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In this paper, we adopt an extended relativized quark model to investigate the triply-heavy tetrquarks systematically. The mass spectra are obtained by solving the four-body relativized Hamiltonian including the Coulomb potential, confining potential, spin-spin interactions, and relativistic corrections. We find that all of the triply-heavy tetraquarks lie above the corresponding meson-meson thresholds, and thus no stable one exists. In particular, besides the spin-spin interactions, the Coulomb and confining potentials also contribute to the mass splittings in the $cb\bar c \bar q$ and $cb\bar b \bar q$ systems. Moreover, the whole mass spectra for triply heavy tetraquarks show quite similar patterns, which preserve the light flavor SU(3) symmetry and heavy quark symmetry well. Through the fall-apart mechanism, the triply-heavy tetraquarks may easily decay into the heavy quarkonium plus heavy-light mesons, which are good candidates for investigation in future experiments., Comment: 15 pages, 4 figures. Minor modifications, accepted version

In this work, the strong decay behaviors of the $\lambda-$mode low-lying $\Xi_{b}$ and $\Xi_{b}^\prime$ baryons are investigated within the $^3P_0$ model. Our results suggest that all of the low-lying $\bar 3_F$ states $\Xi_b(2S)$, $\Xi_b(1P)$, and $\Xi_b(1D)$ have small decay widths of less than 20 MeV, and these states have good potentials to be observed in the $\Xi_b^\prime \pi$ and $\Xi_b^{\prime *} \pi$ invariant masses. Further, most of the $6_F$ multiplets are relatively narrow and may decay into the $\Xi_b \pi$, $\Xi_b^\prime \pi$, $\Xi_b^{\prime *} \pi$, and $\Lambda_b \bar K$ final states. Considering the masses and strong decay behaviors, we can assign the newly observed $\Xi_{b}(6100)$ resonance as the $\Xi_b(1P)$ state with $J^P=3/2^-$ and interpret the $\Xi_{b}(6227)$ structure as the $J^P=3/2^-$ $\Xi_b^\prime(1P)$ state with a proper mixing angle. We expect that our predictions for these excited bottom strange baryons will provide helpful information for future experimental research., Comment: 7 pages, 3 figures. Minor modifications, accepted version

We investigate the solution landscapes of the confined diblock copolymer and homopolymer in two-dimensional domain by using the extended Ohta--Kawasaki model. The projected saddle dynamics method is developed to compute the saddle points with mass conservation and construct the solution landscape by coupling with downward/upward search algorithms. A variety of novel stationary solutions are identified and classified in the solution landscape, including Flower class, Mosaic class, Core-shell class, and Tai-chi class. The relationships between different stable states are shown by either transition pathways connected by index-1 saddle points or dynamical pathways connected by a high-index saddle point. The solution landscapes also demonstrate the symmetry-breaking phenomena, in which more solutions with high symmetry are found when the domain size increases., Comment: 9 pages, 8 figures

Engineering vector spatial modes of photons is an important approach for manipulating high-dimension photonic states in various quantum optical experiments. In this work, we demonstrate generation of heralded single photons with well-defined vector spatial modes by using a self-locking polarizing interferometer comprising a spatial light modulator. Specifically, it is shown that, by carefully tailoring and compensating spatial and temporal amplitudes of manipulated photons, one can exactly convert ultrafast single photons into desired spin-orbit states with extremely high purity. This compact and robust device provides a versatile way for not only generation, but also manipulation and characterization of arbitrary photonic spin-orbit states.

Deep neural networks (DNNs) are being widely applied for various real-world applications across domains due to their high performance (e.g., high accuracy on image classification). Nevertheless, a well-trained DNN after deployment could oftentimes raise errors during practical use in the operational environment due to the mismatching between distributions of the training dataset and the potential unknown noise factors in the operational environment, e.g., weather, blur, noise etc. Hence, it poses a rather important problem for the DNNs' real-world applications: how to repair the deployed DNNs for correcting the failure samples (i.e., incorrect prediction) under the deployed operational environment while not harming their capability of handling normal or clean data. The number of failure samples we can collect in practice, caused by the noise factors in the operational environment, is often limited. Therefore, It is rather challenging how to repair more similar failures based on the limited failure samples we can collect. In this paper, we propose a style-guided data augmentation for repairing DNN in the operational environment. We propose a style transfer method to learn and introduce the unknown failure patterns within the failure data into the training data via data augmentation. Moreover, we further propose the clustering-based failure data generation for much more effective style-guided data augmentation. We conduct a large-scale evaluation with fifteen degradation factors that may happen in the real world and compare with four state-of-the-art data augmentation methods and two DNN repairing methods, demonstrating that our method can significantly enhance the deployed DNNs on the corrupted data in the operational environment, and with even better accuracy on clean datasets., Comment: 14 pages; 5 figures

