arXiv subjects

Chang Liu

Publications and source records attributed to Chang Liu.

At least 1,171 records · Page 65Linked to original sources

arXiv2016

Automated Inference on Sociopsychological Impressions of Attractive Female Faces

This article is a sequel to our earlier work [25]. The main objective of our research is to explore the potential of supervised machine learning in face-induced social computing and cognition, riding on the momentum of much heralded successes of face processing, analysis and recognition on the tasks of biometric-based identification. We present a case study of automated statistical inference on sociopsychological perceptions of female faces controlled for race, attractiveness, age and nationality. Our empirical evidences point to the possibility of training machine learning algorithms, using example face images characterized by internet users, to predict perceptions of personality traits and demeanors.

cs.CV↗

arXiv2016

Ground test of satellite constellation based quantum communication

Satellite based quantum communication has been proven as a feasible way to achieve global scale quantum communication network. Very recently, a low-Earth-orbit (LEO) satellite has been launched for this purpose. However, with a single satellite, it takes an inefficient 3-day period to provide the worldwide connectivity. On the other hand, similar to how the Iridium system functions in classic communication, satellite constellation (SC) composed of many quantum satellites, could provide global real-time quantum communication. In such a SC, most of the satellites will work in sunlight. Unfortunately, none of previous ground testing experiments could be implemented at daytime. During daytime, the bright sunlight background prohibits quantum communication in transmission over long distances. In this letter, by choosing a working wavelength of 1550 nm and developing free-space single-mode fibre coupling technology and ultralow noise up-conversion single photon detectors, we overcome the noise due to sunlight and demonstrate a 53-km free space quantum key distribution (QKD) in the daytime through a 48-dB loss channel. Our system not only shows the feasibility of satellite based quantum communication in daylight, but also has the ability to naturally adapt to ground fibre optics, representing an essential step towards a SC-based global quantum network.

quant-ph↗

arXiv2016

Induced robust topological order on an ordinary insulator hetero-structured with a strong topological insulator

Topological states of matter originate from distinct topological electronic structures of materials. As for strong topological insulators (STIs), the topological surface (interface) is a direct consequence of electronic structure transition between materials categorized to different topological genus. Therefore, it is fundamentally interesting if such topological character can be manipulated. Besides tuning the crystal field and the strength of spin-orbital coupling (e.g., by external strain, or chemical doping), there is currently rare report on topological state induced in ordinary insulators (OIs) by the heterostructure of OI/STI. Here we report the observation of a Dirac cone topological surface state (TSS) induced on the Sb2Se3 layer up to 15 nm thick in the OI/STI heterostructure, in sharp contrast with the OI/OI heterostructure where no sign of TSS can be observed. This is evident for an induced topological state in an OI by heterostructure.

cond-mat.mtrl-sci↗

arXiv2016

Experimental ten-photon entanglement

Quantum entanglement among multiple spatially separated particles is of fundamental interest, and can serve as central resources for studies in quantum nonlocality, quantum-to-classical transition, quantum error correction, and quantum simulation. The ability of generating an increasing number of entangled particles is an important benchmark for quantum information processing. The largest entangled states were previously created with fourteen trapped ions, eight photons, and five superconducting qubits. Here, based on spontaneous parametric down-converted two-photon entanglement source with simultaneously a high brightness of ~12 MHz/W, a collection efficiency of ~70% and an indistinguishability of ~91% between independent photons, we demonstrate, for the first time, genuine and distillable entanglement of ten single photons under different pump power. Our work creates a state-of-the-art platform for multi-photon experiments, and provide enabling technologies for challenging optical quantum information tasks such as high-efficiency scattershot boson sampling with many photons.

quant-ph↗

arXiv2016

Latent Attention For If-Then Program Synthesis

Automatic translation from natural language descriptions into programs is a longstanding challenging problem. In this work, we consider a simple yet important sub-problem: translation from textual descriptions to If-Then programs. We devise a novel neural network architecture for this task which we train end-to-end. Specifically, we introduce Latent Attention, which computes multiplicative weights for the words in the description in a two-stage process with the goal of better leveraging the natural language structures that indicate the relevant parts for predicting program elements. Our architecture reduces the error rate by 28.57% compared to prior art. We also propose a one-shot learning scenario of If-Then program synthesis and simulate it with our existing dataset. We demonstrate a variation on the training procedure for this scenario that outperforms the original procedure, significantly closing the gap to the model trained with all data.

