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Nonlinear Hall effect (NHE) can be generated via Berry curvature dipole (BCD) on nonequilibrium Fermi surface in a non-magnetic system without inversion symmetry.To achieve a large BCD, strong local Berry curvatures and their variation with respect to momentum are necessary and hence topological materials with strong inter-band coupling emerge as promising candidates. In this study, we propose a switchable and robust BCD in the newlydiscovered dual quantum spin Hall insulator (QSHI) $\text{TaIrTe}_4$ by applying out-of-plane electric fields. Switchable BCD could be found along with topological phase transitions or insulator-metal transition in the primitive cell and CDW phases of $\text{TaIrTe}_4$ monolayer. This work presents an instructive strategy for achieving a switchable and robust BCD within dual QSHIs, which should be helpful for designing the NHE-based THz radiations detector.

Secure precision time synchronization is important for applications of Cyber-Physical Systems. However, several attacks, especially the Time Delay Attack (TDA), deteriorates the performance of time synchronization system seriously. Multiple paths scheme is thought as an effective security countermeasure to decrease the influence of TDA. However, the effective secure combination algorithm is still missed for precision time synchronization. In this paper, a secure combination algorithm based on Dempster-Shafer theory is proposed for multiple paths method. Special optimizations are done for the combination algorithm to solve the potential problems due to untrusted evidence. Theoretical simulation shows that the proposed algorithm works much better than Fault Tolerant Algorithm (FTA) and the attack detection method based on single path. And experimental demonstration proves the feasibility and superiority of the proposed algorithm, where the time stability with 27.97 ps, 1.57 ps, and 1.12 ps at average time 1s, 10s, 100s is achieved under TDA and local clock jump. The proposed algorithm can be used to improve the security and resilience of many importance synchronization protocol, such as NTP, PTP, and TWFTT.

Dual quantum spin Hall insulator (QSHI) is a newly discovered topological state in the 2D material TaIrTe$_4$, exhibiting both a traditional $Z_2$ band gap at charge neutrality point and a van Hove singularity (VHS) induced correlated $Z_2$ band gap with weak doping. Inspired by the recent progress in theoretical understanding and experimental measurements, we predicted a promising dual QSHI in the counterpart material of the NbIrTe4 monolayer by first-principles calculations. In addition to the well-known band inversion at the charge neutrality point, two new band inversions were found after CDW phase transition when the chemical potential is near the VHS, one direct and one indirect $Z_2$ band gap. The VHS-induced non-trivial band gap is around 10 meV, much larger than that from TaIrTe$_4$. Furthermore, since the new generated band gap is mainly dominated by the $4d$ orbitals of Nb, electronic correlation effects should be relatively stronger in NbIrTe$_4$ as compared to TaIrTe$_4$. Therefore, the dual QSHI state in the NbIrTe$_4$ monolayer is expected to be a good platform for investigating the interplay between topology and correlation effects.

We investigate the static and dynamic properties of tetratomic molecules formed by two microwave-shielded polar molecules across field-linked resonances. In particular, we focus on two-body physics and experimental techniques unexplored in the recent experiment [X.-Y. Chen {\it et al}., Nature {\bf626}, 283 (2024)]. We show that, compared to the lowest tetramer state, higher tetramer states typically have longer lifetimes, which may facilitate a further cooling of tetramer gases towards quantum degeneracy. To detect tetramers, we identify the distinctive time-of-flight images from ramp dissociation, which can be observed by lowering the ramp rate of the microwave. Remarkably, in the modulational dissociation of tetramers, we find that multi-photon processes induce dissociation even below the threshold modulation frequency when the modulation amplitude is sufficiently high. Given the universal form of the inter-molecular potential for microwave-shielded polar molecules, our results also apply to other molecular gases widely explored in recent experiments.

