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SrCo$_2$P$_2$ with a tetragonal structure is known to be a Stoner-enhanced Pauli paramagnetic metal being nearly ferromagnetic. Recently Schmidt et al. [Phys. Rev. B 108, 174415 (2023)] reported that a ferromagnetic ordered state is actually induced by a small Ni substitution for Co of $x$ = 0.02 in Sr(Co$_{1-x}$Ni$_x$)$_2$P$_2$ where antiferromagnetic ordered phase also appears by further Ni-substitution with $x = 0.06-0.35$. Here, using nuclear magnetic resonance (NMR) measurements on $^{31}$P nuclei, we have investigated how the magnetic properties change by the Ni substitution in Sr(Co$_{1-x}$Ni$_x$)$_2$P$_2$ from a microscopic point of view, especially focusing on the evolution of magnetic fluctuations with the Ni substitution and the characterization of the magnetically ordered states. The temperature dependences of $^{31}$P spin-lattice relaxation rate divided by temperature ($1/T_1T$) and Knight shift ($K$) for SrCo$_2$P$_2$ are reasonably explained by a model where a double-peak structure for the density of states near the Fermi energy is assumed. Based on a Korringa ratio analysis using the $T_1$ and $K$ data, ferromagnetic spin fluctuations are found to dominate in the ferromagnetic Sr(Co$_{1-x}$Ni$_x$)$_2$P$_2$ as well as the antiferromagnets where no clear antiferromagnetic fluctuations are observed. We also found the distribution of the ordered Co moments in the magnetically ordered states from the analysis of the $^{31}$P NMR spectra exhibiting a characteristic rectangular-like shape., Comment: Accepted for publication in Phys. Rev. B. 12 pages, 12 figures

Trillium lattices formed by corner-shared triangular units are the platform for magnetic frustration in three dimensions. Herein, we report structural and magnetic properties of the Cr-based double trillium lattice material KBaCr$_2$(PO$_4$)$_3$ studied by x-ray diffraction, magnetization, heat capacity, thermal conductivity, and $^{31}$P nuclear magnetic resonance (NMR) measurements complemented by density-functional band-structure calculations. Heat capacity and $^{31}$P NMR measurements reveal the magnetic transition at $T_{\rm N1} \simeq 13.5$ K in zero field followed by another transition at $T_{\rm N2} \simeq 7$ K in weak applied fields. The NMR sublattice magnetization confirms that the transition at $T_{\rm N1}$ is 3D in nature. The $^{31}$P spin-lattice relaxation rate in the ordered state follows the $T^3$ behavior indicative of the two-magnon Raman process. The spin lattice of KBaCr$_2$(PO$_4$)$_3$ comprises two crystallographically nonequivalent ferromagnetic sublattices that are coupled antiferromagnetically, thus eliminating frustration in this trillium network., Comment: 12 pages, 13 figures

Current Scene text image super-resolution approaches primarily focus on extracting robust features, acquiring text information, and complex training strategies to generate super-resolution images. However, the upsampling module, which is crucial in the process of converting low-resolution images to high-resolution ones, has received little attention in existing works. To address this issue, we propose the Pixel Adapter Module (PAM) based on graph attention to address pixel distortion caused by upsampling. The PAM effectively captures local structural information by allowing each pixel to interact with its neighbors and update features. Unlike previous graph attention mechanisms, our approach achieves 2-3 orders of magnitude improvement in efficiency and memory utilization by eliminating the dependency on sparse adjacency matrices and introducing a sliding window approach for efficient parallel computation. Additionally, we introduce the MLP-based Sequential Residual Block (MSRB) for robust feature extraction from text images, and a Local Contour Awareness loss ($\mathcal{L}_{lca}$) to enhance the model's perception of details. Comprehensive experiments on TextZoom demonstrate that our proposed method generates high-quality super-resolution images, surpassing existing methods in recognition accuracy. For single-stage and multi-stage strategies, we achieved improvements of 0.7\% and 2.6\%, respectively, increasing the performance from 52.6\% and 53.7\% to 53.3\% and 56.3\%. The code is available at https://github.com/wenyu1009/RTSRN.

