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In this paper, we construct a static spherical symmetric Bardeen-Dirac Stars (BDSs) in the four-dimensional Anti-de Sitter (AdS) spacetime, which consists of the electromagnetic field and Dirac field coupled to gravity. We investigate the ADM mass, Noether charge and light rings of BDSs in AdS spacetime. In asymptotically Minkowski spacetime, the maximum frequency of BDSs is one. However, we observe that the maximum frequency of BDSs increases as the cosmological constant decreases in AdS spacetime. Additionally, BDSs can exhibit extreme behavior at low frequencies, refer to as Frozen Bardeen-Dirac stars (FBDSs) in AdS spacetime. FBDSs have a critical event horizon, where the metric function gtt is very close to zero. The matter is entirely encapsulated by this critical horizon, highly concentrated within it. When the magnetic charge is fixed, the FBDSs gradually disappear as the cosmological constant decreases., Comment: 21 pages, 8 figures, 1 table

The origins of lenticular galaxies (S0s) can be classified into two main categories: ``minor mergers" in low-density environments (LDEs) and ``faded spirals" in high-density environments (HDEs). The transitional phase in the evolution of S0s, namely, star-forming lenticular galaxies (SFS0s), can serve as an important probe for analyzing the complex processes involved in the transformation between different galaxy types and the quenching of star formation (SF). We attempt to find the impact of different environments on the global properties and spatially resolved quantities of SFS0s. We selected 71 SFS0s from the SDSS-IV MaNGA Survey, comprising 23 SFS0s in HDEs (SFS0s$\_$HE) and 48 SFS0s in LDEs (SFS0s$\_$LE). We examined the effects of the environment, by studying the global properties, concentration index, and radial profiles of the derived quantities. The varied environments of SFS0s do not lead to any significant difference in global properties (e.g., S$\acute{\rm e}$rsic index). By calculating $CI_{\rm H_{\alpha}/cont}$, we observe that different environments may cause varying concentrations of SF. Specifically, SFS0s$\_$LE, affected by external gas mergers or inflow, exhibit a more centrally concentrated SF (i.e., larger $CI_{\rm H_{\alpha}/cont}$). This trend is further supported by $CI_{\rm SFR, H_{\alpha}}$, which only considers the gas disk of the galaxy. This observation is aligned with the observed shrinking of gas disks in galaxies affected by ram-pressure stripping in HDEs. Furthermore, their $\Sigma_{\rm SFR}$ or resolved sSFR are comparable. On average, SFS0s$\_$LE display significantly higher values for both quantities. Finally, the observed D$_{\rm n}4000$ and gas-phase metallicity gradient correspond well to their assumed origins. However, we did not find a significantly lower gas-phase metallicity in SFS0s$\_$LE. Abridged, Comment: 15 pages, 7 figures, 4 tables. Accepted for publication in A&A

In this paper, we propose a novel and efficient parameter estimator based on $k$-Nearest Neighbor ($k$NN) and data generation method for the Lognormal-Rician turbulence channel. The Kolmogorov-Smirnov (KS) goodness-of-fit statistical tools are employed to investigate the validity of $k$NN approximation under different channel conditions and it is shown that the choice of $k$ plays a significant role in the approximation accuracy. We present several numerical results to illustrate that solving the constructed objective function can provide a reasonable estimate for the actual values. The accuracy of the proposed estimator is investigated in terms of the mean square error. The simulation results show that increasing the number of generation samples by two orders of magnitude does not lead to a significant improvement in estimation performance when solving the optimization problem by the gradient descent algorithm. However, the estimation performance under the genetic algorithm (GA) approximates to that of the saddlepoint approximation and expectation-maximization estimators. Therefore, combined with the GA, we demonstrate that the proposed estimator achieves the best tradeoff between the computation complexity and the accuracy.

