrimination methods. Moreover, the dataset provides the source code for schematic pulse shape discrimination performance evaluation and anti-noise performance evaluation. This feature enables researchers to evaluate the performance of these methods using standard procedures and assess their anti-noise ability under various noise conditions. In conclusion, this dataset offers a comprehensive set of resources for conducting pulse shape discrimination experiments and evaluating the performance of various pulse shape discrimination methods under different noise scenarios., Comment: 8 pages,10 figures

Spatiotemporal data mining plays an important role in air quality monitoring, crowd flow modeling, and climate forecasting. However, the originally collected spatiotemporal data in real-world scenarios is usually incomplete due to sensor failures or transmission loss. Spatiotemporal imputation aims to fill the missing values according to the observed values and the underlying spatiotemporal dependence of them. The previous dominant models impute missing values autoregressively and suffer from the problem of error accumulation. As emerging powerful generative models, the diffusion probabilistic models can be adopted to impute missing values conditioned by observations and avoid inferring missing values from inaccurate historical imputation. However, the construction and utilization of conditional information are inevitable challenges when applying diffusion models to spatiotemporal imputation. To address above issues, we propose a conditional diffusion framework for spatiotemporal imputation with enhanced prior modeling, named PriSTI. Our proposed framework provides a conditional feature extraction module first to extract the coarse yet effective spatiotemporal dependencies from conditional information as the global context prior. Then, a noise estimation module transforms random noise to realistic values, with the spatiotemporal attention weights calculated by the conditional feature, as well as the consideration of geographic relationships. PriSTI outperforms existing imputation methods in various missing patterns of different real-world spatiotemporal data, and effectively handles scenarios such as high missing rates and sensor failure. The implementation code is available at https://github.com/LMZZML/PriSTI., Comment: This paper has been accepted as a full paper at ICDE 2023

In general, slow solar wind from the streamer belt forms a high plasma beta equatorial plasma sheet around the heliospheric current sheet (HCS) crossing, namely the heliospheric plasma sheet (HPS). Current Parker Solar Probe (PSP) observations show that the HCS crossings near the Sun could be full or partial current sheet crossing (PCS), and they share some common features but also have different properties. In this work, using the PSP observations from encounters 4 to 10, we identify streamer belt solar wind from enhancements in plasma beta, and we further use electron pitch angle distributions to separate it into HPS solar wind that around the full HCS crossings and PCS solar wind that in the vicinity of PCS crossings. Based on our analysis, we find that the PCS solar wind has different characteristics as compared with HPS solar wind: a) PCS solar wind could be non-pressure-balanced structures rather than magnetic holes, and the total pressure enhancement mainly results from the less reduced magnetic pressure; b) some of the PCS solar wind are mirror unstable; c) PCS solar wind is dominated by very low helium abundance but varied alpha-proton differential speed. We suggest the PCS solar wind could originate from coronal loops deep inside the streamer belt, and it is pristine solar wind that still actively interacts with ambient solar wind, thus it is valuable for further investigations on the heating and acceleration of slow solar wind.

Switchbacks are rapid magnetic field reversals that last from seconds to hours. Current Parker Solar Probe (PSP) observations pose many open questions in regard to the nature of switchbacks. For example, are they stable as they propagate through the inner heliosphere, and how are they formed? In this work, we aim to investigate the structure and origin of switchbacks. In order to study the stability of switchbacks, we suppose the small-scale current sheets therein are generated by magnetic braiding, and they should work to stabilize the switchbacks. With more than one thousand switchbacks identified with PSP observations in seven encounters, we find many more current sheets inside than outside switchbacks, indicating that these microstructures should work to stabilize the S-shaped structures of switchbacks. Additionally, we study the helium variations to trace the switchbacks to their origins. We find both helium-rich and helium-poor populations in switchbacks, implying that the switchbacks could originate from both closed and open magnetic field regions in the Sun. Moreover, we observe that the alpha-proton differential speeds also show complex variations as compared to the local Alfv\'en speed. The joint distributions of both parameters show that low helium abundance together with low differential speed is the dominant state in switchbacks. The presence of small-scale current sheets in switchbacks along with the helium features are in line with the hypothesis that switchbacks could originate from the Sun via interchange reconnection process. However, other formation mechanisms are not excluded., Comment: accepted by ApJ