Topological insulating states in two-dimensional (2D) materials are ideal systems to study different types of quantized response signals due to their in gap metallic states. Very recently, the quantum spin Hall (QSH) effect was discovered in monolayer $\text{TaIrTe}_4$ via the observation of quantized longitudinal conductance that rarely exists in other 2D topological insulators. The non-trivial $Z_2$ topological charges can exist at both charge neutrality point and the van Hove singularity point with correlation effect induced band gap. Based on this model 2D material, we studied the switch of quantized signals between longitudinal conductance and transversal Hall conductance via tuning external magnetic field. In $Z_2$ topological phase of monolayer $\text{TaIrTe}_4$, the zero Chern number can be understood as 1-1=0 from the double band inversion from spin-up and spin-down channels. After applying a magnetic field perpendicular to the plane, the Zeeman split changes the band order for one branch of the band inversion from spin-up and spin-down channels, along with a sign charge of the Berry phase. Then the net Chern number of 1-1=0 is tuned to 1+1=2 or -1-1=-2 depending on the orientation of the magnetic field. The quantized signal not only provides another effective method for the verification of topological state in monolayer $\text{TaIrTe}_4$, but also offers a strategy for the utilization of the new quantum topological states based on switchable quantized responses.

Cardinality estimation is a critical component and a longstanding challenge in modern data warehouses. ByteHouse, ByteDance's cloud-native engine for extensive data analysis in exabyte-scale environments, serves numerous internal decision-making business scenarios. With the increasing demand for ByteHouse, cardinality estimation becomes the bottleneck for efficiently processing queries. Specifically, the existing query optimizer of ByteHouse uses the traditional Selinger-like cardinality estimator, which can produce substantial estimation errors, resulting in suboptimal query plans. To improve cardinality estimation accuracy while maintaining a practical inference overhead, we develop a framework ByteCard that enables efficient training and integration of learned cardinality estimators. Furthermore, ByteCard adapts recent advances in cardinality estimation to build models that can balance accuracy and practicality (e.g., inference latency, model size, training overhead). We observe significant query processing speed-up in ByteHouse after replacing the existing cardinality estimator with ByteCard for several optimization scenarios. Evaluations on real-world datasets show the integration of ByteCard leads to an improvement of up to 30% in the 99th quantile of latency. At last, we share our valuable experience in engineering advanced cardinality estimators. This experience can help ByteHouse integrate more learning-based solutions on the critical query execution path in the future.

Fiber-delay measurement is one of the key fundamental technologies in numerous fields. Here we propose and experimentally demonstrate a high-precision and concise optical time delay measurement system based on the technique of linear optical sampling, reaching the precision better than 100 fs under averaging. The use of only two optical frequency combs without locking the carrier-envelope-offset frequency greatly simplifies the structure of the time-delay measurement system. We also experimentally investigate the current limitations on the precision of the system. The timing jitter noises of two sources are mainly non-common mode, and are both restricted to the frequency sources. Our results indicate that the proposed device can measure fiber length fluctuations below 10 $\mu {\rm{m}}$, paving the way for further analyses of the external disturbances on the fiber link., Comment: 7 pages, 4 figures

Since response lags are essential in the feedback loops and are required by most physical systems, it is more appropriate to stabilize McKean-Vlasov stochastic differential equations (MV-SDEs) with common noise through the implementation of delay feedback control mechanisms. The aim of this paper is to design delay feedback control functions of the system state such that the controlled system to be boundedness in infinite horizon and further exponentially stable in the mean square. The designed controller, which depends only on the system state is easier to implement than that in [27] which was designed to depend on both system state and measure. The existence and uniqueness of the global solution of the controlled system is proved. The It\^o formula with respect to both state and measure is derived. The proposed delay feedback control strategies are rendered viable for effective stabilization of MV-SDEs with common noise. Furthermore, the moment Lyapunov exponent, which is intricately linked to the time delays, is meticulously estimated.