In this paper, we study the shortest path problem (SPP) with multiple source-destination pairs (MSD), namely MSD-SPP, to minimize average travel time of all shortest paths. The inherent traffic capacity limits within a road network contributes to the competition among vehicles. Multi-agent reinforcement learning (MARL) model cannot offer effective and efficient path planning cooperation due to the asynchronous decision making setting in MSD-SPP, where vehicles (a.k.a agents) cannot simultaneously complete routing actions in the previous time step. To tackle the efficiency issue, we propose to divide an entire road network into multiple sub-graphs and subsequently execute a two-stage process of inter-region and intra-region route planning. To address the asynchronous issue, in the proposed asyn-MARL framework, we first design a global state, which exploits a low-dimensional vector to implicitly represent the joint observations and actions of multi-agents. Then we develop a novel trajectory collection mechanism to decrease the redundancy in training trajectories. Additionally, we design a novel actor network to facilitate the cooperation among vehicles towards the same or close destinations and a reachability graph aimed at preventing infinite loops in routing paths. On both synthetic and real road networks, our evaluation result demonstrates that our approach outperforms state-of-the-art planning approaches.

Let \mu_{M,D} be the self-similar measure generated by the positive integer M=RN^q and the product-form digit set D=\{0,1,\dots,N-1\}\oplus N^{p_1}\{0,1,\dots,N-1\}\oplus \cdots \oplus N^{p_s}\{0,1,\dots,N-1\}, where R>1, N>1, q, p_i(1\leq i\leq s) are positive integers with gcd(R,N)=1 and p_1

Superconductivity and magnetism are antagonistic quantum matter, while their intertwining has long been considered in frustrated-lattice systems1-3. In this work, we utilize scanning tunneling microscopy and muon spin resonance to discover time-reversal symmetry-breaking superconductivity in kagome metal Cs(V,Ta)3Sb5, where the Cooper pairing exhibits magnetism and is modulated by it. In the magnetic channel, we observe spontaneous internal magnetism in a full-gap superconducting state. Under perturbations of inverse magnetic fields, we detect a time-reversal asymmetrical interference of Bogoliubov quasi-particles at a circular vector. At this vector, the pairing gap spontaneously modulates, which is distinct from pair density waves occurring at a point vector and consistent with the theoretical proposal of unusual interference effect under time-reversal symmetry-breaking. The correlation between internal magnetism, Bogoliubov quasi-particles, and pairing modulation provides a chain of experimental clues for time-reversal symmetry-breaking kagome superconductivity., Comment: To appear in Nature Materials (2024)

Superconductivity involving finite momentum pairing can lead to spatial gap and pair density modulations, as well as Bogoliubov Fermi states within the superconducting gap. However, the experimental realization of their intertwined relations has been challenging. Here, we detect chiral kagome superconductivity modulations with residual Fermi arcs in KV3Sb5 and CsV3Sb5 by normal and Josephson scanning tunneling microscopy down to 30mK with resolved electronic energy difference at microelectronvolt level. We observe a U-shaped superconducting gap with flat residual in-gap states. This gap exhibits chiral 2 by 2 spatial modulations with magnetic field tunable chirality, which align with the chiral 2 by 2 pair density modulations observed through Josephson tunneling. These findings demonstrate a chiral pair density wave (PDW) that breaks time-reversal symmetry. Quasiparticle interference imaging of the in-gap zero-energy states reveals segmented arcs, with high-temperature data linking them to parts of the reconstructed V d-orbital states within the charge order. The detected residual Fermi arcs can be explained by the partial suppression of these d-orbital states through an interorbital 2 by 2 PDW and thus serve as candidate Bogoliubov Fermi states. Additionally, we differentiate the observed PDW order from impurity-induced gap modulations. Our observations not only uncover a chiral PDW order with orbital-selectivity, but also illuminate the fundamental space-momentum correspondence inherent in finite momentum paired superconductivity., Comment: To appear in Nature (2024)

The chiral 2 by 2 charge order has been reported and confirmed in the kagome superconductor RbV3Sb5, while its interplay with superconductivity remains elusive owing to its lowest superconducting transition temperature Tc of about 0.85K among the AV3Sb5 family (A=K, Rb, Cs) that severely challenges electronic spectroscopic probes. Here, utilizing dilution-refrigerator-based scanning tunneling microscopy (STM) down to 30mK, we observe chiral 2 by 2 pair density waves with residual Fermi arcs in RbV3Sb5. We find a superconducting gap of 150{\mu}eV with substantial residual in-gap states. The spatial distribution of this gap exhibits chiral 2 by 2 modulations, signaling a chiral pair density wave (PDW). Our quasi-particle interference imaging of the zero-energy residual states further reveals arc-like patterns. We discuss the relation of the gap modulations with the residual Fermi arcs under the space-momentum correspondence between PDW and Bogoliubov Fermi states., Comment: To appear in Chinese Physics Letters

