Search

Hydrogen and hydrides materials have long been considered promising materials for high-temperature superconductivity. But the extreme pressures required for the metallization of hydrogen-based superconductors limit their applications. Here, we have designed a series of high-temperature perovskite hydrides that can be stable within 10 GPa. Our research covered 182 ternary systems and ultimately determined that 9 compounds were stable within 20 GPa, of which 5 exhibited superconducting transition temperatures exceeding 120 K within 10 GPa. Excitingly, KGaH3 and CsInH3 are thermodynamically stable at 50 GPa. Among these perovskite hydrides, alkali metals are responsible for providing a fixed amount of charge and maintaining structural stability, while the cubic framework formed by IIIA group elements and hydrogen is crucial for high-temperature superconductivity. This work will inspire further experimental exploration and take an important step in the exploration of low-pressure stable high-temperature superconductors.

We surely enjoy the larger the better models for their superior performance in the last couple of years when both the hardware and software support the birth of such extremely huge models. The applied fields include text mining and others. In particular, the success of LLMs on text understanding and text generation draws attention from researchers who have worked on NLP and related areas for years or even decades. On the side, LLMs may suffer from problems like model overfitting, hallucination, and device limitation to name a few. In this work, we suggest a model pruning technique specifically focused on LLMs. The proposed methodology emphasizes the explainability of deep learning models. By having the theoretical foundation, we obtain a trustworthy deep model so that huge models with a massive number of model parameters become not quite necessary. A mutual information-based estimation is adopted to find neurons with redundancy to eliminate. Moreover, an estimator with well-tuned parameters helps to find precise estimation to guide the pruning procedure. At the same time, we also explore the difference between pruning on large-scale models vs. pruning on small-scale models. The choice of pruning criteria is sensitive in small models but not for large-scale models. It is a novel finding through this work. Overall, we demonstrate the superiority of the proposed model to the state-of-the-art models., Comment: 17 pages, 7 figures, 2 tables

High-contrast refractive indexes are pivotal in dielectric metasurfaces for inducing various exotic phenomena, such as the bound state in the continuum (BIC) and electric mirror (EM). However, the limitations of high-index materials are adverse to the practical applications, thus low-contrast metasurfaces with comparable performance are highly desired. Here we present a low-contrast dielectric metasurface comprising radially anisotropic cylinders, which are SiO2 cylinders doped with a small amount of WS2. The cylinder exhibits unidirectional forward superscattering originating from the overlapping of the electric and magnetic dipole resonances. When normal illumination by a near-infrared plane wave, the metasurface consisting of the superscattering constituents manifests a polarization-insensitive EM. Conversely, when subjected to an in-plane incoming wave, the metasurface generates a symmetry-protected BIC characterized by an ultrahigh Q factor and nearly negligible out-of-plane energy radiation. Our work highlights the doping approach as an efficient strategy for designing low-contrast functional metasurfaces and sheds new light on the potential applications in photonic integrated circuits and on-chip optical communication.

The question of whether the central limit theorem (CLT) holds for the total number of edges in exponential random graph models (ERGMs) in the subcritical region of parameters has remained an open problem. In this paper, we establish the CLT in a subset of the subcritical region known as Dobrushin's uniqueness region. As a result of our proof, we also derive a convergence rate for the CLT and an explicit formula for the asymptotic variance. To establish our main result, we develop Stein's method for the normal approximation for general functionals of nonlinear exponential families of random variables, which is of independent interest. In addition to ERGM, our general theorem can also be applied to other models., Comment: 27 pages

As the number of IoT devices increases, security concerns become more prominent. The impact of threats can be minimized by deploying Network Intrusion Detection System (NIDS) by monitoring network traffic, detecting and discovering intrusions, and issuing security alerts promptly. Most intrusion detection research in recent years has been directed towards the pair of traffic itself without considering the interrelationships among them, thus limiting the monitoring of complex IoT network attack events. Besides, anomalous traffic in real networks accounts for only a small fraction, which leads to a severe imbalance problem in the dataset that makes algorithmic learning and prediction extremely difficult. In this paper, we propose an EG-ConMix method based on E-GraphSAGE, incorporating a data augmentation module to fix the problem of data imbalance. In addition, we incorporate contrastive learning to discern the difference between normal and malicious traffic samples, facilitating the extraction of key features. Extensive experiments on two publicly available datasets demonstrate the superior intrusion detection performance of EG-ConMix compared to state-of-the-art methods. Remarkably, it exhibits significant advantages in terms of training speed and accuracy for large-scale graphs.