Revealing the properties of single spin defects in solids is essential for quantum applications based on solid-state systems. However, it is intractable to investigate the temperature-dependent properties of single defects, due to the low precision for single-defect measurements in contrast to defect ensembles. Here we report that the temperature dependence of the Hamiltonian parameters for single negatively charged nitrogen-vacancy (NV$^{-}$) centers in diamond is precisely measured, and the results find a reasonable agreement with first-principles calculations. Particularly, the hyperfine interactions with randomly distributed $^{13}$C nuclear spins are clearly observed to vary with temperature, and the relevant coefficients are measured with Hz-level precision. The temperature-dependent behaviors are attributed to both thermal expansion and lattice vibrations by first-principles calculations. Our results pave the way for taking nuclear spins as more stable thermometers at nanoscale. The methods developed here for high-precision measurements and first-principles calculations can be further extended to other solid-state spin defects.

Generating semantic segmentation datasets has consistently been laborious and time-consuming, particularly in the context of large models or specialized domains(i.e. Medical Imaging or Remote Sensing). Specifically, large models necessitate a substantial volume of data, while datasets in professional domains frequently require the involvement of domain experts. Both scenarios are susceptible to inaccurate data labeling, which can significantly affect the ultimate performance of the trained model. This paper proposes a simple and effective label pixel-level completion method, \textbf{Label Mask AutoEncoder} (L-MAE), which fully uses the existing information in the label to generate the complete label. The proposed model are the first to apply the Mask Auto-Encoder to downstream tasks. In detail, L-MAE adopts the fusion strategy that stacks the label and the corresponding image, namely fuse map. Moreover, since some of the image information is lost when masking the fuse map, direct reconstruction may lead to poor performance. We proposed Image Patch Supplement algorithm to supplement the missing information during the mask-reconstruct process, and empirically found that an average of 4.1\% mIoU can be improved. We conducted a experiment to evaluate the efficacy of L-MAE to complete the dataset. We employed a degraded Pascal VOC dataset and the degraded dataset enhanced by L-MAE to train an identical conventional semantic segmentation model for the initial set of experiments. The results of these experiments demonstrate a performance enhancement of 13.5\% in the model trained with the L-MAE-enhanced dataset compared to the unenhanced dataset.

We present three-dimensional magnetic power spectra in wavevector space to investigate anisotropy and scalings of sub-Alfv\'enic solar wind turbulence at magnetohydrodynamic (MHD) scale using the Magnetospheric Multiscale spacecraft. The magnetic power distributions are organized in a new coordinate determined by wavevectors (k) and background magnetic field ($b_0$) in Fourier space. This study utilizes two approaches to determine wavevectors: singular value decomposition method and timing analysis. The combination of the two methods allows an examination of magnetic field properties in terms of mode compositions without any spatiotemporal hypothesis. Observations show that fluctuations ($\delta B_{\perp1}$) in the direction perpendicular to k and $b_0$ prominently cascade perpendicular to $b_0$, and such anisotropy increases with wavenumber. The reduced power spectra of $\delta B_{\perp1}$ follow Goldreich-Sridhar scalings: $P(k_\perp)\sim k_\perp^{-5/3}$ and $P(k_{||}) \sim k_{||}^{-2}$. In contrast, fluctuations within $kb_0$ plane show isotropic behaviors: perpendicular power distributions are approximately the same as parallel distributions. The reduced power spectra of fluctuations within $kb_0$ plane follow the scalings: $P(k_\perp)\sim k_\perp^{-3/2}$ and $P(k_{||})\sim k_{||}^{-3/2}$. Comparing frequency-wavevector spectra with theoretical dispersion relations of MHD modes, we find that $\delta B_{\perp1}$ are probably associated with Alfven modes. Moreover, for the Alfv\'enic component, the ratio of cascading time to the wave period is found to be a factor of a few, consistent with critical balance in the strong turbulence regime. The magnetic field fluctuations within $kb_0$ plane more likely originate from fast modes based on isotropic behaviors., Comment: 24 pages; 11 Figures; ApJ accepted