Computational complexity of Bayesian learning is impeding its adoption in practical, large-scale tasks. Despite demonstrations of significant merits such as improved robustness and resilience to unseen or out-of-distribution inputs over their non- Bayesian counterparts, their practical use has faded to near insignificance. In this study, we introduce an innovative framework to mitigate the computational burden of Bayesian neural networks (BNNs). Our approach follows the principle of Bayesian techniques based on deep ensembles, but significantly reduces their cost via multiple low-rank perturbations of parameters arising from a pre-trained neural network. Both vanilla version of ensembles as well as more sophisticated schemes such as Bayesian learning with Stein Variational Gradient Descent (SVGD), previously deemed impractical for large models, can be seamlessly implemented within the proposed framework, called Bayesian Low-Rank LeArning (Bella). In a nutshell, i) Bella achieves a dramatic reduction in the number of trainable parameters required to approximate a Bayesian posterior; and ii) it not only maintains, but in some instances, surpasses the performance of conventional Bayesian learning methods and non-Bayesian baselines. Our results with large-scale tasks such as ImageNet, CAMELYON17, DomainNet, VQA with CLIP, LLaVA demonstrate the effectiveness and versatility of Bella in building highly scalable and practical Bayesian deep models for real-world applications., Comment: 17 pages, 14 figures, 11 tables

The development of quantum networks is paramount towards practical and secure communications. Quantum digital signatures (QDS) offer an information-theoretically secure solution for ensuring data integrity, authenticity, and non-repudiation, rapidly growing from proof-of-concept to robust demonstrations. However, previous QDS systems relied on expensive and bulky optical equipment, limiting large-scale deployment and reconfigurable networking construction. Here, we introduce and verify a chip-based QDS network, placing the complicated and expensive measurement devices in the central relay while each user needs only a low-cost transmitter. We demonstrate the network with a three-node setup using an integrated encoder chip and decoder chip. By developing a 1-decoy-state one-time universal hash-QDS protocol, we achieve a maximum signature rate of 0.0414 times per second for a 1 Mbit file over fiber distances up to 200 km, surpassing all current state-of-the-art QDS experiments. This study validates the feasibility of chip-based QDS, paving the way for large-scale deployment and integration with existing fiber infrastructure., Comment: 11 pages, 6 figures

Quantum conference key agreement (QCKA) enables the unconditional secure distribution of conference keys among multiple participants. Due to challenges in high-fidelity preparation and long-distance distribution of multi-photon entanglement, entanglement-based QCKA is facing severe limitations in both key rate and scalability. Here, we propose a source-independent QCKA scheme utilizing the post-matching method, feasible within the entangled photon pair distribution network. We introduce an equivalent distributing virtual multi-photon entanglement protocol for providing the unconditional security proof even in the case of coherent attacks. For the symmetry star-network, comparing with previous $n$-photon entanglement protocol, the conference key rate is improved from $O(\eta^{n})$ to $O(\eta^{2})$, where $\eta$ is the transmittance from the entanglement source to one participant. Simulation results show that the performance of our protocol has multiple orders of magnitude advantages in the intercity distance. We anticipate that our approach will demonstrate its potential in the implementation of quantum networks., Comment: 10 pages, 6 figures

Room-temperature (RT) two-dimensional (2D) van der Waals (vdW) ferromagnets hold immense promise for next-generation spintronic devices for information storage and processing. To achieve high-density energy-efficient spintronic devices, it is essential to understand local magnetic properties of RT 2D vdW magnets. In this work, we realize noninvasive in situ magnetic detection in vdW-layered ferromagnet Fe3GaTe2 using divacancy spins quantum sensor in silicon carbide (SiC) at RT. The structural features and magnetic properties of the Fe3GaTe2 are characterized utilizing Raman spectrum, magnetization and magneto-transport measurements. Further detailed analysis of temperature- and magnetic field-dependent optically detected magnetic resonances of the PL6 divacancy near the Fe3GaTe2 reveal that, the Curie temperature (Tc) of Fe3GaTe2 is ~360K, and the magnetization increases with external magnetic fields. Additionally, spin relaxometry technology is employed to probe the magnetic fluctuations of Fe3GaTe2, revealing a peak in the spin relaxation rate around Tc. These experiments give insights into the intriguing local magnetic properties of 2D vdW RT ferromagnet Fe3GaTe2 and pave the way for the application of SiC quantum sensors in noninvasive in situ magnetic detection of related 2D vdW magnets., Comment: 15 pages, 4 figures

