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Source author record

Ming Lu

Ming Lu appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

ResearcherUnclaimed source record
math.RTComputer Visionhep-phphysics.opticsmath.QAcond-mat.mes-hallcond-mat.mtrl-scieess.IVcond-mat.supr-conGraphicsMachine LearningArtificial Intelligencecond-mat.othercond-mat.quant-gascond-mat.softcond-mat.str-eleess.SPgr-qchep-thmath.AGmath.RANeural and Evolutionary Computingnucl-thphysics.app-phphysics.atom-phphysics.ins-detquant-ph

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Published work

41 published item(s)

preprint2026arXiv

Towards Autonomous Business Intelligence via Data-to-Insight Discovery Agent

Transforming fragmented enterprise data into actionable insights remains a significant challenge for LLMs, constrained by complex database schemas, limitations in dynamic SQL generation, and the need for deep multi-dimensional analysis.In this paper, we propose AIDA(Autonomous Insight Discovery Agent), the first end-to-end framework designed for autonomous exploration in complex business environments. We establish a highly flexible instant retail environment encompassing 200+ metrics and 100+ dimensions, and integrates a proprietary Domain-Specific Language (DSL) that bridges semantic reasoning with precise SQL execution. Our reinforcement learning system subsequently formulates business analysis as a Pareto Principle-guided cumulative reasoning process. Experimental results demonstrate that AIDA significantly outperforms workflow-based agents, and extensive evaluations further reveal that AIDA achieves superior environmental perception and more in-depth analysis from diverse perspectives. Our work ultimately establishes the transformative potential of autonomous intelligence for industrial-scale business intelligence systems.

0 citations0 reviewsNo code linkedOpen access
preprint2024arXiv

Derived Hall algebras of root categories

For a finitary hereditary abelian category $\mathcal{A}$, we define a derived Hall algebra of its root category by counting the triangles and using the octahedral axiom, which is proved to be isomorphic to the Drinfeld double of Hall algebra of $\mathcal{A}$. When applied to finite-dimensional nilpotent representations of the Jordan quiver or coherent sheaves over elliptic curves, these algebras provide categorical realizations of the ring of Laurent symmetric functions and also double affine Hecke algebras.

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preprint2024arXiv

RustNeRF: Robust Neural Radiance Field with Low-Quality Images

Recent work on Neural Radiance Fields (NeRF) exploits multi-view 3D consistency, achieving impressive results in 3D scene modeling and high-fidelity novel-view synthesis. However, there are limitations. First, existing methods assume enough high-quality images are available for training the NeRF model, ignoring real-world image degradation. Second, previous methods struggle with ambiguity in the training set due to unmodeled inconsistencies among different views. In this work, we present RustNeRF for real-world high-quality NeRF. To improve NeRF's robustness under real-world inputs, we train a 3D-aware preprocessing network that incorporates real-world degradation modeling. We propose a novel implicit multi-view guidance to address information loss during image degradation and restoration. Extensive experiments demonstrate RustNeRF's advantages over existing approaches under real-world degradation. The code will be released.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Adaptive Patch Exiting for Scalable Single Image Super-Resolution

Since the future of computing is heterogeneous, scalability is a crucial problem for single image super-resolution. Recent works try to train one network, which can be deployed on platforms with different capacities. However, they rely on the pixel-wise sparse convolution, which is not hardware-friendly and achieves limited practical speedup. As image can be divided into patches, which have various restoration difficulties, we present a scalable method based on Adaptive Patch Exiting (APE) to achieve more practical speedup. Specifically, we propose to train a regressor to predict the incremental capacity of each layer for the patch. Once the incremental capacity is below the threshold, the patch can exit at the specific layer. Our method can easily adjust the trade-off between performance and efficiency by changing the threshold of incremental capacity. Furthermore, we propose a novel strategy to enable the network training of our method. We conduct extensive experiments across various backbones, datasets and scaling factors to demonstrate the advantages of our method. Code is available at https://github.com/littlepure2333/APE

