arXiv subjects

Li Li

Publications and source records attributed to Li Li.

At least 721 records · Page 40Linked to original sources

arXiv2017

Convolutional Neural Network-Based Block Up-sampling for Intra Frame Coding

Inspired by the recent advances of image super-resolution using convolutional neural network (CNN), we propose a CNN-based block up-sampling scheme for intra frame coding. A block can be down-sampled before being compressed by normal intra coding, and then up-sampled to its original resolution. Different from previous studies on down/up-sampling-based coding, the up-sampling methods in our scheme have been designed by training CNN instead of hand-crafted. We explore a new CNN structure for up-sampling, which features deconvolution of feature maps, multi-scale fusion, and residue learning, making the network both compact and efficient. We also design different networks for the up-sampling of luma and chroma components, respectively, where the chroma up-sampling CNN utilizes the luma information to boost its performance. In addition, we design a two-stage up-sampling process, the first stage being within the block-by-block coding loop, and the second stage being performed on the entire frame, so as to refine block boundaries. We also empirically study how to set the coding parameters of down-sampled blocks for pursuing the frame-level rate-distortion optimization. Our proposed scheme is implemented into the High Efficiency Video Coding (HEVC) reference software, and a comprehensive set of experiments have been performed to evaluate our methods. Experimental results show that our scheme achieves significant bits saving compared with HEVC anchor especially at low bit rates, leading to on average 5.5% BD-rate reduction on common test sequences and on average 9.0% BD-rate reduction on ultra high definition (UHD) test sequences.

cs.MM↗

arXiv2017

DeepTrend: A Deep Hierarchical Neural Network for Traffic Flow Prediction

In this paper, we consider the temporal pattern in traffic flow time series, and implement a deep learning model for traffic flow prediction. Detrending based methods decompose original flow series into trend and residual series, in which trend describes the fixed temporal pattern in traffic flow and residual series is used for prediction. Inspired by the detrending method, we propose DeepTrend, a deep hierarchical neural network used for traffic flow prediction which considers and extracts the time-variant trend. DeepTrend has two stacked layers: extraction layer and prediction layer. Extraction layer, a fully connected layer, is used to extract the time-variant trend in traffic flow by feeding the original flow series concatenated with corresponding simple average trend series. Prediction layer, an LSTM layer, is used to make flow prediction by feeding the obtained trend from the output of extraction layer and calculated residual series. To make the model more effective, DeepTrend needs first pre-trained layer-by-layer and then fine-tuned in the entire network. Experiments show that DeepTrend can noticeably boost the prediction performance compared with some traditional prediction models and LSTM with detrending based methods.

cs.LG↗

arXiv2017

Ground-to-satellite quantum teleportation

An arbitrary unknown quantum state cannot be precisely measured or perfectly replicated. However, quantum teleportation allows faithful transfer of unknown quantum states from one object to another over long distance, without physical travelling of the object itself. Long-distance teleportation has been recognized as a fundamental element in protocols such as large-scale quantum networks and distributed quantum computation. However, the previous teleportation experiments between distant locations were limited to a distance on the order of 100 kilometers, due to photon loss in optical fibres or terrestrial free-space channels. An outstanding open challenge for a global-scale "quantum internet" is to significantly extend the range for teleportation. A promising solution to this problem is exploiting satellite platform and space-based link, which can conveniently connect two remote points on the Earth with greatly reduced channel loss because most of the photons' propagation path is in empty space. Here, we report the first quantum teleportation of independent single-photon qubits from a ground observatory to a low Earth orbit satellite - through an up-link channel - with a distance up to 1400 km. To optimize the link efficiency and overcome the atmospheric turbulence in the up-link, a series of techniques are developed, including a compact ultra-bright source of multi-photon entanglement, narrow beam divergence, high-bandwidth and high-accuracy acquiring, pointing, and tracking (APT). We demonstrate successful quantum teleportation for six input states in mutually unbiased bases with an average fidelity of 0.80+/-0.01, well above the classical limit. This work establishes the first ground-to-satellite up-link for faithful and ultra-long-distance quantum teleportation, an essential step toward global-scale quantum internet.