We present an approach for predictive braking of a four-wheeled vehicle on a nonplanar road. Our main contribution is a methodology to consider friction and road contact safety on general smooth road geometry. We use this to develop an active safety system to preemptively reduce vehicle speed for upcoming road geometry, such as off-camber turns. Our system may be used for human-driven or autonomous vehicles and we demonstrate it with a simulated ADAS scenario. We show that loss of control due to driver error on nonplanar roads can be mitigated by our approach.

Pulsed visible lasers either by Q-switching or mode locking have been attracting intense attentions both in solid-state laser and fiber laser. Here, we report on the simultaneous manipulation of reconfigurable sub-pulse sequences and customizable high-order vortex beams in an actively Q-switched visible laser. On the one hand, pulse sequences with up to 4 sub-pulses could be generated and fully controlled by means of an acoustic-optic modulator driven by an arbitrary waveform generator. Both pulse number and pulse intensity can be manipulated through the programmable step-signal, which is also theoretically simulated through the rate equations. On the other hand, assisted by the off-axis pumping technique and the astigmatic mode conversion, the laser cavity could emit high-quality vortex beams carrying Laguerre-Gaussian modes up to 30th order. To the best of our knowledge, this is the most flexible active manipulations not only on the intensity distribution of the transverse modes but also on the temporal distribution of the pulse sequences in a visible laser. The versatile manipulating techniques in this work could be immediately implemented into all other solid-state lasers to obtain sub-pulse vortex beams, which may provide enhanced functionality and flexibility for a large range of laser systems.

Synthetic data is gaining increasing relevance for training machine learning models. This is mainly motivated due to several factors such as the lack of real data and intra-class variability, time and errors produced in manual labeling, and in some cases privacy concerns, among others. This paper presents an overview of the 2nd edition of the Face Recognition Challenge in the Era of Synthetic Data (FRCSyn) organized at CVPR 2024. FRCSyn aims to investigate the use of synthetic data in face recognition to address current technological limitations, including data privacy concerns, demographic biases, generalization to novel scenarios, and performance constraints in challenging situations such as aging, pose variations, and occlusions. Unlike the 1st edition, in which synthetic data from DCFace and GANDiffFace methods was only allowed to train face recognition systems, in this 2nd edition we propose new sub-tasks that allow participants to explore novel face generative methods. The outcomes of the 2nd FRCSyn Challenge, along with the proposed experimental protocol and benchmarking contribute significantly to the application of synthetic data to face recognition., Comment: arXiv admin note: text overlap with arXiv:2311.10476

Skyrmion qubits are a new highly promising logic element for quantum information processing. However, their scalability to multiple interacting qubits remains challenging. We propose a hybrid quantum setup with skyrmion qubits strongly coupled to nanomechanical cantilevers via magnetic coupling, which harnesses phonons as quantum interfaces for the manipulation of distant skyrmion qubits. A linear drive is utilized to achieve the modulation of the stiffness coefficient of the cantilever, resulting in an exponential enhancement of the coupling strength between the skyrmion qubit and the mechanical mode. We also consider the case of a topological resonator array, which allows us to study interactions between skyrmion qubits and topological phonon band structure, as well as chiral skyrmion-skyrmion interactions. The scheme suggested here offers a fascinating platform for investigating quantum information processing and quantum simulation with magnetic microstructures., Comment: To appear in PR Research, 16 pages, 9 figures

Leveraging quantum properties to enhance complex learning tasks has been proven feasible, with excellent recent achievements in the field of unsupervised learning. However, current quantum schemes neglect adaptive adjustments for unsupervised task scenarios. This work proposes a novel quantum unsupervised similarity learning method, QUSL. Firstly, QUSL uses similarity triplets for unsupervised learning, generating positive samples by perturbing anchor images, achieving a learning process independent of classical algorithms. Subsequently, combining the feature interweaving of triplets, QUSL employs metaheuristic algorithms to systematically explore high-performance mapping processes, obtaining quantum circuit architectures more suitable for unsupervised image similarity tasks. Ultimately, QUSL realizes feature learning with lower quantum resource costs. Comprehensive numerical simulations and experiments on quantum computers demonstrate that QUSL outperforms state-of-the-art quantum methods. QUSL achieves over 50% reduction in critical quantum resource utilization. QUSL improves similarity detection correlation by up to 19.5% across multiple datasets, exhibiting robustness in NISQ environments. While using fewer quantum resources, QUSL shows potential for large-scale unsupervised tasks.