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preprint2022arXiv

Efficient Meta-Tuning for Content-aware Neural Video Delivery

Recently, Deep Neural Networks (DNNs) are utilized to reduce the bandwidth and improve the quality of Internet video delivery. Existing methods train corresponding content-aware super-resolution (SR) model for each video chunk on the server, and stream low-resolution (LR) video chunks along with SR models to the client. Although they achieve promising results, the huge computational cost of network training limits their practical applications. In this paper, we present a method named Efficient Meta-Tuning (EMT) to reduce the computational cost. Instead of training from scratch, EMT adapts a meta-learned model to the first chunk of the input video. As for the following chunks, it fine-tunes the partial parameters selected by gradient masking of previous adapted model. In order to achieve further speedup for EMT, we propose a novel sampling strategy to extract the most challenging patches from video frames. The proposed strategy is highly efficient and brings negligible additional cost. Our method significantly reduces the computational cost and achieves even better performance, paving the way for applying neural video delivery techniques to practical applications. We conduct extensive experiments based on various efficient SR architectures, including ESPCN, SRCNN, FSRCNN and EDSR-1, demonstrating the generalization ability of our work. The code is released at \url{https://github.com/Neural-video-delivery/EMT-Pytorch-ECCV2022}.

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preprint2022arXiv

NFANet: A Novel Method for Weakly Supervised Water Extraction from High-Resolution Remote Sensing Imagery

The use of deep learning for water extraction requires precise pixel-level labels. However, it is very difficult to label high-resolution remote sensing images at the pixel level. Therefore, we study how to utilize point labels to extract water bodies and propose a novel method called the neighbor feature aggregation network (NFANet). Compared with pixellevel labels, point labels are much easier to obtain, but they will lose much information. In this paper, we take advantage of the similarity between the adjacent pixels of a local water-body, and propose a neighbor sampler to resample remote sensing images. Then, the sampled images are sent to the network for feature aggregation. In addition, we use an improved recursive training algorithm to further improve the extraction accuracy, making the water boundary more natural. Furthermore, our method utilizes neighboring features instead of global or local features to learn more representative features. The experimental results show that the proposed NFANet method not only outperforms other studied weakly supervised approaches, but also obtains similar results as the state-of-the-art ones.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Non-Hermiticity stabilized Majorana zero modes in semiconductor-superconductor nanowires

Coupled Majorana zero modes with nonzero energies are generally detrimental to the non-Abelian statistics due to the additional dynamic phase. Nevertheless, we show that a well-connected lead can introduce a local non-Hermitian dissipation term to shift the energies of the both coupled Majorana modes to zero, and surprisingly turn the coupled Majorana mode far from the lead into a dark Majorana mode with exponentially small dissipation. This dark Majorana mode can conquer the drawback of the partially overlapped Majorana zero modes and possess the properties of true Majorana zero mode such as the perfect fractional Josephson effect and the non-Abelian statistics.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results. In this challenge, the new Large-scale Diverse Video (LDV) dataset is employed. The challenge has three tracks. Tracks 1 and 2 aim at enhancing the videos compressed by HEVC at a fixed QP, while Track 3 is designed for enhancing the videos compressed by x265 at a fixed bit-rate. Besides, the quality enhancement of Tracks 1 and 3 targets at improving the fidelity (PSNR), and Track 2 targets at enhancing the perceptual quality. The three tracks totally attract 482 registrations. In the test phase, 12 teams, 8 teams and 11 teams submitted the final results of Tracks 1, 2 and 3, respectively. The proposed methods and solutions gauge the state-of-the-art of video quality enhancement. The homepage of the challenge: https://github.com/RenYang-home/NTIRE21_VEnh

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preprint2022arXiv

Structure-aware Editable Morphable Model for 3D Facial Detail Animation and Manipulation

