arXiv subjects
Publications and source records attributed to Peng Gao.
We study the first moments of central values of Hecke $L$-functions associated with quadratic, cubic and quartic symbols to prime moduli. This also enables us to obtain results on first moments of central values of certain families of cubic and quartic Dirichlet $L$-functions of prime moduli.
We obtain an asymptotic formula for the fourth moment of central values of a family of quadratic Hecke $L$-functions in the Gaussian field under the generalized Riemann hypothesis (GRH). We also establish lower bounds unconditionally and upper bounds under GRH for higher moments of the same family.
Organic-inorganic hybrid perovskites (OIHPs) have attracted extensive research interest as a promising candidate for efficient and inexpensive solar cells. Transmission electron microscopy characterizations that can benefit the fundamental understanding and the degradation mechanism are widely used for these materials. However, their sensitivity to the electron beam illumination and hence structural instabilities usually prevent us from obtaining the intrinsic information or even lead to significant artifacts. Here, we systematacially investigate the structural degradation behaviors under different experimental factors to reveal the optimized conditions for TEM characterizations of OIHPs by using low-dose electron diffraction and imaging techniques. We find that a low temperature does not slow down the beam damage but instead induces a rapid amorphization for OIHPs. Moreover, a less severe damage is observed at a higher accelerating voltage. The beam-sensitivity is found to be facet-dependent that a (100) exposed MAPbI3 surface is more stable than (001) surface. With these guidance, we successfully acquire the atomic structure of pristine MAPbI3 and identify the characterization window that is very narrow. These findings are helpful to guide future electron microscopy characterization of these beam-sensitive materials, which are also useful for finding strategies to improve the stability and the performance of the perovskite solar cells.
The need for countering Advanced Persistent Threat (APT) attacks has led to the solutions that ubiquitously monitor system activities in each enterprise host, and perform timely abnormal system behavior detection over the stream of monitoring data. However, existing stream-based solutions lack explicit language constructs for expressing anomaly models that capture abnormal system behaviors, thus facing challenges in incorporating expert knowledge to perform timely anomaly detection over the large-scale monitoring data. To address these limitations, we build SAQL, a novel stream-based query system that takes as input, a real-time event feed aggregated from multiple hosts in an enterprise, and provides an anomaly query engine that queries the event feed to identify abnormal behaviors based on the specified anomaly models. SAQL provides a domain-specific query language, Stream-based Anomaly Query Language (SAQL), that uniquely integrates critical primitives for expressing major types of anomaly models. In the demo, we aim to show the complete usage scenario of SAQL by (1) performing an APT attack in a controlled environment, and (2) using SAQL to detect the abnormal behaviors in real time by querying the collected stream of system monitoring data that contains the attack traces. The audience will have the option to interact with the system and detect the attack footprints in real time via issuing queries and checking the query results through a command-line UI.
We evaluate the first three moments of central values of a family of qudratic Hecke $L$-functions in the Gaussian field with power saving error terms. In particular, we obtain asymptotic formulas for the first two moments with error terms of size $O(X^{1/2+\varepsilon})$. We also study the first and second mollified moments of the same family of $L$-functions to show that at least $87.5\%$ of the members of this family have non-vanishing central values.
Multi-modality fusion technologies have greatly improved the performance of neural network-based Video Description/Caption, Visual Question Answering (VQA) and Audio Visual Scene-aware Dialog (AVSD) over the recent years. Most previous approaches only explore the last layers of multiple layer feature fusion while omitting the importance of intermediate layers. To solve the issue for the intermediate layers, we propose an efficient Quaternion Block Network (QBN) to learn interaction not only for the last layer but also for all intermediate layers simultaneously. In our proposed QBN, we use the holistic text features to guide the update of visual features. In the meantime, Hamilton quaternion products can efficiently perform information flow from higher layers to lower layers for both visual and text modalities. The evaluation results show our QBN improved the performance on VQA 2.0, even though using surpass large scale BERT or visual BERT pre-trained models. Extensive ablation study has been carried out to testify the influence of each proposed module in this study.
In this paper, we study moments of central values of cubic Hecke $L$-functions in $\mathbb{Q}(i)$, and establish quantitative non-vanishing result for those values.
