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The Magellanic Stream, a tidal tail of diffuse gas falling onto the Milky Way, formed by interactions between the Small and Large Magellanic Clouds, is primarily composed of neutral atomic hydrogen (HI). The deficiency of dust and the diffuse nature of the present gas make molecular formation rare and difficult, but if present, could lead to regions potentially suitable for star formation, thereby allowing us to probe conditions of star formation similar to those at high redshifts. We search for HCO$^+$, HCN, HNC, and C$_2$H using the highest sensitivity observations of molecular absorption data from the Atacama Large Millimeter Array to trace these regions, comparing with HI archival data to compare these environments in the Magellanic Stream to the HI column density threshold for molecular formation in the Milky Way. We also compare the line of sight locations with confirmed locations of stars, molecular hydrogen, and OI detections, though at higher sensitivities than the observations presented here. We find no detections to a 3$\sigma$ significance, despite four sightlines having column densities surpassing the threshold for molecular formation in the diffuse regions of the Milky Way. Here we present our calculations for the upper limits of the column densities of each of these molecular absorption lines, ranging from $3 \times 10^{10}$ to $1 \times 10^{13}$ cm$^{-2}$. The non-detection of HCO$^+$ suggests that at least one of the following is true: (i) $X_{HCO^+, \mathrm{MS}}$ is significantly lower than the Milky Way value; (ii) that the widespread diffuse molecular gas observed in the Milky Way's diffuse ISM does not have a direct analog in the MS; (iii) the HI-to-H$_2$ transition occurs in the MS at a higher surface density in the MS than in the LMC or SMC; or (iv) molecular gas exists in the MS, but only in small, dense clumps., Comment: 19 pages, 7 figures, 4 tables, Accepted for publication in PASA

In the rapidly evolving field of scientific research, efficiently extracting key information from the burgeoning volume of scientific papers remains a formidable challenge. This paper introduces an innovative framework designed to automate the extraction of vital data from scientific PDF documents, enabling researchers to discern future research trajectories more readily. AutoIE uniquely integrates four novel components: (1) A multi-semantic feature fusion-based approach for PDF document layout analysis; (2) Advanced functional block recognition in scientific texts; (3) A synergistic technique for extracting and correlating information on molecular sieve synthesis; (4) An online learning paradigm tailored for molecular sieve literature. Our SBERT model achieves high Marco F1 scores of 87.19 and 89.65 on CoNLL04 and ADE datasets. In addition, a practical application of AutoIE in the petrochemical molecular sieve synthesis domain demonstrates its efficacy, evidenced by an impressive 78\% accuracy rate. This research paves the way for enhanced data management and interpretation in molecular sieve synthesis. It is a valuable asset for seasoned experts and newcomers in this specialized field.

Based on an extended Skyrme momentum-dependent interaction (MDI), we derive an isospin asymmetric equation of state, isospin-dependent single-particle potential and the Hamiltonian which can be used in the Boltzmann-Uehling-Uhlenbeck (BUU) model and the quantum molecular dynamics (QMD) model at the beam energy less than 1 GeV/u. As an example of the applications of extended Skyrme MDI, we also present the results obtained with the extended Skyrme momentum-dependent interaction in the improved quantum molecular dynamics model (ImQMD), and the influence of the effective mass splitting on the isospin sensitive observables, i.e., the single and double neutron-to-proton ratios, is discussed again., Comment: 19 pages, 7 figures, accepted by Phys.Rev.C

Diffusion probabilistic models (DPMs) have shown remarkable results on various image synthesis tasks such as text-to-image generation and image inpainting. However, compared to other generative methods like VAEs and GANs, DPMs lack a low-dimensional, interpretable, and well-decoupled latent code. Recently, diffusion autoencoders (Diff-AE) were proposed to explore the potential of DPMs for representation learning via autoencoding. Diff-AE provides an accessible latent space that exhibits remarkable interpretability, allowing us to manipulate image attributes based on latent codes from the space. However, previous works are not generic as they only operated on a few limited attributes. To further explore the latent space of Diff-AE and achieve a generic editing pipeline, we proposed a module called Group-supervised AutoEncoder(dubbed GAE) for Diff-AE to achieve better disentanglement on the latent code. Our proposed GAE has trained via an attribute-swap strategy to acquire the latent codes for multi-attribute image manipulation based on examples. We empirically demonstrate that our method enables multiple-attributes manipulation and achieves convincing sample quality and attribute alignments, while significantly reducing computational requirements compared to pixel-based approaches for representational decoupling. Code will be released soon.