Over the past few years, federated learning has become widely used in various classical machine learning fields because of its collaborative ability to train data from multiple sources without compromising privacy. However, in the area of graph neural networks, the nodes and network structures of graphs held by clients are different in many practical applications, and the aggregation method that directly shares model gradients cannot be directly applied to this scenario. Therefore, this work proposes a federated aggregation method FLGNN applied to various graph federation scenarios and investigates the aggregation effect of parameter sharing at each layer of the graph neural network model. The effectiveness of the federated aggregation method FLGNN is verified by experiments on real datasets. Additionally, for the privacy security of FLGNN, this paper designs membership inference attack experiments and differential privacy defense experiments. The results show that FLGNN performs good robustness, and the success rate of privacy theft is further reduced by adding differential privacy defense methods.

To enhance precision and comprehensiveness in identifying targets in electric power construction monitoring video, a novel target recognition algorithm utilizing infrared imaging is explored. This algorithm employs a color processing technique based on a local linear mapping method to effectively recolor monitoring images. The process involves three key steps: color space conversion, color transfer, and pseudo-color encoding. It is designed to accentuate targets in the infrared imaging. For the refined identification of these targets, the algorithm leverages a support vector machine approach, utilizing an optimal hyperplane to accurately predict target types. We demonstrate the efficacy of the algorithm, which achieves high target recognition accuracy in both outdoor and indoor electric power construction monitoring scenarios. It maintains a false recognition rate below 3% across various environments.

In this paper, we consider the symmetric KL-divergence between the sum of independent variables and a Gaussian distribution, and obtain a convergence rates of order $O\left( \frac{\ln n}{\sqrt{n}}\right)$. The proof is based on Stein's method. The convergence rate of order $O\left( \frac{1}{\sqrt{n}}\right)$ and $O\left( \frac{1}{n}\right) $ are also obtained under higher moment condition., Comment: 33 pages

Fracton codes host unconventional topological states of matter and are promising for fault-tolerant quantum computation due to their large coding space and strong resilience against decoherence and noise. In this work, we investigate the ground-state properties and phase transitions of two prototypical self-dual fracton spin models -- the tetrahedral Ising model and the fractal Ising model -- which correspond to error-correction procedures for the representative fracton codes of type-I and type-II, the checkerboard code and the Haah's code, respectively, in the error-free limit. They are endowed with exotic symmetry-breaking properties that contrast sharply with the spontaneous breaking of global symmetries and deconfinement transition of gauge theories. To show these unconventional behaviors, which are associated with sub-dimensional symmetries, we construct and analyze the order parameters, correlators, and symmetry generators for both models. Notably, the tetrahedral Ising model acquires an extended semi-local ordering moment, while the fractal Ising model fits into a polynomial ring representation and leads to a fractal order parameter. Numerical studies combined with analytical tools show that both models experience a strong first-order phase transition with an anomalous $L^{-(D-1)}$ scaling, despite the fractal symmetry of the latter. Our work provides new understanding of sub-dimensional symmetry breaking and makes an important step for studying quantum-error-correction properties of the checkerboard and Haah's codes., Comment: 13 pages, 6 figures. v2: published version

Investigating the implications of interlayer coupling on superconductivity is essential for comprehending the intrinsic mechanisms of high temperature superconductors. Van der Waals heterojunctions have attracted extensive research due to their exotic interlayer coupling. Here, we present a natural heterojunction superconductor of 6R-TaS2 that demonstrates a double-dome of superconductivity, in addition to, the reemergence of superconducting under high pressures. Our first principles calculation shows that the first dome of superconductivity in 6R-TaS2 can be attributed to changes in interlayer coupling and charge transfer. The second superconducting dome and the reemergence of superconductivity can be ascribed to changes in the density of states resulting from Fermi surface reconstruction, in which the DOS of T-layer and S p-orbitals play a crucial role. We have reported the first observation in TMDs that non-metallic atoms playing a dominant role in the reemergence of superconducting and the influence of two Lifshitz transitions on superconducting properties.