Stacking order has strong influence on the coupling between the two layers of twisted bilayer graphene (BLG), which in turn determines its physical properties. Here, we report the investigation of the interlayer coupling of the epitaxially grown single-crystal 30° twisted BLG on Cu(111) at the atomic scale. The stacking order and morphology of BLG is controlled by a rationally designed two-step growth process, that is, the thermodynamically controlled nucleation and kinetically controlled growth. The crystal structure of the 30°-twisted bilayer graphene (30°-tBLG) is determined to have the quasicrystal like symmetry. The electronic properties and interlayer coupling of the 30°-tBLG is investigated using scanning tunneling microscopy (STM) and spectroscopy (STS). The energy-dependent local density of states (DOS) with in-situ electrostatic doping shows that the electronic states in two graphene layers are decoupled near the Dirac point. A linear dispersion originated from the constituent graphene monolayers is discovered with doubled degeneracy. This study contributes to controlled growth of twist-angle-defined BLG, and provides insights of the electronic properties and interlayer coupling in this intriguing system.
In this paper, we study moments of central values of certain unitary families of Hecke $L$-functions of the Gaussian field, and establish quantitative non-vanishing result for the central values. We also establish an one level density result for the low-lying zeros of these families of Hecke $L$-functions.
We evaluate the average of cubic and quartic Dirichlet character sums with the modulus going up to a size comparable to the length of the individual sums. This generalizes a result of Conrey, Farmer and Soundararajan on quadratic Dirichlet character sums.
Although numerous recent tracking approaches have made tremendous advances in the last decade, achieving high-performance visual tracking remains a challenge. In this paper, we propose an end-to-end network model to learn reinforced attentional representation for accurate target object discrimination and localization. We utilize a novel hierarchical attentional module with long short-term memory and multi-layer perceptrons to leverage both inter- and intra-frame attention to effectively facilitate visual pattern emphasis. Moreover, we incorporate a contextual attentional correlation filter into the backbone network to make our model trainable in an end-to-end fashion. Our proposed approach not only takes full advantage of informative geometries and semantics but also updates correlation filters online without fine-tuning the backbone network to enable the adaptation of variations in the target object's appearance. Extensive experiments conducted on several popular benchmark datasets demonstrate that our proposed approach is effective and computationally efficient.
In this paper, we investigate the impacts of three main aspects of visual tracking, i.e., the backbone network, the attentional mechanism, and the detection component, and propose a Siamese Attentional Keypoint Network, dubbed SATIN, for efficient tracking and accurate localization. Firstly, a new Siamese lightweight hourglass network is specially designed for visual tracking. It takes advantage of the benefits of the repeated bottom-up and top-down inference to capture more global and local contextual information at multiple scales. Secondly, a novel cross-attentional module is utilized to leverage both channel-wise and spatial intermediate attentional information, which can enhance both discriminative and localization capabilities of feature maps. Thirdly, a keypoints detection approach is invented to trace any target object by detecting the top-left corner point, the centroid point, and the bottom-right corner point of its bounding box. Therefore, our SATIN tracker not only has a strong capability to learn more effective object representations, but also is computational and memory storage efficiency, either during the training or testing stages. To the best of our knowledge, we are the first to propose this approach. Without bells and whistles, experimental results demonstrate that our approach achieves state-of-the-art performance on several recent benchmark datasets, at a speed far exceeding 27 frames per second.
Spin waves can probe the Dzyaloshinskii-Moriya interaction (DMI) which gives rise to topological spin textures, such as skyrmions. However, the DMI has not yet been reported in yttrium iron garnet (YIG) with arguably the lowest damping for spin waves. In this work, we experimentally evidence the interfacial DMI in a 7~nm-thick YIG film by measuring the nonreciprocal spin wave propagation in terms of frequency, amplitude and most importantly group velocities using all electrical spin-wave spectroscopy. The velocities of propagating spin waves show chirality among three vectors, i.e. the film normal direction, applied field and spin-wave wavevector. By measuring the asymmetric group velocities, we extract a DMI constant of 16~$μ$J/m$^{2}$ which we independently confirm by Brillouin light scattering. Thickness-dependent measurements reveal that the DMI originates from the oxide interface between the YIG and garnet substrate. The interfacial DMI discovered in the ultrathin YIG films is of key importance for functional chiral magnonics as ultra-low spin-wave damping can be achieved.