This paper presents a numerical method based on the variational quantum algorithm to solve potential and Stokes flow problems. In this method, the governing equations for potential and Stokes flows can be respectively written in the form of Laplace's equation and Stokes equations using velocity potential, stream function and vorticity formulations. Then the finite difference method and the generalised differential quadrature (GDQ) method are applied to discretize the governing equations. For the prescribed boundary conditions, the corresponding linear systems of equations can be obtained. These linear systems are solved by using the variational quantum linear solver (VQLS), which resolves the potential and Stokes flow problems equivalently. To the best of authors' knowledge, this is the first study that incorporates the GDQ method which is inherently a high-order discretization method with the VQLS algorithm. Since the GDQ method can utilize much fewer grid points than the finite difference method to approximate derivatives with a higher order of accuracy, the size of the input matrix for the VQLS algorithm can be smaller. In this way, the computational cost may be saved. The performance of the present method is comprehensively assessed by two representative examples, namely, the potential flow around a circular cylinder and Stokes flow in a lid-driven cavity. Numerical results validate the applicability and accuracy of the present VQLS-based method. Furthermore, its time complexity is evaluated by the heuristic scaling, which demonstrates that the present method scales efficiently in the number of qubits and the precision. This work brings quantum computing to the field of computational fluid dynamics. By virtue of quantum advantage over classical methods, promising advances in solving large-scale fluid mechanics problems of engineering interest may be prompted.

Based on the ultra-relativistic quantum molecular dynamics (UrQMD) model, the impacts of momentum dependent interaction, symmetry energy and near-threshold $NN\to N\Delta$ cross sections on isospin sensitive collective flow and pion observables are investigated. Our results confirm that the elliptic flow of neutrons and charged particles, i.e. $v_2^n$ and $v_2^{ch}$, are sensitive to the strength of momentum dependence interaction and the elliptic flow ratio, i.e., $v_2^n/v_2^{ch}$, is sensitive to the stiffness of symmetry energy. For describing the pion multiplicity near the threshold energy, accurate $NN\to N\Delta$ cross sections are crucial. With the updated momentum dependent interaction and $NN\to N\Delta$ cross sections in UrQMD model, seven observables, such as directed flow and elliptic flow of neutrons and charged particles, the elliptic flow ratio of neutrons to charged particles, charged pion multiplicity and its ratio $\pi^-/\pi^+$, can be well described by the parameter sets with the slope of symmetry energy from 5 MeV to 70 MeV. To describe the constraints of symmetry energy at the densities probed by the collective flow and pion observables, the named characteristic density is investigated and used. Our analysis found that the flow characteristic density is around 1.2$\rho_0$ and pion characteristic density is around 1.5$\rho_0$, and we got the constrains of symmetry energy at characteristic densities are $S(1.2\rho_0)=34\pm 4$ MeV and $S(1.5\rho_0)=36\pm 8$ MeV. These results are consistent with previous analysis by using pion and flow observable with different transport models, and demonstrate a reasonable description of symmetry energy constraint should be presented at the characteristic density of isospin sensitive observables., Comment: 9 pages, 7 figures. arXiv admin note: text overlap with arXiv:2301.00212