Reconstructive phase transitions involving breaking and reconstruction of primary chemical bonds are ubiquitous and important for many technological applications. In contrast to displacive phase transitions, the dynamics of reconstructive phase transitions are usually slow due to the large energy barrier. Nevertheless, the reconstructive phase transformation from $\beta$- to $\lambda$-Ti$_3$O$_5$ exhibits an ultrafast and reversible behavior. Despite extensive studies, the underlying microscopic mechanism remains unclear. Here, we discover a kinetically favorable in-plane nucleated layer-by-layer transformation mechanism through metadynamics and large-scale molecular dynamics simulations. This is enabled by developing an efficient machine learning potential with near first-principles accuracy through an on-the-fly active learning method and an advanced sampling technique. Our results reveal that the $\beta$-$\lambda$ phase transformation initiates with the formation of two-dimensional nuclei in the $ab$-plane and then proceeds layer-by-layer through a multistep barrier-lowering kinetic process via intermediate metastable phases. Our work not only provides important insight into the ultrafast and reversible nature of the $\beta$-$\lambda$ transition, but also presents useful strategies and methods for tackling other complex structural phase transitions., Comment: 26 pages,23 figures (including Supporting Information)

Exploration strategies in continuous action space are often heuristic due to the infinite actions, and these kinds of methods cannot derive a general conclusion. In prior work, it has been shown that policy-based exploration is beneficial for continuous action space in deterministic policy reinforcement learning(DPRL). However, policy-based exploration in DPRL has two prominent issues: aimless exploration and policy divergence, and the policy gradient for exploration is only sometimes helpful due to inaccurate estimation. Based on the double-Q function framework, we introduce a novel exploration strategy to mitigate these issues, separate from the policy gradient. We first propose the greedy Q softmax update schema for Q value update. The expected Q value is derived by weighted summing the conservative Q value over actions, and the weight is the corresponding greedy Q value. Greedy Q takes the maximum value of the two Q functions, and conservative Q takes the minimum value of the two different Q functions. For practicality, this theoretical basis is then extended to allow us to combine action exploration with the Q value update, except for the premise that we have a surrogate policy that behaves like this exploration policy. In practice, we construct such an exploration policy with a few sampled actions, and to meet the premise, we learn such a surrogate policy by minimizing the KL divergence between the target policy and the exploration policy constructed by the conservative Q. We evaluate our method on the Mujoco benchmark and demonstrate superior performance compared to previous state-of-the-art methods across various environments, particularly in the most complex Humanoid environment., Comment: 20 pages

The recent experimental claim of room-temperature ambient-pressure superconductivity in a Cu-doped lead-apatite (LK-99) has ignited substantial research interest in both experimental and theoretical domains. Previous density functional theory (DFT) calculations with the inclusion of an on-site Hubbard interaction $U$ consistently predict the presence of flat bands crossing the Fermi level. This is in contrast to DFT plus dynamical mean field theory calculations, which reveal the Mott insulating behavior for the stoichiometric Pb$_{9}$Cu(PO$_4$)$_6$O compound. Nevertheless, the existing calculations are all based on the $P6_3/m$ structure, which is argued to be not the ground-state structure. Here, we revisit the electronic structure of Pb$_{9}$Cu(PO$_4$)$_6$O with the energetically more favorable $P\bar{3}$ structure, fully taking into account electronic symmetry breaking. We examine all possible configurations for Cu substituting the Pb sites. Our results show that the doped Cu atoms exhibit a preference for substituting the Pb2 sites than the Pb1 sites. In both cases, the calculated substitutional formation energies are large, indicating the difficulty in incorporating Cu at the Pb sites. We find that most of structures with Cu at the Pb2 site tend to be insulating, while the structures with both two Cu atoms at the Pb1 sites (except one configuration) are predicted to be metallic by DFT+$U$ calculations. However, when accounting for the electronic symmetry breaking, some Cu-doped configurations previously predicted to be metallic (including the structure studied in previous DFT+$U$ calculations) become insulating. Our work highlights the importance of symmetry breaking in obtaining correct electronic state for Pb$_{9}$Cu(PO$_4$)$_6$O, thereby reconciling previous DFT+$U$ and DFT+DMFT calculations., Comment: 19 pages, 9 figures (including Supplementary Material)