Solar wind parameters play a dominant role in reconnection rate, which controls the solar wind-magnetosphere coupling efficiency at Earth's magnetopause. Besides, low-energy ions from the ionosphere, frequently detected on the magnetospheric side of the magnetopause, also affect magnetic reconnection. However, the specific role of low-energy ions in reconnection is still an open question under active discussion. In the present work, we report in situ observations of a multiscale, multi-type magnetopause reconnection in the presence of low-energy ions using NASA's Magnetospheric Multiscale data on 11 September 2015. This study divides ions into cold and hot populations. The observations can be interpreted as a secondary reconnection dominated by electrons and cold ions located at the edge of an ion-scale reconnection. This analysis demonstrates a dominant role of cold ions in the secondary reconnection without hot ions' response. Cold ions and electrons are accelerated and heated by the secondary process. The case study provides observational evidence for the simultaneous operation of antiparallel and component reconnection. Our results imply that the pre-accelerated and heated cold ions and electrons in the secondary reconnection may participate in the primary ion-scale reconnection affecting the solar wind-magnetopause coupling and the complicated magnetic field topology affect the reconnection rate.

We report analysis of sub-Alfv\'enic magnetohydrodynamic (MHD) perturbations in the low-\b{eta} radial-field solar wind using the Parker Solar Probe spacecraft data from 31 October to 12 November 2018. We calculate wave vectors using the singular value decomposition method and separate the MHD perturbations into three types of linear eigenmodes (Alfv\'en, fast, and slow modes) to explore the properties of the sub-Alfv\'enic perturbations and the role of compressible perturbations in solar wind heating. The MHD perturbations there show a high degree of Alfv\'enicity in the radial-field solar wind, with the energy fraction of Alfv\'en modes dominating (~45%-83%) over those of fast modes (~16%-43%) and slow modes (~1%-19%). We present a detailed analysis of a representative event on 10 November 2018. Observations show that fast modes dominate magnetic compressibility, whereas slow modes dominate density compressibility. The energy damping rate of compressible modes is comparable to the heating rate, suggesting the collisionless damping of compressible modes could be significant for solar wind heating. These results are valuable for further studies of the imbalanced turbulence near the Sun and possible heating effects of compressible modes at MHD scales in low-\b{eta} plasma., Comment: 17 pages, 8 figures, accepted for publication in ApJ

As fundamental parameters of the Sun, the Alfv\'en radius and angular momentum loss determine how the solar wind changes from sub-Alfv\'enic to super-Alfv\'enic and how the Sun spins down. We present an approach to determining the solar wind angular momentum flux based on observations from Parker Solar Probe (PSP). A flux of about $0.15\times10^{30}$ dyn cm sr$^{-1}$ near the ecliptic plane and 0.7:1 partition of that flux between the particles and magnetic field are obtained by averaging data from the first four encounters within 0.3 au from the Sun. The angular momentum flux and its particle component decrease with the solar wind speed, while the flux in the field is remarkably constant. A speed dependence in the Alfv\'en radius is also observed, which suggests a "rugged" Alfv\'en surface around the Sun. Substantial diving below the Alfv\'en surface seems plausible only for relatively slow solar wind given the orbital design of PSP. Uncertainties are evaluated based on the acceleration profiles of the same solar wind streams observed at PSP and a radially aligned spacecraft near 1 au. We illustrate that the "angular momentum paradox" raised by R\'eville et al. can be removed by taking into account the contribution of the alpha particles. The large proton transverse velocity observed by PSP is perhaps inherent in the solar wind acceleration process, where an opposite transverse velocity is produced for the alphas with the angular momentum conserved. Preliminary analysis of some recovered alpha parameters tends to agree with the results., Comment: Accepted for publication in The Astrophysical Journal Letters