By simultaneously describing the data of isospin sensitive nucleonic flow and pion observables, such as $v_2^n/v_2^{ch}$ and $\pi^-/\pi^+$, with ultra-relativistic quantum molecular dynamics (UrQMD) model, we got the symmetry energy at flow and pion characteristic densities which are $S(1.2\rho_0)=34\pm 4$ MeV and $S(1.5\rho_0)=36\pm 8$ MeV. Within the uncertainties, the constraints of symmetry energy at characteristic densities are consistent with the previous constraints by using other transport models. The consistency suggests that the reliable constraints on symmetry energy should be presented at the characteristic density of isospin sensitive observables. By using the constraints of symmetry energy at two different characteristic densities, the extrapolated value of $L$ is provided. Within $2\sigma$ uncertainty, the extrapolated value of $L$ is in $5-70$ MeV which is consistent with the recent combination analysis from PREX-II and astrophyiscs data. Further, the calculations with the constrained parameter sets can describe the data of charged pion multiplicities from S$\pi$RIT collaboration., Comment: 6 pages, 3 figures

Anisotropic bulk Dirac (or Weyl) cones in three dimensional systems have recently gained intense research interest as they are examples of materials with tilted Dirac (or Weyl) cones indicatig the violation of Lorentz invariance. In contrast, the studies on anisotropic surface Dirac cones in topological materials which contribute to anisotropic carrier mobility have been limited. By employing angle-resolved photoemission spectroscopy and first-principles calculations, we reveal the anisotropic surface Dirac dispersion in a tetradymite material Ti2Te2P on the (001) plane of the Brillioun zone. We observe the quasi-elliptical Fermi pockets at the M -point of the Brillouin zone forming the anisotropic surface Dirac cones. Our calculations of the Z2 indices confirm that the system is topologically non-trivial with multiple topological phases in the same material. In addition, the observed nodal-line like feature formed by bulk bands makes this system topologically rich., Comment: 21 pages, 17 figures, Supplementary Information included

The prosperous development of both hardware and algorithms for quantum computing (QC) potentially prompts a paradigm shift in scientific computing in various fields. As an increasingly active topic in QC, the variational quantum algorithm (VQA) leads a promising direction for solving partial differential equations on Noisy Intermediate Scale Quantum (NISQ) devices. Although a clear perspective on the advantages of QC over classical computing techniques for specific mathematical and physical problems exists, applications of QC in computational fluid dynamics to solve practical flow problems, though promising, are still in an early stage of development. To explore QC in practical simulation of flow problems, this work applies a variational hybrid quantum-classical algorithm, namely the variational quantum linear solver (VQLS), to resolve the heat conduction equation through finite difference discretization of the Laplacian operator. Details of VQLS implementation are discussed by various test instances of linear systems. Finally, the successful statevector simulations of the heat conduction equation in one and two dimensions demonstrate the validity of the present algorithm by proof-of-concept results. In addition, the heuristic scaling for the heat conduction problem indicates that the time complexity of the present approach is logarithmically dependent on the precision {\epsilon} and linearly dependent on the number of qubits n., Comment: 36 pages, 19 figures

Despite being the most studied nodal line semimetal, a clear understanding of the transient state relaxation dynamics and the underlying mechanism in ZrSiS is lacking. Using time and angle resolved photoemission spectroscopy, we study the ultrafast relaxation dynamics in ZrSiS and reveal a unique relaxation in the bulk nodal-line state which is well captured by a simple model based on optical and acoustic phonon cooling. We find linear decay processes for both optical and acoustic phonon relaxations with acoustic cooling suppressed at high temperatures. Our results reveal different decay mechanisms for the bulk and surface states and pave a way to understand the mechanism of conduction in this material., Comment: 7 pages, 4 figures

The measurement of transient optical fields has proven critical to understanding the dynamical mechanisms underlying ultrafast physical and chemical phenomena, and is key to realizing higher speeds in electronics and telecommunications. Complete characterization of optical waveforms, however, requires an optical oscilloscope capable of resolving the electric field oscillations with sub-femtosecond resolution and with single-shot operation. Here, we show that strong-field nonlinear excitation of photocurrents in a silicon-based image sensor chip can provide the sub-cycle optical gate necessary to characterize carrier-envelope phase-stable optical waveforms in the mid-infrared. By mapping the temporal delay between an intense excitation and weak perturbing pulse onto a transverse spatial coordinate of the image sensor, we show that the technique allows single-shot measurement of few-cycle waveforms.