Morphable models are essential for the statistical modeling of 3D faces. Previous works on morphable models mostly focus on large-scale facial geometry but ignore facial details. This paper augments morphable models in representing facial details by learning a Structure-aware Editable Morphable Model (SEMM). SEMM introduces a detail structure representation based on the distance field of wrinkle lines, jointly modeled with detail displacements to establish better correspondences and enable intuitive manipulation of wrinkle structure. Besides, SEMM introduces two transformation modules to translate expression blendshape weights and age values into changes in latent space, allowing effective semantic detail editing while maintaining identity. Extensive experiments demonstrate that the proposed model compactly represents facial details, outperforms previous methods in expression animation qualitatively and quantitatively, and achieves effective age editing and wrinkle line editing of facial details. Code and model are available at https://github.com/gerwang/facial-detail-manipulation.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Uncertainty Guided Depth Fusion for Spike Camera

Depth estimation is essential for various important real-world applications such as autonomous driving. However, it suffers from severe performance degradation in high-velocity scenario since traditional cameras can only capture blurred images. To deal with this problem, the spike camera is designed to capture the pixel-wise luminance intensity at high frame rate. However, depth estimation with spike camera remains very challenging using traditional monocular or stereo depth estimation algorithms, which are based on the photometric consistency. In this paper, we propose a novel Uncertainty-Guided Depth Fusion (UGDF) framework to fuse the predictions of monocular and stereo depth estimation networks for spike camera. Our framework is motivated by the fact that stereo spike depth estimation achieves better results at close range while monocular spike depth estimation obtains better results at long range. Therefore, we introduce a dual-task depth estimation architecture with a joint training strategy and estimate the distributed uncertainty to fuse the monocular and stereo results. In order to demonstrate the advantage of spike depth estimation over traditional camera depth estimation, we contribute a spike-depth dataset named CitySpike20K, which contains 20K paired samples, for spike depth estimation. UGDF achieves state-of-the-art results on CitySpike20K, surpassing all monocular or stereo spike depth estimation baselines. We conduct extensive experiments to evaluate the effectiveness and generalization of our method on CitySpike20K. To the best of our knowledge, our framework is the first dual-task fusion framework for spike camera depth estimation. Code and dataset will be released.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Deep Likelihood Network for Image Restoration with Multiple Degradation Levels

Convolutional neural networks have been proven effective in a variety of image restoration tasks. Most state-of-the-art solutions, however, are trained using images with a single particular degradation level, and their performance deteriorates drastically when applied to other degradation settings. In this paper, we propose deep likelihood network (DL-Net), aiming at generalizing off-the-shelf image restoration networks to succeed over a spectrum of degradation levels. We slightly modify an off-the-shelf network by appending a simple recursive module, which is derived from a fidelity term, for disentangling the computation for multiple degradation levels. Extensive experimental results on image inpainting, interpolation, and super-resolution show the effectiveness of our DL-Net.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Hall algebras and quantum symmetric pairs I: foundations

A quantum symmetric pair consists of a quantum group $\mathbf U$ and its coideal subalgebra ${\mathbf U}^{\imath}_{\boldsymbolς}$ with parameters $\boldsymbolς$ (called an $\imath$quantum group). We initiate a Hall algebra approach for the categorification of $\imath$quantum groups. A universal $\imath$quantum group $\widetilde{\mathbf U}^{\imath}$ is introduced and ${\mathbf U}^{\imath}_{\boldsymbolς}$ is recovered by a central reduction of $\widetilde{\mathbf U}^{\imath}$. The semi-derived Ringel-Hall algebras of the first author and Peng, which are closely related to semi-derived Hall algebras of Gorsky and motivated by Bridgeland's work, are extended to the setting of 1-Gorenstein algebras, as shown in Appendix A by the first author. A new class of 1-Gorenstein algebras (called $\imath$quiver algebras) arising from acyclic quivers with involutions is introduced. The semi-derived Ringel-Hall algebras for the Dynkin $\imath$quiver algebras are shown to be isomorphic to the universal quasi-split $\imath$quantum groups of finite type. Monomial bases and PBW bases for these Hall algebras and $\imath$quantum groups are constructed.