Microinstabilities and waves excited at moderate-Mach-number perpendicular shocks in the near-Sun solar wind are investigated by full particle-in-cell (PIC) simulations. By analyzing the dispersion relation of fluctuating field components directly issued from the shock simulation, we obtain key findings concerning wave excitations at the shock front: (1) at the leading edge of the foot, two types of electrostatic (ES) waves are observed. The relative drift of the reflected ions versus the electrons triggers an electron cyclotron drift instability (ECDI) which excites the first ES wave. Because the bulk velocity of gyro-reflected ions shifts to the direction of the shock front, the resulting ES wave propagates oblique to the shock normal. Immediately, a fraction of incident electrons are accelerated by this ES wave and a ring-like velocity distribution is generated. They can couple with the hot Maxwellian core and excite the second ES wave around the upper hybrid frequency. (2) from the middle of the foot all the way to the ramp, electrons can couple with both incident and reflected ions. ES waves excited by ECDI in different directions propagate across each other. Electromagnetic (EM) waves (X mode) emitted toward upstream are observed in both regions. They are probably induced by a small fraction of relativistic electrons. Results shed new insight on the mechanism for the occurrence of ES wave excitations and possible EM wave emissions at young CME-driven shocks in the near-Sun solar wind.

We present Luce, the first life-long predictive model for automated property valuation. Luce addresses two critical issues of property valuation: the lack of recent sold prices and the sparsity of house data. It is designed to operate on a limited volume of recent house transaction data. As a departure from prior work, Luce organizes the house data in a heterogeneous information network (HIN) where graph nodes are house entities and attributes that are important for house price valuation. We employ a Graph Convolutional Network (GCN) to extract the spatial information from the HIN for house-related data like geographical locations, and then use a Long Short Term Memory (LSTM) network to model the temporal dependencies for house transaction data over time. Unlike prior work, Luce can make effective use of the limited house transactions data in the past few months to update valuation information for all house entities within the HIN. By providing a complete and up-to-date house valuation dataset, Luce thus massively simplifies the downstream valuation task for the targeting properties. We demonstrate the benefit of Luce by applying it to large, real-life datasets obtained from the Toronto real estate market. Extensive experimental results show that Luce not only significantly outperforms prior property valuation methods but also often reaches and sometimes exceeds the valuation accuracy given by independent experts when using the actual realization price as the ground truth., Comment: 14 pages, journal

We investigate the kinetic properties of a typical fast-mode shock inside an interplanetary coronal mass ejection (ICME) observed on 1998 August 6 at 1 AU, including particle distributions and wave analysis with the in situ measurements from Wind. Key results are obtained concerning the shock and the shock-ICME interaction at kinetic scales: (1) gyrating ions, which may provide energy dissipation at the shock in addition to wave-particle interactions, are observed around the shock ramp; (2) despite the enhanced proton temperature anisotropy of the shocked plasma, the low plasma beta inside the ICME constrains the shocked plasma under the thresholds of the ion cyclotron and mirror-mode instabilities; (3) whistler heat flux instabilities, which can pitch--angle scatter halo electrons through a cyclotron resonance, are observed around the shock, and can explain the disappearance of bidirectional electrons inside the ICME together with normal betatron acceleration; (4) whistler waves near the shock are likely associated with the whistler heat flux instabilities excited at the shock ramp, which is consistent with the result that the waves may originate from the shock ramp; (5) the whistlers share a similar characteristic with the shocklet whistlers observed by Wilson et al, providing possible evidence that the shock is decaying because of the strong magnetic field inside the ICME., Comment: Published in ApJL

There is a key research issue to accurately select out neutron signals and discriminate gamma signals from a mixed radiation field in the neutron detection. This paper proposes a fractal spectrum discrimination approach by means of different spectrum characteristics of neutron and gamma. Figure of merit and average discriminant error ratio are adopted together to evaluate the discriminant effects. Different neutron and gamma signals with various noises and pulse pile-ups are simulated according to real data in the literature. The proposed approach is compared with the digital charge integration and pulse gradient methods. It is found that the fractal approach exhibits the best discriminant performance among three methods. The fractal spectrum approach is not sensitive to the high frequency noises and pulse pile-ups. It means that the proposed approach takes the advantages of anti-noises and high discriminant ability, and can be used to better discriminate neutron and gamma in neutron detection., Comment: 10 pages, 8 figures, 6 tables in Chinese Physics C 2016