The deepfake threats to society and cybersecurity have provoked significant public apprehension, driving intensified efforts within the realm of deepfake video detection. Current video-level methods are mostly based on {3D CNNs} resulting in high computational demands, although have achieved good performance. This paper introduces an elegantly simple yet effective strategy named Thumbnail Layout (TALL), which transforms a video clip into a pre-defined layout to realize the preservation of spatial and temporal dependencies. This transformation process involves sequentially masking frames at the same positions within each frame. These frames are then resized into sub-frames and reorganized into the predetermined layout, forming thumbnails. TALL is model-agnostic and has remarkable simplicity, necessitating only minimal code modifications. Furthermore, we introduce a graph reasoning block (GRB) and semantic consistency (SC) loss to strengthen TALL, culminating in TALL++. GRB enhances interactions between different semantic regions to capture semantic-level inconsistency clues. The semantic consistency loss imposes consistency constraints on semantic features to improve model generalization ability. Extensive experiments on intra-dataset, cross-dataset, diffusion-generated image detection, and deepfake generation method recognition show that TALL++ achieves results surpassing or comparable to the state-of-the-art methods, demonstrating the effectiveness of our approaches for various deepfake detection problems. The code is available at https://github.com/rainy-xu/TALL4Deepfake., Comment: Accepted by IJCV

One-bit sampling has emerged as a promising technique in multiple-input multiple-output (MIMO) radar systems due to its ability to significantly reduce data volume and processing requirements. Nevertheless, current detection methods have not adequately addressed the impact of colored noise, which is frequently encountered in real scenarios. In this paper, we present a novel detection method that accounts for colored noise in MIMO radar systems. Specifically, we derive Rao's test by computing the derivative of the likelihood function with respect to the target reflectivity parameter and the Fisher information matrix, resulting in a detector that takes the form of a weighted matched filter. To ensure the constant false alarm rate (CFAR) property, we also consider noise covariance uncertainty and examine its effect on the probability of false alarm. The detection probability is also studied analytically. Simulation results demonstrate that the proposed detector provides considerable performance gains in the presence of colored noise.

We investigate the thermoelectric effect, which describes the generation of an electric field induced by temperature and conserved charge chemical potential gradients, in the hot and dense hadronic matter created in heavy-ion collisions. Utilizing the Boltzmann kinetic theory within the repulsive mean-field hadron resonance gas model, we evaluate both the diffusion thermopower matrix and diffusion coefficient matrix for the baryon number ($B$), electric charge ($Q$), and strangeness ($S$). The Landau-Lifshitz choice for the rest frame of the fluid is enforced in the derivation. We find that the thermoelectric effect hinders the diffusion processes of multiple conserved charges, particularly reducing the coupling between electric charge and baryon number (strangeness) in baryon (strangeness) diffusion. Given that the repulsive mean-field interactions between hadrons have a significant effect on the diffusion thermopower matrix and diffusion coefficient matrix in the baryon-rich region, we extend the investigation to include the impact of magnetic fields, analyzing the magneto-thermoelectric effect on both the diffusion coefficient matrix and the Hall-like diffusion coefficient matrix. The sensitivities of the magnetic field-dependent diffusion thermopower matrix and magneto-thermoelectric modified diffusion coefficient matrix to the choices of various transverse conditions are also studied., Comment: 21 pages, 12 figures, Version accepted by Phys. Rev. D