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preprint2021arXiv

Hall algebras and quantum symmetric pairs III: Quiver varieties

The $\imath$quiver algebras were introduced recently by the authors to provide a Hall algebra realization of universal $\imath$quantum groups, which is a generalization of Bridgeland's Hall algebra construction for (Drinfeld doubles of) quantum groups; here an $\imath$quantum group and a corresponding Drinfeld-Jimbo quantum group form a quantum symmetric pair. In this paper, the Dynkin $\imath$quiver algebras are shown to arise as new examples of singular Nakajima-Keller-Scherotzke categories. Then we provide a geometric construction of the universal $\imath$quantum groups and their ``dual canonical bases" with positivity, via the quantum Grothendieck rings of Nakajima-Keller-Scherotzke quiver varieties, generalizing Qin's geometric realization of quantum groups of type ADE.

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preprint2021arXiv

Realistic flat-band model based on degenerate $p$-orbitals in two-dimensional ionic materials

Though several theoretical models have been proposed to design electronic flat-bands, the definite experimental realization in two-dimensional atomic crystal is still lacking. Here we propose a novel and realistic flat-band model based on threefold degenerate $p$-orbitals in two-dimensional ionic materials. Our theoretical analysis and first-principles calculations show that the proposed flat-band can be realized in 1T layered materials of alkali-metal chalogenides and metal-carbon group compounds. Some of the former are theoretically predicted to be stable as layered materials (e.g., K$_2$S), and some of the latter have been experimentally fabricated in previous works (e.g., Gd$_2$CCl$_2$). More interestingly, the flat-band is partially filled in the heterostructure of a K$_2$S monolayer and graphene layers. The spin polarized nearly flat-band can be realized in the ferromagnetic state of a Gd$_2$CCl$_2$ monolayer, which has been fabricated in experiments. Our theoretical model together with the material predictions provide a realistic platform for the study of flat-bands and related exotic quantum phases.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Semi-derived Ringel-Hall algebras and Drinfeld double

Let $\mathcal{A}$ be an arbitrary hereditary abelian category that may not have enough projective objects. For example, $\mathcal{A}$ can be the category of finite-dimensional representations of a quiver or the category of coherent sheaves on a smooth projective curve or on a weighted projective line. Inspired by the works of Bridgeland and Gorsky, we define the semi-derived Ringel-Hall algebra of $\mathcal{A}$, denoted by $\mathcal{S}\mathcal{D}\mathcal{H}_{\mathbb{Z}/2}(\mathcal{A})$, to be the localization of a quotient algebra of the Ringel-Hall algebra of the category of $\mathbb{Z}/2$-graded complexes over $\mathcal{A}$. We obtain the following three main results. The semi-derived Ringel-Hall algebra has a natural basis. A twisted version of the semi-derived Ringel-Hall algebra of $\mathcal{A}$ is isomorphic to the Drinfeld double of the twisted extended Ringel-Hall algebra $\mathcal{H}_{tw}^e(\mathcal{A})$ of $\mathcal{A}$. If $\mathcal{A}$ has a tilting object $T$, then its semi-derived Ringel-Hall algebra is isomorphic to the $\mathbb{Z}/2$-graded semi-derived Hall algebra $\mathcal{S}\mathcal{D}\mathcal{H}_{\mathbb{Z}/2}(\mathrm{add} T)$ of the exact category $\mathrm{add} T$ defined by Gorsky, and so is isomorphic to Bridgeland's Hall algebra of $\mod (\mathrm{End}(T)^{op})$.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

A chip-scale oscillation-mode optomechanical inertial sensor near the thermodynamical limits