Recently, Lee et al. reported the experimental discovery of room-temperature ambient-pressure superconductivity in a Cu-doped lead-apatite (LK-99) (arXiv:2307.12008, arXiv:2307.12037). Remarkably, the superconductivity persists up to 400 K at ambient pressure. Despite strong experimental evidence, the electronic structure of LK-99 has not yet been studied. Here, we investigate the electronic structures of LK-99 and its parent compound using first-principles calculations, aiming to elucidate the doping effects of Cu. Our results reveal that the parent compound Pb$_{10}$(PO$_4$)$_6$O is an insulator, while Cu doping induces an insulator-metal transition and thus volume contraction. The band structures of LK-99 around the Fermi level are featured by a half-filled flat band and a fully-occupied flat band. These two flat bands arise from both the $2p$ orbitals of $1/4$-occupied O atoms and the hybridization of the $3d$ orbitals of Cu with the $2p$ orbitals of its nearest-neighboring O atoms. Interestingly, we observe four van Hove singularities on these two flat bands. Furthermore, we show that the flat band structures can be tuned by including electronic correlation effects or by doping different elements. We find that among the considered doping elements (Ni, Cu, Zn, Ag, and Au), both Ni and Zn doping result in the gap opening, whereas Au exhibits doping effects more similar to Cu than Ag. Our work provides a foundation for future studies on the role of unique electronic structures of LK-99 in superconductivity.

Bronchoscopy with transbronchial biopsy is a minimally invasive and effective method for early lung cancer intervention. Robot-assisted bronchoscopy offers improved precision, spatial flexibility, and reduced risk of cross-infection. This paper introduces a novel teleoperated robotic bronchoscopy system and a three-stage procedure designed for robot-assisted bronchoscopy. The robotic mechanism enables a clinical practice similar to traditional bronchoscopy, augmented by the control of a novel variable stiffness catheter for tissue sampling. A rapid prototype of the robotic system has been fully developed and validated through in-vivo experiments. The results demonstrate the potential of the proposed robotic bronchoscopy system and variable stiffness catheter in enhancing accuracy and safety during bronchoscopy procedures.

Ultracold polyatomic molecules offer intriguing new opportunities in cold chemistry, precision measurements, and quantum information processing, thanks to their rich internal structure. However, their increased complexity compared to diatomic molecules presents a formidable challenge to employ conventional cooling techniques. Here, we demonstrate a new approach to create ultracold polyatomic molecules by electroassociation in a degenerate Fermi gas of microwave-dressed polar molecules through a field-linked resonance. Starting from ground state NaK molecules, we create around $1.1\times 10^3$ tetratomic (NaK)$_2$ molecules, with a phase space density of $0.040(3)$ at a temperature of $134(3)\,\text{nK}$, more than $3000$ times colder than previously realized tetratomic molecules. We observe a maximum tetramer lifetime of $8(2)\,\text{ms}$ in free space without a notable change in the presence of an optical dipole trap, indicating these tetramers are collisionally stable. The measured binding energy and lifetime agree well with parameter-free calculations, which outlines pathways to further increase the lifetime of the tetramers. Moreover, we directly image the dissociated tetramers through microwave-field modulation to probe the anisotropy of their wave function in momentum space. Our result demonstrates a universal tool for assembling ultracold polyatomic molecules from smaller polar molecules, which is a crucial step towards Bose--Einstein condensation (BEC) of polyatomic molecules and towards a new crossover from a dipolar Bardeen-Cooper-Schrieffer (BCS) superfluid to a BEC of tetramers. Additionally, the long-lived FL state provides an ideal starting point for deterministic optical transfer to deeply bound tetramer states.

Superhard materials with good fracture toughness have found wide industrial applications, which necessitates the development of accurate hardness and fracture toughness models for efficient materials design. Although several macroscopic models have been proposed, they are mostly semiempirical based on prior knowledge or assumptions, and obtained by fitting limited experimental data. Here, through an unbiased and explanatory symbolic regression technique, we built a macroscopic hardness model and fracture toughness model, which only require shear and bulk moduli as inputs. The developed hardness model was trained on an extended dataset, which not only includes cubic systems, but also contains non-cubic systems with anisotropic elastic properties. The obtained models turned out to be simple, accurate, and transferable. Moreover, we assessed the performance of three popular deep learning models for predicting bulk and shear moduli, and found that the crystal graph convolutional neural network and crystal explainable property predictor perform almost equally well, both better than the atomistic line graph neural network. By combining the machine-learned bulk and shear moduli with the hardness and fracture toughness prediction models, potential superhard materials with good fracture toughness can be efficiently screened out through high-throughput calculations.

