We prove the long-standing Payne conjecture that the $k^{text{th}}$ eigenvalue in the buckling problem for a clamped plate is not less than the ${k+1}^{text{st}}$ eigenvalue for the membrane of the same shape which is fixed on the boundary. Moreover,
we show that the Payne conjecture is still true for $n$-dimensional case ($nge 2)$.
This paper is devoted to investigate the heat trace asymptotic expansion corresponding to the magnetic Steklov eigenvalue problem on Riemannian manifolds with boundary. We establish an effective procedure, by which we can calculate all the coefficien
ts $a_0$, $a_1$, $dots$, $a_{n-1}$ of the heat trace asymptotic expansion. In particular, we explicitly give the expressions for the first four coefficients. These coefficients are spectral invariants which provide precise information concerning the volume and curvatures of the boundary of the manifold and some physical quantities by the magnetic Steklov eigenvalues.
Dual-functional radar-communication (DFRC) systems can simultaneously perform both radar and communication functionalities using the same hardware platform and spectrum resource. In this paper, we consider multi-input multi-output (MIMO) DFRC systems
and focus on transmit beamforming designs to provide both radar sensing and multi-user communications. Unlike conventional block-level precoding techniques, we propose to use the recently emerged symbol-level precoding approach in DFRC systems, which provides additional degrees of freedom (DoFs) that guarantee preferable instantaneous transmit beampatterns for radar sensing and achieve better communication performance. In particular, the squared error between the designed and desired beampatterns is minimized subject to the quality-of-service (QoS) requirements of the communication users and the constant-modulus power constraint. Two efficient algorithms are developed to solve this non-convex problem on both the Euclidean and Riemannian spaces. The first algorithm employs penalty dual decomposition (PDD), majorization-minimization (MM), and block coordinate descent (BCD) methods to convert the original optimization problem into two solvable sub-problems, and iteratively solves them using efficient algorithms. The second algorithm provides a much faster solution at the price of a slight performance loss, first transforming the original problem into Riemannian space, and then utilizing the augmented Lagrangian method (ALM) to obtain an unconstrained problem that is subsequently solved via a Riemannian Broyden-Fletcher-Goldfarb-Shanno (RBFGS) algorithm. Extensive simulations verify the distinct advantages of the proposed symbol-level precoding designs in both radar sensing and multi-user communications.
Recent years pre-trained language models hit a success on modeling natural language sentences and (semi-)structured tables. However, existing table pre-training techniques always suffer from low data quality and low pre-training efficiency. In this p
aper, we show that table pre-training can be realized by learning a neural SQL executor over a synthetic corpus, which is obtained by automatically synthesizing executable SQL queries. By pre-training on the synthetic corpus, our approach TAPEX dramatically improves the performance on downstream tasks, boosting existing language models by at most 19.5%. Meanwhile, TAPEX has remarkably high pre-training efficiency and yields strong results when using a small pre-trained corpus. Experimental results demonstrate that TAPEX outperforms previous table pre-training approaches by a large margin, and our model achieves new state-of-the-art results on four well-known datasets, including improving the WikiSQL denotation accuracy to 89.6% (+4.9%), the WikiTableQuestions denotation accuracy to 57.5% (+4.8%), the SQA denotation accuracy to 74.5% (+3.5%), and the TabFact accuracy to 84.6% (+3.6%). Our work opens the way to reason over structured data by pre-training on synthetic executable programs.
In the paper, we study the plane Couette flow of a rarefied gas between two parallel infinite plates at $y=pm L$ moving relative to each other with opposite velocities $(pm alpha L,0,0)$ along the $x$-direction. Assuming that the stationary state tak
es the specific form of $F(y,v_x-alpha y,v_y,v_z)$ with the $x$-component of the molecular velocity sheared linearly along the $y$-direction, such steady flow is governed by a boundary value problem on a steady nonlinear Boltzmann equation driven by an external shear force under the homogeneous non-moving diffuse reflection boundary condition. In case of the Maxwell molecule collisions, we establish the existence of spatially inhomogeneous non-equilibrium stationary solutions to the steady problem for any small enough shear rate $alpha>0$ via an elaborate perturbation approach using Caflischs decomposition together with Guos $L^inftycap L^2$ theory. The result indicates the polynomial tail at large velocities for the stationary distribution. Moreover, the large time asymptotic stability of the stationary solution with an exponential convergence is also obtained and as a consequence the nonnegativity of the steady profile is justified.