Neutral atom platform has become an attractive choice to study the science of quantum information and quantum simulation, where intense efforts have been devoted to the entangling processes between individual atoms. For the development of this area, two-qubit controlled-PHASE gate via Rydberg blockade is one of the most essential elements. Recent theoretical studies have suggested the advantages of introducing non-trivial waveform modulation into the gate protocol, which is anticipated to improve its performance towards the next stage. We report our recent experimental results in realizing a two-qubit controlled-PHASE($C_Z$) gate via off-resonant modulated driving(ORMD) embedded in two-photon transition for Rb atoms. It relies upon a single modulated driving pulse with a carefully calculated smooth waveform to gain the appropriate phase accumulations required by the two-qubit gate. Combining this $C_Z$ gate with global microwave pulses, two-atom entanglement is generated with the raw fidelity of 0.945(6). Accounting for state preparation and measurement (SPAM) errors, we extract the entanglement operation fidelity to be 0.980(7). Our work features completing the $C_Z$ gate operation within a single pulse to avoid shelved Rydberg population, thus demonstrate another promising route for realizing high-fidelity two-qubit gate for neutral atom platform., Comment: 4 figures

With autonomous driving developing in a booming stage, accurate object detection in complex scenarios attract wide attention to ensure the safety of autonomous driving. Millimeter wave (mmWave) radar and vision fusion is a mainstream solution for accurate obstacle detection. This article presents a detailed survey on mmWave radar and vision fusion based obstacle detection methods. First, we introduce the tasks, evaluation criteria, and datasets of object detection for autonomous driving. The process of mmWave radar and vision fusion is then divided into three parts: sensor deployment, sensor calibration, and sensor fusion, which are reviewed comprehensively. Specifically, we classify the fusion methods into data level, decision level, and feature level fusion methods. In addition, we introduce three-dimensional(3D) object detection, the fusion of lidar and vision in autonomous driving and multimodal information fusion, which are promising for the future. Finally, we summarize this article.

In this paper, a multi-cluster game with high-order players is investigated. Different from the well-known multi-cluster games, the dynamics of players are taken into account in our problem. Due to the high-order dynamics of players, existing algorithms for multi-cluster games cannot solve the problem. For purpose of seeking the Nash equilibrium of the game, we design a distributed algorithm based on gradient descent and state feedback, where a distributed estimator is embedded for the players to estimate the decisions of other players. Furthermore, we analyze the exponential convergence of the algorithm via variational analysis and Lyapunov stability theory. Finally, a numerical simulation verifies the effectiveness of our method.

Most existing works on random access for machine-type communication (MTC) assume independent device activities. However, in several Internet-of-Things (IoT) applications, device activities are driven by events and hence may be correlated. This paper investigates the joint optimization of preamble selection and access barring for correlated device activities. We adopt a random access scheme with general random preamble selection parameterized by the preamble selection distributions of all devices and an access barring scheme parameterized by the access barring factor, to maximally exploit correlated device activities for improving the average throughput. First, we formulate the average throughput maximization problem with respect to the preamble selection distributions and the access barring factor. It is a challenging nonconvex problem. We characterize an optimality property of the problem. Then, we develop two iterative algorithms to obtain a stationary point and a low-complexity solution respectively by using the block coordinate descend (BCD) method. Numerical results show that the two proposed solutions achieve significant gains over existing schemes, demonstrating the significance of exploiting correlation of device activities in improving the average throughput. Numerical results also show that compared to the stationary point, the low-complexity solution achieves a similar average throughput with much lower computational complexity, demonstrating the effectiveness of the low-complexity solution., Comment: 6 pages, conference