Graph convolutional networks (GCN) is widely used to handle irregular data since it updates node features by using the structure information of graph. With the help of iterated GCN, high-order information can be obtained to further enhance the representation of nodes. However, how to apply GCN to structured data (such as pictures) has not been deeply studied. In this paper, we explore the application of graph attention networks (GAT) in image feature extraction. First of all, we propose a novel graph generation algorithm to convert images into graphs through matrix transformation. It is one magnitude faster than the algorithm based on K Nearest Neighbors (KNN). Then, GAT is used on the generated graph to update the node features. Thus, a more robust representation is obtained. These two steps are combined into a module called pixel-wise graph attention module (PGA). Since the graph obtained by our graph generation algorithm can still be transformed into a picture after processing, PGA can be well combined with CNN. Based on these two modules, we consulted the ResNet and design a pixel-wise graph attention network (PGANet). The PGANet is applied to the task of person re-identification in the datasets Market1501, DukeMTMC-reID and Occluded-DukeMTMC (outperforms state-of-the-art by 0.8\%, 1.1\% and 11\% respectively, in mAP scores). Experiment results show that it achieves the state-of-the-art performance. \href{https://github.com/wenyu1009/PGANet}{The code is available here}.

$^{31}$P nuclear magnetic resonance (NMR) measurements have been carried out to investigate the magnetic properties and spin dynamics of Fe$^{3+}$ ($S$ = 5/2) spins in the two-dimensional triangular lattice (TL) compound Na$_3$Fe(PO$_4$)$_2$. The temperature ($T$) dependence of nuclear spin-lattice relaxation rates ($1/T_1$) shows a clear peak around N\'eel temperature, $T_{\rm N} = 10.9$~K, corresponding to an antiferromagnetic (AFM) transition. From the temparature dependence of NMR shift ($K$) above $T_{\rm N}$, an exchange coupling between Fe$^{3+}$ spins was estimated to be $J/k_{\rm B}\simeq 1.9$~K using the spin-5/2 Heisenberg isotropic-TL model. The temperature dependence of $1/T_1T$ divided by the magnetic susceptibility ($\chi$), $1/T_1T\chi$, above $T_{\rm N}$ proves the AFM nature of spin fluctuations below $\sim$ 50 K in the paramagnetic state. In the magnetically ordered state below $T_{\rm N}$, the characteristic rectangular shape of the NMR spectra is observed, indicative of a commensurate AFM state in its ground state. The strong temperature dependence of 1/$T_1$ in the AFM state is well explained by the two-magnon (Raman) process of the spin waves in a 3D antiferromagnet with a spin-anisotropy energy gap of 5.7 K. The temperature dependence of sublattice magnetization is also well reproduced by the spin waves. Those results indicate that the magnetically ordered state of Na$_3$Fe(PO$_4$)$_2$ is a conventional 3D AFM state, and no obvious spin frustration effects were detected in its ground state., Comment: 17 pages, 9 figures

We report the structural and magnetic properties of a new spin-$\frac12$ antiferromagnet NaZnVOPO$_4$(HPO$_4$) studied via x-ray diffraction, magnetic susceptibility, high-field magnetization, specific heat, and $^{31}$P nuclear magnetic resonance (NMR) measurements, as well as density-functional band-structure calculations. While thermodynamic properties of this compound are well described by the $J_1-J_2$ square-lattice model, \textit{ab initio} calculations suggest a significant deformation of the spin lattice. From fits to the magnetic susceptibility we determine the averaged nearest-neighbor and second-neighbor exchange couplings of $\bar J_1\simeq -1.3$ K and $\bar J_2\simeq 5.6$ K, respectively. Experimental saturation field of 15.3\,T is consistent with these estimates if 20\% spatial anisotropy in $J_1$ is taken into account. Specific heat data signal the onset of a magnetic long-range order at $T_{\rm N} \simeq 2.1$ K, which is further supported by a sharp peak in the NMR spin-lattice relaxation rate. The NMR spectra mark the superposition of two P lines due to two noneqivalent P sites where the broad line with the strong hyperfine coupling and short $T_1$ is identified as the P(1) site located within the magnetic planes, while the narrow line with the weak hyperfine coupling and long $T_1$ is designated as the P(2) site located between the planes., Comment: 13 pages, 11 figures