Metals can undergo geometric quantum phase transitions where the local curvature of the Fermi surface changes sign without a change in symmetry or topology. At the inflection points on the Fermi surface, the local curvature vanishes, leading to an anomalous dynamics of quasiparticles. In this paper, we study geometric quantum critical metals that support inflection points in two dimensions, and show that the decay rate of quasiparticles goes as $E^{\alpha}$ with $1<\alpha<2$ as a function of quasiparticle energy $E$ at the inflection points., Comment: 7 pages, 4 figures

In general, space-time wave packets with correlations between transverse spatial fields and temporal frequency spectra can lead to unique spatiotemporal dynamics, thus enabling control of the instantaneous light properties. However, spatiotemporal dynamics generated in previous approaches manifest themselves at a given propagation distance yet not arbitrarily tailored longitudinally. Here, we propose and demonstrate a new versatile class of judiciously synthesized wave packets whose spatiotemporal evolution can be arbitrarily engineered to take place at various predesigned distances along the longitudinal propagation path. Spatiotemporal synthesis is achieved by introducing a 2-dimensional spectrum comprising both temporal and longitudinal wavenumbers associated with specific transverse Bessel-Gaussian fields. The resulting spectra are then employed to produce wave packets evolving in both time and axial distance - in full accord with the theoretical analysis. In this respect, various light degrees of freedom can be independently manipulated, such as intensity, polarization, and transverse spatial distribution (e.g., orbital angular momentum). Through a temporal-longitudinal frequency comb spectrum, we simulate the synthesis of the aforementioned wave packet properties, indicating a decrease in relative error compared to the desired phenomena as more spectral components are incorporated. Additionally, we experimentally demonstrate tailorable spatiotemporal fields carrying time- and longitudinal-varying orbital angular momentum, such that the local topological charge evolves every ~1 ps in the time domain and 10 cm axially. We believe that our space-time wave packets can significantly expand the exploration of spatiotemporal dynamics in the longitudinal dimension, and potentially enable novel applications in ultrafast microscopy, light-matter interactions, and nonlinear optics.

In the literature of high-dimensional central limit theorems, there is a gap between results for general limiting correlation matrix $\Sigma$ and the strongly non-degenerate case. For the general case where $\Sigma$ may be degenerate, under certain light-tail conditions, when approximating a normalized sum of $n$ independent random vectors by the Gaussian distribution $N(0,\Sigma)$ in multivariate Kolmogorov distance, the best-known error rate has been $O(n^{-1/4})$, subject to logarithmic factors of the dimension. For the strongly non-degenerate case, that is, when the minimum eigenvalue of $\Sigma$ is bounded away from 0, the error rate can be improved to $O(n^{-1/2})$ up to a $\log n$ factor. In this paper, we show that the $O(n^{-1/2})$ rate up to a $\log n$ factor can still be achieved in the degenerate case, provided that the minimum eigenvalue of the limiting correlation matrix of any three components is bounded away from 0. We prove our main results using Stein's method in conjunction with previously unexplored inequalities for the integral of the first three derivatives of the standard Gaussian density over convex polytopes. These inequalities were previously known only for hyperrectangles. Our proof demonstrates the connection between the three-components condition and the third moment Berry--Esseen bound., Comment: 32 pages