High-precision inertial sensing and gravity sensing are key in navigation, oil exploration, and earthquake prediction. In contrast to prior accelerometers using piezoelectric or electronic capacitance readout techniques, optical readout provides narrow-linewidth high-sensitivity laser detection along with low-noise resonant optomechanical transduction near the thermodynamical limits. Here an optomechanical inertial sensor with 8.2micro-g/Hz^1/2 velocity random walk (VRW) at acquisition rate of 100 Hz and 50.9 micro-g bias instability is demonstrated, suitable for consumer and industrial grade applications, e.g., inertial navigation, inclination sensing, platform stabilization, and/or wearable device motion detection. Driven into optomechanical sustained-oscillation, the slot photonic crystal cavity provides radio-frequency readout of the optically-driven transduction with enhanced 625 microg/Hz sensitivity. Measuring the optomechanically-stiffened oscillation shift, instead of the optical transmission shift, provides a 220x VRW enhancement over pre-oscillation mode detection due to the strong optomechanical transduction. Supported by theory, this inertial sensor operates 2.56x above the thermodynamical limit at small integration times, with 43-dB dynamic range, in a solid-state room-temperature readout architecture.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Neural Video Coding using Multiscale Motion Compensation and Spatiotemporal Context Model

Over the past two decades, traditional block-based video coding has made remarkable progress and spawned a series of well-known standards such as MPEG-4, H.264/AVC and H.265/HEVC. On the other hand, deep neural networks (DNNs) have shown their powerful capacity for visual content understanding, feature extraction and compact representation. Some previous works have explored the learnt video coding algorithms in an end-to-end manner, which show the great potential compared with traditional methods. In this paper, we propose an end-to-end deep neural video coding framework (NVC), which uses variational autoencoders (VAEs) with joint spatial and temporal prior aggregation (PA) to exploit the correlations in intra-frame pixels, inter-frame motions and inter-frame compensation residuals, respectively. Novel features of NVC include: 1) To estimate and compensate motion over a large range of magnitudes, we propose an unsupervised multiscale motion compensation network (MS-MCN) together with a pyramid decoder in the VAE for coding motion features that generates multiscale flow fields, 2) we design a novel adaptive spatiotemporal context model for efficient entropy coding for motion information, 3) we adopt nonlocal attention modules (NLAM) at the bottlenecks of the VAEs for implicit adaptive feature extraction and activation, leveraging its high transformation capacity and unequal weighting with joint global and local information, and 4) we introduce multi-module optimization and a multi-frame training strategy to minimize the temporal error propagation among P-frames. NVC is evaluated for the low-delay causal settings and compared with H.265/HEVC, H.264/AVC and the other learnt video compression methods following the common test conditions, demonstrating consistent gains across all popular test sequences for both PSNR and MS-SSIM distortion metrics.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Dielectric Metasurfaces for Complete and Independent Control of Optical Amplitude and Phase

Metasurfaces are optically thin metamaterials that promise complete control of the wavefront of light but are primarily used to control only the phase of light. Here, we present an approach, simple in concept and in practice, that uses meta-atoms with a varying degree of form birefringence and rotation angles to create high-efficiency dielectric metasurfaces that control both the optical amplitude and phase at one or two frequencies. This opens up applications in computer-generated holography, allowing faithful reproduction of both the phase and amplitude of a target holographic scene without the iterative algorithms required in phase-only holography. We demonstrate all-dielectric metasurface holograms with independent and complete control of the amplitude and phase at up to two optical frequencies simultaneously to generate two- and three-dimensional holographic objects. We show that phase-amplitude metasurfaces enable a few features not attainable in phase-only holography; these include creating artifact-free two-dimensional holographic images, encoding phase and amplitude profiles separately at the object plane, encoding intensity profiles at the metasurface and object planes separately, and controlling the surface textures of three-dimensional holographic objects.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Higgs amplitude mode in massless Dirac fermion systems