cs.CL↗

arXiv2016

Go-With-The-Winner: Client-Side Server Selection for Content Delivery

Content delivery networks deliver much of the web and video content in the world by deploying a large distributed network of servers. We model and analyze a simple paradigm for client-side server selection that is commonly used in practice where each user independently measures the performance of a set of candidate servers and selects the one that performs the best. For web (resp., video) delivery, we propose and analyze a simple algorithm where each user randomly chooses two or more candidate servers and selects the server that provided the best hit rate (resp., bit rate). We prove that the algorithm converges quickly to an optimal state where all users receive the best hit rate (resp., bit rate), with high probability. We also show that if each user chose just one random server instead of two, some users receive a hit rate (resp., bit rate) that tends to zero. We simulate our algorithm and evaluate its performance with varying choices of parameters, system load, and content popularity.

cs.NI↗

arXiv2016

Robust High-Dimensional Linear Regression

The effectiveness of supervised learning techniques has made them ubiquitous in research and practice. In high-dimensional settings, supervised learning commonly relies on dimensionality reduction to improve performance and identify the most important factors in predicting outcomes. However, the economic importance of learning has made it a natural target for adversarial manipulation of training data, which we term poisoning attacks. Prior approaches to dealing with robust supervised learning rely on strong assumptions about the nature of the feature matrix, such as feature independence and sub-Gaussian noise with low variance. We propose an integrated method for robust regression that relaxes these assumptions, assuming only that the feature matrix can be well approximated by a low-rank matrix. Our techniques integrate improved robust low-rank matrix approximation and robust principle component regression, and yield strong performance guarantees. Moreover, we experimentally show that our methods significantly outperform state of the art both in running time and prediction error.

cs.LG↗

arXiv2016

A Paradigm for Modeling and Computation of Gas Dynamics

In the continuum flow regime, the Navier-Stokes equations are usually used for the description of gas dynamics. On the other hand, the Boltzmann equation is applied for the rarefied gas dynamics. Both equations are constructed from modeling flow physics in different scales. Fortunately, due to the distinct separation of scales, i.e., the hydrodynamic and kinetic ones, both Navier-Stokes equations and the Boltzmann equation are valid in their respectable domains. However, in real physical application, there may not have such a distinctive scale separation. For example, around a hypersonic flying vehicle, the flow physics at different regions may correspond to different regimes, where the local Knudsen number can be changed in several order of magnitudes. With a variation of modeling scale, theoretically a continuous governing equation from kinetic Boltzmann equation to the hydrodynamic Navier-Stokes equations should exist. However, due to the difficulties of a direct modeling of flow physics in the scale between the kinetic and hydrodynamic ones, there is basically no reliable theory or valid governing equation to cover the whole transition regime. In fact, it is an unresolved problem about the exact scale for the validity of the NS equations as Reynolds number decreases. The traditional computational fluid dynamics (CFD) is based on the numerical solution of partial differential equations (PDE), and it targets on the recovering of the exact solution of the PDEs as mesh size and time step converging to zero. This methodology can be hardly applied here because there is no such a complete PDE for flow physics in all scales. It may be the time to combine the modeling and computation together without going through the process of constructing PDEs. In other words, the CFD research is not only to obtain the numerical solution of governing equation, but also to construct a valid discrete governing equation to identify the flow physics in the mesh size and time step scales. In this paper, we are going to present the idea for the modeling and computation. This methodology leads to the unified gas-kinetic scheme (UGKS) for flow simulation in all flow regimes. Based on UGKS, the boundary for the validation of the Navier-Stokes equations can be quantitatively evaluated. The combination of modeling and computation provides a paradigm for the description of multiscale transport process.

physics.flu-dyn↗

arXiv2016

Multi-wavelength Study of Transition Region Penumbral Subarcsecond Bright Dots Using IRIS and NST

Using high-resolution transition region (TR) observations taken by the Interface Region Imaging Spectrograph (IRIS) mission, Tian et al. (2014b) revealed numerous short-lived subarcsecond bright dots (BDs) above sunspots (mostly located in the penumbrae), which indicate yet unexplained small-scale energy releases. Moreover, whether these subarcsecond TR brightenings have any signature in the lower atmosphere and how they are formed are still not fully resolved. This paper presents a multi-wavelength study of the TR penumbral BDs using a coordinated observation of a near disk-center sunspot with IRIS and the 1.6 m New Solar Telescope (NST) at the Big Bear Solar Observatory. NST provides high-resolution chromospheric and photospheric observations with narrow-band H-alpha imaging spectroscopy and broad-band TiO images, respectively, complementary to IRIS TR observations. A total of 2692 TR penumbral BDs are identified from a 37-minute time series of IRIS 1400 A slitjaw images. Their locations tend to be associated more with downflowing and darker fibrils in the chromosphere, and weakly associated with bright penumbral features in the photosphere. However, temporal evolution analyses of the BDs show that there is no consistent and convincing brightening response in the chromosphere. These results are compatible with a formation mechanism of the TR penumbral BDs by falling plasma from coronal heights along more vertical and dense magnetic loops. The BDs may also be produced by small-scale impulsive magnetic reconnection taking place sufficiently high in the atmosphere that has no energy release in the chromosphere.