A spin-triplet superconducting state mediated by ferromagnetic (FM) spin fluctuations has been suggested to occur in the newly discovered heavy-fermion superconductor UTe$_2$. However, the recent neutron scattering measurements revealed the presence of antiferromagnetic (AFM) spin fluctuations in UTe$_2$. Here, we report the $^{125}$Te nuclear magnetic resonance (NMR) studies of a single-crystal UTe$_2$, suggesting the coexistence of FM and AFM spin fluctuations in UTe$_2$. Owing to the two different Te sites in the compound, we conclude that the FM spin fluctuations are dominant within ladders and the AFM spin fluctuations originate from the inter-ladder magnetic coupling. Although AFM spin fluctuations exist in the system, the FM spin fluctuations in the ladders may play an important role in the appearance of the spin-triplet superconducting state of UTe$_2$., Comment: 6 pages, 4 figures, accepted for publication as a Letter in Phys. Rev. B

In point cloud analysis, point-based methods have rapidly developed in recent years. These methods have recently focused on concise MLP structures, such as PointNeXt, which have demonstrated competitiveness with Convolutional and Transformer structures. However, standard MLPs are limited in their ability to extract local features effectively. To address this limitation, we propose a Vector-oriented Point Set Abstraction that can aggregate neighboring features through higher-dimensional vectors. To facilitate network optimization, we construct a transformation from scalar to vector using independent angles based on 3D vector rotations. Finally, we develop a PointVector model that follows the structure of PointNeXt. Our experimental results demonstrate that PointVector achieves state-of-the-art performance $\textbf{72.3\% mIOU}$ on the S3DIS Area 5 and $\textbf{78.4\% mIOU}$ on the S3DIS (6-fold cross-validation) with only $\textbf{58\%}$ model parameters of PointNeXt. We hope our work will help the exploration of concise and effective feature representations. The code will be released soon., Comment: Accepted by CVPR2023

In this paper, we introduce a challenging global large-scale ship database (called GLSD), designed specifically for ship detection tasks. The designed GLSD database includes a total of 212,357 annotated instances from 152,576 images. Based on the collected images, we propose 13 ship categories that widely exist in international routes. These categories include Sailing boat, Fishing boat, Passenger ship, Warship, General cargo ship, Container ship, Bulk cargo carrier, Barge, Ore carrier, Speed boat, Canoe, Oil carrier, and Tug. The motivations of developing GLSD include the following: 1) providing a refine and extensive ship detection database that benefits the object detection community, 2) establishing a database with exhaustive labels (bounding boxes and ship class categories) in a uniform classification scheme, and 3) providing a large-scale ship database with geographic information (covering more than 3000 ports and 33 routes) that benefits multi-modal analysis. In addition, we discuss the evaluation protocols corresponding to image characteristics in GLSD and analyze the performance of selected state-of-the-art object detection algorithms on GSLD, aiming to establish baselines for future studies. More information regarding the designed GLSD can be found at https://github.com/jiaming-wang/GLSD., Comment: 11 pages, 7 figures

We present the structural and magnetic properties of KNaCuP$_2$O$_7$ investigated via x-ray diffraction, magnetization, specific heat, and $^{31}$P NMR and $^{23}$Na NMR measurements and complementary electronic structure calculations. The temperature dependent magnetic susceptibility and $^{31}$P NMR shift could be modeled very well by the uniform spin-$1/2$ Heisenberg antiferromagnetic chain model with nearest-neighbour interaction $J/k_{\rm B}\simeq 58.7$ K. The corresponding mapping using first principles electronic structure calculations leads to $J^{\rm DFT}/k_{\rm B} \simeq 59$ K with negligibly small inter-chain couplings ($J^{\prime}/k_{\rm B}$, $J^{\prime \prime}/k_{\rm B} < 0.1$ K), further confirming that the system is indeed an one-dimensional uniform spin-$1/2$ Heisenberg antiferromagnet. The temperature-dependent unit cell volume could be described well using the Debye approximation with a Debye temperature of $\Theta_{\rm D} \simeq 294$ K, consistent with the heat capacity data. The diverging trend of the NMR spin-lattice relaxation rates ($^{31}1/T_1$ and $^{23}1/T_1$) imply the onset of a magnetic long-range-ordering at very low temperatures supporting the anticipated $T_{\rm N} \simeq 0.38$ K from the inter-chain couplings. Moreover, the NMR spin-lattice relaxation rates show the dominant contributions from uniform ($q=0$) and staggered ($q = \pm \pi/a$) spin fluctuations in the high and low temperature regimes, respectively mimicking one-dimensionality of the spin-lattice. We have also demonstrated that $^{31}1/T_1$ in high temperatures varies linearly with $1/\sqrt{H}$ reflecting the effect of spin diffusion on the dynamic susceptibility. Further, the inter-chain frustration also substantially impede the magnetic ordering rendering the spin-lattice a perfect one-dimensional uniform spin-$1/2$ Heisenberg antiferromagnet over a wide temperature range., Comment: 15 pages, 13 figures, 1 table