The Higgs amplitude mode in superconductors is the condensed matter analogy of Higgs bosons in particle physics. We investigate the time evolution of Higgs amplitude mode in massless Dirac systems, induced by a weak quench of an attractive interaction. We find that the Higgs amplitude mode in the half-filling honeycomb lattice has a logarithmic decaying behaviour, qualitatively different from the $1/\sqrt{t}$ decay in the normal superconductors. Our study is also extended to the doped cases in honeycomb lattice. As for the 3D Dirac semimetal at half filling, we obtain an undamped oscillation of the amplitude mode. Our finding is not only an important supplement to the previous theoretical studies on normal fermion systems, but also provide an experimental signature to characterize the superconductivity in 2D or 3D Dirac systems.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Singularity categories of some 2-CY-tilted algebras

We define a class of finite-dimensional Jacobian algebras, which are called (simple) polygon-tree algebras, as a generalization of cluster-tilted algebras of type $\D$. They are $2$-CY-tilted algebras. Using a suitable process of mutations of quivers with potentials (which are also BB-mutations) inducing derived equivalences, and one-pointed (co)extensions which preserve singularity equivalences, we find a connected selfinjective Nakayama algebra whose stable category is equivalent to the singularity category of a simple polygon-tree algebra. Furthermore, we also give a classification of algebras of this kind up to representation type.

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preprint2015arXiv

Singularity categories of skewed-gentle algebras

Let $K$ be an algebraically closed field. Let $(Q,Sp,I)$ be a skewed-gentle triple, $(Q^{sg},I^{sg})$ and $(Q^g,I^{g})$ be its corresponding skewed-gentle pair and associated gentle pair respectively. It proves that the skewed-gentle algebra $KQ^{sg}/< I^{sg}>$ is singularity equivalent to $KQ/< I>$. Moreover, we use $(Q,Sp,I)$ to describe the singularity category of $KQ^g/< I^g>$. As a corollary, we get that $\mathrm{gldim} KQ^{sg}/< I^{sg}><\infty$ if and only if $\mathrm{gldim} KQ/< I><\infty$ if and only if $\mathrm{gldim} KQ^{g}/< I^{g}><\infty$.

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preprint2014arXiv

Coherent spin control of a nanocavity-enhanced qubit in diamond

A central aim of quantum information processing is the efficient entanglement of multiple stationary quantum memories via photons. Among solid-state systems, the nitrogen-vacancy (NV) centre in diamond has emerged as an excellent optically addressable memory with second-scale electron spin coherence times. Recently, quantum entanglement and teleportation have been shown between two NV-memories, but scaling to larger networks requires more efficient spin-photon interfaces such as optical resonators. Here, we demonstrate such NV-nanocavity systems with optical quality factors approaching 10,000 and electron spin coherence times exceeding 200 $μ$s using a silicon hard-mask fabrication process. This spin-photon interface is integrated with on-chip microwave striplines for coherent spin control, providing an efficient quantum memory for quantum networks.

0 citations0 reviewsNo code linkedOpen access
preprint2014arXiv

Photon transport enhanced by transverse Anderson localization in disordered superlattices

One of the daunting challenges in optical physics is to accurately control the flow of light at the subwavelength scale, by patterning the optical medium one can design anisotropic media. The light transport can also be significantly affected by Anderson localization, namely the wave localization in a disordered medium, a ubiquitous phenomenon in wave physics. Here we report the photon transport and collimation enhanced by transverse Anderson localization in chip-scale dispersion engineered anisotropic media. We demonstrate a new type of anisotropic photonic structure in which diffraction is nearly completely arrested by cascaded resonant tunneling through transverse guided resonances. By perturbing the shape of more than 4,000 scatterers in these superlattices we add structural disordered in a controlled manner and uncover the mechanism of disorder-induced transverse localization at the chip-scale. Arrested spatial divergence is captured in the power-law scaling, along with exponential asymmetric mode profiles and enhanced collimation bandwidth for increasing disorder. With increasing disorder, we observe the crossover from cascaded guided resonances into the transverse localization regime, beyond the ballistic and diffusive transport of photons.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