The search for high-temperature superconductors in hydrides under high pressure has always been a research hotspot. Hydrogen-based superconductors offer an avenue to achieve the long-sought goal of superconductivity at room temperature. We systematically explore the high-pressure phase diagram, electronic properties, lattice dynamics and superconductivity of the ternary Ca-Al-H system using ab initio methods. We found two stable ternary hydrides at 50 GPa: Cmcm-CaAlH5 and Pnnm-CaAl2H8, which both are semiconductors. At 200 GPa, a new phase of P21/m-CaAlH5, P4/mmm-CaAlH7 and a metastable compound Immm-Ca2AlH12 were found. Furthermore, P4/mmm-CaAlH7 has obvious phonon softening of high frequency vibrations along the Z-A direction, point A and point X, which improves the strength of electron-phonon coupling. Therefore, a superconducting transition temperature Tc of 71 K is generated at 50 GPa. In addition, the thermodynamic metastable Immm-Ca2AlH12 exhibits a superconducting transition temperature of 118 K at 250 GPa. These results are very useful for the experimental searching of new high-Tc superconductors in ternary hydrides., Comment: 10 pages,5 figures

Metasurfaces that can work without the rigorous periodic arrangement of meta-atoms are highly desired by practical optical micro-nano devices. In this work, we proposed two kinds of Kerker-type metasurfaces possessing positional disorder immunity. The metasurfaces are composed of two different core-shell cylinders satisfying the first and second Kerker conditions, respectively. Even with large positional disorder perturbation of the meta-atoms, the metasurfaces can still maintain the same excellent performances as periodic ones, such as the total transmission and magnetic mirror responses. This disorder immunity is due to the unidirectional forward and backward scatterings of a single core-shell cylinder leading to very weak lateral couplings between neighboring cylinders thus rarely affecting the multiple scatterings in the forward or backward direction. In contrast, the dominant response of the disordered non-Kerker-type metasurface decreases significantly. Our findings provide a new idea for designing robust metasurfaces and extend the scope of metasurface applications in sensing and communication under complex practical circumstances., Comment: 18 pages, 9 figures

Fracton order describes novel quantum phases of matter that host quasiparticles with restricted mobility, and thus lies beyond the existing paradigm of topological order. In particular, excitations that cannot move without creating multiple excitations are called fractons. Here we address a fundamental open question -- can the notion of self-exchange statistics be naturally defined for fractons, given their complete immobility as isolated excitations? Surprisingly, we demonstrate how fractons can be exchanged, and show that their self-statistics is a key part of the characterization of fracton orders. We derive general constraints satisfied by the fracton self-statistics in a large class of Abelian fracton orders. Finally, we show the existence of nontrivial fracton self-statistics in some twisted variants of the checkerboard model and Haah's code, establishing that these models are in distinct quantum phases as compared to their untwisted cousins., Comment: 6+9 pages, 5+3 figures, PRL Editors' Suggestion. v2: published version

Room-temperature superconductivity has been a long-standing goal for scientific progress and human development. Thermodynamic stability is a prerequisite for material synthesis and application. Here, we perform a combination of high-throughput screening and structural search and uncover two thermodynamically stable room-temperature superconductors, Fd-3m-Li2NaH17 and Pm-3n-LiNa3H23, exhibiting extraordinary critical temperature of 340 K at 300 GPa and 310 K at 350 GPa, respectively. Li2NaH17 possesses the highest Tc among all the thermodynamically stable ternary hydrides hitherto found. The dominated H density of states at the Fermi level and the strong Fermi surface nesting are favorable for the emergence of room-temperature superconductivity. Their excellent superconducting properties help us understand the mechanism of room-temperature superconductivity and find new room-temperature superconductors. Interestingly, the structures of LiNa3H23 and Li2NaH17 equal to the identified type-I and II clathrate geometry. Our results provide a structural reference and theoretical guidance for later experimental structure determination and theoretical search for high temperature superconductors.