Magnetic nulls are ubiquitous in space plasmas, and are of interest as sites of localized energy dissipation or magnetic reconnection. As such, a number of methods have been proposed for detecting nulls in both simulation data and in situ spacecraft data from Earth's magnetosphere. The same methods can be applied to detect stagnation points in flow fields. In this paper we describe a systematic comparison of different methods for finding magnetic nulls. The Poincare index method, the first-order Taylor expansion (FOTE) method, and the trilinear method are considered. We define a magnetic field containing fourteen magnetic nulls whose positions and types are known to arbitrary precision. Furthermore, we applied the selected techniques in order to find and classify those nulls. Two situations are considered: one in which the magnetic field is discretized on a rectangular grid, and the second in which the magnetic field is discretized along synthetic `spacecraft trajectories' within the domain. At present, FOTE and trilinear are the most reliable methods for finding nulls in the spacecraft data and in numerical simulations on Cartesian grids, respectively. The Poincare index method is suitable for simulations on both tetrahedral and hexahedral meshes. The proposed magnetic field configuration can be used for grading and benchmarking the new and existing tools for finding magnetic nulls and flow stagnation points., Comment: Reproduced with permission from Astronomy & Astrophysics, \c{opyright} ESO

For neutral atom qubits, the two-qubit gate is typically realized via the Rydberg blockade effect, which hints about the special status of the Rydberg level besides the regular qubit register states. Here, we carry out experimental and theoretical studies to reveal how the ground-Rydberg coherence of the control qubit atom affects the process of two-qubit Controlled-Z ($C_Z$) gate, such as the commonly used ground-Rydberg $\pi$-gap-$\pi$ pulse sequence originally proposed in Phys. Rev. Lett. \textbf{85}, 2208 (2000). We measure the decoherence of the control qubit atom after the $\pi$-gap-$\pi$ pulses and make a direct comparison with the typical decoherence time $\tau_{gr}$ extracted from Ramsey fringes of the ground-Rydberg transition. In particular, we observe that the control qubit atom subject to such pulse sequences experiences a process which is essentially similar to the ground-Rydberg Ramsey interference. Furthermore, we build a straightforward theoretical model to link the decoherence process of control qubit subject to $C_Z$ gate $\pi$-gap-$\pi$ pulse sequence and the $\tau_{gr}$, and also analyze the typical origins of decoherence effects. Finally, we discuss the $C_Z$ gate fidelity loss due to the limits imposed by the ground-Rydberg coherence properties and prospective for improving fidelity with new gate protocols., Comment: 8 figures

The $N\Delta\to NN$ cross sections, which take into account the $\Delta$-mass dependence of M-matrix and momentum $p_{N\Delta}$, are applied on the calculation of pion production within the framework of the UrQMD model. Our study shows that UrQMD calculations with the $\Delta$-mass dependent $N\Delta\to NN$ cross sections enhance the pion multiplicities and decrease the $\pi^-/\pi^+$ ratios. By analyzing the time evolution of the pion production rate and the density in the overlapped region for Au+Au at the beam energy of 0.4A GeV, we find that the pion multiplicity probes the symmetry energy in the region of 1-2 times normal density. The process of pion production in the reaction is tracked including the loops of $NN\leftrightarrow N\Delta$ and $\Delta\leftrightarrow N\pi$, our calculations show that the sensitivity of $\pi^-/\pi^+$ to symmetry energy is weakened after 4-5 N-$\Delta$-$\pi$ loops in the pion production path, while the $\pi^{-}/\pi^{+}$ ratio in reactions at near threshold energies remains its sensitivity to the symmetry energy. By comparing the calculations to the FOPI data, we obtain a model dependent conclusion on the symmetry energy and the symmetry energy at two times normal density is $S(2\rho_0)$=38-73 MeV within $1\sigma$ uncertainties. Under the constraints of tidal deformability and maximum mass of neutron star, the symmetry energy at two times normal density is reduced to $48-58$ MeV and slope of symmetry energy $L=54-81$ MeV, and it is consistent with the constraints from ASY-EOS flow data., Comment: 11 pages, 9 fiigures