Antiferromagnetic Domain Structure in Bilayer Manganite

We report a novel soft x-ray nanodiffraction study of antiferromagnetic domains in the strongly correlated bylayer manganite La$_{0.96}$Sr$_{2.04}$Mn$_{2}$O$_{7}$. We find that the antiferromagnetic domains are quenched, forming a unique domain pattern with each domain having an intrinsic memory of its spin direction, and with associated domain walls running along crystallographic directions. This can be explained by the presence of crystallographic or magnetic imperfections locked in during the crystal growth process which pin the antiferromagnetic domains. The antiferromagnetic domain pattern shows two distinct types of domain. We observe, in one type only, a periodic ripple in the manganese spin direction with a period of approximately 4 \micro\meter. We propose that the loss of inversion symmetry within a bilayer is responsible for this ripple structure through a Dzyaloshinskii-Moriya-type interaction.

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preprint2013arXiv

Coxeter transformations of the derived categories of coherent sheaves

In this paper, we study the Coxeter transformation of the derived categories of coherent sheaves on smooth complete varieties. We first obtain that if the rank of the Grothendieck group is finite, say $m$, then its characteristic polynomials is $(λ+(-1)^{n})^m$, where $n$ is dimension of the variety. We then study the Jordan canonical forms of the Coxeter transformations for rational surfaces, smooth complete toric varieties with ample canonical or anticanonical bundles, and prove that their Jordan canonical forms can determine and be determined by the Betti numbers of these varieties. As an application, we compute the Jordan canonical forms of tensor products of matrices.

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preprint2013arXiv

Feedback and harmonic locking of slot-type optomechanical oscillators to external low-noise reference clocks

We demonstrate feedback and harmonic locking of chip-scale slot-type optomechanical oscillators to external low-noise reference clocks, with suppressed timing jitter by three orders of magnitude. The feedback and compensation techniques significantly reduce the close-to-carrier phase noise, especially within the locking bandwidth for the integral root-mean-square timing jitter. Harmonic locking via high-order carrier signals is also demonstrated with similar phase noise and integrated root-mean-square timing jitter reduction. The chip-scale optomechanical oscillators are tunable over an 80-kHz range by tracking the reference clock, with potential applications in tunable radio-frequency photonics platforms.

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preprint2012arXiv

Ring-like spin segregation of binary mixtures in a high-velocity rotating drum

We present molecular dynamics simulations on the segregation of binary mixtures in a high-velocity rotating drum. Depending on the ratio of particle's radius and density, the ring-like spin segregation patterns in radial direction show similarities to the Brazil-nut effect and its reverse form. The smaller and heavier particles are easier to accumulate towards the drum wall and the bigger and lighter ones towards the drum center. Furthermore, we quantify the effects of particle's radius and density on the segregation states and plot the phase diagram of segregation in the ${ρ_b}/{ρ_s}$ - ${r_b}/{r_s}$ space. The observed phenomena can also be well explained by the combined actions, i.e., the percolation effect and the buoyancy effect.

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preprint2010arXiv

Nanopatterning of Si surfaces by normal incident ion erosion: influence of metal incorporation on surface morphology evolution

The morphology evolution of Si (100) surfaces under 1200 eV Ar+ ion bombardment at normal incidence with and without metal incorporation is presented. The formation of nanodot patterns is observed only when the stationary Fe concentration in the surface is above 8x10^14 cm^-2. This is interpreted in terms of an additional surface instability due to non-uniform sputtering in connection with metal enrichment at the nanodots. At low metal concentration smoothing dominates and pattern formation is thus inhibited. The transition from a k^-2 to a k^-4 behavior in the asymptotic power spectral density function supports the conclusion that ballistic smoothing and ion-enhanced viscous flow are the two dominant mechanisms of surface relaxation.

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preprint1996arXiv

Heavy Baryon Mixing in Chiral Perturbation Theory

We discuss the SU(3) and heavy quark spin-symmetry breaking mixing between the Xi_c and Xi'_c charmed baryons. Chromomagnetic hyperfine interactions are the leading source of spin-symmetry breaking and together with the SU(3) breaking mass differences between the lightest pseudo-Goldstone bosons gives the leading contribution to the mixing. Such contributions are computed in chiral perturbation theory and compared to quark model expectations. We also compute the leading contribution to the semileptonic decay Xi_b -> Xi'_c l nu at zero recoil, and find that it is an order of magnitude smaller than naive power counting would suggest. It appears that Xi_b -> Xi'_c l nu is dominated by incalculable counterterms, and we discuss the implications for quark models based on the essential role of hyperfine interactions.