We study the $l^p$ norms of a class of weighted mean matrices whose diagonal terms are given by $n^α/\sum^{n}_{i=1}i^α$ with $α> -1$. The $l^p$ norms of such matrices are known for $p \geq 2, (α+1)p >1$ and $1<p \leq 4/3, 1/p \leq α\leq 1$. In this paper, we determine the $l^p$ norms of such matrices for $p \geq 1.35, 0\leq α\leq 1$.
The ability to controllably manipulate the complex topological polar configurations, such as polar flux-closure via external stimuli, enables many applications in electromechanical devices and nanoelectronics including high-density information storage. Here, by using the atomically resolved in situ scanning transmission electron microscopy, we find that a polar flux-closure structure in PbTiO3/SrTiO3 superlattices films can be reversibly switched to ordinary mono ferroelectric c domain or a domain under electric field or stress. Specifically, the electric field initially drives the flux-closure move and breaks them to form intermediate a/c striped domains, while the mechanical stress firstly starts to squeeze the flux-closures to convert into small vortices at the interface and form a continues dipole wave. After the removal of the external stimuli, the flux-closure structure spontaneously returns. Our atomic study provides valuable insights into understanding the lattice-charge interactions and the competing interactions balance in these complex topological structures. Such reversible switching between the flux-closure and ordinary ferroelectric domains also provides the foundation for applications such as memories and sensors.
Contact interface properties are important in determining the performances of devices based on atomically thin two-dimensional (2D) materials, especially those with short channels. Understanding the contact interface is therefore quite important to design better devices. Herein, we use scanning transmission electron microscopy, electron energy loss spectroscopy, and first-principles calculations to reveal the electronic structures within the metallic (1T')-semiconducting (2H) MoTe2 coplanar phase boundary across a wide spectral range and correlate its properties and atomic structure. We find that the 2H-MoTe2 excitonic peaks cross the phase boundary into the 1T' phase within a range of approximately 150 nm. The 1T'-MoTe2 crystal field can penetrate the boundary and extend into the 2H phase by approximately two unit cells. The plasmonic oscillations exhibit strong angle dependence, i.e., a red-shift (approximately 0.3 eV-1.2 eV) occurs within 4 nm at 1T'/2H-MoTe2 boundaries with large tilt angles, but there is no shift at zero-tilted boundaries. These atomic-scale measurements reveal the structure-property relationships of 1T'/2H-MoTe2 boundary, providing useful information for phase boundary engineering and device development based on 2D materials.
Van der Waals (vdW) layered materials have rather weaker interlayer bonding than the intra-layer bonding, therefore the exfoliation along the stacking direction enables the achievement of monolayer or few layers vdW materials with emerging novel physical properties and functionalities. The ferroelectricity in vdW materials recently attracts renewed interest for the potential use in high-density storage devices. As the thickness going thinner, the competition between the surface energy, depolarization field and interfacial chemical bonds may give rise to the modification of ferroelectricity and crystalline structure, which has limited investigations. In this work, combining the piezoresponse force microscope scanning, contact resonance imaging, we report the existence of the intrinsic in-plane polarization in vdW ferroelectrics CuInP2S6 (CIPS) single crystals, whereas below a critical thickness between 90-100 nm, the in-plane polarization disappears. The Young's modulus also shows an abrupt stiffness at the critical thickness. Based on the density functional theory calculations, we ascribe these behaviors to a structural phase transition from monoclinic to trigonal structure, which is further verified by transmission electron microscope technique. Taken together, these findings demonstrate the foundational importance of structural phase transition for enhancing the rich functionality and broad utility of vdW ferroelectrics.
Defects ubiquitously exist in crystal materials and usually exhibit a very different nature than the bulk matrix, and hence, their presence can have significant impacts on the properties of devices. Although it is well accepted that the properties of defects are determined by their unique atomic environments, the precise knowledge of such relationships is far from clear for most oxides due to the complexity of defects and difficulties in characterization. Here, we fabricate a 36.8° SrRuO3 grain boundary of which the transport measurements show a spin-valve magnetoresistance. We identify its atomic arrangement, including oxygen, using scanning transmission electron microscopy and spectroscopy. Based on the as-obtained atomic structure, the density functional theory calculations suggest that the spin-valve magnetoresistance is because of the dramatically reduced magnetic moments at the boundary. The ability to manipulate magnetic properties at the nanometer scale via defect control allows new strategies to design magnetic/electronic devices with low-dimensional magnetic order.