This paper describes the submission of the NiuTrans end-to-end speech translation system for the IWSLT 2021 offline task, which translates from the English audio to German text directly without intermediate transcription. We use the Transformer-based
model architecture and enhance it by Conformer, relative position encoding, and stacked acoustic and textual encoding. To augment the training data, the English transcriptions are translated to German translations. Finally, we employ ensemble decoding to integrate the predictions from several models trained with the different datasets. Combining these techniques, we achieve 33.84 BLEU points on the MuST-C En-De test set, which shows the enormous potential of the end-to-end model.
Let $G$ be a simple graph with $2n$ vertices and a perfect matching. The forcing number of a perfect matching $M$ of $G$ is the smallest cardinality of a subset of $M$ that is contained in no other perfect matching of $G$. Let $f(G)$ and $F(G)$ denot
e the minimum and maximum forcing number of $G$ among all perfect matchings, respectively. Hetyei obtained that the maximum number of edges of graphs $G$ with a unique perfect matching is $n^2$ (see Lov{a}sz [20]). We know that $G$ has a unique perfect matching if and only if $f(G)=0$. Along this line, we generalize the classical result to all graphs $G$ with $f(G)=k$ for $0leq kleq n-1$, and obtain that the number of edges is at most $n^2+2nk-k^2-k$ and characterize the extremal graphs as well. Conversely, we get a non-trivial lower bound of $f(G)$ in terms of the order and size. For bipartite graphs, we gain corresponding stronger results. Further, we obtain a new upper bound of $F(G)$. Finally some open problems and conjectures are proposed.
In this paper, we consider two types of traveling wave systems of the generalized Kundu-Mukherjee-Naskar equation. Firstly, due to the integrity, we obtain their energy functions. Then, the dynamical system method is applied to study bifurcation beha
viours of the two types of traveling wave systems to obtain corresponding global phase portraits in different parameter bifurcation sets. According to them, every bounded and unbounded orbits can be identified clearly and investigated carefully which correspond to various traveling wave solutions of the generalized Kundu-Mukherjee-Naskar equation exactly. Finally, by integrating along these orbits and calculating some complicated elliptic integral, we obtain all type I and type II traveling wave solutions of the generalized Kundu-Mukherjee-Naskar equation without loss.
Quantum illumination is a quantum sensing technique where entanglement is exploited to improve the detection of low-reflectivity targets in a strong thermal background. In this paper, we study the quantum illumination of suspected targets under the c
urved spacetime background of the Earth. It is counterintuitive to find that to achieve the same error-probability both target detection scenarios, the illumination strategy curved spacetime consumes less resources than the flat spacetime strategy. That is to say, the gravitational effect of the Earth can promote the efficiency of quantum spatial target detection. This is because the average particle number of the thermal signal reflected in the curved spacetime is always less than the number in flat spacetime. We also find that the spatial quantum target detection with bipartite entangled state is more efficient than the coherent state strategy in the curved spacetime.
The IBF and the transparent rate of electrons are two essential indicators of TPC, which affect the energy resolution and counting rate respectively. In this paper, we propose several novel strategies of staggered multi-THGEM to suppress IBF, where t
he geometry of the first layer THGEM will be optimized to increase the electron transparent rate. By Garfield++ simulation, the electron transparency rate can be more than 90% of single THGEM with a optimized large hole. By simulating these configurations of triple and quadruple THGEM structures, we conclude that the IBF can be reduced to 0.2% level in an optimized configuration denoted as ACBA. This strategy for staggered THGEM could have potential applications in future TPC projects.