quant-ph↗

arXiv2017

Exact Non-Markovian master equation for the Spin-Boson and Jaynes-Cummings models

We provide the exact non-Markovian master equation for a two-level system interacting with a thermal bosonic bath, and we write the solution of such a master equation in terms of the Bloch vector. We show that previous approximated results are particular limits of our exact master equation. We generalize these results to more complex systems involving an arbitrary number of two-level systems coupled to different thermal baths, providing the exact master equations also for these systems. As an example of this general case we derive the master equation for the Jaynes-Cummings model.

quant-ph↗

arXiv2017

Experimental Blind Quantum Computing for a Classical Client

To date, blind quantum computing demonstrations require clients to have weak quantum devices. Here we implement a proof-of-principle experiment for completely classical clients. Via classically interacting with two quantum servers that share entanglement, the client accomplishes the task of having the number 15 factorized by servers who are denied information about the computation itself. This concealment is accompanied by a verification protocol that tests servers' honesty and correctness. Our demonstration shows the feasibility of completely classical clients and thus is a key milestone towards secure cloud quantum computing.

quant-ph↗

arXiv2017

By-passing the Kohn-Sham equations with machine learning

Last year, at least 30,000 scientific papers used the Kohn-Sham scheme of density functional theory to solve electronic structure problems in a wide variety of scientific fields, ranging from materials science to biochemistry to astrophysics. Machine learning holds the promise of learning the kinetic energy functional via examples, by-passing the need to solve the Kohn-Sham equations. This should yield substantial savings in computer time, allowing either larger systems or longer time-scales to be tackled, but attempts to machine-learn this functional have been limited by the need to find its derivative. The present work overcomes this difficulty by directly learning the density-potential and energy-density maps for test systems and various molecules. Both improved accuracy and lower computational cost with this method are demonstrated by reproducing DFT energies for a range of molecular geometries generated during molecular dynamics simulations. Moreover, the methodology could be applied directly to quantum chemical calculations, allowing construction of density functionals of quantum-chemical accuracy.

physics.comp-ph↗

arXiv2017

Homogeneous solutions of stationary Navier-Stokes equations with isolated singularities on the unit sphere. I. One singularity

We classify all $(-1)-$homogeneous axisymmetric no swirl solutions of incompressible stationary Navier-Stokes equations in three dimension which are smooth on the unit sphere minus the south pole, parameterize them as a two dimensional surface with boundary, and analyze their pressure profiles near the north pole. Then we prove that there is a curve of $(-1)-$homogeneous axisymmetric solutions with nonzero swirl, having the same smoothness property, emanating from every point of the interior and one part of the boundary of the solution surface. Moreover we prove that there is no such curve of solutions for any point on the other part of the boundary. We also establish asymptotic expansions for every (-1)-homogeneous axisymmetric solutions in a neighborhood of the singular point on the unit sphere.

math.AP↗

arXiv2017

Frobenius semisimplicity for convolution morphisms

This article concerns properties of mixed $\ell$-adic complexes on varieties over finite fields, related to the action of the Frobenius automorphism. We establish a fiberwise criterion for the semisimplicity and Frobenius semisimplicity of the direct image complex under a proper morphism of varieties over a finite field. We conjecture that the direct image of the intersection complex on the domain is always semisimple and Frobenius semisimple; this conjecture would imply that a strong form of the decomposition theorem of Beilinson-Bernstein-Deligne-Gabber is valid over finite fields. We prove our conjecture for (generalized) convolution morphisms associated with partial affine flag varieties for split connected reductive groups over finite fields, and we prove allied Frobenius semisimplicity results for the intersection cohomology groups of twisted products of Schubert varieties. We offer two proofs for these results: one is based on the paving by affine spaces of the fibers of certain convolution morphisms, the other involves a new schematic theory of "big cells" adapted to partial affine flag varieties, and combines Deligne's theory of weights with a suitable contracting $\mathbb G_m$-action on those big cells. Both proofs rely on our general result that the intersection complex of the image of a proper map of varieties over a finite field is a direct summand of the direct image of the intersection complex of the domain. With suitable reformulations, the main results are valid over any algebraically closed ground field.