In this work, we investigated the decays of the fully open-flavor tetraquark state $X_0(2900)$ which was observed by the LHCb Collaboration very recently. Here, the $X_0(2900)$ was assigned as a $S-$wave $\bar D^\ast K^\ast$ hadronic molecule with $I=0$, and the effective lagrangian approach was applied to estimate the partial decay widths. Moreover, we also predicted the decay behaviors of the other unobserved $X_{J(J=1,2)}$, which were the spin partners of the $X_0(2900)$ in the $S-$wave $\bar D^\ast K^\ast$ picture. It was pointed out that the $X_1$ state with $I=0$ was a broad state with the width more than one hundred MeV, while another $X_2$ state with $I=0$ was a narrow state with the width approaching half of that for the $X_0(2900)$. In addition, our results also showed that the $\bar D^\ast K$ mode was expected to be the dominant decay mode for both $X_1$ and $X_2$. Searching for those unobserved $X_{J(J=1,2)}$ in the future experiments might be helpful to understand the nature of $X_0(2900)$.

In present work, we systematically calculate the mass spectra of open charm and bottom tetraquarks $q q\bar q \bar Q$ within an extended relativized quark model. The four-body relativized Hamiltonians including the Coulomb potential, confining potential, spin-spin interactions, and relativistic corrections are solved by using the variational method. It is found that the predicted masses of four $0^+$ $ud\bar s \bar c$ states are 2765, 3065, 3152, and 3396 MeV, which disfavor the assignment of the newly observed $X_0(2900)$ as a compact tetraquark. Moreover, the whole mass spectra of the open charm and bottom tetraquarks show quite similar patterns, which preserve the light flavor SU(3) symmetry and heavy quark symmetry well. In addition, our results suggest that the flavor exotic states $nn\bar s \bar c$, $nn\bar s \bar b$, $ss\bar n \bar c$, and $ss\bar n \bar b$ and their antiparticles can be searched in the heavy-light meson plus kaon final states by future experiments. More theoretical and experimental efforts are needed to investigate these singly heavy tetraquarks., Comment: 11 pages, 3 figures, comments and suggestions are welcome

Inspired by recent measurement of possible fully charmed tetraquarks in LHCb Collaboration, we investigate the mass spectra of fully heavy tetraquarks $QQ \bar Q \bar Q$ in an extended relativized quark model. Our estimations indicate that the broad structure around 6.4 GeV should contain one or more ground $cc \bar c \bar c$ tetraquark states, while the narrow structure near 6.9 GeV can be categorized as the first radial excitation of $cc \bar c \bar c$ system. Moreover, with the wave functions of the tetraquarks and mesons, the strong decays of tetraquarks into heavy quarkonium pair are qualitatively discussed, which can be further checked by the LHCb and CMS Collaborations., Comment: 7 pages, 3 figures, comments and suggestions are welcome

In the present work, the mass spectra of doubly heavy tetraquarks $T_{QQ^\prime}$ are systematically investigated in a relativized quark model. The four-body systems including the Coulomb potential, confining potential, spin-spin interactions, and relativistic corrections are solved within the variational method. Our results suggest that the $IJ^P=01^+$ $bb \bar u \bar d$ state is 54 MeV below the relevant $\bar B \bar B$ and $\bar B \bar B^*$ thresholds, which indicates that both strong and electromagnetic decays are forbidden, and thus this state can be a stable one. Its large hidden color component and small root mean square radius demonstrate that it is a compact tetraquark rather than a loosely bound molecule or point-like diquark-antidiquark structure. Our predictions of the doubly heavy tetraquarks may provide valuable information for future experimental searches., Comment: 13 pages, 7 figures, comments and suggestions are welcome

The scarcity of class-labeled data is a ubiquitous bottleneck in many machine learning problems. While abundant unlabeled data typically exist and provide a potential solution, it is highly challenging to exploit them. In this paper, we address this problem by leveraging Positive-Unlabeled~(PU) classification and the conditional generation with extra unlabeled data \emph{simultaneously}. In particular, we present a novel training framework to jointly target both PU classification and conditional generation when exposed to extra data, especially out-of-distribution unlabeled data, by exploring the interplay between them: 1) enhancing the performance of PU classifiers with the assistance of a novel Classifier-Noise-Invariant Conditional GAN~(CNI-CGAN) that is robust to noisy labels, 2) leveraging extra data with predicted labels from a PU classifier to help the generation. Theoretically, we prove the optimal condition of CNI-CGAN, and experimentally, we conducted extensive evaluations on diverse datasets, verifying the simultaneous improvements in both classification and generation.