Three-dimensional topological insulators (TIs) have emerged as a unique state of quantum matter and generated enormous interests in condensed matter physics. The surfaces of a three dimensional (3D) TI are composed of a massless Dirac cone, which is characterized by the Z2 topological invariant. Introduction of magnetism on the surface of TI is essential to realize the quantum anomalous Hall effect (QAHE) and other novel magneto-electric phenomena. Here, by using a combination of first principles calculations, magneto-transport, angle-resolved photoemission spectroscopy (ARPES), and time resolved ARPES (tr-ARPES), we study the electronic properties of Gadolinium (Gd) doped Sb2Te3. Our study shows that Gd doped Sb2Te3 is a spin-orbit-induced bulk band-gap material, whose surface is characterized by a single topological surface state. We further demonstrate that introducing diluted 4f-electron magnetism into the Sb2Te3 topological insulator system by the Gd doping creates surface magnetism in this system. Our results provide a new platform to investigate the interaction between dilute magnetism and topology in doped topological materials., Comment: 8 pages, 4 figures

Targeted immunization or attacks of large-scale networks has attracted significant attention by the scientific community. However, in real-world scenarios, knowledge and observations of the network may be limited thereby precluding a full assessment of the optimal nodes to immunize (or remove) in order to avoid epidemic spreading such as that of current COVID-19 epidemic. Here, we study a novel immunization strategy where only $n$ nodes are observed at a time and the most central between these $n$ nodes is immunized (or attacked). This process is continued repeatedly until $1-p$ fraction of nodes are immunized (or attacked). We develop an analytical framework for this approach and determine the critical percolation threshold $p_c$ and the size of the giant component $P_{\infty}$ for networks with arbitrary degree distributions $P(k)$. In the limit of $n\to\infty$ we recover prior work on targeted attack, whereas for $n=1$ we recover the known case of random failure. Between these two extremes, we observe that as $n$ increases, $p_c$ increases quickly towards its optimal value under targeted immunization (attack) with complete information. In particular, we find a new scaling relationship between $|p_c(\infty)-p_c(n)|$ and $n$ as $|p_c(\infty)-p_c(n)|\sim n^{-1}\exp(-\alpha n)$. For Scale-free (SF) networks, where $P(k)\sim k^{-\gamma}, 2<\gamma<3$, we find that $p_c$ has a transition from zero to non-zero when $n$ increases from $n=1$ to order of $\log N$ ($N$ is the size of network). Thus, for SF networks, knowledge of order of $\log N$ nodes and immunizing them can reduce dramatically an epidemics.

Industrial control systems are critical to the operation of industrial facilities, especially for critical infrastructures, such as refineries, power grids, and transportation systems. Similar to other information systems, a significant threat to industrial control systems is the attack from cyberspace---the offensive maneuvers launched by "anonymous" in the digital world that target computer-based assets with the goal of compromising a system's functions or probing for information. Owing to the importance of industrial control systems, and the possibly devastating consequences of being attacked, significant endeavors have been attempted to secure industrial control systems from cyberattacks. Among them are intrusion detection systems that serve as the first line of defense by monitoring and reporting potentially malicious activities. Classical machine-learning-based intrusion detection methods usually generate prediction models by learning modest-sized training samples all at once. Such approach is not always applicable to industrial control systems, as industrial control systems must process continuous control commands with limited computational resources in a nonstop way. To satisfy such requirements, we propose using online learning to learn prediction models from the controlling data stream. We introduce several state-of-the-art online learning algorithms categorically, and illustrate their efficacies on two typically used testbeds---power system and gas pipeline. Further, we explore a new cost-sensitive online learning algorithm to solve the class-imbalance problem that is pervasive in industrial intrusion detection systems. Our experimental results indicate that the proposed algorithm can achieve an overall improvement in the detection rate of cyberattacks in industrial control systems.