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preprint1996arXiv

Higher Order QCD Corrections to $b\to c\overline{c}s$

We calculate the ${\cal O}(α_s^2 β_0 )$ corrections to the decay rate $b\rightarrow c\bar c s$. For reasonable values of $m_c/m_b$ this term is of the same order as both the one-loop and $\CO(α_s^2 \log^2 m_W/m_b)$ corrections to the decay rate. For $m_c/m_b=0.3$ the $\CO(α_s^2β_0)$ corrections enhance the rate by $\sim 18\%$ . We also discuss the $\CO(α_s^2β_0)$ corrections to $R_τ$, the $B$ semileptonic branching fraction and the charm multiplicity.

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preprint1995arXiv

The Radiative Charmed Baryon Decay $Ξ_{c2}^{0*} \to Ξ_{c1}^0 γ$

V-spin symmetry ($s \leftrightarrow d$ symmetry) forbids the radiative decay $Ξ_{c2}^{0*} \rightarrow Ξ_{c1}^0 γ$ in the SU(3) limit. The quark mass term breaks V-spin symmetry and the leading nonanalytic contribution to the radiative decay amplitude is computable in heavy baryon chiral perturbation theory. The radiative decay branching ratio is determined by the coupling constant $g_2$ and at leading order in chiral perturbation theory is given by $Br(Ξ_{c2}^{0*} \rightarrow Ξ_{c1}^0 γ) = 1.0\times 10^{-3} g_2^2$. Measurement of this branching fraction will determine $|g_2|$.

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preprint1994arXiv

Strong $Λπ$ Phase Shifts for CP Violation in Weak $Ξ\rightarrow Λπ$ Decay

Strong interaction $Λπ$ phase shifts relevant for the weak nonleptonic decay $Ξ\rightarrow Λπ$ are calculated using baryon chiral perturbation theory. We find in leading order that the S-wave phase shift vanishes and the $J={1 \over 2}$ P-wave phase shift is $-1.7 ^{\rm o} $. The small phase shifts imply that CP violation in this decay will be difficult to observe. Our results follow from chiral $SU(2)_L\times SU(2)_R$ symmetry.

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preprint1993arXiv

Black Holes with a Generalized Gravitational Action

Microscopic black holes are sensitive to higher dimension operators in the gravitational action. We compute the influence of these operators on the Schwarzschild solution using perturbation theory. All (time reversal invariant) operators of dimension six are included (dimension four operators don't alter the Schwarzschild solution). Corrections to the relation between the Hawking temperature and the black hole mass are found. The entropy is calculated using the Gibbons-Hawking prescription for the Euclidean path integral and using naive thermodynamic reasoning. These two methods agree, however, the entropy is not equal to 1/4 the area of the horizon.

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preprint1992arXiv

Two Photon Contribution to Polarization in $K^+ \rightarrow π^+ μ^+ μ^-$

Short distance physics involving virtual top and charm quarks contributes to $μ^+$ (and $μ^-$) polarization in the decay $K^+ \rightarrow π^+ μ^+ μ^-$. Measurement of the parity violating asymmetry $(Γ_R - Γ_L)/(Γ_R + Γ_L)$, where $Γ_R$ and $Γ_L$ are the rates to produce right and left-handed $μ^+$, may provide valuable information on the unitarity triangle. The parity violating asymmetry also gets a contribution from Feynman diagrams with two photon intermediate states. We estimate this two photon contribution to the asymmetry and discuss briefly the two photon contribution to time reversal odd asymmetries that involve both the $μ^+$ and $μ^-$ polarizations.

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