astro-ph.SR↗

arXiv2016

Privacy Knowledge Modelling for Internet of Things: A Look Back

Internet of Things (IoT) and cloud computing together give us the ability to sense, collect, process, and analyse data so we can use them to better understand behaviours, habits, preferences and life patterns of users and lead them to consume resources more efficiently. In such knowledge discovery activities, privacy becomes a significant challenge due to the extremely personal nature of the knowledge that can be derived from the data and the potential risks involved. Therefore, understanding the privacy expectations and preferences of stakeholders is an important task in the IoT domain. In this paper, we review how privacy knowledge has been modelled and used in the past in different domains. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT. Finally, we discuss major research challenges and opportunities.

cs.CY↗

arXiv2016

DeepFood: Deep Learning-Based Food Image Recognition for Computer-Aided Dietary Assessment

Worldwide, in 2014, more than 1.9 billion adults, 18 years and older, were overweight. Of these, over 600 million were obese. Accurately documenting dietary caloric intake is crucial to manage weight loss, but also presents challenges because most of the current methods for dietary assessment must rely on memory to recall foods eaten. The ultimate goal of our research is to develop computer-aided technical solutions to enhance and improve the accuracy of current measurements of dietary intake. Our proposed system in this paper aims to improve the accuracy of dietary assessment by analyzing the food images captured by mobile devices (e.g., smartphone). The key technique innovation in this paper is the deep learning-based food image recognition algorithms. Substantial research has demonstrated that digital imaging accurately estimates dietary intake in many environments and it has many advantages over other methods. However, how to derive the food information (e.g., food type and portion size) from food image effectively and efficiently remains a challenging and open research problem. We propose a new Convolutional Neural Network (CNN)-based food image recognition algorithm to address this problem. We applied our proposed approach to two real-world food image data sets (UEC-256 and Food-101) and achieved impressive results. To the best of our knowledge, these results outperformed all other reported work using these two data sets. Our experiments have demonstrated that the proposed approach is a promising solution for addressing the food image recognition problem. Our future work includes further improving the performance of the algorithms and integrating our system into a real-world mobile and cloud computing-based system to enhance the accuracy of current measurements of dietary intake.

cs.CV↗

arXiv2016

Self-regular black holes quantized by means of an analogue to hydrogen atoms

We suggest a quantum black hole model that is based on an analogue to hydrogen atoms. A self-regular Schwarzschild-AdS black hole is investigated, where the mass density of the extreme black hole is given by the probability density of the ground state of hydrogen atoms and the mass densities of non-extreme black holes are given by the probability densities of excited states with no angular momenta. Such an analogue is inclined to adopt quantization of black hole horizons. In this way, the total mass of black holes is quantized. Furthermore, the quantum hoop conjecture and the Correspondence Principle are discussed.

hep-th↗

arXiv2016

A new form of (unexpected) Dirac fermions in the strongly-correlated cerium monopnictides

Discovering Dirac fermions with novel properties has become an important front in condensed matter and materials sciences. Here, we report the observation of unusual Dirac fermion states in a strongly-correlated electron setting, which are uniquely distinct from those of graphene and conventional topological insulators. In strongly-correlated cerium monopnictides, we find two sets of highly anisotropic Dirac fermions that interpenetrate each other with negligible hybridization, and show a peculiar four-fold degeneracy where their Dirac nodes overlap. Despite the lack of protection by crystalline or time-reversal symmetries, this four-fold degeneracy is robust across magnetic phase transitions. Comparison of these experimental findings with our theoretical calculations suggests that the observed surface Dirac fermions arise from bulk band inversions at an odd number of high-symmetry points, which is analogous to the band topology which describes a $\mathbb{Z}_{2}$-topological phase. Our findings open up an unprecedented and long-sought-for platform for exploring novel Dirac fermion physics in a strongly-correlated semimetal.

cond-mat.str-el↗

arXiv2016

Unprecedented Fine Structure of a Solar Flare Revealed by the 1.6~m New Solar Telescope

Solar flares signify the sudden release of magnetic energy and are sources of so called space weather. The fine structures (below 500 km) of flares are rarely observed and are accessible to only a few instruments world-wide. Here we present observation of a solar flare using exceptionally high resolution images from the 1.6~m New Solar Telescope (NST) equipped with high order adaptive optics at Big Bear Solar Observatory (BBSO). The observation reveals the process of the flare in unprecedented detail, including the flare ribbon propagating across the sunspots, coronal rain (made of condensing plasma) streaming down along the post-flare loops, and the chromosphere's response to the impact of coronal rain, showing fine-scale brightenings at the footpoints of the falling plasma. Taking advantage of the resolving power of the NST, we measure the cross-sectional widths of flare ribbons, post-flare loops and footpoint brighenings, which generally lie in the range of 80-200 km, well below the resolution of most current instruments used for flare studies. Confining the scale of such fine structure provides an essential piece of information in modeling the energy transport mechanism of flares, which is an important issue in solar and plasma physics.