We report the discovery of a first-order phase transition at around 125 K in NbCrP, which is a nonsymmorphic crystal with Pnma space group. From the resistivity, magnetic susceptibility, and nuclear magnetic resonance measurements using the crystals made by the Sn-flux method, the high-temperature (HT) phase is characterized to be metallic with a non-negligible magnetic anisotropy. The low-temperature (LT) phase is also found to be a nonmagnetic metallic state with a crystal of lower symmetry. In the LT phase, the spin susceptibility is reduced by ~30 % from that in the HT phase, suggesting that the phase transition is triggered by the electronic instability. The possible origin of the phase transition in NbCrP is discussed based on the electronic structure by comparing with those in other nonsymmorphic compounds RuP and RuAs., Comment: 9 pages, 9 Postscript figures

Whereas magnetic frustration is typically associated with local-moment magnets in special geometric arrangements, here we show that SrCo$_{2}$As$_{2}$ is a candidate for frustrated itinerant magnetism. Using inelastic neutron scattering (INS), we find that antiferromagnetic (AF) spin fluctuations develop in the square Co layers of SrCo$_{2}$As$_{2}$ below $T\approx100$ K centered at the stripe-type AF propagation vector of $(\frac{1}{2},~\frac{1}{2})$, and that their development is concomitant with a suppression of the uniform magnetic susceptibility determined via magnetization measurements. We interpret this switch in spectral weight as signaling a temperature-induced crossover from an instability towards FM ordering to an instability towards stripe-type AF ordering on cooling, and show results from Monte-Carlo simulations for a $J_{1}$-$J_{2}$ Heisenberg model that illustrate how the crossover develops as a function of the frustration ratio $-J_1/(2J_2)$. By putting our INS data on an absolute scale, we quantitatively compare them and our magnetization data to exact-diagonalization calculations for the $J_{1}$-$J_{2}$ model [N. Shannon et al., Eur. Phys. J. B 38, 599 (2004)], and show that the calculations predict a lower level of magnetic frustration than indicated by experiment. We trace this discrepancy to the large energy scale of the fluctuations ($J_{\text{avg}}\gtrsim75$ meV), which, in addition to the steep dispersion, is more characteristic of itinerant magnetism., Comment: To appear in Phys. Rev. B

Nonunitary superconductivity is a rare and striking phenomenon in which spin up and spin down electrons segregate into two different quantum condensates. Because they support topological excitations, such superconductors are being seriously considered for potential quantum information applications. We report the discovery of nonunitary spin-triplet superconductivity in UTe2, featuring the high transition temperature of 1.6 K and a remarkably large and anisotropic upper critical field exceeding 40 T. In this unusual superconducting state, electrons with parallel spins pair, yet only half of the available electrons participate, yielding a spin-polarized condensate that coexists with a spin-polarized metal. The superconducting order parameter, which breaks both gauge and time reversal symmetries, arises from strong ferromagnetic fluctuations, placing UTe2 as the paramagnetic end member of the ferromagnetic superconductor series. This discovery yields a new platform for encoding information using topological excitations and for manipulation of spinpolarized currents.

In this paper, by using the $G_2$-structure on Im$(\mathbb O)\cong\mathbb R^7$ from the octonions $\mathbb O$, the $G_2$-binormal motion of curves $\gamma(t,s)$ in $\mathbb R^7$ associated to the almost complex structure on $\mathbb S^6$ is studied. The motion is proved to be equivalent to Schr\"odinger flows from $\mathbb R^1$ to $\mathbb S^6$, and also to a nonlinear Schr\"odinger-type system in three unknown complex functions that generalizes the famous correspondence between the binormal motion of curves in $\mathbb{R}^3$ and the focusing nonlinear Schr\"odinger equation. Some related geometric properties of the surface $\Sigma$ in Im$(\mathbb O)$ swept by $\gamma(t,s)$ are determined., Comment: 20 pages, comments are welcome