Excellent high-temperature mechanical properties of Ni-based single crystal superalloys (NSCSs) are attributed to the yield strength anomaly of Ni$_{3}$Al that is intimately related to generalized stacking fault energies (GSFEs). Therefore, clarifying the effects of alloying elements on the GSFEs is of great significance for alloys design. Here, by means of ab initio density functional theory calculations, we systematically calculated the GSFEs of different slip systems of Ni and Ni$_{3}$Al without and with alloying elements using the alias shear method. We obtained that for Ni, except for magnetic elements Mn, Fe, and Co, most of alloying elements decrease the unstable stacking fault energy ($\gamma_{usf}$) of the $[01\bar{1}](111)$ and $[11\bar{2}](111)$ slip systems and also decrease the stable stacking fault energy ($\gamma_{sf}$) of the $[11\bar{2}](111)$ slip system. For Ni$_{3}$Al, most of alloying elements in groups IIIB-VIIB show a strong Al site preference. Except for Mn and Fe, the elements in groups VB-VIIB and the first column of group VIII increase the values of $\gamma_{usf}$ of different slip systems of Ni$_{3}$Al. On the other hand, the elements in groups IIIB-VIIB also increase the value of $\gamma_{sf}$. We found that Re is an excellent strengthening alloying element that significantly increases the slip barrier of the tailing slip process for Ni, and also enhances the slip barrier of the leading slip process of three slip systems for Ni$_{3}$Al. W and Mo exhibit similar effects as Re. We predicted that Os, Ru, and Ir are good strengthening alloying elements as well, since they show the strengthening effects on both the leading and tailing slip process for Ni and Ni$_{3}$Al.

Federated Learning (FL) is a popular collaborative learning scheme involving multiple clients and a server. FL focuses on protecting clients' data but turns out to be highly vulnerable to Intellectual Property (IP) threats. Since FL periodically collects and distributes the model parameters, a free-rider can download the latest model and thus steal model IP. Split Federated Learning (SFL), a recent variant of FL that supports training with resource-constrained clients, splits the model into two, giving one part of the model to clients (client-side model), and the remaining part to the server (server-side model). Thus SFL prevents model leakage by design. Moreover, by blocking prediction queries, it can be made resistant to advanced IP threats such as traditional Model Extraction (ME) attacks. While SFL is better than FL in terms of providing IP protection, it is still vulnerable. In this paper, we expose the vulnerability of SFL and show how malicious clients can launch ME attacks by querying the gradient information from the server side. We propose five variants of ME attack which differs in the gradient usage as well as in the data assumptions. We show that under practical cases, the proposed ME attacks work exceptionally well for SFL. For instance, when the server-side model has five layers, our proposed ME attack can achieve over 90% accuracy with less than 2% accuracy degradation with VGG-11 on CIFAR-10., Comment: Its Neurips Review is available at https://openreview.net/forum?id=vdxOesWgbyN

Recently, near-ambient superconductivity has been experimentally evidenced in a nitrogen-doped lutetium hydride by Dasenbrock-Gammon \emph{et al.} [Nature 615, 244 (2023)], which yields a remarkable maximum $T_c$ of 294 K at just 10 kbar. However, due to the difficulty of x-ray diffraction (XRD) in identifying light elements such as hydrogen and nitrogen, the crystal structure of the superconductor remains elusive, in particular for the actual stoichiometry of hydrogen and nitrogen and their atomistic positions. This holds even for its parent structure. Here, we set out to address this issue by performing a thorough density functional theory study on the structural, electronic, dynamical, and optical properties of lutetium hydrides. Through thermal and lattice dynamic analysis as well as XRD and superconductor color comparisons, we unambiguously clarified that the parent structures are a mixture of dominant LuH$_2$ phase of the CaF$_2$-type (instead of originally proposed LuH$_3$ structure of $Fm\bar{3}m$ space group) and minor LuH phase of the NaCl-type., Comment: 4 pages, 3 figures