Achieving superconductivity at room temperature (RT) is a holy grail in physics. Recent discoveries on high-Tc superconductivity in binary hydrides H3S and LaH10 at high pressure have directed the search for RT superconductors to compress hydrides with conventional electron-phonon mechanisms. Here, we predict an exceptional family of superhydrides under high pressures, MH12 (M = Mg, Sc, Zr, Hf, Lu), all exhibiting RT superconductivity with calculated Tcs ranging from 313 to 398 K. In contrast to H3S and LaH10, the hydrogen sublattice in MH12 is arranged as quasi-atomic H2 units. This unique configuration is closely associated with high Tc, attributed to the high electronic density of states derived from H2 antibonding states at the Fermi level and the strong electron-phonon coupling related to the bending vibration of H2 and H-M-H. Notably, MgH12 and ScH12 remain dynamically stable even at pressure below 100 GPa. Our findings offer crucial insights into achieving RT superconductivity and pave the way for innovative directions in experimental research.

Edgeworth expansion provides higher-order corrections to the normal approximation for a probability distribution. The classical proof of Edgeworth expansion is via characteristic functions. As a powerful method for distributional approximations, Stein's method has also been used to prove Edgeworth expansion results. However, these results assume that either the test function is smooth (which excludes indicator functions of the half line) or that the random variables are continuous (which excludes random variables having only a continuous component). Thus, how to recover the classical Edgeworth expansion result using Stein's method has remained an open problem. In this paper, we develop Stein's method for two-term Edgeworth expansions in a general case. Our approach involves repeated use of Stein equations, Stein identities via Stein kernels, and a replacement argument., Comment: 22 pages

One of the main objectives of quantum error-correction theory is to construct quantum codes with optimal parameters and properties. In this paper, we propose a class of 2-generator quasi-cyclic codes and study their applications in the construction of quantum codes over small fields. Firstly, some sufficient conditions for these 2-generator quasi-cyclic codes to be dual-containing concerning Hermitian inner product are determined. Then, we utilize these Hermitian dual-containing quasi-cyclic codes to produce quantum codes via the famous Hermitian construction. Moreover, we present a lower bound on the minimum distance of these quasi-cyclic codes, which is helpful to construct quantum codes with larger lengths and dimensions. As the computational results, many new quantum codes that exceed the quantum Gilbert-Varshamov bound are constructed over $F_q$, where $q$ is $2,3,4,5$. In particular, 16 binary quantum codes raise the lower bound on the minimum distance in Grassl's table \cite{Grassl:codetables}. In nonbinary cases, many quantum codes are new or have better parameters than those in the literature., Comment: There was a minor problem with Theorem 7 in the previous version, which we have fixed in this version

Let $t \in \{2,8,10,12,14,16,18\}$ and $n=31s+t\geq 14$, $d_{a}(n,5)$ and $d_{l}(n,5)$ be distances of binary $[n,5]$ optimal linear codes and optimal linear complementary dual (LCD) codes, respectively. We show that an $[n,5,d_{a}(n,5)]$ optimal linear code is not an LCD code, there is an $[n,5,d_{l}(n,5)]=[n,5,d_{a}(n,5)-1]$ optimal LCD code if $t\neq 16$, and an optimal $[n,5,d_{l}(n,5)]$ optimal LCD code has $d_{l}(n,5)=16s+6=d_{a}(n,5)-2$ for $t=16$. Combined with known results on optimal LCD code, $d_{l}(n,5)$ of all $[n,5]$ LCD codes are completely determined., Comment: 15pages,7tables

Compressed hydrogen-rich compounds have received extensive attention as appealing contenders for superconductors, and further challenges are maintaining the stability and superconductivity of hydrides at lower pressures. In this work, we found several novel hydrides YZrH6, YZrH8 and YZrH12 with excellent superconductivity in the Y-Zr-H ternary system. Interestingly, YZrH6 with an A15-type structure can maintain dynamic stability down to 0.01 GPa and still with a critical temperature (Tc) of 16 K. YZrH8 and YZrH12 have high Tc of 70 K and 183 K at 200 GPa and 160 GPa, respectively. The phonon modes associated with H atoms contribute significantly to the electron-phonon coupling, and the H-driven electronic density of states play an important role in superconductivity. These findings highlight relationship between the H-driven electronic density of states, electron-phonon coupling and the superconductivity in a distinct class of hydrides, opening new avenues for designing and optimizing new hydrogen-rich high temperature superconductors., Comment: 15 pages, 8 figures