Stellar flares are critical phenomena on stellar surfaces, which are closely tied to stellar magnetism. While extensively studied in main-sequence (MS) stars, their occurrence in evolved compact stars, specifically hot subdwarfs and white dwarfs (WDs), remains scarcely explored. Based on Cycles 1-5 of TESS photometry, we conducted a pioneering survey of flare events in $\sim12,000$ compact stars, corresponding to $\sim38,000$ light curves with 2-minute cadence. Through dedicated techniques for detrending light curves, identifying preliminary flare candidates, and validating them via machine learning, we established a catalog of 1016 flares from 193 compact stars, including 182 from 58 sdB/sdO stars and 834 from 135 WDs, respectively. However, all flaring compact stars showed signs of contamination from nearby objects or companion stars, preventing sole attribution of the detected flares. For WDs, it is highly probable that the flares originated from their cool MS companions. In contrast, the higher luminosities of sdB/sdO stars diminish companion contributions, suggesting that detected flares originated from sdB/sdO stars themselves or through close magnetic interactions with companions. Focusing on a refined sample of 23 flares from 13 sdB/sdO stars, we found their flare frequency distributions were slightly divergent from those of cool MS stars; instead, they resemble those of hot B/A-type MS stars having radiative envelopes. This similarity implies the flares on sdB/sdO stars, if these flares did originate from them, may share underlying mechanisms with hot MS stars, which warrants further investigation., Comment: 25 pages, 11 figures, 5 tables, accepted for publication in ApJS

For the Fornberg-Whitham equation, the local well-posedness in the critical Besov space $B_{p, 1}^{1+\frac{1}{p}}(\mathbb{R})$ with $1\leq p <\infty$ has been studied in (Guo, Nonlinear Anal. RWA., 2023). However, for the endpoint case $p=\infty$, whether it is locally well-posed or ill-posed in $B_{\infty, 1}^{1}(\mathbb{R})$ is still unknown. In this paper, we prove that the Fornberg-Whitham equation is well-posed in the critical Besov space $B_{\infty, 1}^{1}(\mathbb{R})$ with solutions depending continuously on initial data, which is different from that of the Camassa-Holm equation (Guo et al., J. Differ. Equ., 2022). In addition, we show that this dependence is sharp by showing that the solution map is not uniformly continuous on the initial data.

Neutrinoless double beta ($0\nu\beta\beta$) decay is the most promising way to determine whether neutrinos are Majorana particles. There are many experiments based on different isotopes searching for $0\nu\beta\beta$ decay. Combining the searches of $0\nu\beta\beta$ decay in multiple isotopes provides a possible method to distinguish operators and different models. The contributions to $0\nu\beta\beta$ decay come from standard, long-range, and short-range mechanisms. We analyze the scenario in which the standard and short-range operators exist simultaneously within the framework of low-energy effective field theory. Five specific models are considered, which can realize neutrino mass and can contribute to $0\nu\beta\beta$ decay via multiple mechanisms. A criterion to evaluate the possibilities of future experiments to discriminate operators and models is built. We find that the complementary searches for $0\nu\beta\beta$ decay in different isotopes can distinguish the cases that contain the low-energy effective operators $\mathcal{O}_{1,2,5}$ and R-parity violating supersymmetry model. For other cases and models, the experimental searches within multiple isotopes can also more effectively constrain the parameter region than with only one isotope., Comment: 29 pages, 16 figures. (discussions and descriptions added)

Numerous applications at the photon-starved regime require a free-space coupling singlephoton detector with a large active area, low dark count rate (DCR), and superior time resolutions. Here,we developed a superconducting microstrip single-photon detector (SMSPD), with a large active area of 260 um in diameter, a DCR of ~5 kcps, and a low time jitter of ~171 ps, operated at near-infrared of 1550 nm. As a demonstration, we applied the detector to a single-pixel galvanometer scanning system and successfully reconstructed object information in depth and intensity using a time-correlated photon counting technology., Comment: 12 pages, 6 figures

The CMS and ATLAS have recently reported their results searching for light Higgs boson with mass around 95 GeV, based on the full Run 2 data set. In the framework of the CP-violating (CPV) $\mu\nu$SSM, we discuss a $\sim$ 2.9$\sigma$ (local) excess at 95 GeV in the light Higgs boson search in the diphoton decay mode as reported by ATLAS and CMS, together with a $\sim$ 2$\sigma$ excess (local) in the $b\bar{b}$ final state at LEP in the same mass range. By introducing CPV phases as well as by mixing CP-even Higgs and CP-odd Higgs, a lighter Higgs boson in the $\mu\nu$SSM can be produced, which can account for the "di-photon excess"., Comment: 29 pages, 7 figures, accepted for publication in Physical Review D