The discovery of topological insulator phase has ignited massive research interests in novel quantum materials. Topological insulators with superconductivity further invigorate the importance of materials providing the platform to study the interplay between these two unique states. However, the candidates of such materials are rare. Here, we report a systematic angle-resolved photoemission spectroscopy (ARPES) study of a superconducting material CaBi2 [Tc = 2 K], corroborated by the first principles calculations. Our study reveals the presence of Dirac cones with a topological protection in this system. Systematic topological analysis based on symmetry indicator shows the presence of weak topological indices in this material. Furthermore, our transport measurements show the presence of large magnetoresistance in this compound. Our results indicate that CaBi2 could potentially provide a material platform to study the interplay between superconductivity and topology., Comment: 3 figures, 6 pages

The higher order topological insulator (HOTI) has enticed enormous research interests owing to its novelty in supporting gapless states along the hinges of the crystal. Despite several theoretical predictions, enough experimental confirmation of HOTI state in crystalline solids is still lacking. It has been well known that interplay between topology and magnetism can give rise to various magnetic topological states including HOTI and Axion insulator states. Here using the high-resolution angle-resolved photoemission spectroscopy (ARPES) combined with the first-principles calculations, we report a systematic study on the electronic band topology across the magnetic phase transition in EuIn2As2 which possesses an antiferromagnetic ground state below 16 K. Antiferromagnetic EuIn2As2 has been predicted to host both the Axion insulator and HOTI phase. Our experimental results show the clear signature of the evolution of the topological state across the magnetic transition. Our study thus especially suited to understand the interaction of higher order topology with magnetism in materials., Comment: 6 pages, 4 figures

Characterizing and controlling electronic properties of quantum materials require direct measurements of non-equilibrium electronic band structures over large regions of momentum space. Here, we demonstrate an experimental apparatus for time- and angle-resolved photoemission spectroscopy using high-order harmonic probe pulses generated by a robust, moderately high power (20 W) Yb:KGW amplifier with tunable repetition rate between 50 and 150 kHz. By driving high-order harmonic generation (HHG) with the second harmonic of the fundamental 1025 nm laser pulses, we show that single-harmonic probe pulses at 21.8 eV photon energy can be effectively isolated without the use of a monochromator. The on-target photon flux can reach 5 x 10^10 photons/second at 50 kHz, and the time resolution is measured to be 320 fs. The relatively long pulse duration of the Yb-driven HHG source allows us to reach an excellent energy resolution of 21.5 meV, which is achieved by suppressing the space-charge broadening using a low photon flux of 1.5 x 10^8 photons/second at a higher repetition rate of 150 kHz. The capabilities of the setup are demonstrated through measurements in the topological semimetal ZrSiS and the topological insulator Sb2-xGdxTe3., Comment: 13 pages, 8 figures

Based on the newly updated version of the ultrarelativistic quantum molecular dynamics (UrQMD) model, the pion potentials obtained from the in-medium dispersion relation of the $\Delta$-hole model and from the modified phenomenological approach are further introduced. Both the rapidity $y_0$ and transverse-velocity $u_{t0}$ dependence of directed $v_1$ and elliptic $v_2$ flows of ${\pi}^{+}$ and ${\pi}^{-}$ charged mesons produced from Au+Au collisions at two beam energies of 1.0 GeV/nucleon and 1.5 GeV/nucleon and within a large centrality region of $0

A numerical solver for the elastic wave eigenmodes in acoustic waveguides of inhomogeneous cross-section is presented. Operating under the assumptions of linear, isotropic materials, it utilizes a finite-difference method on a staggered grid to solve for the acoustic eigenmodes of the vector-field elastic wave equation. Free, fixed, symmetry, and anti-symmetry boundary conditions are implemented, enabling efficient simulation of acoustic structures with geometrical symmetries and terminations. Perfectly matched layers are also implemented, allowing for the simulation of radiative (leaky) modes. The method is analogous to eigenmode solvers ubiquitously employed in electromagnetics to find waveguide modes, and enables design of acoustic waveguides as well as seamless integration with electromagnetic solvers for optomechanical device design. The accuracy of the solver is demonstrated by calculating eigenfrequencies and mode shapes for common acoustic modes in several simple geometries and comparing the results to analytical solutions where available or to numerical solvers based on more computationally expensive methods.