math.AG↗

arXiv2017

Homogeneous solutions of stationary Navier-Stokes equations with isolated singularities on the unit sphere. II. Classification of axisymmetric no-swirl solutions

We classify all (-1)-homogeneous axisymmetric no-swirl solutions of incompressible stationary Navier-Stokes equations in three dimension which are smooth on the unit sphere minus the south and north poles, parameterizing them as a four dimensional surface with boundary in appropriate function spaces. Then we establish smoothness properties of the solution surface in the four parameters. The smoothness properties will be used in a subsequent paper where we study the existence of (-1)-homogeneous axisymmetric solutions with non-zero swirl on $\mathbb{S}^2\setminus\{S,N\}$, emanating from the four dimensional solution surface.

math.AP↗

arXiv2017

New Combinatorial Formulas for Cluster Monomials of Type A Quivers

Lots of research focuses on the combinatorics behind various bases of cluster algebras. This paper studies the natural basis of a type A cluster algebra, which consists of all cluster monomials. We introduce a new kind of combinatorial formulas for the cluster monomials in terms of the so-called globally compatible collections. We give bijective proofs of these formulas by comparing with the well-known combinatorial models of the T-paths and of the perfect matchings in a snake diagram. For cluster variables of a type A cluster algebra, we give a bijection that relates our new formula with the theta functions constructed by Gross, Hacking, Keel and Kontsevich.

math.CO↗

arXiv2017

Phase transition for accessibility percolation on hypercubes

In this paper, we consider accessibility percolation on hypercubes, i.e., we place i.i.d. uniform [0,1] random variables on vertices of a hypercube, and study whether there is a path connecting two vertices such that the values of these random variables increase along the path. We establish a sharp phase transition depending on the difference of the values at the two endpoints, and determine the critical window of the phase transition. Our result completely resolves a conjecture of Berestycki, Brunet and Shi (2014).

math.PR↗

arXiv2017

Optimal Selection of Small-Scale Hybrid PV-battery Systems to Maximize Economic Benefit Based on Temporal Load Data

Continued advances in PV and battery energy storage technologies have made hybrid PV-battery systems an attractive prospect for residential energy consumers. However the process to select an appropriate system is complicated by the relatively high cost of batteries, a multitude of available retail electricity plans and the removal of PV installation incentive schemes. In this paper, an optimization strategy based on an individual customer's temporal load profile is established to maximize electricity cost savings through optimal selection of PV-battery system size, orientation and retail electricity plan. Quantum-behaved particle swarm optimization is applied as the underlying algorithm given its well-suited application to problems involving hybrid energy system specification. The optimization strategy is tested using real-world residential consumption data, current system pricing and available retail electricity plans to establish the efficacy of a hybrid PV-battery solution.

math.OC↗

arXiv2017

Intertwined Orders in Holography: Pair and Charge Density Waves

Building on [1], we examine a holographic model in which a U(1) symmetry and translational invariance are broken spontaneously at the same time. The symmetry breaking is realized through the Stückelberg mechanism, and leads to a scalar condensate and a charge density which are spatially modulated and exhibit unidirectional stripe order. Depending on the choice of parameters, the oscillations of the scalar condensate can average out to zero, with a frequency which is half of that of the charge density. In this case the system realizes some of the key features of pair density wave order. The model also admits a phase with co-existing superconducting and charge density wave orders, in which the scalar condensate has a uniform component. In our construction the various orders are intertwined with each other and have a common origin. The fully backreacted geometry is computed numerically, including for the case in which the theory contains axions. The latter can be added to explicitly break translational symmetry and mimic lattice-type effects.

hep-th↗

arXiv2017

Learning to Refine Object Contours with a Top-Down Fully Convolutional Encoder-Decoder Network