Recent lattice QCD calculations showed that a $d_{N\Omega}$ dibaryon state similar to the deuteron with small binding energy may exist. In this work we propose a hadronic molecular approach to study the dynamical properties of this exotic state. We use a phenomenological Lagrangian approach to describe the coupling of the $d_{N\Omega}$ state to its constituents and the decays into conventional hadrons, $d_{N\Omega} \to \Lambda \Xi$ and $d_{N\Omega} \to \Sigma \Xi$. Predictions for the sum of the decay rates are in the range of a few hundred keV. In addition, we find that the $d_{N\Omega} \to \Lambda \Xi$ mode is dominant, preferably searched for in a future RHIC experiment.

We report a detailed study of tunneling spectra measured on 2H-Ta$_x$Nb$_{1-x}$Se$_2$ ($x=0\sim 0.1$) single crystals using a low-temperature scanning tunneling microscope. The prominent gap-like feature unintelligible for a long time was found to be accompanied by some "in-gap" fine structures. By investigating the second-derivative spectra and their temperature and magnetic field dependencies, we were able to prove that inelastic electron tunneling is the origin of these features and obtain the Eliashberg function of 2H-Ta$_x$Nb$_{1-x}$Se$_2$ at atomic scale, providing a potential way to study the local Eliashberg function and phonon spectra of the related transition-metal dichalcogenides., Comment: 6 pages, 5 figures. To appear in Physical Review Letters

We introduce a generalized numerical algorithm to construct the solution landscape, which is a pathway map consisting of all stationary points and their connections. Based on the high-index optimization-based shrinking dimer (HiOSD) method for gradient systems, a generalized high-index saddle dynamics (GHiSD) is proposed to compute any-index saddles of dynamical systems. Linear stability of the index-$k$ saddle point can be proved for the GHiSD system. A combination of the downward search algorithm and the upward search algorithm is applied to systematically construct the solution landscape, which not only provides a powerful and efficient way to compute multiple solutions without tuning initial guesses, but also reveals the relationships between different solutions. Numerical examples, including a three-dimensional example and the phase field model, demonstrate the novel concept of the solution landscape by showing the connected pathway maps.

The state-of-the-art deep neural networks (DNNs) are vulnerable against adversarial examples with additive random-like noise perturbations. While such examples are hardly found in the physical world, the image blurring effect caused by object motion, on the other hand, commonly occurs in practice, making the study of which greatly important especially for the widely adopted real-time image processing tasks (e.g., object detection, tracking). In this paper, we initiate the first step to comprehensively investigate the potential hazards of the blur effect for DNN, caused by object motion. We propose a novel adversarial attack method that can generate visually natural motion-blurred adversarial examples, named motion-based adversarial blur attack (ABBA). To this end, we first formulate the kernel-prediction-based attack where an input image is convolved with kernels in a pixel-wise way, and the misclassification capability is achieved by tuning the kernel weights. To generate visually more natural and plausible examples, we further propose the saliency-regularized adversarial kernel prediction, where the salient region serves as a moving object, and the predicted kernel is regularized to achieve naturally visual effects. Besides, the attack is further enhanced by adaptively tuning the translations of object and background. A comprehensive evaluation on the NeurIPS'17 adversarial competition dataset demonstrates the effectiveness of ABBA by considering various kernel sizes, translations, and regions. The in-depth study further confirms that our method shows more effective penetrating capability to the state-of-the-art GAN-based deblurring mechanisms compared with other blurring methods. We release the code to https://github.com/tsingqguo/ABBA., Comment: 19 pages, 16 figures. This paper has been accepted to NeurIPS 2020

The $\rho$ meson gravitational form factors are studied based on a light-front constituent quark model which has been successfully employed to calculate its generalized parton distributions and some low-energy observables. The distributions of energy, spin, pressures, and shear forces inside the $\rho$ meson are explicitly given.