astro-ph.SR↗

arXiv2016

Secret sharing of a quantum state

Secret sharing of a quantum state, or quantum secret sharing, in which a dealer wants to share certain amount of quantum information with a few players, has wide applications in quantum information. The critical criterion in a threshold secret sharing scheme is confidentiality, with less than the designated number of players, no information can be recovered. Furthermore, in a quantum scenario, one additional critical criterion exists, the capability of sharing entangled and unknown quantum information. Here by employing a six-photon entangled state, we demonstrate a quantum threshold scheme, where the shared quantum secrecy can be efficiently reconstructed with a state fidelity as high as 93%. By observing that any one or two parties cannot recover the secrecy, we show that our scheme meets the confidentiality criterion. Meanwhile, we also demonstrate that entangled quantum information can be shared and recovered via our setting, which demonstrates that our implemented scheme is fully quantum. Moreover, our experimental setup can be treated as a decoding circuit of the 5-qubit quantum error-correcting code with two erasure errors.

quant-ph↗

arXiv2016

Structural and magnetic phase transitions in Ca$_{0.73}$La$_{0.27}$FeAs$_2$ with electron overdoped FeAs layers

We report a study of the Ca$_{0.73}$La$_{0.27}$FeAs$_2$ single crystals. We unravel a monoclinic to triclinic phase transition at 58 K, and a paramagnetic to stripe antiferromagnetic (AFM) phase transition at 54 K, below which spins order 45$^\circ$ away from the stripe direction. Furthermore, we demonstrate this material is substantially structurally untwinned at ambient pressure with the formation of spin rotation walls (S-walls). Finally, in addition to the central-hole and corner-electron Fermi pockets usually appearing in Fe pnictide superconductors, angle-resolved photoemission (ARPES) measurements resolve a Fermiology where an extra electron pocket of mainly As chain character exists at the Brillouin zone edge.

cond-mat.supr-con↗

arXiv2016

Irreversible Rapid Changes of Magnetic Field Associated with the 2012 October 23 Circular Near-limb X1.8 Flare

It has been found that photospheric magnetic fields can change in accordance with the three-dimensional magnetic field restructuring following solar eruptions. Previous studies mainly use vector magnetic field data taken for events near the disk center. In this paper, we analyze the magnetic field evolution associated with the 2012 October 23 X1.8 flare in NOAA AR 11598 that is close to the solar limb, using both the 45 s cadence line-of-sight and 12 minute cadence vector magnetograms from the Helioseismic and Magnetic Imager on board Solar Dynamic Observatory. This flare is classified as a circular-ribbon flare with spine-fan type magnetic topology containing a null point. In the line-of-sight magnetograms, there are two apparent polarity inversion lines (PIL). The PIL closer to the limb is affected more by the projection effect. Between these two PILs there lie positive polarity magnetic fields, which are surrounded by negative polarity fields outside the PILs. We find that after the flare, both the apparent limb-ward and disk-ward negative fluxes decrease, while the positive flux in-between increases. We also find that the horizontal magnetic fields have a significant increase along the disk-ward PIL, while in surrounding area, they decrease. Synthesizing the observed field changes, we conclude that the magnetic fields collapse toward the surface above the disk-ward PIL as depicted in the coronal implosion scenario, while the peripheral field turns to a more vertical configuration after the flare. We also suggest that this event is an asymmetric circular-ribbon flare: a flux rope is likely present above the disk-ward PIL. Its eruption causes the instability of the entire fan-spine structure and the implosion near that PIL.

astro-ph.SR↗

arXiv2016

Adjoint Fokker-Planck equation and runaway electron dynamics

The adjoint Fokker-Planck equation method is applied to study the runaway probability function and the expected slowing-down time for highly relativistic runaway electrons, including the loss of energy due to synchrotron radiation. In direct correspondence to Monte Carlo simulation methods, the runaway probability function has a smooth transition across the runaway separatrix, which can be attributed to effect of the pitch angle scattering term in the kinetic equation. However, for the same numerical accuracy, the adjoint method is more efficient than the Monte Carlo method. The expected slowing-down time gives a novel method to estimate the runaway current decay time in experiments. A new result from this work is that the decay rate of high energyelectrons is very slow when E is close to the critical electric field. This effect contributes further to a hysteresis previously found in the runaway electron population.

physics.plasm-ph↗