We develop a novel deep contour detection algorithm with a top-down fully convolutional encoder-decoder network. Our proposed method, named TD-CEDN, solves two important issues in this low-level vision problem: (1) learning multi-scale and multi-level features; and (2) applying an effective top-down refined approach in the networks. TD-CEDN performs the pixel-wise prediction by means of leveraging features at all layers of the net. Unlike skip connections and previous encoder-decoder methods, we first learn a coarse feature map after the encoder stage in a feedforward pass, and then refine this feature map in a top-down strategy during the decoder stage utilizing features at successively lower layers. Therefore, the deconvolutional process is conducted stepwise, which is guided by Deeply-Supervision Net providing the integrated direct supervision. The above proposed technologies lead to a more precise and clearer prediction. Our proposed algorithm achieved the state-of-the-art on the BSDS500 dataset (ODS F-score of 0.788), the PASCAL VOC2012 dataset (ODS F-score of 0.588), and and the NYU Depth dataset (ODS F-score of 0.735).

cs.CV↗

arXiv2017

Co-projection-plane based 3-D padding for polyhedron projection for 360-degree video

The polyhedron projection for 360-degree video is becoming more and more popular since it can lead to much less geometry distortion compared with the equirectangular projection. However, in the polyhedron projection, we can observe very obvious texture discontinuity in the area near the face boundary. Such a texture discontinuity may lead to serious quality degradation when motion compensation crosses the discontinuous face boundary. To solve this problem, in this paper, we first propose to fill the corresponding neighboring faces in the suitable positions as the extension of the current face to keep approximated texture continuity. Then a co-projection-plane based 3-D padding method is proposed to project the reference pixels in the neighboring face to the current face to guarantee exact texture continuity. Under the proposed scheme, the reference pixel is always projected to the same plane with the current pixel when performing motion compensation so that the texture discontinuity problem can be solved. The proposed scheme is implemented in the reference software of High Efficiency Video Coding. Compared with the existing method, the proposed algorithm can significantly improve the rate-distortion performance. The experimental results obviously demonstrate that the texture discontinuity in the face boundary can be well handled by the proposed algorithm.

cs.MM↗

arXiv2017

Experimental quantum channel simulation

Quantum simulation is of great importance in quantum information science. Here, we report an experimental quantum channel simulator imbued with an algorithm for imitating the behavior of a general class of quantum systems. The reported quantum channel simulator consists of four single-qubit gates and one controlled-NOT gate. All types of quantum channels can be decomposed by the algorithm and implemented on this device. We deploy our system to simulate various quantum channels, such as quantum-noise channels and weak quantum measurement. Our results advance experimental quantum channel simulation, which is integral to the goal of quantum information processing.

quant-ph↗

arXiv2017

Observation of Ten-photon Entanglement Using Thin BiB$_{3}$O$_{6}$ Crystals

We report on the experimental realization of a ten-photon Greenberger-Horne-Zeilinger state using thin BiB$_{3}$O$_{6}$ crystals. The observed fidelity is $0.606\pm0.029$, demonstrating a genuine entanglement with a standard deviation of 3.6 $σ$. This result is further verified using $p$-value calculation, obtaining an upper bound of $3.7\times10^{-3}$ under an assumed hypothesis test. Our experiment paves a new way to efficiently engineer BiB$_{3}$O$_{6}$ crystal-based multi-photon entanglement systems, which provides a promising platform for investigating advanced optical quantum information processing tasks such as boson sampling, quantum error correction and quantum-enhanced measurement.

quant-ph↗

arXiv2017

Projection based advanced motion model for cubic mapping for 360-degree video

This paper proposes a novel advanced motion model to handle the irregular motion for the cubic map projection of 360-degree video. Since the irregular motion is mainly caused by the projection from the sphere to the cube map, we first try to project the pixels in both the current picture and reference picture from unfolding cube back to the sphere. Then through utilizing the characteristic that most of the motions in the sphere are uniform, we can derive the relationship between the motion vectors of various pixels in the unfold cube. The proposed advanced motion model is implemented in the High Efficiency Video Coding reference software. Experimental results demonstrate that quite obvious performance improvement can be achieved for the sequences with obvious motions.

cs.MM↗