We investigate the prospects for micron-scale acoustic wave components and circuits on chip in solid planar structures that do not require suspension. We leverage evanescent guiding of acoustic waves by high slowness contrast materials readily available in silicon complementary metal-oxide semiconductor (CMOS) processes. High slowness contrast provides strong confinement of GHz frequency acoustic fields in micron-scale structures. We address the fundamental implications of intrinsic material and radiation losses on operating frequency, bandwidth, device size and as a result practicality of multi-element microphononic circuits based on solid embedded waveguides. We show that a family of acoustic components based on evanescently guided acoustic waves, including waveguide bends, evanescent couplers, Y-splitters, and acoustic-wave microring resonators, can be realized in compact, micron-scale structures, and provide basic scaling and performance arguments for these components based on material properties and simulations. We further find that wave propagation losses are expected to permit high quality factor (Q), narrowband resonators and propagation lengths allowing delay lines and the coupling or cascading of multiple components to form functional circuits, of potential utility in guided acoustic signal processing on chip. We also address and simulate bends and radiation loss, providing insight into routing and resonators. Such circuits could be monolithically integrated with electronic and photonic circuits on a single chip with expanded capabilities.

Caching in wireless device-to-device (D2D) networks can be utilized to offload data traffic during peak times. However, the design of incentive mechanisms is challenging due to the heterogeneous preference and selfish nature of user terminals (UTs). In this paper, we propose an incentive mechanism in which the base station (BS) rewards those UTs that share contents with others using D2D communication. We study the cost minimization problem for the BS and the utility maximization problem for each UT. In particular, the BS determines the rewarding policy to minimize his total cost, while each UT aims to maximize his utility by choosing his caching policy. We formulate the conflict among UTs and the tension between the BS and the UTs as a Stackelberg game. We show the existence of the equilibrium and propose an iterative gradient algorithm (IGA) to obtain the Stackelberg Equilibrium. Extensive simulations are carried out to evaluate the performance of the proposed caching scheme and comparisons are drawn with several baseline caching schemes with no incentives. Numerical results show that the caching scheme under our incentive mechanism outperforms other schemes in terms of the BS serving cost and the utilities of the UTs., Comment: Accepted to IEEE International Conference on Communications (ICC) 2016, Kuala Lumpur, Malaysia

High-Q ring resonators with contacts to the waveguide core provide a versatile platform for various applications in chip-scale optomechanics, thermo- and electro-optics. We propose and demonstrate a novel approach to implement azimuthally periodic contacted ring resonators based on multi-mode Bloch matching that support contacts on both the inner and outer radius edges with small degradation to the optical Q. Radiative coupling between degenerate modes of adjacent transverse spatial order leads to imaginary frequency (Q) splitting and a scatterer avoiding high-Q "wiggler" supermode field. We experimentally measure Q's up to 258,000 in devices fabricated in a silicon device layer on buried oxide undercladding, and up to 139,000 in devices fully suspended in air using an undercut step. Wiggler supermodes are true modes of the microphotonic system that offer new degrees of freedom in electrical, thermal and mechanical design.

We experimentally demonstrate broadband waveguide crossing arrays showing ultra low loss down to $0.04\,$dB/crossing ($0.9\%$), matching theory, and crosstalk suppression over $35\,$dB, in a CMOS-compatible geometry. The principle of operation is the tailored excitation of a low-loss spatial Bloch wave formed by matching the periodicity of the crossing array to the difference in propagation constants of the 1$^\text{st}$- and 3$^\text{rd}$-order TE-like modes of a multimode silicon waveguide. Radiative scattering at the crossing points acts like a periodic imaginary-permittivity perturbation that couples two supermodes, which results in imaginary (radiative) propagation-constant splitting and gives rise to a low-loss, unidirectional breathing Bloch wave. This type of crossing array provides a robust implementation of a key component enabling dense photonic integration.

The allowed patterns of a map on a one-dimensional interval are those permutations that are realized by the relative order of the elements in its orbits. The set of allowed patterns is completely determined by the minimal patterns that are not allowed. These are called basic forbidden patterns. In this paper we study basic forbidden patterns of several functions. We show that the logistic map L_r(x)=rx(1-x) and some generalizations have infinitely many of them for 1